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Numerous ephemeral rivers and thousands of natural pans characterize the transboundary Iishana-System of the Cuvelai Basin between Namibia and Angola. After the rainy season, surface water stored in pans is often the only affordable water source for many people in rural areas. High inter- and intra-annual rainfall variations in this semiarid environment provoke years of extreme flood events and long periods of droughts. Thus, the issue of water availability is playing an increasingly important role in one of the most densely populated and fastest growing regions in southwestern Africa. Currently, there is no transnational approach to quantifying the potential storage and supply functions of the Iishana-System. To bridge these knowledge gaps and to increase the resilience of the local people's livelihood, suitable pans for expansion as intermediate storage were identified and their metrics determined. Therefore, a modified Blue Spot Analysis was performed, based on the high-resolution TanDEM-X digital elevation model. Further, surface area–volume ratio calculations were accomplished for finding suitable augmentation sites in a first step. The potential water storage volume of more than 190,000 pans was calculated at 1.9 km\(^3\). Over 2200 pans were identified for potential expansion to facilitate increased water supply and flood protection in the future.
With accelerating global climate change, the Antarctic Ice Sheet is exposed to increasing ice dynamic change. During 1992 and 2017, Antarctica contributed ~7.6 mm to global sea-level-rise mainly due to ocean thermal forcing along West Antarctica and atmospheric warming along the Antarctic Peninsula (API). Together, these processes caused the progressive retreat of glaciers and ice shelves and weakened their efficient buttressing force causing widespread ice flow accelerations. Holding ~91% of the global ice mass and 57.3 m of sea-level-equivalent, the Antarctic Ice Sheet is by far the largest potential contributor to future sea-level-rise.
Despite the improved understanding of Antarctic ice dynamics, the future of Antarctica remains difficult to predict with its contribution to global sea-level-rise representing the largest uncertainty in current projections. Given that recent studies point towards atmospheric warming and melt intensification to become a dominant driver for future Antarctic ice mass loss, the monitoring of supraglacial lakes and their impacts on ice dynamics is of utmost importance. In this regard, recent progress in Earth Observation provides an abundance of high-resolution optical and Synthetic Aperture Radar (SAR) satellite data at unprecedented spatial and temporal coverage and greatly supports the monitoring of the Antarctic continent where ground-based mapping efforts are difficult to perform. As an automated mapping technique for supraglacial lake extent delineation in optical and SAR satellite imagery as well as a pan-Antarctic inventory of Antarctic supraglacial lakes at high spatial and temporal resolution is entirely missing, this thesis aims to advance the understanding of Antarctic surface hydrology through exploitation of spaceborne remote sensing.
In particular, a detailed literature review on spaceborne remote sensing of Antarctic supraglacial lakes identified several research gaps including the lack of (1) an automated mapping technique for optical or SAR satellite data that is transferable in space and time, (2) high-resolution supraglacial lake extent mappings at intra-annual and inter-annual temporal resolution and (3) large-scale mapping efforts across the entire Antarctic continent. In addition, past method developments were found to be restricted to purely visual, manual or semi-automated mapping techniques hindering their application to multi-temporal satellite imagery at large-scale. In this context, the development of automated mapping techniques was mainly limited by sensor-specific characteristics including the similar appearance of supraglacial lakes and other ice sheet surface features in optical or SAR data, the varying temporal signature of supraglacial lakes throughout the year as well as effects such as speckle noise and wind roughening in SAR data or cloud coverage in optical data. To overcome these limitations, this thesis exploits methods from artificial intelligence and big data processing for development of an automated processing chain for supraglacial lake extent delineation in Sentinel-1 SAR and optical Sentinel-2 satellite imagery. The combination of both sensor types enabled to capture both surface and subsurface lakes as well as to acquire data during cloud cover or wind roughening of lakes. For Sentinel-1, a deep convolutional neural network based on residual U-Net was trained on the basis of 21,200 labeled Sentinel-1 SAR image patches covering 13 Antarctic regions. Similarly, optical Sentinel-2 data were collected over 14 Antarctic regions and used for training of a Random Forest classifier. Optical and SAR classification products were combined through decision-level fusion at bi-weekly temporal scale and unprecedented 10 m spatial resolution. Finally, the method was implemented as part of DLR’s High-Performance Computing infrastructure allowing for an automated processing of large amounts of data including all required pre- and postprocessing steps. The results of an accuracy assessment over independent test scenes highlighted the functionality of the classifiers returning accuracies of 93% and 95% for supraglacial lakes in Sentinel-1 and Sentinel-2 satellite imagery, respectively.
Exploiting the full archive of Sentinel-1 and Sentinel-2, the developed framework for the first time enabled the monitoring of seasonal characteristics of Antarctic supraglacial lakes over six major ice shelves in 2015-2021. In particular, the results for API ice shelves revealed low lake coverage during 2015-2018 and particularly high lake coverage during the 2019-2020 and 2020-2021 melting seasons. On the contrary, East Antarctic ice shelves were characterized by high lake coverage during 2016-2019 and
extremely low lake coverage during the 2020-2021 melting season. Over all six investigated ice shelves, the development of drainage systems was revealed highlighting an increased risk for ice shelf instability. Through statistical correlation analysis with climate data at varying time lags as well as annual data on Southern Hemisphere atmospheric modes, environmental drivers for meltwater ponding were revealed. In addition, the influence of the local glaciological setting was investigated through computation of annual recurrence times of lakes. Over both ice sheet regions, the complex interplay between local, regional and large-scale environmental drivers was found to control supraglacial lake formation despite local to regional discrepancies, as revealed through pixel-based correlation analysis. Local control factors included the ice surface topography, the ice shelf geometry, the presence of low-albedo features as well as a reduced firn air content and were found to exert strong control on lake distribution. On the other hand, regional controls on lake evolution were revealed to be the amount of incoming solar radiation, air temperature and wind occurrence. While foehn winds were found to dictate lake evolution over the API, katabatic winds influenced lake ponding in East Antarctica. Furthermore, the regional near-surface climate was shown to be driven by large-scale atmospheric modes and teleconnections with the tropics. Overall, the results highlight that similar driving factors control supraglacial lake formation on the API and EAIS pointing towards their transferability to other Antarctic regions.
The area northeast of Sudbury, Ontario, is known for one of the largest unexplained geophysical anomalies on the Canadian Shield, the 1,200 km2 Temagami Anomaly. The geological cause of this regional magnetic, conductive and gravity feature has previously been modelled to be a mafic-ultramafic body at relatively great depth (2–15 km) of unknown age and origin, which may or may not be related to the meteorite impact-generated Sudbury Igneous Complex in its immediate vicinity. However, with a profound lack of outcrops and drill holes, the geological cause of the anomaly remains elusive, a genetic link to the 1.85 Ga Sudbury impact event purely speculative.
In search for any potential surface expression of the deep-seated cause of the Temagami Anomaly, this study provides a first, yet comprehensive petrological and geochemical assessment of exotic igneous dykes recently discovered in outcrops above, and drill cores into, the Temagami Anomaly. Based on cross-cutting field relations, petrographic studies, lithogeochemistry, whole-rock Nd-Sr-Pb isotope systematics, and U-Pb geochronology, it was possible to identify, and distinguish between, at least six different groups of igneous dykes: (i) Calc-alkaline quartz diorite dykes related to the 1.85 Ga Sudbury Igneous Complex (locally termed Offset Dykes); (ii) tholeiitic quartz diabase of the regional 2.22 Ga Nipissing Suite/Senneterre Dyke Swarm; (iii) calc-alkaline quartz diabase of the regional 2.17 Ga Biscotasing Dyke Swarm; (iv) alkaline ultrabasic dykes correlated with the 1.88–1.86 Ga Circum-Superior Large Igneous Province (LIP); and (v) aplitic dykes as well as (vi) a hornblende syenite, the latter two of more ambiguous age and stratigraphic position.
The findings presented in this study – the discovery of three new Offset Dykes in particular – offer some unexpected insights into the geology and economic potential of one of the least explored areas of the world-class Sudbury Mining Camp as well as into the nature and distribution of both allochthonous and autochthonous impactites within one of the oldest and largest impact structures known on Earth. Not only do the geometric patterns of dyke (and breccia) distribution reaffirm previous notions of the existence of discrete ring structures in the sense of a ~200-km multi-ring basin, but they provide critical constraints as to the pre-erosional thickness and extent of the impact melt sheet, thus helping to identity new areas for Ni-Cu-PGE exploration. Furthermore, this study provides important insights into the pre-impact stratigraphy and the magmatic evolution of the region in general, which reveals to be much more complex, compositionally divers, and protracted than initially assumed. Of note is the discovery of rocks related to the 2.17 Ga Biscotasing and the 1.88–1.86 Ga Circum-Superior magmatic events, as these were not previously known to occur on the southeast margin of the Superior Craton. Shortly predating the Sudbury impact and being contemporaneous with ore-forming events at Thompson (Manitoba) and Raglan (Cape Smith), these magmatic rocks could provide the missing link between unusual mafic, pre-enriched, crustal target rocks, and the unique metal endowment of the Sudbury Impact Structure.
The actual geological cause of the Temagami Anomaly remains open to debate and requires the downward extension of existing bore holes as well as more detailed geophysical investigations. The hypothesis of a genetic relationship between Sudbury impact event and Temagami Anomaly is neither borne out by any evidence nor particularly realistic, even in case of an oblique impact, and should thus be abandoned. It is instead proposed, based on circumstantial evidence, that the anomaly might be explained by an ultramafic complex of the 1.88–1.86 Ga Circum-Superior LIP.
Optical remote sensing is an important tool in the study of animal behavior providing ecologists with the means to understand species-environment interactions in combination with animal movement data. However, differences in spatial and temporal resolution between movement and remote sensing data limit their direct assimilation. In this context, we built a data-driven framework to map resource suitability that addresses these differences as well as the limitations of satellite imagery. It combines seasonal composites of multiyear surface reflectances and optimized presence and absence samples acquired with animal movement data within a cross-validation modeling scheme. Moreover, it responds to dynamic, site-specific environmental conditions making it applicable to contrasting landscapes. We tested this framework using five populations of White Storks (Ciconia ciconia) to model resource suitability related to foraging achieving accuracies from 0.40 to 0.94 for presences and 0.66 to 0.93 for absences. These results were influenced by the temporal composition of the seasonal reflectances indicated by the lower accuracies associated with higher day differences in relation to the target dates. Additionally, population differences in resource selection influenced our results marked by the negative relationship between the model accuracies and the variability of the surface reflectances associated with the presence samples. Our modeling approach spatially splits presences between training and validation. As a result, when these represent different and unique resources, we face a negative bias during validation. Despite these inaccuracies, our framework offers an important basis to analyze species-environment interactions. As it standardizes site-dependent behavioral and environmental characteristics, it can be used in the comparison of intra- and interspecies environmental requirements and improves the analysis of resource selection along migratory paths. Moreover, due to its sensitivity to differences in resource selection, our approach can contribute toward a better understanding of species requirements.
By 2050, two-third of the world’s population will live in cities. In this study, we develop a framework for analyzing urban growth-related imperviousness in North Rhine-Westphalia (NRW) from the 1980s to date using Landsat data. For the baseline 2017-time step, official geodata was extracted to generate labelled data for ten classes, including three classes representing low, middle, and high level of imperviousness. We used the output of the 2017 classification and information based on radiometric bi-temporal change detection for retrospective classification. Besides spectral bands, we calculated several indices and various temporal composites, which were used as an input for Random Forest classification. The results provide information on three imperviousness classes with accuracies exceeding 75%. According to our results, the imperviousness areas grew continuously from 1985 to 2017, with a high imperviousness area growth of more than 167,000 ha, comprising around 30% increase. The information on the expansion of urban areas was integrated with population dynamics data to estimate the progress towards SDG 11. With the intensity analysis and the integration of population data, the spatial heterogeneity of urban expansion and population growth was analysed, showing that the urban expansion rates considerably excelled population growth rates in some regions in NRW. The study highlights the applicability of earth observation data for accurately quantifying spatio-temporal urban dynamics for sustainable urbanization and targeted planning.
Public safety and socio-economic development of the Jharia coalfield (JCF) in India is critically dependent on precise monitoring and comprehensive understanding of coal fires, which have been burning underneath for more than a century. This study utilizes New-Small BAseline Subset (N-SBAS) technique to compute surface deformation time series for 2017–2020 to characterize the spatiotemporal dynamics of coal fires in JCF. The line-of-sight (LOS) surface deformation estimated from ascending and descending Sentinel-1 SAR data are subsequently decomposed to derive precise vertical subsidence estimates. The most prominent subsidence (~22 cm) is observed in Kusunda colliery. The subsidence regions also correspond well with the Landsat-8 based thermal anomaly map and field evidence. Subsequently, the vertical surface deformation time-series is analyzed to characterize temporal variations within the 9.5 km\(^2\) area of coal fires. Results reveal that nearly 10% of the coal fire area is newly formed, while 73% persisted throughout the study period. Vulnerability analyses performed in terms of the susceptibility of the population to land surface collapse demonstrate that Tisra, Chhatatanr, and Sijua are the most vulnerable towns. Our results provide critical information for developing early warning systems and remediation strategies.
Supraglacial meltwater accumulation on ice sheets can be a main driver for accelerated ice discharge, mass loss, and global sea-level-rise. With further increasing surface air temperatures, meltwater-induced hydrofracturing, basal sliding, or surface thinning will cumulate and most likely trigger unprecedented ice mass loss on the Greenland and Antarctic ice sheets. While the Greenland surface hydrological network as well as its impacts on ice dynamics and mass balance has been studied in much detail, Antarctic supraglacial lakes remain understudied with a circum-Antarctic record of their spatio-temporal development entirely lacking. This study provides the first automated supraglacial lake extent mapping method using Sentinel-1 synthetic aperture radar (SAR) imagery over Antarctica and complements the developed optical Sentinel-2 supraglacial lake detection algorithm presented in our companion paper. In detail, we propose the use of a modified U-Net for semantic segmentation of supraglacial lakes in single-polarized Sentinel-1 imagery. The convolutional neural network (CNN) is implemented with residual connections for optimized performance as well as an Atrous Spatial Pyramid Pooling (ASPP) module for multiscale feature extraction. The algorithm is trained on 21,200 Sentinel-1 image patches and evaluated in ten spatially or temporally independent test acquisitions. In addition, George VI Ice Shelf is analyzed for intra-annual lake dynamics throughout austral summer 2019/2020 and a decision-level fused Sentinel-1 and Sentinel-2 maximum lake extent mapping product is presented for January 2020 revealing a more complete supraglacial lake coverage (~770 km\(^2\)) than the individual single-sensor products. Classification results confirm the reliability of the proposed workflow with an average Kappa coefficient of 0.925 and a F\(_1\)-score of 93.0% for the supraglacial water class across all test regions. Furthermore, the algorithm is applied in an additional test region covering supraglacial lakes on the Greenland ice sheet which further highlights the potential for spatio-temporal transferability. Future work involves the integration of more training data as well as intra-annual analyses of supraglacial lake occurrence across the whole continent and with focus on supraglacial lake development throughout a summer melt season and into Antarctic winter.
The monitoring of land cover and land use change is critical for assessing the provision of ecosystem services. One of the sources for long-term land cover change quantification is through the classification of historical and/or current maps. Little research has been done on historical maps using Object-Based Image Analysis (OBIA). This study applied an object-based classification using eCognition tool for analyzing the land cover based on historical maps in the Main river catchment, Upper Franconia, Germany. This allowed land use change analysis between the 1850s and 2015, a time span which covers the phase of industrialization of landscapes in central Europe. The results show a strong increase in urban area by 2600%, a severe loss of cropland (−24%), a moderate reduction in meadows (−4%), and a small gain in forests (+4%). The method proved useful for the application on historical maps due to the ability of the software to create semantic objects. The confusion matrix shows an overall accuracy of 82% for the automatic classification compared to manual reclassification considering all 17 sample tiles. The minimum overall accuracy was 65% for historical maps of poor quality and the maximum was 91% for very high-quality ones. Although accuracy is between high and moderate, coarse land cover patterns in the past and trends in land cover change can be analyzed. We conclude that such long-term analysis of land cover is a prerequisite for quantifying long-term changes in ecosystem services.
Forests in Germany cover around 11.4 million hectares and, thus, a share of 32% of Germany's surface area. Therefore, forests shape the character of the country's cultural landscape. Germany's forests fulfil a variety of functions for nature and society, and also play an important role in the context of climate levelling. Climate change, manifested via rising temperatures and current weather extremes, has a negative impact on the health and development of forests. Within the last five years, severe storms, extreme drought, and heat waves, and the subsequent mass reproduction of bark beetles have all seriously affected Germany’s forests. Facing the current dramatic extent of forest damage and the emerging long-term consequences, the effort to preserve forests in Germany, along with their diversity and productivity, is an indispensable task for the government. Several German ministries have and plan to initiate measures supporting forest health. Quantitative data is one means for sound decision-making to ensure the monitoring of the forest and to improve the monitoring of forest damage. In addition to existing forest monitoring systems, such as the federal forest inventory, the national crown condition survey, and the national forest soil inventory, systematic surveys of forest condition and vulnerability at the national scale can be expanded with the help of a satellite-based earth observation. In this review, we analysed and categorized all research studies published in the last 20 years that focus on the remote sensing of forests in Germany. For this study, 166 citation indexed research publications have been thoroughly analysed with respect to publication frequency, location of studies undertaken, spatial and temporal scale, coverage of the studies, satellite sensors employed, thematic foci of the studies, and overall outcomes, allowing us to identify major research and geoinformation product gaps.
Forecasting spatio-temporal dynamics on the land surface using Earth Observation data — a review
(2020)
Reliable forecasts on the impacts of global change on the land surface are vital to inform the actions of policy and decision makers to mitigate consequences and secure livelihoods. Geospatial Earth Observation (EO) data from remote sensing satellites has been collected continuously for 40 years and has the potential to facilitate the spatio-temporal forecasting of land surface dynamics. In this review we compiled 143 papers on EO-based forecasting of all aspects of the land surface published in 16 high-ranking remote sensing journals within the past decade. We analyzed the literature regarding research focus, the spatial scope of the study, the forecasting method applied, as well as the temporal and technical properties of the input data. We categorized the identified forecasting methods according to their temporal forecasting mechanism and the type of input data. Time-lagged regressions which are predominantly used for crop yield forecasting and approaches based on Markov Chains for future land use and land cover simulation are the most established methods. The use of external climate projections allows the forecasting of numerical land surface parameters up to one hundred years into the future, while auto-regressive time series modeling can account for intra-annual variances. Machine learning methods have been increasingly used in all categories and multivariate modeling that integrates multiple data sources appears to be more popular than univariate auto-regressive modeling despite the availability of continuously expanding time series data. Regardless of the method, reliable EO-based forecasting requires high-level remote sensing data products and the resulting computational demand appears to be the main reason that most forecasts are conducted only on a local scale. In the upcoming years, however, we expect this to change with further advances in the field of machine learning, the publication of new global datasets, and the further establishment of cloud computing for data processing.
Landslide susceptibility assessment in the Chiconquiaco Mountain Range area, Veracruz (Mexico)
(2022)
In Mexico, numerous landslides occur each year and Veracruz represents the state with the third highest number of events. Especially the Chiconquiaco Mountain Range, located in the central part of Veracruz, is highly affected by landslides and no detailed information on the spatial distribution of existing landslides or future occurrences is available. This leaves the local population exposed to an unknown threat and unable to react appropriately to this hazard or to consider the potential landslide occurrence in future planning processes.
Thus, the overall objective of the present study is to provide a comprehensive assessment of the landslide situation in the Chiconquiaco Mountain Range area. Here, the combination of a site-specific and a regional approach enables to investigate the causes, triggers, and process types as well as to model the landslide susceptibility for the entire study area.
For the site-specific approach, the focus lies on characterizing the Capulín landslide, which represents one of the largest mass movements in the area. In this context, the task is to develop a multi-methodological concept, which concentrates on cost-effective, flexible and non-invasive methods. This approach shows that the applied methods complement each other very well and their combination allows for a detailed characterization of the landslide.
The analyses revealed that the Capulín landslide is a complex mass movement type. It comprises rotational movement in the upper parts and translational movement in the lower areas, as well as flow processes at the flank and foot area and therefore, is classified as a compound slide-flow according to Cruden and Varnes (1996). Furthermore, the investigations show that the Capulín landslide represents a reactivation of a former process. This is an important new information, especially with regard to the other landslides identified in the study area. Both the road reconstructed after the landslide, which runs through the landslide mass, and the stream causing erosion processes at the foot of the landslide severely affect the stability of the landslide, making it highly susceptible to future reactivation processes. This is particularly important as the landslide is located only few hundred meters from the village El Capulín and an extension of the landslide area could cause severe damage.
The next step in the landslide assessment consists of integrating the data obtained in the site-specific approach into the regional analysis. Here, the focus lies on transferring the generated data to the entire study area. The developed methodological concept yields applicable results, which is supported by different validation approaches.
The susceptibility modeling as well as the landslide inventory reveal that the highest probability of landslides occurrence is related to the areas with moderate slopes covered by slope deposits. These slope deposits comprise material from old mass movements and erosion processes and are highly susceptible to landslides. The results give new insights into the landslide situation in the Chiconquiaco Mountain Range area, since previously landslide occurrence was related to steep slopes of basalt and andesite.
The susceptibility map is a contribution to a better assessment of the landslide situation in the study area and simultaneously proves that it is crucial to include specific characteristics of the respective area into the modeling process, otherwise it is possible that the local conditions will not be represented correctly.
Protection and recovery of natural resource and biodiversity requires accurate monitoring at multiple scales. Airborne Laser Scanning (ALS) provides high-resolution imagery that is valuable for monitoring structural changes to vegetation, providing a reliable reference for ecological analyses and comparison purposes, especially if used in conjunction with other remote-sensing and field products. However, the potential of ALS data has not been fully exploited, due to limits in data availability and validation. To bridge this gap, the global network for airborne laser scanner data (GlobALS) has been established as a worldwide network of ALS data providers that aims at linking those interested in research and applications related to natural resources and biodiversity monitoring. The network does not collect data itself but collects metadata and facilitates networking and collaborative research amongst the end-users and data providers. This letter describes this facility, with the aim of broadening participation in GlobALS.
In China, freshwater is an increasingly scarce resource and wetlands are under great pressure. This study focuses on China's second largest freshwater lake in the middle reaches of the Yangtze River — the Dongting Lake — and its surrounding wetlands, which are declared a protected Ramsar site. The Dongting Lake area is also a research region of focus within the Sino-European Dragon Programme, aiming for the international collaboration of Earth Observation researchers. ESA's Copernicus Programme enables comprehensive monitoring with area-wide coverage, which is especially advantageous for large wetlands that are difficult to access during floods. The first year completely covered by Sentinel-1 SAR satellite data was 2016, which is used here to focus on Dongting Lake's wetland dynamics. The well-established, threshold-based approach and the high spatio-temporal resolution of Sentinel-1 imagery enabled the generation of monthly surface water maps and the analysis of the inundation frequency at a 10 m resolution. The maximum extent of the Dongting Lake derived from Sentinel-1 occurred in July 2016, at 2465 km\(^2\), indicating an extreme flood year. The minimum size of the lake was detected in October, at 1331 km\(^2\). Time series analysis reveals detailed inundation patterns and small-scale structures within the lake that were not known from previous studies. Sentinel-1 also proves to be capable of mapping the wetland management practices for Dongting Lake polders and dykes. For validation, the lake extent and inundation duration derived from the Sentinel-1 data were compared with excerpts from the Global WaterPack (frequently derived by the German Aerospace Center, DLR), high-resolution optical data, and in situ water level data, which showed very good agreement for the period studied. The mean monthly extent of the lake in 2016 from Sentinel-1 was 1798 km\(^2\), which is consistent with the Global WaterPack, deviating by only 4%. In summary, the presented analysis of the complete annual time series of the Sentinel-1 data provides information on the monthly behavior of water expansion, which is of interest and relevance to local authorities involved in water resource management tasks in the region, as well as to wetland conservationists concerned with the Ramsar site wetlands of Dongting Lake and to local researchers.
Supraglacial lakes can have considerable impact on ice sheet mass balance and global sea-level-rise through ice shelf fracturing and subsequent glacier speedup. In Antarctica, the distribution and temporal development of supraglacial lakes as well as their potential contribution to increased ice mass loss remains largely unknown, requiring a detailed mapping of the Antarctic surface hydrological network. In this study, we employ a Machine Learning algorithm trained on Sentinel-2 and auxiliary TanDEM-X topographic data for automated mapping of Antarctic supraglacial lakes. To ensure the spatio-temporal transferability of our method, a Random Forest was trained on 14 training regions and applied over eight spatially independent test regions distributed across the whole Antarctic continent. In addition, we employed our workflow for large-scale application over Amery Ice Shelf where we calculated interannual supraglacial lake dynamics between 2017 and 2020 at full ice shelf coverage. To validate our supraglacial lake detection algorithm, we randomly created point samples over our classification results and compared them to Sentinel-2 imagery. The point comparisons were evaluated using a confusion matrix for calculation of selected accuracy metrics. Our analysis revealed wide-spread supraglacial lake occurrence in all three Antarctic regions. For the first time, we identified supraglacial meltwater features on Abbott, Hull and Cosgrove Ice Shelves in West Antarctica as well as for the entire Amery Ice Shelf for years 2017–2020. Over Amery Ice Shelf, maximum lake extent varied strongly between the years with the 2019 melt season characterized by the largest areal coverage of supraglacial lakes (~763 km\(^2\)). The accuracy assessment over the test regions revealed an average Kappa coefficient of 0.86 where the largest value of Kappa reached 0.98 over George VI Ice Shelf. Future developments will involve the generation of circum-Antarctic supraglacial lake mapping products as well as their use for further methodological developments using Sentinel-1 SAR data in order to characterize intraannual supraglacial meltwater dynamics also during polar night and independent of meteorological conditions. In summary, the implementation of the Random Forest classifier enabled the development of the first automated mapping method applied to Sentinel-2 data distributed across all three Antarctic regions.
The Mesoproterozoic Aggeneys-Gamsberg ore district, South Africa, is one of the world´s largest sulfidic base metal concentrations and well-known as a prime example of Broken Hill-type base metal deposits, traditionally interpreted as metamorphosed SEDEX deposits. Within this district, the Gamsberg deposit stands out for its huge size and strongly Zn-dominated ore ( >14 Mt contained Zn). New electron microprobe analyses and element abundance maps of sulfides and silicates point to fluid-driven sulfidation during retrograde metamorphism. Differences in the chemistry of sulfide inclusions within zoned garnet grains reflect different degrees of interaction of sulfides with high metal/sulfur-ratio with a sulfur-rich metamorphic fluid. Independent evidence of sulfidation during retrograde metamorphism comes from graphic-textured sulfide aggregates that previously have been interpreted as quenched sulfidic melts, replacement of pyrrhotite by pyrite along micro-fractures, and sulfides in phyllic alteration zones. Limited availability of fluid under retrograde conditions caused locally different degrees of segregation of Fe-rich sphalerite into Zn-rich sphalerite and pyrite, and thus considerable heterogeneity in sphalerite chemistry. The invoked sulfur-rich metamorphic fluids would have been able to sulfidize base metal-rich zones in the whole deposit and thus camouflage a potential pre-metamorphic oxidation. These findings support the recently established hypothesis of a pre-Klondikean weathering-induced oxidation event and challenge the traditional explanation of Broken Hill-type deposits as merely metamorphosed SEDEX deposits. Instead, we suggest that the massive sulfide deposits experienced a complex history, starting with initial SEDEX-type mineralization, followed by near-surface oxidation with spatial metal separation, and then sulfidation of this oxidized ore during medium- to high-grade metamorphism.
During strong El Niño events, below-average rainfall is expected in large parts of southern Africa. The 1992 El Niño season was associated with one of the worst drought episodes in large parts of South Africa. Using reanalysis data set from NCEP-NCAR, this study examined circulation types (CTs) in Africa south of the equator that are statistically related to the El Niño signal in the southwest Indian Ocean and the implication of this relationship during the 1992 drought episode in South Africa. A statistically significant correlation was found between the above-average Nino 3.4 index and a CT that features widespread cyclonic activity in the tropical southwest Indian Ocean, coupled with a weaker state of the south Indian Ocean high-pressure. During the analysis period, it was found that the El Niño signal enhanced the amplitude of the aforementioned CT. The impacts of the El Niño signal on CTs in southern Africa, which could have contributed to the 1992 severe drought episode in South Africa, were reflected in (i) robust decrease in the frequency of occurrence of the austral summer climatology pattern of atmospheric circulation that favors southeasterly moisture fluxes, advected by the South Indian Ocean high-pressure; (ii) modulation of easterly moisture fluxes, advected by the South Atlantic Ocean high-pressure, ridging south of South Africa; (iii) and enhancement of the amplitude of CTs that both enhances subsidence over South Africa, and associated with the dominance of westerlies across the Agulhas current. Under the ssp585 scenario, the analyzed climate models suggested that the impact of radiative heating on the CT significantly related to El Niño might result in an anomalous increase in surface pressure at the eastern parts of South Africa.
Atmospheric circulation is a vital process in the transport of heat, moisture, and pollutants around the globe. The variability of rainfall depends to some extent on the atmospheric circulation. This paper investigates synoptic situations in southern Africa that can be associated with wet days and dry days in Free State, South Africa, in addition to the underlying dynamics. Principal component analysis was applied to the T-mode matrix (variable is time series and observation is grid points at which the field was observed) of daily mean sea level pressure field from 1979 to 2018 in classifying the circulation patterns in southern Africa. 18 circulation types (CTs) were classified in the study region. From the linkage of the CTs to the observed rainfall data, from 11 stations in Free State, it was found that dominant austral winter and late austral autumn CTs have a higher probability of being associated with dry days in Free State. Dominant austral summer and late austral spring CTs were found to have a higher probability of being associated with wet days in Free State. Cyclonic/anti-cyclonic activity over the southwest Indian Ocean, explained to a good extent, the inter-seasonal variability of rainfall in Free State. The synoptic state associated with a stronger anti-cyclonic circulation at the western branch of the South Indian Ocean high-pressure, during austral summer, leading to enhanced low-level moisture transport by southeast winds was found to have the highest probability of being associated with above-average rainfall in most regions in Free State. On the other hand, the synoptic state associated with enhanced transport of cold dry air, by the extratropical westerlies, was found to have the highest probability of being associated with (winter) dryness in Free State.
Die Covid-19-Pandemie gilt in vielen gesellschaftlichen Teilbereichen als Beschleuniger für Transformationsprozesse. Auch im Bereich der Organisation urbaner Logistik und Einzelhandelslandschaften etablieren sich neue Akteur*innen und Funktionen. Logistiker*innen integrieren lokale Onlinemarktplätze in ihre Profile und der stationäre Einzelhandel generiert Wettbewerbsfähigkeit gegenüber großen Onlinehändler*innen über die Nutzung lokaler Radlogistiknetzwerke, mittels derer Lieferungen noch am Tag der Bestellung (Same-Day-Delivery) verteilt werden können. Damit leisten die involvierten Akteur*innen potenziell auch einen Beitrag zur Nachhaltigkeitstransformation im Bereich urbaner Logistiksysteme. Im Fokus steht das Fallbeispiel WüLivery, ein Kooperationsprojekt des Stadtmarketingvereins, der Wirtschaftsförderung, Radlogistiker*innen sowie Einzelhändler*innen in Würzburg, welches während des zweiten coronabedingten Lockdowns im November 2020 umgesetzt wurde. Die entstehenden Dynamiken und Organisationsformen werden auf Basis von 11 Expert*inneninterviews dargestellt und analysiert. Es kann gezeigt werden, dass städtische Akteur*innen grundlegende Mediator*innen für Transformationsprozesse darstellen und Einzelhändler*innen und lokale Onlinemarktplätze als Katalysator*innen fungieren können. Das ist auch vor dem Hintergrund planerischer und politischer Kommunikationsprozesse zur Legitimation neuer Verkehrsinfrastrukturen nutzbar, da die einzelnen Akteur*innengruppen in Austausch kommen und ein gesteigertes Bewusstsein für die jeweiligen Bedarfe entsteht.
The Kunduz River is one of the main tributaries of the Amu Darya Basin in North Afghanistan. Many communities live in the Kunduz River Basin (KRB), and its water resources have been the basis of their livelihoods for many generations. This study investigates climate change impacts on the KRB catchment. Rare station data are, for the first time, used to analyze systematic trends in temperature, precipitation, and river discharge over the past few decades, while using Mann–Kendall and Theil–Sen trend statistics. The trends show that the hydrology of the basin changed significantly over the last decades. A comparison of landcover data of the river basin from 1992 and 2019 shows significant changes that have additional impact on the basin hydrology, which are used to interpret the trend analysis. There is considerable uncertainty due to the data scarcity and gaps in the data, but all results indicate a strong tendency towards drier conditions. An extreme warming trend, partly above 2 °C since the 1960s in combination with a dramatic precipitation decrease by more than −30% lead to a strong decrease in river discharge. The increasing glacier melt compensates the decreases and leads to an increase in runoff only in the highland parts of the upper catchment. The reduction of water availability and the additional stress on the land leads to a strong increase of barren land and a reduction of vegetation cover. The detected trends and changes in the basin hydrology demand an active management of the already scarce water resources in order to sustain water supply for agriculture and ecosystems in the KRB.
Land surface temperature (LST) is a fundamental parameter within the system of the Earth’s surface and atmosphere, which can be used to describe the inherent physical processes of energy and water exchange. The need for LST has been increasingly recognised in agriculture, as it affects the growth phases of crops and crop yields. However, challenges in overcoming the large discrepancies between the retrieved LST and ground truth data still exist. Precise LST measurement depends mainly on accurately deriving the surface emissivity, which is very dynamic due to changing states of land cover and plant development. In this study, we present an LST retrieval algorithm for the combined use of multispectral optical and thermal UAV images, which has been optimised for operational applications in agriculture to map the heterogeneous and diverse agricultural crop systems of a research campus in Germany (April 2018). We constrain the emissivity using certain NDVI thresholds to distinguish different land surface types. The algorithm includes atmospheric corrections and environmental thermal emissions to minimise the uncertainties. In the analysis, we emphasise that the omission of crucial meteorological parameters and inaccurately determined emissivities can lead to a considerably underestimated LST; however, if the emissivity is underestimated, the LST can be overestimated. The retrieved LST is validated by reference temperatures from nearby ponds and weather stations. The validation of the thermal measurements indicates a mean absolute error of about 0.5 K. The novelty of the dual sensor system is that it simultaneously captures highly spatially resolved optical and thermal images, in order to construct the precise LST ortho-mosaics required to monitor plant diseases and drought stress and validate airborne and satellite data.
Information about land use/land cover (LULC) and their changes is useful for different stakeholders to assess future pathways of sustainable land use for food production as well as for nature conservation. In this study, we assess LULC changes in the Kilombero catchment in Tanzania, an important area of recent development in East Africa. LULC change is assessed in two ways: first, post-classification comparison (PCC) which allows us to directly assess changes from one LULC class to another, and second, spectral change detection. We perform LULC classification by applying random forests (RF) on sets of multitemporal metrics that account for seasonal within-class dynamics. For the spectral change detection, we make use of the robust change vector analysis (RCVA) and determine those changes that do not necessarily lead to another class. The combination of the two approaches enables us to distinguish areas that show (a) only PCC changes, (b) only spectral changes that do not affect the classification of a pixel, (c) both types of change, or (d) no changes at all. Our results reveal that only one-quarter of the catchment has not experienced any change. One-third shows both, spectral changes and LULC conversion. Changes detected with both methods predominantly occur in two major regions, one in the West of the catchment, one in the Kilombero floodplain. Both regions are important areas of food production and economic development in Tanzania. The Kilombero floodplain is a Ramsar protected area, half of which was converted to agricultural land in the past decades. Therefore, LULC monitoring is required to support sustainable land management. Relatively poor classification performances revealed several challenges during the classification process. The combined approach of PCC and RCVA allows us to detect spatial patterns of LULC change at distinct dimensions and intensities. With the assessment of additional classifier output, namely class-specific per-pixel classification probabilities and derived parameters, we account for classification uncertainty across space. We overlay the LULC change results and the spatial assessment of classification reliability to provide a thorough picture of the LULC changes taking place in the Kilombero catchment.
Illegal small-scale mining (galamsey) in South-Western Ghana has grown tremendously in the last decade and caused significant environmental degradation. Excessive cloud cover in the area has limited the use of optical remote sensing data to map and monitor the extent of these activities. This study investigated the use of annual time-series Sentinel-1 data to map and monitor illegal mining activities along major rivers in South-Western Ghana between 2015 and 2019. A change detection approach, based on three time-series features — minimum, mean, maximum — was used to compute a backscatter threshold value suitable to identify/detect mining-induced land cover changes in the study area. Compared to the mean and maximum, the minimum time-series feature (in both VH and VV polarization) was found to be more sensitive to changes in backscattering within the period of investigation. Our approach permitted the detection of new illegal mining areas on an annual basis. A backscatter threshold value of +1.65 dB was found suitable for detecting illegal mining activities in the study area. Application of this threshold revealed illegal mining area extents of 102 km\(^2\), 60 km\(^2\) and 33 km\(^2\) for periods 2015/2016–2016/2017, 2016/2017–2017/2018 and 2017/2018–2018/2019, respectively. The observed decreasing trend in new illegal mining areas suggests that efforts at stopping illegal mining yielded positive results in the period investigated. Despite the advantages of Synthetic Aperture Radar data in monitoring phenomena in cloud-prone areas, our analysis revealed that about 25% of the Sentinel-1 data, mostly acquired in March and October (beginning and end of rainy season respectively), were unusable due to atmospheric effects from high intensity rainfall events. Further investigation in other geographies and climatic regions is needed to ascertain the susceptibility of Sentinel-1 data to atmospheric conditions.
Many parts of sub-Saharan Africa (SSA) are prone to land use and land cover change (LULCC). In many cases, natural systems are converted into agricultural land to feed the growing population. However, despite climate change being a major focus nowadays, the impacts of these conversions on water resources, which are essential for agricultural production, is still often neglected, jeopardizing the sustainability of the socio-ecological system. This study investigates historic land use/land cover (LULC) patterns as well as potential future LULCC and its effect on water quantities in a complex tropical catchment in Tanzania. It then compares the results using two climate change scenarios. The Land Change Modeler (LCM) is used to analyze and to project LULC patterns until 2030 and the Soil and Water Assessment Tool (SWAT) is utilized to simulate the water balance under various LULC conditions. Results show decreasing low flows by 6–8% for the LULC scenarios, whereas high flows increase by up to 84% for the combined LULC and climate change scenarios. The effect of climate change is stronger compared to the effect of LULCC, but also contains higher uncertainties. The effects of LULCC are more distinct, although crop specific effects show diverging effects on water balance components. This study develops a methodology for quantifying the impact of land use and climate change and therefore contributes to the sustainable management of the investigated catchment, as it shows the impact of environmental change on hydrological extremes (low flow and floods) and determines hot spots, which are critical for environmental development.
Large-area remote sensing time-series offer unique features for the extensive investigation of our environment. Since various error sources in the acquisition chain of datasets exist, only properly validated results can be of value for research and downstream decision processes. This review presents an overview of validation approaches concerning temporally dense time-series of land surface geo-information products that cover the continental to global scale. Categorization according to utilized validation data revealed that product intercomparisons and comparison to reference data are the conventional validation methods. The reviewed studies are mainly based on optical sensors and orientated towards global coverage, with vegetation-related variables as the focus. Trends indicate an increase in remote sensing-based studies that feature long-term datasets of land surface variables. The hereby corresponding validation efforts show only minor methodological diversification in the past two decades. To sustain comprehensive and standardized validation efforts, the provision of spatiotemporally dense validation data in order to estimate actual differences between measurement and the true state has to be maintained. The promotion of novel approaches can, on the other hand, prove beneficial for various downstream applications, although typically only theoretical uncertainties are provided.
Land cover is a key variable in monitoring applications and new processing technologies made deriving this information easier. Yet, classification algorithms remain dependent on samples collected on the field and field campaigns are limited by financial, infrastructural and political boundaries. Here, animal tracking data could be an asset. Looking at the land cover dependencies of animal behaviour, we can obtain land cover samples over places that are difficult to access. Following this premise, we evaluated the potential of animal movement data to map land cover. Specifically, we used 13 White Storks (Cicona cicona) individuals of the same population to map agriculture within three test regions distributed along their migratory track. The White Stork has adapted to foraging over agricultural lands, making it an ideal source of samples to map this land use. We applied a presence-absence modelling approach over a Normalized Difference Vegetation Index (NDVI) time series and validated our classifications, with high-resolution land cover information. Our results suggest White Stork movement is useful to map agriculture, however, we identified some limitations. We achieved high accuracies (F1-scores > 0.8) for two test regions, but observed poor results over one region. This can be explained by differences in land management practices. The animals preferred agriculture in every test region, but our data showed a biased distribution of training samples between irrigated and non-irrigated land. When both options occurred, the animals disregarded non-irrigated land leading to its misclassification as non-agriculture. Additionally, we found difference between the GPS observation dates and the harvest times for non-irrigated crops. Given the White Stork takes advantage of managed land to search for prey, the inactivity of these fields was the likely culprit of their underrepresentation. Including more species attracted to agriculture - with other land-use dependencies and observation times - can contribute to better results in similar applications.
Advances in remote inventory and analysis of forest resources during the last decade have reached a level to be now considered as a crucial complement, if not a surrogate, to the long-existing field-based methods. This is mostly reflected in not only the use of multiple-band new active and passive remote sensing data for forest inventory, but also in the methodic and algorithmic developments and/or adoptions that aim at maximizing the predictive or calibration performances, thereby minimizing both random and systematic errors, in particular for multi-scale spatial domains. With this in mind, this editorial note wraps up the recently-published Remote Sensing special issue “Remote Sensing-Based Forest Inventories from Landscape to Global Scale”, which hosted a set of state-of-the-art experiments on remotely sensed inventory of forest resources conducted by a number of prominent researchers worldwide.
The alarming increase in the magnitude and spatiotemporal patterns of changes in composition, structure and function of forest ecosystems during recent years calls for enhanced cross-border mitigation and adaption measures, which strongly entail intensified research to understand the underlying processes in the ecosystems as well as their dynamics. Remote sensing data and methods are nowadays the main complementary sources of synoptic, up-to-date and objective information to support field observations in forest ecology. In particular, analysis of three-dimensional (3D) remote sensing data is regarded as an appropriate complement, since they are hypothesized to resemble the 3D character of most forest attributes. Following their use in various small-scale forest structural analyses over the past two decades, these sources of data are now on their way to be integrated in novel applications in fields like citizen science, environmental impact assessment, forest fire analysis, and biodiversity assessment in remote areas. These and a number of other novel applications provide valuable material for the Forests special issue “3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function”, which shows the promising future of these technologies and improves our understanding of the potentials and challenges of 3D remote sensing in practical forest ecology worldwide.
Human health is known to be affected by the physical environment. Various environmental influences have been identified to benefit or challenge people's physical condition. Their heterogeneous distribution in space results in unequal burdens depending on the place of living. In addition, since societal groups tend to also show patterns of segregation, this leads to unequal exposures depending on social status. In this context, environmental justice research examines how certain social groups are more affected by such exposures. Yet, analyses of this per se spatial phenomenon are oftentimes criticized for using “essentially aspatial” data or methods which neglect local spatial patterns by aggregating environmental conditions over large areas. Recent technological and methodological developments in satellite remote sensing have proven to provide highly detailed information on environmental conditions. This narrative review therefore discusses known influences of the urban environment on human health and presents spatial data and applications for analyzing these influences. Furthermore, it is discussed how geographic data are used in general and in the interdisciplinary research field of environmental justice in particular. These considerations include the modifiable areal unit problem and ecological fallacy. In this review we argue that modern earth observation data can represent an important data source for research on environmental justice and health. Especially due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics. As a future perspective, ongoing earth observation missions, as well as processing architectures, ensure data availability and applicability of ’big earth data’ for future environmental justice analyses.
Estimating penetration-related X-band InSAR elevation bias: a study over the Greenland ice sheet
(2019)
Accelerating melt on the Greenland ice sheet leads to dramatic changes at a global scale. Especially in the last decades, not only the monitoring, but also the quantification of these changes has gained considerably in importance. In this context, Interferometric Synthetic Aperture Radar (InSAR) systems complement existing data sources by their capability to acquire 3D information at high spatial resolution over large areas independent of weather conditions and illumination. However, penetration of the SAR signals into the snow and ice surface leads to a bias in measured height, which has to be corrected to obtain accurate elevation data. Therefore, this study purposes an easy transferable pixel-based approach for X-band penetration-related elevation bias estimation based on single-pass interferometric coherence and backscatter intensity which was performed at two test sites on the Northern Greenland ice sheet. In particular, the penetration bias was estimated using a multiple linear regression model based on TanDEM-X InSAR data and IceBridge laser-altimeter measurements to correct TanDEM-X Digital Elevation Model (DEM) scenes. Validation efforts yielded good agreement between observations and estimations with a coefficient of determination of R\(^2\) = 68% and an RMSE of 0.68 m. Furthermore, the study demonstrates the benefits of X-band penetration bias estimation within the application context of ice sheet elevation change detection.
Invasive plant species are major threats to biodiversity. They can be identified and monitored by means of high spatial resolution remote sensing imagery. This study aimed to test the potential of multiple very high-resolution (VHR) optical multispectral and stereo imageries (VHRSI) at spatial resolutions of 1.5 and 5 m to quantify the presence of the invasive lantana (Lantana camara L.) and predict its distribution at large spatial scale using medium-resolution fractional cover analysis. We created initial training data for fractional cover analysis by classifying smaller extent VHR data (SPOT-6 and RapidEye) along with three dimensional (3D) VHRSI derived digital surface model (DSM) datasets. We modelled the statistical relationship between fractional cover and spectral reflectance for a VHR subset of the study area located in the Himalayan region of India, and finally predicted the fractional cover of lantana based on the spectral reflectance of Landsat-8 imagery of a larger spatial extent. We classified SPOT-6 and RapidEye data and used the outputs as training data to create continuous field layers of Landsat-8 imagery. The area outside the overlapping region was predicted by fractional cover analysis due to the larger extent of Landsat-8 imagery compared with VHR datasets. Results showed clear discrimination of understory lantana from upperstory vegetation with 87.38% (for SPOT-6), and 85.27% (for RapidEye) overall accuracy due to the presence of additional VHRSI derived DSM information. Independent validation for lantana fractional cover estimated root-mean-square errors (RMSE) of 11.8% (for RapidEye) and 7.22% (for SPOT-6), and R\(^2\) values of 0.85 and 0.92 for RapidEye (5 m) and SPOT-6 (1.5 m), respectively. Results suggested an increase in predictive accuracy of lantana within forest areas along with increase in the spatial resolution for the same Landsat-8 imagery. The variance explained at 1.5 m spatial resolution to predict lantana was 64.37%, whereas it decreased by up to 37.96% in the case of 5 m spatial resolution data. This study revealed the high potential of combining small extent VHR and VHRSI- derived 3D optical data with larger extent, freely available satellite data for identification and mapping of invasive species in mountainous forests and remote regions.
Via providing various ecosystem services, the old-growth Hyrcanian forests play a crucial role in the environment and anthropogenic aspects of Iran and beyond. The amount of growing stock volume (GSV) is a forest biophysical parameter with great importance in issues like economy, environmental protection, and adaptation to climate change. Thus, accurate and unbiased estimation of GSV is also crucial to be pursued across the Hyrcanian. Our goal was to investigate the potential of ALOS-2 and Sentinel-1's polarimetric features in combination with Sentinel-2 multi-spectral features for the GSV estimation in a portion of heterogeneously-structured and mountainous Hyrcanian forests. We used five different kernels by the support vector regression (nu-SVR) for the GSV estimation. Because each kernel differently models the parameters, we separately selected features for each kernel by a binary genetic algorithm (GA). We simultaneously optimized R\(^2\) and RMSE in a suggested GA fitness function. We calculated R\(^2\), RMSE to evaluate the models. We additionally calculated the standard deviation of validation metrics to estimate the model's stability. Also for models over-fitting or under-fitting analysis, we used mean difference (MD) index. The results suggested the use of polynomial kernel as the final model. Despite multiple methodical challenges raised from the composition and structure of the study site, we conclude that the combined use of polarimetric features (both dual and full) with spectral bands and indices can improve the GSV estimation over mixed broadleaf forests. This was partially supported by the use of proposed evaluation criterion within the GA, which helped to avoid the curse of dimensionality for the applied SVR and lowest over estimation or under estimation.
Projected climate changes for the 21st century may cause great uncertainties on the hydrology of a river basin. This study explored the impacts of climate change on the water balance and hydrological regime of the Jhelum River Basin using the Soil and Water Assessment Tool (SWAT). Two downscaling methods (SDSM, Statistical Downscaling Model and LARS-WG, Long Ashton Research Station Weather Generator), three Global Circulation Models (GCMs), and two representative concentration pathways (RCP4.5 and RCP8.5) for three future periods (2030s, 2050s, and 2090s) were used to assess the climate change impacts on flow regimes. The results exhibited that both downscaling methods suggested an increase in annual streamflow over the river basin. There is generally an increasing trend of winter and autumn discharge, whereas it is complicated for summer and spring to conclude if the trend is increasing or decreasing depending on the downscaling methods. Therefore, the uncertainty associated with the downscaling of climate simulation needs to consider, for the best estimate, the impact of climate change, with its uncertainty, on a particular basin. The study also resulted that water yield and evapotranspiration in the eastern part of the basin (sub-basins at high elevation) would be most affected by climate change. The outcomes of this study would be useful for providing guidance in water management and planning for the river basin under climate change.
Das Ziel dieser Arbeit war neue Eingangsdaten für die Landoberflächenbeschreibung des regionalen Klimamodells REMO zu finden und ins Modell zu integrieren, um die Vorhersagequalität des Modells zu verbessern. Die neuen Daten wurden so in das Modell eingebaut, dass die bisherigen Daten weiterhin als Option verfügbar sind. Dadurch kann überprüft werden, ob und in welchem Umfang sich die von jedem Klimamodell benötigten Rahmendaten auf Modellergebnisse auswirken. Im Zuge der Arbeit wurden viele unterschiedliche Daten und Methoden zur Generierung neuer Parameter miteinander verglichen, denn neben dem Ersetzen der konstanten Eingangswerte für verschiedene Oberflächenparameter und den damit verbundenen Änderungen wurden als zusätzliche Verbesserung auch Veränderungen an der Parametrisierung des Bodens speziell in Hinblick auf die Bodentemperaturen in REMO vorgenommen. Im Rahmen dieser Arbeit wurden die durch die verschiedenen Änderungen ausgelösten Auswirkungen für das CORDEX-Gebiet EUR-44 mit einer Auflösung von ca. 50km und für das in dem darin eingebetteten neu definierten Deutschlandgebiet GER-11 mit einer Auflösung von ca. 12km getestet sowie alle Änderungen anhand von verschiedenen Beobachtungsdatensätzen validiert.
Die vorgenommenen Arbeiten gliederten sich in drei Hauptteile. Der erste Teil bestand in dem vom eigentlichen Klimamodell unabhängigen Vergleich der verschiedenen Eingangsdaten auf unterschiedlichen Auflösungen und deren Performanz in allen Teilen der Erde, wobei ein besonderer Fokus auf der Qualität in den späteren Modellgebieten lag. Unter Berücksichtigung der Faktoren, wie einer globalen Verfügbarkeit der Daten, einer verbesserten räumlichen Auflösung und einer kostenlosen Nutzung der Daten sowie verschiedener Validationsergebnissen von anderen Studien, wurden in dieser Arbeit vier neue Topographiedatensätze (SRTM, ALOS, TANDEM und ASTER) und drei neue Bodendatensätze (FAOn, Soilgrid und HWSD) für die Verwendung im Präprozess von REMO aufbereitet und miteinander sowie mit den bisher in REMO verwendeten Daten verglichen. Auf Grundlage dieser Vergleichsstudien schieden bei den Topographiedaten die verwendeten Datensatz-Versionen von SRTM, ALOS und TANDEM für die in dieser Arbeit durchgeführten REMO-Läufe aus. Bei den neuen Bodendatensätzen wurde ausgenutzt, dass diese verschiedenen Bodeneigenschaften für unterschiedliche Tiefen als Karten zur Verfügung stellen. In REMO wurden bisher alle benötigten Bodenparameter abhängig von fünf verschiedenen Bodentexturklassen und einer zusätzlichen Torfklasse ausgewiesen und als konstant über die gesamte Modellbodensäule (bis ca. 10m) angenommen. Im zweiten Teil wurden auf Basis der im ersten Teil ausgewählten neuen Datensätze und den neu verfügbaren Bodenvariablen verschiedene Sensitivitätsstudien über das Beispieljahr 2000 durchgeführt. Dabei wurden verschiedene neue Parametrisierungen für die bisher aus der Textur abgeleiteten Bodenvariablen und die Parametrisierung von weiteren hydrologischen und thermalen Bodeneigenschaften verglichen. Ferner wurde aufgrund der neuen nicht über die Tiefe konstanten Bodeneigenschaften eine neue numerische Methode zur Berechnung der Bodentemperaturen der fünf Schichten in REMO getestet, welche wiederum andere Anpassungen erforderte. Der Test und die Auswahl der verschiedenen Datensatz- und Parametrisierungsversionen auf die Modellperformanz wurde in drei Experimentpläne unterteilt. Im ersten Plan wurden die Auswirkungen der ausgewählten Topographie- und Bodendatensätze überprüft. Der zweite Plan behandelte die Unterschiede der verschiedenen Parametrisierungsarten der Bodenvariablen hinsichtlich der verwendeten Variablen zur Berechnung der Bodeneigenschaften, der über die Tiefe variablen oder konstanten Eigenschaften und der verwendeten Berechnungsmethode der Bodentemperaturänderungen. Durch die Erkenntnisse aus diesen beiden Experimentplänen, die für beide Untersuchungsgebiete durchgeführt wurden, ergaben sich im dritten Plan weitere Parametrisierungsänderungen. Alle Änderungen dieses dritten Experimentplans wurden sukzessiv getestet, sodass der paarweise Vergleich von zwei aufeinanderfolgenden Modellläufen die Auswirkungen der Neuerung im jeweils zweiten Lauf widerspiegelt. Der letzte Teil der Arbeit bestand aus der Analyse von fünf längeren Modellläufen (2000-2018), die zur Überprüfung der Ergebnisse aus den Sensitivitätsstudien sowie zur Einschätzung der Performanz in weiteren teilweise extremen atmosphärischen Bedingungen durchgeführt wurden. Hierfür wurden die bisherige Modellversion von REMO (id01) für die beiden Untersuchungsgebiete EUR-44 und GER-11 als Referenzläufe, zwei aufgrund der Vergleichsergebnisse von Experimentplan 3 selektierte Modellversionen (id06 und id15a für GER-11) sowie die finale Version (id18a für GER-11), die alle vorgenommenen Änderungen dieser Arbeit enthält, ausgewählt.
Es stellte sich heraus, dass sowohl die neuen Topographiedaten als auch die neuen Bodendaten große Differenzen zu den bisherigen Daten in REMO haben. Zudem änderten sich die von diesen konstanten Eingangsdaten abgeleiteten Hilfsvariablen je nach verwendeter Parametrisierung sehr deutlich. Dies war besonders gut anhand der Bodenparameter zu erkennen. Sowohl die räumliche Verteilung als auch der Wertebereich der verschiedenen Modellversionen unterschieden sich stark. Eine Einschätzung der Qualität der resultierenden Parameter wurde jedoch dadurch erschwert, dass auch die verschiedenen zur Validierung herangezogenen Bodendatensätze für diese Parameter deutlich voneinander abweichen. Die finale Modellversion id18a ähnelte trotz der umfassenden Änderungen in den meisten Variablen den Ergebnissen der bisherigen REMO-Version. Je nach zeitlicher und räumlicher Aggregation sowie unterschiedlichen Regionen und Jahreszeiten wurden leichte Verbesserungen, aber auch leichte Verschlechterungen im Vergleich zu den klimatologischen Validationsdaten festgestellt. Größere Veränderungen im Vergleich zur bisherigen Modellversion konnten in den tieferen Bodenschichten aufgezeigt werden, welche allerdings aufgrund von fehlenden Validationsdaten nicht beurteilt werden konnten. Für alle 2m-Temperaturen konnte eine tendenzielle leichte Erwärmung im Vergleich zum bisherigen Modelllauf beobachtet werden, was sich einerseits negativ auf die ohnehin durchschnittlich zu hohe Minimumtemperatur, aber andererseits positiv auf die bisher zu niedrige Maximumtemperatur des Modells in den betrachteten Gebieten auswirkte. Im Niederschlagssignal und in den 10m-Windvariablen konnten keine signifikanten Änderungen nachgewiesen werden, obwohl die neue Topographie an manchen Stellen im Modellgebiet deutlich von der bisherigen abweicht. Des Weiteren variierte das Ranking der verschiedenen Modellversionen jeweils nach dem angewendeten Qualitätsindex.
Um diese Ergebnisse besser einordnen zu können, muss berücksichtigt werden, dass die neuen Daten für Modellgebiete mit 50 bzw. 12km räumlicher Auflösung und der damit verbundenen hydrostatischen Modellversion getestet wurden. Zudem sind vor allem in Fall der Topographie die bisher enthaltenen GTOPO-Daten (1km Auflösung) für die Aggregation auf diese gröbere Modellauflösung geeignet. Die bisherigen Bodendaten stoßen jedoch mit 50km Auflösung bereits an ihre Grenzen. Zusätzlich ist zu beachten, dass nicht nur die Mittelwerte dieser Daten, sondern auch deren Subgrid-Variabilität als Variablen im Modell für verschiedene Parametrisierungen verwendet werden. Daher ist es essentiell, dass die Eingangsdaten eine deutlich höhere Auflösung bereitstellen als die zur Modellierung definierte Auflösung. Für lokale Klimasimulationen mit Auflösungen im niedrigen Kilometerbereich spielen auch die Vertikalbewegungen (nicht-hydrostatische Modellversion) eine wichtige Rolle, die stark von der Topographie sowie deren horizontaler und vertikaler Änderungsrate beeinflusst werden, was die in dieser Arbeit eingebauten wesentlich höher aufgelösten Daten für die zukünftige Weiterentwicklung von REMO wertvoll machen kann.
Episodic low oxygenated conditions on the sea-floor are likely responsible for exceptional preservation of animal remains in the upper Amouslek Formation (lower Cambrian, Stage 3) on the northern slope of the western Anti-Atlas, Morocco. This stratigraphic interval has yielded trilobite, brachiopod, and hyolith fossils with preserved soft parts, including some of the oldest known trilobite guts. The "Souss fossil lagerstatte" (newly proposed designation) represents the first Cambrian fossil lagerstatte in Cambrian strata known from Africa and is one of the oldest trilobite-bearing fossil lagerstatten on Earth. Inter-regional correlation of the Souss fossil lagerstatte in West Gondwana suggests its development during an interval of high eustatic levels recorded by dark shales that occur in informal upper Cambrian Series 2 in Siberia, South China, and East Gondwana.
Die imperiale Lebensweise westlicher Industrienationen, die sich durch ein permanentes Streben nach Wirtschaftswachstum ausdrückt, bringt den Planeten an die Grenzen seiner Tragfähigkeit. In den letzten Jahren wurden jedoch – bestärkt durch die Weltwirtschaftskrise 2007/08 – Alternativen zum Modell des permanenten Wachstums immer populärer, die sich anstatt auf ökonomischen Wohlstand vermehrt auf soziale und ökologische Belange des gesellschaftlichen Zusammenlebens fokussierten. Unter dem Begriff der Postwachstumsbewegung sammelten sich Ansätze, Ideen und Akteure, die gemeinsam für eine Zukunft fernab jeglicher Wachstumszwänge und innerhalb der planetaren Grenzen kämpfen.
Vor dem Hintergrund der zunehmenden sozialen und ökologischen Herausforderungen wurden nun erstmals sozial-ökologische Nischenakteure aus drei unterschiedlichen Bereichen der Postwachstumsbewegung gemeinsam in einem Forschungsvorhaben – unter besonderer Berücksichtigung gesellschaftlicher, organisatorischer und territorialer Einbettungsprozesse – untersucht. Eingebettet ist diese Untersuchung in den theoretisch-konzeptionellen Ansatz der sozial-ökologischen Transformation, deren inkrementeller Wandel mithilfe der Multi-Level-Perspektive beschrieben werden kann. Die Kombination dieses spezifischen theoretisch-konzeptionellen Ansatzes und der empirischen Erhebung ist das Alleinstellungsmerkmal der vorliegenden Untersuchung.
Es zeigte sich, dass alle untersuchten Nischenakteure eine deutlich progressive Unternehmungsphilosophie vertreten, die häufig in einer Unternehmungsorganisation mit flachen Hierarchien und konsensbasierten Entscheidungsfindungen mündet. Besonders gesellschaftliche Einbettungsprozesse bedingen den Erfolg oder Misserfolg der Nischenentwicklung. Organisatorische Einbettung kommt derweil vor allem im Aufbau weitreichender Netzwerkstrukturen zum Tragen, die die Innovationsfähigkeit und Stabilität der Nische unterstützen. Eine starke territoriale Einbettung steigert den lokal-regionalen Einfluss der Nischeninnovationen und generiert Rückhalt in der Bevölkerung.
This study examines the relationship between variations of the Southern Annular Mode (SAM) and black carbon (BC) at 550 nm aerosol optical depth (AOD) in the Western Cape province (WC). Variations of the positive (negative) phase of the SAM are found to be related to regional circulation types (CTs) in southern Africa, associated with suppressed (enhanced) westerly wind over the WC through the southward (northward) migration of Southern Hemisphere mid-latitude cyclones. The CTs related to positive (negative) SAM anomalies induce stable (unstable) atmospheric conditions over the southwestern regions of the WC, especially during the austral winter and autumn seasons. Through the control of CTs, positive (negative) SAM phases tend to contribute to the build-up (dispersion and dilution) of BC in the study region because they imply dry (wet) conditions which favor the build-up (washing out) of pollutant particles in the atmosphere. Indeed, recent years with an above-average frequency of CTs related to positive (negative) SAM anomalies are associated with a high (low) BC AOD over southwesternmost Africa.
Sacred water canals or lakes, which provided water for all kinds of purification rites and other activities, were very specific and important features of temples in ancient Egypt. In addition to the longer-known textual record, preliminary geoarchaeological surveys have recently provided evidence of a sacred canal at the Temple of Bastet at Bubastis. In order to further explore the location, shape, and course of this canal and to find evidence of the existence of a second waterway, also described by Herodotus, 34 drillings and five 2D geoelectrical measurements were carried out in 2019 and 2020 near the temple. The drillings and 2D ERT surveying revealed loamy to clayey deposits with a thickness of up to five meters, most likely deposited in a very low energy fluvial system (i.e., a canal), allowing the reconstruction of two separate sacred canals both north and south of the Temple of Bastet. In addition to the course of the canals, the width of about 30 m fits Herodotus’ description of the sacred waterways. The presence of numerous artefacts proved the anthropogenic use of the ancient canals, which were presumably connected to the Nile via a tributary or canal located west or northwest of Bubastis.
The detrimental impacts of climate variability on water, agriculture, and food resources in East Africa underscore the importance of reliable seasonal climate prediction. To overcome this difficulty RARIMAE method were evolved. Applications RARIMAE in the literature shows that amalgamating different methods can be an efficient and effective way to improve the forecasts of time series under consideration. With these motivations, attempt have been made to develop a multiple linear regression model (MLR) and a RARIMAE models for forecasting seasonal rainfall in east Africa under the following objectives:
1. To develop MLR model for seasonal rainfall prediction in East Africa.
2. To develop a RARIMAE model for seasonal rainfall prediction in East Africa.
3. Comparison of model's efficiency under consideration
In order to achieve the above objectives, the monthly precipitation data covering the period from 1949 to 2000 was obtained from Climate Research Unit (CRU). Next to that, the first differenced climate indices were used as predictors.
In the first part of this study, the analyses of the rainfall fluctuation in whole Central- East Africa region which span over a longitude of 15 degrees East to 55 degrees East and a latitude of 15 degrees South to 15 degrees North was done by the help of maps. For models’ comparison, the R-squared values for the MLR model are subtracted from the R-squared values of RARIMAE model. The results show positive values which indicates that R-squared is improved by RARIMAE model. On the other side, the root mean square errors (RMSE) values of the RARIMAE model are subtracted from the RMSE values of the MLR model and the results show negative value which indicates that RMSE is reduced by RARIMAE model for training and testing datasets.
For the second part of this study, the area which is considered covers a longitude of 31.5 degrees East to 41 degrees East and a latitude of 3.5 degrees South to 0.5 degrees South. This region covers Central-East of the Democratic Republic of Congo (DRC), north of Burundi, south of Uganda, Rwanda, north of Tanzania and south of Kenya. Considering a model constructed based on the average rainfall time series in this region, the long rainfall season counts the nine months lead of the first principal component of Indian sea level pressure (SLP_PC19) and the nine months lead of Dipole Mode Index (DMI_LR9) as selected predictors for both statistical and predictive model. On the other side, the short rainfall season counts the three months lead of the first principal component of Indian sea surface temperature (SST_PC13) and the three months lead of Southern Oscillation Index (SOI_SR3) as predictors for predictive model. For short rainfall season statistical model SAOD current time series (SAOD_SR0) was added on the two predictors in predictive model. By applying a MLR model it is shown that the forecast can explain 27.4% of the total variation and has a RMSE of 74.2mm/season for long rainfall season while for the RARIMAE the forecast explains 53.6% of the total variation and has a RMSE of 59.4mm/season. By applying a MLR model it is shown that the forecast can explain 22.8% of the total variation and has a RMSE of 106.1 mm/season for short rainfall season predictive model while for the RARIMAE the forecast explains 55.1% of the total variation and has a RMSE of 81.1 mm/season.
From such comparison, a significant rise in R-squared, a decrease of RMSE values were observed in RARIMAE models for both short rainfall and long rainfall season averaged time series. In terms of reliability, RARIMAE outperformed its MLR counterparts with better efficiency and accuracy. Therefore, whenever the data suffer from autocorrelation, we can go for MLR with ARIMA error, the ARIMA error part is more to correct the autocorrelation thereby improving the variance and productiveness of the model.
The natural cyclical development of palsas makes it difficult to use visible signs of decay as reference points for environmental change. Thus, to determine the actual development stage of a palsa, investigations of the internal structure are crucial. Our study presents 2‐D and 3‐D electrical resistivity imaging (ERI) and 2‐D ground‐penetrating radar (GPR) results, measurements of surface and subsurface temperatures, and of the soil matric potential from Orravatnsrústir Palsa Site in Central Iceland. By a joint interpretation of the results, we deduce the internal structure (i.e., thickness of thaw zone and permafrost, ice/water content) of five palsas of different size and shape. The results differentiate between initial and mature development stages and show that palsas of different development stages can exist in close proximity. While internal characteristics indicate undisturbed development of four palsas, one palsa shows indications of environmental change. Our study shows the value of the multimethod geophysical approach and introduces measurements of the soil matric potential as a promising method to assess the current state of the subsurface.
Pre‐Klondikean oxidation prepared the ground for Broken Hill‐type mineralization in South Africa
(2021)
New Cu isotope data obtained on chalcopyrite from the Black Mountain and the Broken Hill deposits in the medium‐ to high‐grade metamorphic Aggeneys‐Gamsberg ore district (South Africa) require a revision of our understanding of the genesis of metamorphic Broken Hill‐type massive sulphide deposits. Chalcopyrite from both deposits revealed unusually wide ranges in δ\(^{65}\)Cu (−2.41 to 2.84‰ NIST 976 standard) in combination with distinctly positive mean values (0.27 and 0.94‰, respectively). This is interpreted to reflect derivation from various silicate and oxide precursor minerals in which Cu occurred in higher oxidation states. Together with the observation of a typical supergene base metal distribution within the deposits and their spatial association with an unconformity only meters above the ore horizon, our new data are best explained by supergene oxidation of originally possibly SEDEX deposits prior to metamorphic sulphide formation, between the Okiepian (1,210–1,180 Ma) and Klondikean (1,040–1,020 Ma) orogenic events.
Andauernde Starkniederschläge führten 1987 in zahlreichen Alpentälem zu schweren Hochwasser- und Murkatastrophen. Auch das von der Ruetz entwässerte Tiroler Stubaital südwestlich Innsbruck zählte zu den betroffenen Tälern. Im Abstand von nur sechs Wochen verursachten hier zwei Hochwasserereignisse ähnlichen Ausmaßes schwere Verwüstungen und Landschaftsschäden.
Die Auswirkungen beider Hochwässer bildeten die Ansatzpunkte der als Teilprojekt Stubai von Mitte 1988 bis Ende 1991 im Stubaital und einem seiner Seitentäler laufenden Forschungsarbeit.
Das Hauptinteresse galt dabei, nach Abschluß einer ausführlichen Schadenskartierung und Photodokumentation, den Ursachen, Zusammenhängen und Auswirkungen einzelner morphodynamisch wirksamer Prozesse.
Verschiedene Felduntersuchungen in einem Seitental des Stubaitales gaben hinsichtlich des Zusammenspiels von Abfluß, Niederschlag, Hangabtrag und Vegetation Aufschluß darüber, wann, wie und in welchem Zeitraum einzelne morphodynamisch wirksame Prozesse im Bachbett bzw. im Kontaktbereich Hang/Bach ablaufen.
Um Aussagen darüber machen zu können, inwieweit das Hochwassersedimentationsverhalten der Ruetz innerhalb der letzten Jahrhunderte klimatisch beeinflußt wurde, und ob die touristische Erschließung des hinteren Stubaitales das Hochwasserabflußgeschehen der Ruetz in Bezug auf Häufigkeit und Intensität in den letzten Jahren erkennbar beeinflußte, wurden im Auebereich der Ruetz mehrere Schlitzsonden- und Kernbohrungen abgeteuft.
Die Auswertung der Bohrkeme und verschiedene Laboranalysen des gewonnenen Probenmaterials gaben einerseits Auskunft über Zusammensetzung, Mächtigkeit und Herkunft einzelner Hochwasserablagerungen, andererseits konnten anhand dieser Aussagen das frühere Akkumulationsverhalten und verschiedene Laufverlagerungen der Ruetz für diesen Auebereich rekonstruiert werden.
Ebenso konnte der direkte Einfluß des Menschen auf das Hochwassersed imentationsgeschehen und somit die anthropogene Beeinflussung der Hochflut-/Auedynamik bereits für historische Zeit festgestellt und belegt werden.
In der vorliegenden Studie wurden auf der Basis langer mitteleuropäischer Zeitreihen der Temperatur und des Niederschlags sowie rekonstruierter monatlicher Bodenluftdruckfelder für den Bereich Nordatlantik-Europa Untersuchungen zur langperiodischen klimatischen und zirkulationsdynamischen Variabilität im Zeitraum 1780-1995 durchgeführt. Der im Rahmen dieser Arbeit betrachtete Zeitraum umfaßt damit neben dem 20. Jahrhundert, das durch eine zunehmende menschliche Einflußnahme auf das Globalklima gekennzeichnet ist, eine historische, bezüglich ihrer Klimacharakteristik anthropogen nahezu unbeeinflußte Periode.
Vor dem Hintergrund der zeitlichen Limitierung bisheriger zirkulationsdynamischer und synoptisch-klimatologischer Forschungsarbeiten auf die letzten etwa 100 Jahre wurden folgende zentrale Zielsetzungen formuliert:
- Erfassung und Darstellung der räumlich differenzierten, niederfrequenten thermischen und hygrischen Variabilität in Mitteleuropa seit 1780, auf einer möglichst umfassenden und hinsichtlich ihres klimatologischen Aussagewertes optimierten
Datenbasis.
- Untersuchung der korrespondierenden nordatlantisch-europäischen Zirkulationsveränderungen und ihrer Relevanz für die zeitlichen Variationen von Temperatur und Niederschlag in Mitteleuropa.
- Analyse der zeitlichen Variabilität der Beziehungen zwischen großräumiger atmosphärischer Zirkulation und regionalem Klima auf multidekadischer Zeitskala.
Ein erster wesentlicher Arbeitsschritt umfaßte die Überprüfung der Homogenität der verfügbaren - im Rahmen der Arbeit teilweise wesentlich erweiterten - mitteleuropäischen Temperatur- und Niederschlagszeitreihen (72 bzw. 62 Stationsreihen) mittels verschiedener absoluter und relativer Homogenitätstests. Für einen beträchtlichen Teil der Zeitreihen wurden signifikante Inhomogenitäten diagnostiziert, die unter Verwendung homogener Referenzreihen homogenisiert werden konnten.
Um die angestrebte räumlich differenzierte Analyse der klimatischen Veränderungen seit 1780 zu ermöglichen, erfolgten - basierend auf nichthierarchischen Clusteranalysen der Matrizen der paarweisen Korrelationen zwischen allen Temperatur- bzw. Niederschlagsreihen - objektive Regionalisierungen von Temperatur und Niederschlag.
Für die resultierenden acht thermischen und neun hygrischen Regionen Mitteleuropas wurden regionale Temperatur- und Niederschlagsreihen berechnet, die bezüglich ihrer langperiodischen Variabilität analysiert wurden. Im Vordergrund standen dabei die Ermittlung der zeitlichen Abfolge thermischer bzw. hygrischer Anomaliephasen seit 1780 sowie der klimatische Vergleich der sog. frühinstrumentellen Periode (1780-1860) mit einer modernen Referenzperiode (1915-1995).
Als wesentliches Ergebnis konnte eine gegenüber dem Zeitraum 1780-1860 verminderte kontinentale Prägung des mitteleuropäischen Klimas - mit wärmeren, feuchteren Wintern und kühleren Sommern - in diesem Jahrhundert (1915-1995) festgestellt werden.
Als Grundlage für die Analyse der korrespondierenden zirkulationsdynamischen Variabilität wurde eine automatische - hauptkomponenten- und clusteranalytische - Klassifikation rekonstruierter monatlicher nordatlantisch-europäischer Bodenluftdruckfelder erarbeitet. Ein zweiter automatischer Klassifikationsalgorithmus wurde in Anlehnung an die Großwettertypenklassifikation nach Hess/Brezowski unter besonderer Berücksichtigung der Strömungsverhältnisse über Europa entwickelt.
Die aus den Klassifikationsverfahren resultierenden Druckmusterklassen repräsentieren wesentliche Zustandsformen der atmosphärischen Zirkulation im nordatlantisch-europäischen Bereich. Basierend auf der Untersuchung der zeitlichen Veränderungen der Auftrittshäufigkeiten der verschiedenen Druckmusterklassen konnten die folgenden wesentlichen Aussagen zur zirkulationsdynamischen Variabilität seit 1780 formuliert werden:
- Die zeitliche Entwicklung der Auftrittshäufigkeiten der einzelnen Zirkulationstypen und der daraus aggregierten Zirkulationsformen - zonal, gemischt, meridional
- zeigt keine deutlichen langzeitlichen Trends, sondern ist von Schwankungen unterschiedlicher Periodenlänge und Amplitude gekennzeichnet.
- Einige rezent zu beobachtende Veränderungstendenzen (beispielsweise die Zunahme der winterlichen Zonalzirkulation seit den 1970er Jahren) erscheinen bei Betrachtung des 216-jährigen Gesamtzeitraums als nicht außergewöhnliche Ereignisse im Rahmen langperiodischer (dekadischer bis säkularer) zirkulationsdynamischer
Variabilität.
Aus dem direkten zirkulationsdynamischen Vergleich der beiden Zeiträume 1780-1860 und 1915-1995 ergeben sich folgende saisonal differenzierte Unterschiede:
- In den Wintermonaten Dezember und Januar sind in diesem Jahrhundert deutlich größere Auftrittshäufigkeiten von Zirkulationstypen mit südwestlicher bis nordwestlicher Richtungsorientierung des Isobarenverlaufs bei gleichzeitig reduzierten Häufigkeiten winterkalter meridionaler Druckmuster festzustellen. Zeitliche Veränderungen umgekehrten Vorzeichens manifestieren sich hingegen im Februar.
- Bei intrasaisonal variierenden Befunden im Frühjahr überwiegt bei saisonaler Betrachtung eine Zunahme meridionaler Strömungskonfigurationen auf Kosten der zonalen und vor allem der gemischten Zirkulationsform.
- Im Sommer dominiert eine Abnahme der zonalen Zirkulationsform zugunsten meridionaler Zirkulationstypen, die eine Anströmung aus dem nördlichen Richtungssektor implizieren.
- Für die Herbstmonate September mit November ergeben sich in diesem Jahrhundert vor allem gesteigerte Häufigkeiten von Strömungskonfigurationen, die die Heranführung von Luftmassen aus westlichen bis nordwestlichen Richtungen bedingen.
- Eine möglicherweise grundlegende Modifikation der nordatlantisch-europäischen Zirkulation in diesem Jahrhundert deutet sich bezüglich des häufigeren Wechsels zwischen stark zonal bzw. meridional geprägten Phasen - vor allem im Winter - an.
Mittels eines einfachen empirischen Modellansatzes wurde anschließend analysiert, inwieweit sich die diagnostizierten klimatischen Unterschiede zwischen den beiden Zeiträumen 1780-1860 und 1915-1995 aus den festgestellten zeitlichen Veränderungen der Zirkulationsstrukturen ergeben. Es wurde deutlich, daß nur ein Teil der Temperatur- und Niederschlagsveränderungen zwischen historischem Zeitraum und diesem Jahrhundert durch differierende Auftrittshäufigkeiten witterungsklimatisch homogener Zirkulationstypen erklärt werden kann. Ein beträchtlicher Anteil der klimatischen Unterschiedlichkeiten der beiden Vergleichszeiträume ist offensichtlich auf zeitlich variierende Witterungscharakteristika der einzelnen Strömungskonfigurationen („within-type changes“ - zirkulationstypinterne Veränderungen) zurückzuführen.
Das Ausmaß der typinternen klimatischen Modifikationen konnte durch die Berechnung der in den beiden Vergleichszeiträumen ausgebildeten typspezifischen mittleren Temperatur- und Niederschlagsverhältnisse quantifiziert werden. Die Fraktionierung der zirkulationstypspezifischen Temperatur- bzw. Niederschlagsänderungsbeträge in einen durch variierende Auftrittshäufigkeiten bedingten sowie einen auf typinterne Veränderungen zurückzuführenden Anteil belegt, daß in allen Jahreszeiten internen klimatischen Modifikationen der Zirkulationstypen mit südwestlicher bis nordwestlicher Isobarenverlaufsrichtung eine gewichtige Rolle bei der Generierung zeitlicher Unterschiede der mitteleuropäischen Temperatur- und Niederschlagscharakteristik zukommt.
Als Ursache der zirkulationstypinternen Veränderungen konnten zum einen unterschiedliche Ausgestaltungen der typspezifischen Druckmuster im historischen und im rezenten Zeitraum identifiziert werden (beispielsweise zeitlich variierende Druckgradienten bei generell übereinstimmenden Strömungskonfigurationen), zum anderen deuten sich auf der täglichen Zeitskala Veränderungen der Persistenzen einzelner Zirkulationstypen an.
Diese zirkulationsdynamischen Modifikationen stellen aber nicht in allen Fällen einen hinreichenden Erklärungsansatz für die diagnostizierten „within-type changes“ dar, so daß zusätzlich andere verursachende Faktorenkomplexe in Betracht gezogen werden müssen (beispielsweise modifizierte thermische und hygrische Luftmasseneigenschaften aufgrund veränderter Energieflüsse zwischen Ozean und Atmosphäre).
Mit Blick auf diese Resultate wurden die Beziehungen zwischen großräumiger Zirkulation und regionalem bodennahem Klima mittels kanonischer Korrelationsanalysen monatlicher Bodenluftdruckfelder und regionaler mitteleuropäischer Temperatur- und Niederschlagszeitreihen detaillierter hinsichtlich ihrer zeitlichen Variabilität untersucht. Die wesentlichen Ergebnisse lassen sich wie folgt zusammenfassen:
- In allen Jahreszeiten zeigen sich im Zeitraum 1780-1995 ausgeprägte zeitliche Schwankungen des statistisch beschreibbaren Zusammenhangs zwischen großräumiger atmosphärischer Zirkulation und regionalem Klima (Temperatur und Niederschlag in Mitteleuropa).
- Ein Vergleich der beiden Perioden 1780-1860 und 1915-1995 hinsichtlich der Kopplungsmechanismen zwischen Bodenluftdruckverteilung und Klima ergibt teilweise hochsignifikante Unterschiede.
- Die Modellierung von Temperatur und Niederschlag in Mitteleuropa aus monatlichen Druckfeldern jeweils einem der Zeitabschnitte 1780-1860 und 1915-1995 unter Verwendung der im jeweils anderen Zeitraum etablierten statistischen Zusammenhänge erbringt nur in einem Fall (Januartemperaturen) befriedigende Übereinstimmungen zwischen den modellierten und beobachteten Klimaverhältnissen.
Die in dieser Arbeit vorgestellten Untersuchungsergebnisse lassen die Schlußfolgerung zu, daß sich die im 20. Jahrhundert zu verzeichnenden Zirkulationsveränderungen im nordatlantisch-europäischen Sektor bislang noch in das Spektrum natürlicher zirkulationsdynamischer Variabilität einfügen.
Diese Aussage stellt aber weder die wahrscheinliche Mitwirkung des anthropogen verstärkten Treibhauseffekts an den in diesem Jahrhundert beobachteten Zirkulationsdynamischen Entwicklungen im euro-atlantischen Bereich in Frage, noch kann sie als Argument für die Aufschiebung notwendiger klimapolitischer Entscheidungen oder für die verzögerte Entwicklung und Umsetzung von Handlungsstrategien zur wirksamen Reduzierung klimawirksamer Treibhausgasemissionen aufgefaßt werden.
Statistical modeling of phenology in Bavaria based on past and future meteorological information
(2020)
Plant phenology is well known to be affected by meteorology. Observed changes in the occurrence of phenological phases arecommonly considered some of the most obvious effects of climate change. However, current climate models lack a representationof vegetation suitable for studying future changes in phenology itself. This study presents a statistical-dynamical modelingapproach for Bavaria in southern Germany, using over 13,000 paired samples of phenological and meteorological data foranalyses and climate change scenarios provided by a state-of-the-art regional climate model (RCM). Anomalies of severalmeteorological variables were used as predictors and phenological anomalies of the flowering date of the test plantForsythiasuspensaas predictand. Several cross-validated prediction models using various numbers and differently constructed predictorswere developed, compared, and evaluated via bootstrapping. As our approach needs a small set of meteorological observationsper phenological station, it allows for reliable parameter estimation and an easy transfer to other regions. The most robust andsuccessful model comprises predictors based on mean temperature, precipitation, wind velocity, and snow depth. Its averagecoefficient of determination and root mean square error (RMSE) per station are 60% and ± 8.6 days, respectively. However, theprediction error strongly differs among stations. When transferred to other indicator plants, this method achieves a comparablelevel of predictive accuracy. Its application to two climate change scenarios reveals distinct changes for various plants andregions. The flowering date is simulated to occur between 5 and 25 days earlier at the end of the twenty-first century comparedto the phenology of the reference period (1961–1990).
The new ellipsocephaloid trilobite species Kingaspidoides spinirecurvatus has a spectacular morphology because of a unique set of two long and anteriorly recurved spines on the occipital ring and the axial ring of thoracic segment 8. Together with the long genal spines this whimsical dorsally directed spine arrangement is thought to act as a non-standard protective device against predators. This is illustrated by the body posture during different stages of enrolment, contrasting with the more sophisticated spinosities seen in later trilobites, which are discussed in brief. Kingaspidoides spinirecurvatus from the lower–middle Cambrian boundary interval of the eastern Anti-Atlas in Morocco has been known for about two decades, with specimens handled as precious objects on the fossil market. Similar, but far less spectacular, spine arrangements on the thoracic axial rings are known from other ellipsocephaloid trilobites from the Anti-Atlas of Morocco and the Franconian Forest region of Germany. This suggests that an experimental phase of spine development took place within the Kingaspi-doides clade during the early–middle Cambrian boundary interval.
The DAEDALUS mission concept aims at exploring and characterising the entrance and initial part of Lunar lava tubes within a compact, tightly integrated spherical robotic device, with a complementary payload set and autonomous capabilities.
The mission concept addresses specifically the identification and characterisation of potential resources for future ESA exploration, the local environment of the subsurface and its geologic and compositional structure.
A sphere is ideally suited to protect sensors and scientific equipment in rough, uneven environments.
It will house laser scanners, cameras and ancillary payloads.
The sphere will be lowered into the skylight and will explore the entrance shaft, associated caverns and conduits. Lidar (light detection and ranging) systems produce 3D models with high spatial accuracy independent of lighting conditions and visible features.
Hence this will be the primary exploration toolset within the sphere.
The additional payload that can be accommodated in the robotic sphere consists of camera systems with panoramic lenses and scanners such as multi-wavelength or single-photon scanners.
A moving mass will trigger movements.
The tether for lowering the sphere will be used for data communication and powering the equipment during the descending phase.
Furthermore, the connector tether-sphere will host a WIFI access point, such that data of the conduit can be transferred to the surface relay station. During the exploration phase, the robot will be disconnected from the cable, and will use wireless communication.
Emergency autonomy software will ensure that in case of loss of communication, the robot will continue the nominal mission.
Availability of water and desiccation of important water reservoirs is a vital challenge in semi-arid to arid climates with growing economy and population. Low quantities of precipitation and high evaporation rates leave the water supply vulnerable to human activity and climatic variations. Endorheic basins of Northern Iran were hydrologically landlocked within geological timescales and thus bear evidence of past variations of water resources in generations of water related landforms, like abandoned lake level shorelines, alluvial fans and stream terraces. Understanding the development of these landforms reveals crucial information about past water reservoirs and landscape history.
This study offers a comprehensive approach on understanding the geomorphological development of the landscape throughout Late Pleistocene and Holocene times. It integrates remote sensing and geographic information system analysis, with geomorphological and stratigraphical mapping fieldwork and detailed sedimentological investigations.
The work shows the importance of analytical geomorphological mapping for delineating stratigraphic units of the Iranian Quaternary. Thus, several phases of drying and lake level retreat were identified in parallel geoarchives and could be dated to a time span from today to Late Pleistocene. The findings link the fate of the citizens of the ancient city of "Tepe Hissar" to their access to water and to the power of geomorphological processes, which started changing their environment.
In recent years, the midlatitudes are characterized by more intense heatwaves in summer and sometimes severe cold spells in winter that might emanate from changes in atmospheric circulation, including synoptic‐scale and planetary wave activity in the midlatitudes. In this study, we investigate the heat and momentum exchange between the mean flow and atmospheric waves in the North Atlantic sector and adjacent continents by means of the physically consistent Eliassen–Palm flux diagnostics applied to reanalysis and forced climate model data. In the long‐term mean, momentum is transferred from the mean flow to atmospheric waves in the northwest Atlantic region, where cyclogenesis prevails. Further downstream over Europe, eddy fluxes return momentum to the mean flow, sustaining the jet stream against friction. A global climate model is able to reproduce this pattern with high accuracy. Atmospheric variability related to atmospheric wave activity is much more expressed at the intraseasonal rather than the interannual time‐scale. Over the last 40 years, reanalyses reveal a northward shift of the jet stream and a weakening of intraseasonal weather variability related to synoptic‐scale and planetary wave activity. This pertains to the winter and summer seasons, especially over central Europe, and correlates with changes in the North Atlantic Oscillation as well as regional temperature and precipitation. A very similar phenomenon is found in a climate model simulation with business‐as‐usual scenario, suggesting an anthropogenic trigger in the weakening of intraseasonal weather variability in the midlatitudes.
Periglacial environments are facing dramatic changes. Warming air temperatures and strong snow cover variations fundamentally affect landforming processes in this hotspot region of Climate Change. But before we can assess the response of landform development to a changing climate, we need to enhance our understanding of the internal structure of those landforms. Within this study, a broad scope of landform types from alpine and subarctic regions is investigated: rock glaciers, solifluction lobes, palsas and patterned ground. By using the geophysical methods 2-D and 3-D ERI, as well as GPR surveying, structural differences and similarities between landform units of different or the same landform types are highlighted. This enables a reconstruction of their past and a projection of their future development.
The heavily debris-covered Inylchek glaciers in the central Tian Shan are the largest glacier system in the Tarim catchment. It is assumed that almost 50% of the discharge of Tarim River are provided by glaciers. For this reason, climatic changes, and thus changes in glacier mass balance and glacier discharge are of high impact for the whole region. In this study, a conceptual hydrological model able to incorporate discharge from debris-covered glacier areas is presented. To simulate glacier melt and subsequent runoff in the past (1970/1971–1999/2000) and future (2070/2071–2099/2100), meteorological input data were generated based on ECHAM5/MPI-OM1 global climate model projections. The hydrological model HBV-LMU was calibrated by an automatic calibration algorithm using runoff and snow cover information as objective functions. Manual fine-tuning was performed to avoid unrealistic results for glacier mass balance. The simulations show that annual runoff sums will increase significantly under future climate conditions. A sensitivity analysis revealed that total runoff does not decrease until the glacier area is reduced by 43%. Ice melt is the major runoff source in the recent past, and its contribution will even increase in the coming decades. Seasonal changes reveal a trend towards enhanced melt in spring, but a change from a glacial-nival to a nival-pluvial runoff regime will not be reached until the end of this century.
Peatlands located on slopes (herein called slope bogs) are typical landscape units in the Hunsrueck, a low mountain range in Southwestern Germany. The pathways of the water feeding the slope bogs have not yet been documented and analyzed. The identification of the different mechanisms allowing these peatlands to originate and survive requires a better understanding of the subsurface lithology and hydrogeology. Hence, we applied a multi-method approach to two case study sites in order to characterize the subsurface lithology and to image the variable spatio-temporal hydrological conditions. The combination of Electrical Resistivity Tomography (ERT) and an ERT-Monitoring and Ground Penetrating Radar (GPR), in conjunction with direct methods and data (borehole drilling and meteorological data), allowed us to gain deeper insights into the subsurface characteristics and dynamics of the peatlands and their catchment area. The precipitation influences the hydrology of the peatlands as well as the interflow in the subsurface. Especially, the geoelectrical monitoring data, in combination with the precipitation and temperature data, indicate that there are several forces driving the hydrology and hydrogeology of the peatlands. While the water content of the uppermost layers changes with the weather conditions, the bottom layer seems to be more stable and changes to a lesser extent. At the selected case study sites, small differences in subsurface properties can have a huge impact on the subsurface hydrogeology and the water paths. Based on the collected data, conceptual models have been deduced for the two case study sites.
Summary
Introduction. Rapid and uncontrolled industrialisation and urbanisation in most developing countries are resulting in land, air and water pollution at rates that the natural environment cannot fully renew. These contemporary environmental issues have attracted local, national and international attention. The problem of urban garbage management is associated with rapid population growth in developing countries. These are pertinent environmental crises of sustainability and sanitation in Sub-Saharan Africa and other Third World countries. Despite efforts of the various tiers of government (the case of Nigeria with three tiers: Federal, State and Local governments) in managing solid waste in urban centres, it is still overflowing open dumpsites, litters streets and encroaches into water bodies. These affect the quality of urban living conditions and the natural environment.
Sub-Saharan and other developing countries are experiencing an upsurge in the accumulation and the diversity of waste including E-waste, waste agricultural biomass and waste plastics. The need for effective, sustainable and efficient management of waste through the application of 3Rs principle (Reduce, Reuse, and Recycle) is an essential element for promoting sustainable patterns of consumption and production. This study examined waste management in Imo State, Nigeria as an aspect correlated to the sustainability of its environment.
Materials and methods. To analyse waste management as a correlate of environmental sustainability in Sub-Saharan Africa, Imo State, in eastern Nigeria was chosen as a study area. Issues about waste handling and its impact on the environment in Imo have been reported since its creation in 1976; passing through the State with the cleanest State capital in 1980 to a ‘dunghill’ in 2013 and a ‘garbage capital’ on October 1, 2016. Within this State, three study sites were selected – Owerri metropolis (the State capital) Orlu and Okigwe towns. At these sites, households, commercial areas, accommodation and recreational establishments and schools, as well as dumpsites were investigated to ascertain the composition, quantity, distribution, handling patterns of waste in relation to the sustainability of the State’s environment. This was done conveniently but randomly through questionnaires, interviews, focus group discussions and non-participant observation; these were all heralded by a detailed deskwork. Data were entered using Microsoft Office Excel and were explored and analysed using the Statistical Package for Social Sciences - SPSS.
Data were made essentially of categorical variables and were analysed using descriptive statistics. The association between categorical variables was measured using Cramer’s V the Chi-Square that makes the power and the reliability of the test. Cramer’s V is a measure of association tests directly integrated with cross-tabulation. The Chi-Square test of equal proportions was used to compare proportions for significant differences at 0.05 levels. The statistical package - the Epi Info 6.04d was also used since a contingency table had to be created from several sub-outputs and determine the extent of association between the row and column categories.
The scale variable ‘quantity of waste generated’ was described using measures of central tendency. It was screened for normality using the Kolmogorov-Smirnov and Shapiro-Wilk tests for normality; in all context, the normality assumption was violated (P<0.05). Five null hypotheses were tested using Logistic Regression model. The explanatory power of individual conceptual component was calculated using the Cox & Snell R2 and that of individual indicators was also appraised using the Likelihood Ratio test.
In the context of this work, the significance of the variability explained by the model (baseline model) was appraised using the Omnibus Tests of Model Coefficients, the magnitude of this variability explained by the model using the Cox & Snell R2 and the effects of individual predictors using the Likelihood Ratio test.
Qualitatively, data from open-ended items, observations and interviews were analysed using the process of thematic analysis whereby concepts or ideas were grouped under umbrella terms or keywords. The results were presented using tables, charts, graphs, photos and maps.
Findings and discussions. The total findings and analyses indicated that proper waste handling in Imo State, Nigeria has a positive impact on the environment. This was assessed by the community’s awareness of waste management via sources like the radio and the TV, their education on waste management and schools’ integration of environmental education in their program. Although most community members perceived the State’s environment as compared to it about 10 years’ back has worsened, where they were conscious of proper waste handling measures, the environment was described to be better. This influence of environmental awareness and education on environmental sustainability appraised using Logistic Regression Model, portrayed a significant variability (Omnibus Tests of Model Coefficients: χ2=42.742; P=0.014), inferring that environmental awareness and education significantly predict environmental sustainability.
The findings also revealed that organic waste generation spearheaded amongst other waste types like paper, plastic, E-waste, metal, textile and glass. While waste pickers always sorted paper, plastics, aluminium and metal, some of them also sorted out textile and glass. Statistically (P<0.05), in situations where waste was least generated (i.e., 1-2kg per day), community members maintained that the environmental quality was better in comparison to 10 years’ back. Waste items like broken glass and textile as well as the remains of E-waste after the extraction of copper and brass were not sorted for and these contributed more to environmental degradation.
Similarly, the influence of wealth on environmental sustainability was appraised using Logistic Regression Model including development index related indicators like education, occupation, income and the ability to pay for waste disposal. Harmonising the outcome, farmers, who were mostly the least educated claimed to notice more environmental improvement. In addition, those who did not agree to pay for waste disposal who were mostly those with low income (less than 200,000 Naira, i.e. about 620 Euros monthly) perceived environmental improvement more than those with income above 200,000 Naira. This irony can be attributed to the fact that those with low educational backing lack the capacity to appreciate environmental sustainability pointers well as compared to those with a broader educational background with critical thinking.
The employment and poverty reduction opportunities pertaining to waste management on environmental sustainability was appraised using qualitative thematic analysis. All community members involved in sorting, buying and selling of waste items had no second job. They attested that the money earned from their activities sustained their livelihood and families. Some expressed love for the job, especially as they were their own masters. Waste picking and trading in waste items are offering employment opportunities to many communities around the world. For instance, in the waste recycling, waste composting, waste-to-energy plants and die Stadtreiniger in Würzburg city. The workers in these enterprises have jobs as a result of waste.
Waste disposal influence on environmental sustainability was appraised using the Binary Logistic Regression Model and the variability explained by the model was significant. The validity was also supported by the Wald statistics (P<0.05), which indicates the effect of the predictors is significant. Environmental sustainability was greatly reliant on indicators like the frequency at which community members emptied their waste containers; how/where waste is disposed of, availability of disposal site or public bin near the house, etc. Imolites who asserted to have public waste bins or disposal sites near their houses maintained that the quality of the State’s environment had worsened as such containers/disposal sites were always stinking as well as had animals and smoke around them. Imolites around disposal sites complained of traits like diarrhoea, catarrh, insect bites, malaria, smoke and polluted air.
Conclusions. The liaison between poor waste management strategies and the sustainability of the Imo State environment was considered likely as statistically significant ineffectiveness, lack of awareness, poverty, insufficient and unrealistic waste management measures were found in this study area. In these situations, the environment was said to have not improved. Such inadequacies in the handling of generated waste did not only expose the citizenry to health dangers but also gave rise to streets and roads characterized by filth and many unattended disposal sites unleashing horrible odour to the environment and attracting wild animals. This situation is not only prevalent in Imo State, Nigeria but in many Sub-Saharan cities.
Future Perspectives. To improve the environment in Sub-Saharan Africa, it is imperative to practice an inclusive and integrated sustainable waste management system. The waste quantity in this region is fast growing, especially food/organic waste. The region should aim at waste management laws and waste reduction strategies, which will help save and produce more food that it really needs. Waste management should be dissociated from epidemic outbreaks like cholera, typhoid, Lassa fever and malaria, whose vectors thrive in filthy environments. Water channels and water bodies should not be waste disposal channels or waste disposal sites.
Diese Arbeit stellt die Ergebnisse der stratigraphischen und tektonischen Aufnahme des Blattes 5827 Maßbach vor. Sie erfolgte im Rahmen der geologischen Landesaufnahme von Bayern 1:25.000 sowie im Auftrag des Bayerischen Landesamts für Umwelt und beruht auf einer geologischen Detailkartierung im Maßstab 1:10.000. Die wesentlichen Ergebnisse sind folglich in der Geologischen Karte 1:25.000 und in der Strukturkarte 1:50.000 dargestellt.
Zur Aufgabenstellung gehörten ebenfalls eine moderne Erfassung und Darstellung der Schichtenfolge unter stratigraphischen und faziellen Gesichtspunkten sowie die Aufnahme und Interpretation geologischer Strukturen und deren Einbindung in den regionalen Rahmen (Anlage 7). Dieser Arbeit kommt somit nicht nur akademisches Interesse zu. Vielmehr ist sie auch für angewandte Fachbereiche wesentlich: u.a. für Hydrogeologie, Geothermie oder für Fragen der Raumplanung.
Das Kartenblatt 5827 Maßbach liegt im nordöstlichen Unterfranken im Norden Bayerns. Die nächstgrößere Stadt, südlich des Blattgebietes, ist Schweinfurt. Das Gebiet zeigt einen Ausschnitt des südwestdeutschen Schichtstufenlandes innerhalb der Südwestdeutschen Großscholle sensu CARLÉ (1955). Geomorphologen rechnen es der Hochfläche der „Schweinfurter Rhön“ zu. Ein naturräumlicher Überblick über Geographie, Geologie, Hydrogeologie, Rohstoffgeologie und Bodenkunde sowie ein erdgeschichtlicher Abriss werden im ersten Teil der Arbeit (S. 2–15) gegeben.
Die Kartierung erfolgte als Lesesteinkartierung; denn die Aufschlussverhältnisse waren schlecht. Auch existieren nur wenige auswertbare Bohrungen. Vor diesem Hintergrund stellt der zweite Teil der Arbeit die zu Tage ausstreichende mesozoische Schichtenfolge vor (S.16–76). Die Schichtenfolge gehört ausschließlich in die Trias, reicht vom Unteren Muschelkalk bis zum Unteren Gipskeuper und umfasst etwa 270 bis 280 Meter. Hinzu kommen verschiedene quartäre Sedimente geringer Mächtigkeit.
Der dritte Teil der Arbeit (S. 77–95) befasst sich mit den Lagerungsverhältnissen und der tektonischen Zergliederung des Gebietes. Das tektonische Relief auf Blatt 5827 Maßbach misst etwa 260–270 m. Prägendes Element ist der Kissingen–Haßfurter Sattel, dessen Sattelachse das Blattgebiet von NW nach SE quert. Im SW–Quadranten ist die in Südwestdeutschland bedeutsame Kissingen–Haßfurter–Störungszone wirksam
Im regionalen Rahmen verbinden sich eine Vielzahl von nachgewiesenen tektonischen Elementen zu sich überlagernden tektonischen Strukturen. Deren Ausgestaltung verlief mehrphasig und sie erhielten ihre heute bestehende Form wohl durch die Fernwirkung der alpidischen Orogenese. Die Anlage der tektonischen Hauptelemente hingegen reicht wahrscheinlich bis in die ausgehende variszidische Gebirgsbildung zurück. Die zusammen-fassende Analyse und Darstellung der Ergebnisse führt in dieser Arbeit zur Einarbeitung des Blattes 5827 Maßbach in den regionalen stratigraphischen wie tektonischen Rahmen der umliegenden Blätter der GK 25.
The use of inverse methods allow efficient model calibration. This study employs PEST to calibrate a large catchment scale transient flow model. Results are demonstrated by comparing manually calibrated approaches with the automated approach. An advanced Tikhonov regularization algorithm was employed for carrying out the automated pilot point (PP) method. The results indicate that automated PP is more flexible and robust as compared to other approaches. Different statistical indicators show that this method yields reliable calibration as values of coefficient of determination (R-2) range from 0.98 to 0.99, Nash Sutcliffe efficiency (ME) range from 0.964 to 0.976, and root mean square errors (RMSE) range from 1.68 m to 1.23 m, for manual and automated approaches, respectively. Validation results of automated PP show ME as 0.969 and RMSE as 1.31 m. The results of output sensitivity suggest that hydraulic conductivity is a more influential parameter. Considering the limitations of the current study, it is recommended to perform global sensitivity and linear uncertainty analysis for the better estimation of the modelling results.
Estimating flood risks and managing disasters combines knowledge in climatology, meteorology, hydrology, hydraulic engineering, statistics, planning and geography - thus a complex multi-faceted problem. This study focuses on the capabilities of multi-source remote sensing data to support decision-making before, during and after a flood event. With our focus on urbanized areas, sample methods and applications show multi-scale products from the hazard and vulnerability perspective of the risk framework. From the hazard side, we present capabilities with which to assess flood-prone areas before an expected disaster. Then we map the spatial impact during or after a flood and finally, we analyze damage grades after a flood disaster. From the vulnerability side, we monitor urbanization over time on an urban footprint level, classify urban structures on an individual building level, assess building stability and quantify probably affected people. The results show a large database for sustainable development and for developing mitigation strategies, ad-hoc coordination of relief measures and organizing rehabilitation.
West Africa is one of the fastest growing regions in the world with annual population growth rates of more than three percent for several countries. Since the 1950s, West Africa experienced a fivefold increase of inhabitants, from 71 to 353 million people in 2015 and it is expected that the region’s population will continue to grow to almost 800 million people by the year 2050. This strong trend has and will have serious consequences for food security since agricultural productivity is still on a comparatively low level in most countries of West Africa. In order to compensate for this low productivity, an expansion of agricultural areas is rapidly progressing. The mapping and monitoring of agricultural areas in West Africa is a difficult task even on the basis of remote sensing. The small scale extensive farming practices with a low level of agricultural inputs and mechanization make the delineation of cultivated land from other land cover and land use (LULC) types highly challenging. In addition, the frequent cloud coverage in the region considerably decreases the availability of earth observation datasets. For the accurate mapping of agricultural area in West Africa, high temporal as well as spatial resolution is necessary to delineate the small-sized fields and to obtain data from periods where different LULC types are distinguishable. However, such consistent time series are currently not available for West Africa. Thus, a spatio-temporal data fusion framework was developed in this thesis for the generation of high spatial and temporal resolution time series.
Data fusion algorithms such as the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) enjoyed increasing popularity during recent years but they have hardly been used for the application on larger scales. In order to make it applicable for this purpose and to increase the input data availability, especially in cloud-prone areas such as West Africa, the ESTARFM framework was developed in this thesis introducing several enhancements. An automatic filling of cloud gaps was included in the framework in order to use even partly cloud-covered Landsat images for the fusion without producing gaps on the output images. In addition, the ESTARFM algorithm was improved to automatically account for regional differences in the heterogeneity of the study region. Further improvements comprise the automation of the time series generation as well as the significant acceleration of the processing speed through parallelization. The performance of the developed ESTARFM framework was tested by fusing an 8-day NDVI time series from Landsat and MODIS data for a focus area of 98,000 km² in the border region between Burkina Faso and Ghana. The results of this test show the capability of the ESTARFM framework to accurately produce high temporal resolution time series while maintaining the spatial detail, even in such a heterogeneous and cloud-prone region.
The successfully tested framework was subsequently applied to generate consistent time series as the basis for the mapping of agricultural area in Burkina Faso for the years 2001, 2007, and 2014. In a first step, high temporal (8-day) and high spatial (30 m) resolution NDVI time series for the entire country and the three years were derived with the ESTARFM framework. More than 500 Landsat scenes and 3000 MODIS scenes were automatically processed for this purpose. From the fused ESTARFM NDVI time series, phenological metrics were extracted and together with the single time steps of NDVI served as input for the delineation of rainfed agricultural areas, irrigated agricultural areas and plantations. The classification was conducted with the random forest algorithm at a 30 m spatial resolution for entire Burkina Faso and the three years 2001, 2007, and 2014. For the training and validation of the classifier, a randomly sampled reference dataset was generated from Google Earth images based on expert knowledge of the region. The overall classification accuracies of 92% (2001), 91% (2007), and 91% (2014) indicate the well-functioning of the developed methodology. The resulting maps show an expansion of agricultural area of 91% from about 61,000 km² in 2001 to 116,900 km² in 2014. While rainfed agricultural areas account for the major part of this increase, irrigated areas and plantations also spread considerably. Especially the expansion of irrigation systems and plantation area can be explained by the promotion through various national and international development projects. The increase of agricultural areas goes in line with the rapid population growth in most of Burkina Faso’s provinces which still had available land resources for an expansion of agricultural area. An analysis of the development of agricultural areas in the vicinity of protected areas highlighted the increased human pressure on these reserves. The protection of the remnant habitats for flora and fauna while at the same time improving food security for a rapidly growing population, are the major challenges for the region in the future.
The developed ESTARFM framework showed great potential beyond its utilization for the mapping of agricultural area. Other large-scale research that requires a sufficiently high temporal and spatial resolution such as the monitoring of land degradation or the investigation of land surface phenology could greatly benefit from the application of this framework.
As a cradle of ancient Chinese civilization, the Yellow River Basin has a very long human-environment interrelationship, where early anthropogenic activities re- sulted in large scale landscape modifications. Today, the impact of this relationship
has intensified further as the basin plays a vital role for China’s continued economic
development. It is one of the most densely-populated, fastest growing, and most dynamic
regions of China with abundant natural and environmental resources providing a livelihood for almost 190 million people. Triggered by fundamental economic reforms, the
basin has witnessed a spectacular economic boom during the last decades and can be
considered as an exemplary blueprint region for contemporary dynamic Global Change
processes occurring throughout the country, which is currently transitioning from an
agrarian-dominated economy into a modern urbanized society. However, this resourcesdemanding growth has led to profound land use changes with adverse effects on the Yellow
River social-ecological systems, where complex challenges arise threatening a long-term
sustainable development.
Consistent and continuous remote sensing-based monitoring of recent and past land
cover and land use change is a fundamental requirement to mitigate the adverse impacts
of Global Change processes. Nowadays, technical advancement and the multitude of
available satellite sensors, in combination with the opening of data archives, allow the
creation of new research perspectives in regional land cover applications over heterogeneous landscapes at large spatial scales. Despite the urgent need to better understand the
prevailing dynamics and underlying factors influencing the current processes, detailed
regional specific land cover data and change information are surprisingly absent for this
region.
In view of the noted research gaps and contemporary developments, three major objectives are defined in this thesis. First (i), the current and most pressing social-ecological
challenges are elaborated and policy and management instruments towards more sustainability are discussed. Second (ii), this thesis provides new and improved insights on
the current land cover state and dynamics of the entire Yellow River Basin. Finally (iii),
the most dominant processes related to mining, agriculture, forest, and urban dynamics
are determined on finer spatial and temporal scales.
The complex and manifold problems and challenges that result from long-term abuse
of the water and land resources in the basin have been underpinned by policy choices,
cultural attitude, and institutions that have evolved over centuries in China. The tremendous economic growth that has been mainly achieved by extracting water and exploiting
land resources in a rigorous, but unsustainable manner, might not only offset the economic benefits, but could also foster social unrest. Since the early emergence of the first Chinese dynasties, flooding was considered historically as a primary issue in river management and major achievements have been made to tame the wild nature of the Yellow
River. Whereas flooding is therefore largely now under control, new environmental and
social problems have evolved, including soil and water pollution, ecological degradation,
biodiversity decline, and food security, all being further aggravated by anthropogenic
climate change. To resolve the contemporary and complex challenges, many individual
environmental laws and regulations have been enacted by various Chinese ministries.
However, these policies often pursue different, often contradictory goals, are too general
to tackle specific problems and are usually implemented by a strong top-down approach.
Recently, more flexible economic and market-based incentives (pricing, tradable permits,
investments) have been successfully adopted, which are specifically tailored to the respective needs, shifting now away from the pure command and regulating instruments.
One way towards a more holistic and integrated river basin management could be the
establishment of a common platform (e.g. a Geographical Information System) for data
handling and sharing, possibly operated by the Yellow River Basin Conservancy Commission (YRCC), where available spatial data, statistical information and in-situ measures
are coalesced, on which sustainable decision-making could be based. So far, the collected
data is hardly accessible, fragmented, inconsistent, or outdated.
The first step to address the absence and lack of consistent and spatially up-to-date
information for the entire basin capturing the heterogeneous landscape conditions was
taken up in this thesis. Land cover characteristics and dynamics were derived from
the last decade for the years 2003 and 2013, based on optical medium-resolution hightemporal MODIS Normalized Differenced Vegetation Index (NDVI) time series at 250 m.
To minimize the inherent influence of atmospheric and geometric interferences found in
raw high temporal data, the applied adaptive Savitzky-Golay filter successfully smoothed
the time series and substantially reduced noise. Based on the smoothed time series
data, a large variety of intra-annual phenology metrics as well as spectral and multispectral annual statistics were derived, which served as input variables for random
forest (RF) classifiers. High quality reference data sets were derived from very high
resolution imagery for each year independently of which 70 % trained the RF models. The
accuracy assessments for all regionally specific defined thematic classes were based on the
remaining 30 % reference data split and yielded overall accuracies of 87 % and 84 % for
2003 and 2013, respectively. The first regional adapted Yellow River Land Cover Products
(YRB LC) depict the detail spatial extent and distribution of the current land cover status
and dynamics. The novel products overall differentiate overall 18 land cover and use
classes, including classes of natural vegetation (terrestrial and aquatic), cultivated classes,
mosaic classes, non-vegetated, and artificial classes, which are not presented in previous
land cover studies so far.
Building on this, an extended multi-faceted land cover analysis on the most prominent
land cover change types at finer spatial and temporal scales provides a better and more
detailed picture of the Yellow River Basin dynamics. Precise spatio-temporal products
about mining, agriculture, forest, and urban areas were examined from long-trem Landsat
satellite time series monitored at annual scales to capture the rapid rate of change in four
selected focus regions. All archived Landsat images between 2000 and 2015 were used to
derive spatially continuous spectral-temporal, multi-spectral, and textural metrics. For
each thematic region and year RF models were built, trained and tested based on a stablepixels reference data set. The automated adaptive signature (AASG) algorithm identifies those pixels that did not change between the investigated time periods to generate a
mono-temporal reference stable-pixels data set to keep manual sampling requirements
to a minimum level. Derived results gained high accuracies ranging from 88 % to 98 %.
Throughout the basin, afforestation on the Central Loess Plateau and urban sprawl are
identified as most prominent drivers of land cover change, whereas agricultural land
remained stable, only showing local small-scale dynamics. Mining operations started in
2004 on the Qinghai-Tibet Plateau, which resulted in a substantial loss of pristine alpine
meadows and wetlands.
In this thesis, a novel and unique regional specific view of current and past land cover
characteristics in a complex and heterogeneous landscape was presented by using a
multi-source remote sensing approach. The delineated products hold great potential for
various model and management applications. They could serve as valuable components
for effective and sustainable land and water management to adapt and mitigate the
predicted consequences of Global Change processes.
Pedosedimentäre Archive liefern einen wichtigen Beitrag zur Rekonstruktion der Landschaftsgeschichte. Die anthropogene Besiedlung und Nutzung der Landoberfläche seit dem Beginn des Holozäns verursacht Boden-, Vegetations- und Reliefveränderungen, welche sich durch die Verbreitung von Böden mit ihren Erosionsstadien und Kolluvien zeigen. Das Ausmaß und die Art der Bodenerosion und die damit verbundene Bildung der Kolluvien werden neben den natürlichen Faktoren wesentlich durch die Landnutzung bestimmt. Böden und Kolluvien enthalten wichtige Informationen über die ursprüngliche Landschaft, ehemalige Landnutzungsphasen und Umweltveränderungen. Die spezifischen Merkmale in Kombination mit den archäologischen Befunden ermöglichen Rückschlüsse auf vergangene Natur- und Kulturräume.
Das Ziel der vorliegenden Arbeit ist es, ein besseres Verständnis über die Siedlungs- und Landschaftsentwicklung der untersuchten Gebiete in Franken zu erlangen. Hierfür ist es angebracht, mehrere räumlich verteilte Standorte zu untersuchen. Um den menschlichen Einfluss auf die prähistorische Landschaft besser verstehen zu können, kam ein interdisziplinärer Ansatz mit archäologischen und physisch-geographischen Methoden zur Anwendung. Die Umgebungen der einzelnen Untersuchungsstandorte wurden nach geomorphologischen Kriterien charakterisiert und ausgewählten Befunde nach bodenkundlichen Fragestellungen aufgenommen. Die Bestimmung der bodenphysikalischen und -chemischen Eigenschaften von Böden und Sedimenten erfolgte anhand repräsentativer Probenmengen. Bei ausgewählten Profilen kamen zusätzlich die Analysen zur Bestimmung der Gesamt- und Tonmineralogie sowie die Methode der 14C-Datierung für Bodensedimente, Tierknochen und Holzkohlen hinzu. Die physisch-geographischen Ergebnisse konnten anschließend mit den archäologischen Informationen ergänzt.
Die drei ausgewählten Untersuchungsgebiete befinden sich im Fränkischen Schichtstufenland. Der Bullenheimer Berg wurde aufgrund seiner bedeutenden Besiedlungsgeschichte ausgewählt. Die ausgewählten Profile liegen in verschiedenen Nutzungsarealen auf dem Plateau.
Die Standorte Marktbergel und Ergersheim liegen im Gebiet des Fränkischen Gipskarstes. Diese Untersuchungen sind ein Teil des DFG-geförderten Projektes „Prähistorische Mensch-Umwelt-Beziehungen im Gipskarst der Windsheimer Bucht, Nordbayern. Dolinen als Archive für Siedlungs- und Landschaftsentwicklung.“
Die vorliegenden Ergebnisse zeigen, dass der anthropogene Einfluss zu einer deutlichen Veränderung in der Landschaft führte. Für die Untersuchungsräume zeichnet sich eine lange Nutzungsgeschichte seit dem Beginn des Holozäns ab. Durch die Auswertung der Geländebefunde und der labortechnisch erzeugten Kennwerte konnten die untersuchten Profile in mehrere Phasen gegliedert werden. Es zeigten sich Stabilitätsphasen in denen Bodenbildung stattfinden konnte, aber auch geomorphodynamisch aktive Phasen der Erosion und Akkumulation von Bodensedimenten.
Der anthropogene Klimawandel ist eine der größten Herausforderungen des 21. Jahrhunderts. Eine Hauptschwierigkeit liegt dabei in der Unsicherheit bezüglich der regionalen Änderung von Niederschlag und Temperatur. Hierdurch wird die Entwicklung geeigneter Anpassungsstrategien deutlich erschwert.
In der vorliegenden Arbeit werden vier Evaluationsansätze mit insgesamt 13 Metriken für aktuelle globale (zwei Generationen) und regionale Klimamodelle entwickelt und verglichen, um anschließend eine Analyse der Projektionsunsicherheit vorzunehmen. Basierend auf den erstellten Modellbewertungen werden durch Gewichtung Aussagen über den Unsicherheitsbereich des zukünftigen Klimas getroffen. Die Evaluation der Modelle wird im Mittelmeerraum sowie in acht Unterregionen durchgeführt. Dabei wird der saisonale Trend von Temperatur und Niederschlag im Evaluationszeitraum 1960–2009 ausgewertet. Zusätzlich wird für bestimmte Metriken jeweils das klimatologische Mittel oder die harmonischen Zeitreiheneigenschaften evaluiert. Abschließend werden zum Test der Übertragbarkeit der Ergebnisse neben den Hauptuntersuchungsgebieten sechs global verteilte Regionen untersucht. Außerdem wird die zeitliche Konsistenz durch Analyse eines zweiten, leicht versetzten Evaluationszeitraums behandelt, sowie die Abhängigkeit der Modellbewertungen von verschiedenen Referenzdaten mit Hilfe von insgesamt drei Referenzdatensätzen untersucht.
Die Ergebnisse legen nahe, dass nahezu alle Metriken zur Modellevaluierung geeignet sind. Die Auswertung unterschiedlicher Variablen und Regionen erzeugt Modellbewertungen, die sich in den Kontext aktueller Forschungsergebnisse einfügen. So wurde die Leistung der globalen Klimamodelle der neusten Generation (2013) im Vergleich zur Vorgängergeneration (2007) im Schnitt ähnlich hoch bzw. in vielen Situationen auch stärker eingeordnet. Ein durchweg bestes Modell konnte nicht festgestellt werden. Der Großteil der entwickelten Metriken zeigt für ähnliche Situationen übereinstimmende Modellbewertungen. Bei der Gewichtung hat sich der Niederschlag als besonders geeignet herausgestellt. Grund hierfür sind die im Schnitt deutlichen Unterschiede der Modellleistungen in Zusammenhang mit einer geringeren Simulationsgüte. Umgekehrt zeigen die Metriken für die Modelle der Temperatur allgemein überwiegend hohe Evaluationsergebnisse, wodurch nur wenig Informationsgewinn durch Gewichtung erreicht werden kann. Während die Metriken gut für unterschiedliche Regionen und Skalenniveaus verwendet werden Evaluationszeiträume nicht grundsätzlich gegeben. Zusätzlich zeigen die Modellranglisten unterschiedlicher Regionen und Jahreszeiten häufig nur geringe Korrelationen. Dies gilt besonders für den Niederschlag. Bei der Temperatur sind hingegen leichte Übereinstimmungen auszumachen. Beim Vergleich der mittleren Ranglisten über alle Modellbewertungen und Situationen der Hauptregionen des Mittelmeerraums mit den Globalregionen besteht eine signifikante Korrelation von 0,39 für Temperatur, während sie für Niederschlag um null liegt. Dieses Ergebnis ist für alle drei verwendeten Referenzdatensätze im Mittelmeerraum gültig. So schwankt die Korrelation der Modellbewertungen des Niederschlags für unterschiedliche Referenzdatensätze immer um Null und die der Temperaturranglisten zwischen 0,36 und 0,44. Generell werden die Metriken als geeignete Evaluationswerkzeuge für Klimamodelle eingestuft. Daher können sie einen Beitrag zur Änderung des Unsicherheitsbereichs und damit zur Stärkung des Vertrauens in Klimaprojektionen leisten.
Die Abhängigkeit der Modellbewertungen von Region und Untersuchungszeitraum muss dabei jedoch berücksichtigt werden. So besitzt die Analyse der Konsistenz von Modellbewertungen sowie der Stärken und Schwächen der Klimamodelle großes Potential für folgende Studien, um das Vertrauen in Modellprojektionen weiter zu steigern.
Bei der Cu-Zn-Lagerstätte bei Kupferberg, 10 km nordöstlich von Kulmbach, handelt es sich um Bayerns größten, historischen Buntmetallabbau. Der etwa 4 km lange Zug einzelner, stratiformer Erzlinsen befindet sich im Nordwesten in der parautochthonen Randschiefer Formation und im Südosten in der Prasinit-Phyllit Formation, die ein Teil der allochthonen Münchberger Gneismasse ist. Bisherige Versuche, die Genese der Lagerstätte zu erklären, scheiterten daran, den versatzlosen Übertritt einer stratiformen Lagerstätte über eine regional bedeutende Störungszone zu erklären.
U-Pb Zirkondatierungen an mafischen und felsischen Vulkaniten im Umfeld der Lagerstätte bestätigten das Bild eines kambrisch-ordovizischen Extensionsvulkanismus. Das Fehlen von N-MORB-ähnlichen geochemischen Signaturen in den untersuchten Proben der gesamten südwestlichen, saxothuringischen Vogtland Synklinale deutet auf eine gescheiterte Riftbildung am Nordrand Gondwanas hin und setzt somit den geotektonischen Rahmen für die Ablagerung der Wirtsformation(en).
Die Cu-Zn-Vererzung selbst liegt hier im Wesentlichen als Vergesellschaftung von Pyrit, Chalkopyrit, Sphalerit, Quarz und Kalzit in kohlenstoffreichem Tonschiefer vor. Die verschiedenen Untersuchungen an den beiden Erzlinsen zeigten, dass in der „St. Veits“ Erzlinse eine syngenetische Pyrit-Anreicherung mit charakteristisch niedrigen Co/Ni-Verhältnissen (ø = 3,7) vorliegt. Darüber hinaus konnte dort noch mindestens eine hydrothermale Pyrit-Generation (Co/Ni-Verhältnis ca. 35) nachgewiesen werden, die nur dort auftritt, wo auch Chalkopyrit angereichert ist und deutlich höhere Co/Ni-Verhältnisse aufweist (ø = 35). Die Ermittlung der Cu-Isotopenverhältnisse des Chalkopyrits zeigte ein δ65Cu-Spektrum von -0,26 bis 0,36 ‰, was stark für eine hydrothermale Anreicherung unter hohen (>250 °C) Temperaturbedingungen spricht.
Während sich die Erzlinsen in der Randschiefer und Prasinit-Phyllit Formation hinsichtlich ihrer Sulfid-Mineralogie so ähnlich sind, dass sie bisher immer als eine Lagerstätte angesprochen wurden, erbrachte ein statistischer Vergleich der beiden δ34S-Datensätze, dass es sich hier nur mit einer Wahrscheinlichkeit von ca. 2 % um Stichproben der gleichen Grundgesamtheit handelt. Entsprechend liegen innerhalb der Kupferberger Lagerstätte zwei unterschiedliche Schichten, reich an syngenetischem Pyrit, vor. Die Tatsache, dass das δ34S-Spektrum potentieller Schwefelquellen für die hydrothermale Chalkopyrit-Mineralisation theoretisch sehr groß, de facto aber mit dem δ34S-Spektrum der syngenetischen Sulfidanreicherung fast identisch ist (δ34S = 3,2 ± 0,6 ‰ bzw. δ34S = 3,1 ± 0,9 ‰), spricht für eine schichtinterne Sulfidmobilisierung.
Aus den hier erbrachten Ergebnissen wird ein genetisches Modell für die Kupferberger Lagerstätte geschlussfolgert, in dem jeweils eine der zahlreichen sedimentären, Pyrit-reichen Schichten aus der Randschiefer und der Prasinit-Phyllit Formation bei der Überschiebung der Münchberger Gneismasse tektonisch in Kontakt gebracht wurden. Im Zuge eben dieser Raumnahme der allochthonen Masse wurden Teile der Randschiefer Formation unter Grünschiefer-fazielle Bedingungen gebracht. Dabei kam es sowohl zur Freisetzung von Buntmetallen, die vorher zum Großteil in Pyrit gebunden waren, als auch zur Entwässerung der umliegenden Tonschiefer. Durch die überlagernden, impermeablen metamorphen Decken wurde das entstandene metallreiche Fluid an der Überschiebungsbahn kanalisiert. Durch den Druckabfall in der Spröde-Duktil-Übergangszone kam es zum Sieden des aufsteigenden Fluids, was zur Ausfällung der Sulfide führte. Die Bildung bedeutender Erzlinsen erfolgte vor allem dort, wo das übersättigte Fluid auf Pyrit-reiche Schwarzschiefer bzw. Phyllite traf. Da die Abbauwürdigkeit dieser Erzlinsen im Wesentlichen auf die epigenetische Überprägung im Zuge der Deckenüberschiebung zurückzuführen ist, handelt es sich bei der Kupferberger Cu-Zn-Vererzung um eines der seltenen Beispiele für eine tatsächliche metamorphogene bzw. syntektonische Buntmetalllagerstätte.
The Kaapvaal Craton hosts a number of large gold deposits (e.g. Witwatersrand Supergroup) which mining companies have exploited at certain stratigraphic positions. It also hosts the largest platinum group element (PGE) deposits (e.g. Bushveld Igneous Complex) which mining companies have exploited in different mineralised layered magmatic zones. In spite of the extensive exploration history in the Kaapvaal Craton, the origin of the Witwatersrand gold deposits and Bushveld Igneous Complex PGE deposits has remained one of the most debated topics in economic geology. The goal of this study was to identify the geochemical characteristics of marine shales in the Barberton, Witwatersrand, and Transvaal supergroups in South Africa in order to make inferences on their sediment provenance and siderophile element endowments. Understanding why some of the Archaean and Proterozoic hinterlands are heavily mineralised, compared to others with similar geological characteristics, will aid in the development of more efficient exploration models. Fresh, unmineralised marine shales from the Barberton (Fig Tree and Moodies groups), Witwatersrand (West Rand and Central Rand groups), and Transvaal (Black Reef Formation and Pretoria Group) supergroups were sampled from drill core and underground mining exposures. Analytical methods, such as X-ray powder diffraction (XRD), optical microscopy, X-ray fluorescence (XRF), inductively coupled plasma optical emission spectroscopy (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), and electron microprobe analysis (EMPA) were applied to comprehensively characterise the shales. All of the Au and PGE assays examined the newly collected shale samples.
The Barberton Supergroup shales consist mainly of quartz, illite, chlorite, and albite, with diverse heavy minerals, including sulfides and oxides, representing the minor constituents. The regionally persistent Witwatersrand Supergroup shales consist mainly of quartz, muscovite, and chlorite, and also contain minor constituents of sulfides and oxides. The Transvaal Supergroup shales comprise quartz, chlorite, and carbonaceous material. Major, trace (including rare-earth element) concentrations were determined for shales from the above supergroups to constrain their source and post-depositional evolution. Chemical variations were observed in all the studied marine shales. Results obtained from this study revealed that post-depositional modification of shale chemistry was significant only near contacts with over- and underlying coarser-grained siliciclastic rocks and along cross-cutting faults, veins, and dykes. Away from such zones, the shale composition remained largely unaltered and can be used to draw inferences concerning sediment provenance and palaeoweathering in the source region and/or on intrabasinal erosion surfaces. Evaluation of weathering profiles through sections of the studied supergroups revealed that the shales therein are characterised by high chemical index of alteration (CIA), chemical index of weathering (CIW), and index of compositional variability (ICV), suggesting that the source area was lithologically complex and subject to intense chemical weathering.
A progressive change in the chemical composition was identified, from a dominant ultramafic–mafic source for the Fig Tree Group to a progressively felsic–plutonic provenance for the Moodies Group. The West Rand Group of the Witwatersrand Supergroup shows a dominance of tonalite–trondhjemite–granodiorite and calcalkaline granite sources. Compositional profiles through the only major marine shale unit within the Central Rand Group indicate the progressive unroofing of a granitic source in an otherwise greenstone-dominated hinterland during the course of sedimentation. No plausible likely tectonic setting was obtained through geochemical modelling. However, the combination of the systematic shale chemistry, geochronology, and sedimentology in the Witwatersrand Supergroup supports the hypothesised passive margin setting for the >2.98 to 2.91 Ga West Rand Group, and an active continental margin source for the overlying >2.90 to 2.78 Ga Central Rand Group, along with a foreland basin setting for the latter.
Ultra-low detection limit analyses of gold and PGE concentrations revealed a variable degree of gold accumulation within pristine unmineralised shales. All the studied shales contain elevated gold and PGE contents relative to the upper continental crust, with marine shales from the Central Rand Group showing the highest Au (±9.85 ppb) enrichment. Based on this variation in the provenance of contemporaneous sediments in different parts of the Kaapvaal Craton, one can infer that the siderophile elements were sourced from a fertile hinterland, but concentrated into the marine shales by a combination of different processes. It is proposed that accumulation of siderophile elements in the studied marine shales was mainly controlled by mechanical coagulation and aggregation. These processes involved suspended sediments, fine gold particles, and other trace elements being trapped in marine environments. Mechanical coagulation and aggregation resulted in gold enrichments by 2–3 orders of magnitude, whereas some of the gold in these marine shales can be reconciled by seawater adsorption into sedimentary pyrite.
For the source of gold and PGEs in the studied marine shales in the Kaapvaal Craton, a genetic model is proposed that involves the following:
(1) A highly siderophile elements enriched upper mantle domain, herein referred to as “geochemically anomalous mantle domain”, from which the Kaapvaal crust was sourced. This mantle domain enriched in highly siderophile elements was formed either by inhomogeneous mixing with cosmic material that was added during intense meteorite bombardment of the Hadaean to Palaeoarchaean Earth or by plume-like ascent of relics from the core–mantle boundary. In both cases, elevated siderophile elements concentrations would be expected. The geochemically anomalous mantle domain is likely the ultimate source of the Witwatersrand modified palaeoplacer gold deposits and was tapped again ca. 2.054 Ga during the emplacement of the Bushveld Igneous Complex. Therefore, I propose that there is a genetic link (i.e. common geochemically anomalous mantle source) between the Witwatersrand gold deposits and the younger Bushveld Igneous Complex PGE deposits.
(2) Scavenging of crustal gold by various surface processes such as trapping of gold from Archaean/Palaeoproterozoic river water on the surface of local photosynthesizing cyanobacterial or microbial mats, and reworking of these mats into erosion channels during flooding events.
The above two models complement each other, with model (1) providing a common geological source for the Witwatersrand gold and Bushveld Igneous Complex PGE deposits, and model (2) explaining the processes responsible for Witwatersrand-type gold pre-concentration processes. In sequences such as the Transvaal Supergroup, a less fertile hinterland and/or less reworking of older sediments led to a correspondingly lower gold endowment. These findings indicate temporal distribution of siderophile elements in the upper crust (e.g. marine shales). The overall implications of these findings are that background concentrations of gold and PGEs can be used to target potential exploration areas in other cratons of similar age. This increases the likelihood of finding other Witwatersrand-type gold or Bushveld Igneous Complex-type PGE deposits in other cratons.
Diese Arbeit widmet sich detaillierten stratigraphischen und paläopedologischen Studien an Löss-Paläoboden Sequenzen (LPS) im kontinentalen Nordosten Österreichs, im Lee der Böhmischen Masse relativ zur Westwindzone. Neben methodischen Erkenntnissen ergeben sich allgemeine Schlussfolgerungen über die Klima- und Landschaftsentwicklung während der letzten Million Jahre.
Die untersuchten Aufschlüsse liegen in der Region um Krems (Krems-Schießstätte, Paudorf, Stiefern) und in Stillfried. Einige sind weithin bekannt als ehemalige Typuslokalitäten der Quartärstratigraphie, aber nach fundamentalen Revisionen in den 1970er Jahren schwand das Interesse an diesen merklich. Die LPS befinden sich in Hanglage, so sind polygenetische Einheiten und Erosionslücken üblich. Als Archive einer komplexen geomorphologischen Entwicklung sind sie nicht geeignet für die Anwendung üblicher paläoklimatischer Proxies.
Um die Entstehung der untersuchten LPS zu verstehen, wurde ein multimethodischer Ansatz entwickelt, der detaillierte Untersuchungen von der Landschafts- bis auf die Mikroebene umfasst. Innovativ ist die Verwendung quantitativer Farbmessungen in hoher Auflösung zum Zwecke einer standardisierten Klassifikation von Profileinheiten. Detaillierte mikromorphologische Untersuchungen sind Basis für die Rekonstruktion des Wechselspiels aus äolischer Sedimentation, Pedogenese und Hangprozessen.
Die Korrelation der LPS basiert auf mehreren geochronologischen Ankerpunkten und ist zugleich Hinweis auf tiefgreifende morphologische Veränderungen in der Region Krems während des Pleistozäns. Im chronologischen Rahmen ergeben sich unter Anwendung des Konzepts der klimaphytomorphen Böden qualitative paläoklimatische Schlussfolgerungen:
Kräftig verwitterte Bodenhorizonte sind polygenetisch und nicht das Resultat feuchterer Klimabedingungen während dezidierter Entwicklungsphasen. Die Kontinentalität des Untersuchungsgebiets blieb währenden der letzten Million Jahre weitgehend bestehen, teils mit erhöhtem mediterranem Einfluss. Eine Dominanz atlantischer Feuchte beschränkt(e) sich auf die Regionen westlich der Böhmischen Masse. Die Paläoklimate des Untersuchungs-gebiets waren eher vergleichbar mit jenen des Pannonischen Beckens, obgleich die untersuchten Sequenzen keinen Hinweis auf den dort vermuteten Gradienten zunehmender Aridität zeigen. Interessant sind ferner zahlreiche gebleichte Horizonte innerhalb der Lösssedimente, die als Reste von Tundragleyen interpretiert werden. Diese sind im Löss des Pannonischen Becken nicht nachweisbar. Hieraus wird ein mitteleuropäischer Charakter kaltzeitlichen Klimas innerhalb des untersuchten Zeitrahmens gefolgert.
The 2010 eruption of Eyjafjallajokull volcano was characterized by pulsating activity. Discrete ash bursts merged at higher altitude and formed a sustained quasi-continuous eruption column. High-resolution near-field videos were recorded on 8-10 May, during the second explosive phase of the eruption, and supplemented by contemporary aerial observations. In the observed period, pulses occurred at intervals of 0.8 to 23.4 s (average, 4.2 s). On the basis of video analysis, the pulse volume and the velocity of the reversely buoyant jets that initiated each pulse were determined. The expansion history of jets was tracked until the pulses reached the height of transition from a negatively buoyant jet to a convective buoyant plume about 100 m above the vent. Based on the assumption that the density of the gas-solid mixture making up the pulse approximates that of the surrounding air at the level of transition from the jet to the plume, a mass flux ranging between 2.2 and 3.5 . 10\(^4\) kg/s was calculated. This mass eruption rate is in good agreement with results obtained with simple models relating plume height with mass discharge at the vent. Our findings indicate that near-field measurements of eruption source parameters in a pulsating eruption may prove to be an effective monitoring tool. A comparison of the observed pulses with those generated in calibrated large-scale experiments reveals very similar characteristics and suggests that the analysis of near-field sensors could in the future help to constrain the triggering mechanism of explosive eruptions.
Environmental interlinked problems such as human-induced land cover change, water scarcity, loss in soil fertility, and anthropogenic climate change are expected to affect the viability of agriculture and increase food insecurity in many developing countries. Climate change is certainly the most serious of these challenges for the twenty-first century. The poorest regions of the world – tropical West Africa included – are the most vulnerable due to their high dependence on climate and weather sensitive activities such as agriculture, and the widespread poverty that limits the institutional and economic capacities to adapt to the new stresses brought about by climate change. Climate change is already acting negatively on the poor smallholders of tropical West Africa whose livelihoods dependent mainly on rain-fed agriculture that remains the cornerstone of the economy in the region. Adaptation of the agricultural systems to climate change effects is, therefore, crucial to secure the livelihoods of these rural communities. Since information is a key for decision-making, it is important to provide well-founded information on the magnitude of the impacts in order to design appropriate and sustainable adaptation strategies.
Considering the case of agricultural production in the Republic of Benin, this study aims at using large-scale climatic predictors to assess the potential impacts of past and future climate change on agricultural productivity at a country scale in West Africa. Climate signals from large-scale circulation were used because state-of-the art regional climate models (RCM) still do not perfectly resolve synoptic and mesoscale convective processes. It was hypothesised that in rain-fed systems with low investments in agricultural inputs, yield variations are widely governed by climatic factors. Starting with pineapple, a perennial fruit crops, the study further considered some annual crops such as cotton in the group of fibre crops, maize, sorghum and rice in the group of cereals, cowpeas and groundnuts belonging to the legume crops, and cassava and yams which are root and tuber crops. Thus the selected crops represented the three known groups of photosynthetic pathways (i.e. CAM, C3, and C4 plants).
In the study, use was made of the historical agricultural yield statistics for the Republic of Benin, observed precipitation and mean near-surface air temperature data from the Climatic Research Unit (CRU TS 3.1) and the corresponding variables simulated by the regional climate model (RCM) REMO. REMO RCM was driven at its boundaries by the global climate model ECHAM 5. Simulations with different greenhouse gas concentrations (SRES-A1B and B1 emission scenarios) and transient land cover change scenarios for present-day and future conditions were considered. The CRU data were submitted to empirical orthogonal functions analysis over the north hemispheric part of Africa to obtain large-scale observed climate predictors and associated consistent variability modes. REMO RCM data for the same region were projected on the derived climate patterns to get simulated climate predictors. By means of cross-validated Model Output Statistics (MOS) approach combined with Bayesian model averaging (BMA) techniques, the observed climate predictors and the crop predictand were further on used to derive robust statistical relationships. The robust statistical crop models perform well with high goodness-of-fit coefficients (e.g. for all combined crop models: 0.49 ≤ R2 ≤ 0.99; 0.28 ≤ Brier-Skill-Score ≤ 0.90).
Provided that REMO RCM captures the main features of the real African climate system and thus is able to reproduce its inter-annual variability, the time-independent statistical transfer functions were then used to translate future climate change signal from the simulated climate predictors into attainable crop yields/crop yield changes. The results confirm that precipitation and air temperature governed agricultural production in Benin in general, and particularly, pineapple yield variations are mainly influenced by temperature. Furthermore, the projected yield changes under future anthropogenic climate change during the first-half of the 21st century amount up to -12.5% for both maize and groundnuts, and -11%, -29%, -33% for pineapple, cassava, and cowpeas respectively. Meanwhile yield gain of up to +10% for sorghum and yams, +24% for cotton, and +39% for rice are expected. Over the time period 2001 – 2050, on average the future yield changes range between -3% and -13% under REMO SRES–B1 (GHG)+LCC, -2% and -11% under REMO SRES–A1B (GHG only),and -3% and -14% under REMO SRES–A1B (GHG)+LCC for pineapple, maize, sorghum, groundnuts, cowpeas and cassava. In the meantime for yams, cotton and rice, the average yield gains lie in interval of about +2% to +7% under REMO SRES–B1 (GHG)+LCC, +0.1% and +12% under REMO SRES–A1B (GHG only), and +3% and +10% under REMO SRES–A1B (GHG)+LCC. For sorghum, although the long-term average future yield depicts a reduction there are tendencies towards increasing yields in the future. The results also reveal that the increases in mean air temperature more than the changes in precipitation patterns are responsible for the projected yield changes. As well the results suggest that the reductions in pineapple yields cannot be attributed to the land cover/land use changes across sub-Saharan Africa. The production of groundnuts and in particular yams and cotton will profit from the on-going land use/land cover changes while the other crops will face detrimental effects.
Henceforth, policymakers should take effective measures to limit the on-going land degradation processes and all other anthropogenic actions responsible for temperature increase. Biotechnological improvement of the cultivated crop varieties towards development of set of seed varieties adapted to hotter and dry conditions should be included in the breeding pipeline programs. Amongst other solutions, application of appropriate climate-smart agricultural practices and conservation agriculture are also required to offset the negative impacts of climate change in agriculture.
Considering its social, economic and natural conditions the Mediterranean Area is a highly vulnerable region by designated affections of climate change. Furthermore, its climatic characteristics are subordinated to high natural variability and are steered by various elements, leading to strong seasonal alterations. Additionally, General Circulation Models project compelling trends in specific climate variables within this region. These circumstances recommend this region for the scientific analyses conducted within this study. Based on the data of the CMIP3 database, the fundamental aim of this study is a detailed investigation of the total variability and the accompanied uncertainty, which superpose these trends, in the projections of temperature, precipitation and sea-level pressure by GCMs and their specific realizations. Special focus in the whole study is dedicated to the German model ECHAM5/MPI-OM. Following this ambition detailed trends and mean values are calculated and displayed for meaningful time periods and compared to reanalysis data of ERA40 and NCEP. To provide quantitative comparison the mentioned data are interpolated to a common 3x3° grid.
The total amount of variability is separated in its contributors by the application of an Analysis of Variance (ANOVA). For individual GCMs and their ensemble-members this is done with the application of a 1-way ANOVA, separating a treatment common to all ensemble-members and variability perturbating the signal given by different initial conditions. With the 2-way ANOVA the projections of numerous models and their realizations are analysed and the total amount of variability is separated into a common treatment effect, a linear bias between the models, an interaction coefficient and the residuals.
By doing this, the study is fulfilled in a very detailed approach, by considering yearly and seasonal variations in various reasonable time periods of 1961-2000 to match up with the reanalysis data, from 1961-2050 to provide a transient time period, 2001-2098 with exclusive regard on future simulations and 1901-2098 to comprise a time period of maximum length. The statistical analyses are conducted for regional-averages on the one hand and with respect to individual grid-cells on the other hand. For each of these applications the SRES scenarios of A1B, A2 and B1 are utilized. Furthermore, the spatial approach of the ANOVA is substituted by a temporal approach detecting the temporal development of individual variables. Additionally, an attempt is made to enlarge the signal by applying selected statistical methods.
In the detailed investigation it becomes evident, that the different parameters (i.e. length of temporal period, geographic location, climate variable, season, scenarios, models, etc…) have compelling impact on the results, either in enforcing or weakening them by different combinations. This holds on the one hand for the means and trends but also on the other hand for the contributions of the variabilities affecting the uncertainty and the signal. While temperature is a climate variable showing strong signals across these parameters, for precipitation mainly the noise comes to the fore, while for sea-level pressure a more differentiated result manifests. In turn, this recommends the distinguished consideration of the individual parameters in climate impact studies and processes in model generation, as the affecting parameters also provide information about the linkage within the system.
Finally, an investigation of extreme precipitation is conducted, implementing the variables of the total amount of heavy precipitation, the frequency of heavy-precipitation events, the percentage of this heavy precipitation to overall precipitation and the mean daily intensity from events of heavy precipitation. Each time heavy precipitation is defined to exceed the 95th percentile of overall precipitation. Consecutively mean values of these variables are displayed for ECHAM5/MPI-OM and the multi-model mean and climate sensitivities, by means of their difference between their average of the past period of 1981-2000 and the average of one of the future periods of 2046-2065 or 2081-2100. Following this investigation again an ANOVA is conducted providing a quantitative measurement of the severity of change of trends in heavy precipitation across several GCMs.
Besides it is a difficult task to account for extreme precipitation by GCMs, it is noteworthy that the investigated models differ highly in their projections, resulting partially in a more smoothed and meaningful multi-model mean. Seasonal alterations of the strength of this behaviour are quantitatively supported by the ANOVA.
The glaciers in Norway exert a strong influence on Norwegian economy and society. Unlike many glaciers elsewhere and despite ongoing climate change and warming, many of them showed renewed advances and positive net mass changes in the 1980's and 1990's, followed by rapid retreats and mass losses since 2000. This difference in behaviour may be attributed to differences and shifts in the glaciological regime - the differences in the magnitude of impacts of climatic and non-climatic geographical factors on the glacier mass.
This study investigates the influence of various atmospheric variables on mass balance changes of a selection of glaciers in Norway by means of Pearson correlation analyses and cross-validated stepwise multiple regression analyses. The analyses are carried out for three time periods (1949-2008, 1949-1988, 1989-2008) separately in order to take into consideration the possible shift in the glaciological regime in the 1980's. The atmospheric variables are constructed from ERA40 and NCEP/NCAR re-analysis datasets and include regional means of seasonal air temperature and precipitation rates and atmospheric circulation indices. The multiple regression models trained in these time periods are then applied to predictors reconstructed from the CMIP3 climate model dataset to generate an estimate for mass changes from the year 1950 to 2100. The temporal overlap of estimates and observations is used for calibration. Finally, observed atmospheric states in seasons that are characterised by a particularly positive or negative mass balance are categorised into time periods of modelled climate by the application of a Bayesian classification procedure.
The strongest influence on winter mass balance is exerted by different indices of the North Atlantic Oscillation (NAO), Northern Annular Mode (NAM) and precipitation. The correlation coefficients and explained variances determined from the multiple regression analyses reveal an East-West gradient, suggesting a weaker influence of the NAO and NAM on glaciers underlying a more continental regime. The highest correlation coefficients and explained variances were obtained for the 1989-2008 time period, which might be due to a strong and predominantly positive phase of the NAO. Multi-model ensemble means of the estimates show a mass loss for all three eastern glaciers, while the estimates for the more maritime glaciers are ambivalent. In general, the estimates show a greater sensitivity to the training time period than to the greenhouse gas emission scenarios according to which the climates were simulated. The average net mass change by the end of 2100 is negative for all glaciers except for the northern Engabreen. For many glaciers, the Bayesian classification of observed atmospheric states into time periods of modelled climate reveals a decrease in probability of atmospheric states favouring extremes in winter, and an increase in probability of atmospheric states favouring extreme mass loss in summer for the distant future (2071-2100). This pattern of probabilities for the ablation season is most pronounced for glaciers underlying a continental and intermediate regime.
The ecosystem of the high northern latitudes is affected by the recently changing environmental conditions. The Arctic has undergone a significant climatic change over the last decades. The land coverage is changing and a phenological response to the warming is apparent. Remotely sensed data can assist the monitoring and quantification of these changes. The remote sensing of the Arctic was predominantly carried out by the usage of optical sensors but these encounter problems in the Arctic environment, e.g. the frequent cloud cover or the solar geometry. In contrast, the imaging of Synthetic Aperture Radar is not affected by the cloud cover and the acquisition of radar imagery is independent of the solar illumination. The objective of this work was to explore how polarimetric Synthetic Aperture Radar (PolSAR) data of TerraSAR-X, TanDEM-X, Radarsat-2 and ALOS PALSAR and interferometric-derived digital elevation model data of the TanDEM-X Mission can contribute to collect meaningful information on the actual state of the Arctic Environment. The study was conducted for Canadian sites of the Mackenzie Delta Region and Banks Island and in situ reference data were available for the assessment. The up-to-date analysis of the PolSAR data made the application of the Non-Local Means filtering and of the decomposition of co-polarized data necessary.
The Non-Local Means filter showed a high capability to preserve the image values, to keep the edges and to reduce the speckle. This supported not only the suitability for the interpretation but also for the classification. The classification accuracies of Non-Local Means filtered data were in average +10% higher compared to unfiltered images. The correlation of the co- and quad-polarized decomposition features was high for classes with distinct surface or double bounce scattering and a usage of the co-polarized data is beneficial for regions of natural land coverage and for low vegetation formations with little volume scattering. The evaluation further revealed that the X- and C-Band were most sensitive to the generalized land cover classes. It was found that the X-Band data were sensitive to low vegetation formations with low shrub density, the C-Band data were sensitive to the shrub density and the shrub dominated tundra. In contrast, the L-Band data were less sensitive to the land cover. Among the different dual-polarized data the HH/VV-polarized data were identified to be most meaningful for the characterization and classification, followed by the HH/HV-polarized and the VV/VH-polarized data. The quad-polarized data showed highest sensitivity to the land cover but differences to the co-polarized data were small. The accuracy assessment showed that spectral information was required for accurate land cover classification. The best results were obtained when spectral and radar information was combined. The benefit of including radar data in the classification was up to +15% accuracy and most significant for the classes wetland and sparse vegetated tundra. The best classifications were realized with quad-polarized C-Band and multispectral data and with co-polarized X-Band and multispectral data. The overall accuracy was up to 80% for unsupervised and up to 90% for supervised classifications. The results indicated that the shortwave co-polarized data show promise for the classification of tundra land cover since the polarimetric information is sensitive to low vegetation and the wetlands. Furthermore, co-polarized data provide a higher spatial resolution than the quad-polarized data.
The analysis of the intermediate digital elevation model data of the TanDEM-X showed a high potential for the characterization of the surface morphology. The basic and relative topographic features were shown to be of high relevance for the quantification of the surface morphology and an area-wide application is feasible. In addition, these data were of value for the classification and delineation of landforms. Such classifications will assist the delineation of geomorphological units and have potential to identify locations of actual and future morphologic activity.
Irrigated agriculture in the Khorezm region in the arid inner Aral Sea Basin faces enormous challenges due to a legacy of cotton monoculture and non-sustainable water use. Regional crop growth monitoring and yield estimation continuously gain in importance, especially with regard to climate change and food security issues. Remote sensing is the ideal tool for regional-scale analysis, especially in regions where ground-truth data collection is difficult and data availability is scarce. New satellite systems promise higher spatial and temporal resolutions. So-called light use efficiency (LUE) models are based on the fraction of photosynthetic active radiation absorbed by vegetation (FPAR), a biophysical parameter that can be derived from satellite measurements. The general objective of this thesis was to use satellite data, in conjunction with an adapted LUE model, for inferring crop yield of cotton and rice at field (6.5 m) and regional (250 m) scale for multiple years (2003-2009), in order to assess crop yield variations in the study area. Intensive field measurements of FPAR were conducted in the Khorezm region during the growing season 2009. RapidEye imagery was acquired approximately bi-weekly during this time. The normalized difference vegetation index (NDVI) was calculated for all images. Linear regression between image-based NDVI and field-based FPAR was conducted. The analyses resulted in high correlations, and the resulting regression equations were used to generate time series of FPAR at the RapidEye level. RapidEye-based FPAR was subsequently aggregated to the MODIS scale and used to validate the existing MODIS FPAR product. This step was carried out to evaluate the applicability of MODIS FPAR for regional vegetation monitoring. The validation revealed that the MODIS product generally overestimates RapidEye FPAR by about 6 to 15 %. Mixture of crop types was found to be a problem at the 1 km scale, but less severe at the 250 m scale. Consequently, high resolution FPAR was used to calibrate 8-day, 250 m MODIS NDVI data, this time by linear regression of RapidEye-based FPAR against MODIS-based NDVI. The established FPAR datasets, for both RapidEye and MODIS, were subsequently assimilated into a LUE model as the driving variable. This model operated at both satellite scales, and both required an estimation of further parameters like the photosynthetic active radiation (PAR) or the actual light use efficiency (LUEact). The latter is influenced by crop stress factors like temperature or water stress, which were taken account of in the model. Water stress was especially important, and calculated via the ratio of the actual (ETact) to the potential, crop-specific evapotranspiration (ETc). Results showed that water stress typically occurred between the beginning of May and mid-September and beginning of May and end of July for cotton and rice crops, respectively. The mean water stress showed only minor differences between years. Exceptions occurred in 2008 and 2009, where the mean water stress was higher and lower, respectively. In 2008, this was likely caused by generally reduced water availability in the whole region. Model estimations were evaluated using field-based harvest information (RapidEye) and statistical information at district level (MODIS). The results showed that the model at both the RapidEye and the MODIS scale can estimate regional crop yield with acceptable accuracy. The RMSE for the RapidEye scale amounted to 29.1 % for cotton and 30.4 % for rice, respectively. At the MODIS scale, depending on the year and evaluated at Oblast level, the RMSE ranged from 10.5 % to 23.8 % for cotton and from -0.4 % to -19.4 % for rice. Altogether, the RapidEye scale model slightly underestimated cotton (bias = 0.22) and rice yield (bias = 0.11). The MODIS-scale model, on the other hand, also underestimated official rice yield (bias from 0.01 to 0.87), but overestimated official cotton yield (bias from -0.28 to -0.6). Evaluation of the MODIS scale revealed that predictions were very accurate for some districts, but less for others. The produced crop yield maps indicated that crop yield generally decreases with distance to the river. The lowest yields can be found in the southern districts, close to the desert. From a temporal point of view, there were areas characterized by low crop yields over the span of the seven years investigated. The study at hand showed that light use efficiency-based modeling, based on remote sensing data, is a viable way for regional crop yield prediction. The found accuracies were good within the boundaries of related research. From a methodological viewpoint, the work carried out made several improvements to the existing LUE models reported in the literature, e.g. the calibration of FPAR for the study region using in situ and high resolution RapidEye imagery and the incorporation of crop-specific water stress in the calculation.
Information on the state of the terrestrial vegetation cover is important for several ecological, economical, and planning issues. In this regard, vegetation properties such as the type, vitality, or density can be described by means of continuous biophysical parameters. One of these parameters is the leaf area index (LAI), which is defined as half the total leaf area per unit ground surface area. As leaves constitute the interface between the biosphere and the atmosphere, the LAI is used to model exchange processes between plants and their environment. However, to account for the variability of ecosystems, spatially and temporally explicit information on LAI is needed both for monitoring and modeling applications.
Remote sensing aims at providing such information. LAI is commonly derived from remote sensing data by empirical-statistical or physical models. In the first approach, an empirical relationship between LAI measured in situ and the corresponding canopy spectral signature is established. Although this method achieves accurate LAI estimates, these relationships are only valid for the place and time at which the field data were sampled, which hampers automated LAI derivation. The physical approach uses a radiation transfer model to simulate canopy reflectance as a function of the scene’s geometry and of leaf and canopy parameters, from which LAI is derived through model inversion based on remote sensing data. However, this model inversion is not stable, as it is an under-determined and ill-posed problem.
Until now, LAI research focused either on the use of coarse resolution remote sensing data for global applications, or on LAI modeling over a confined area, mostly in forest and crop ecosystems, using medium to high spatial resolution data. This is why to date no study is available in which high spatial resolution data are used for LAI mapping in a heterogeneous, natural landscape such as alpine grasslands, although a growing amount of high spatial and temporal resolution remote sensing data would allow for an improved environmental monitoring. Therefore, issues related to model parameterization and inversion regularization techniques improving its stability have not yet been investigated for this ecosystem.
This research gap was taken up by this thesis, in which the potential of high spatial resolution remote sensing data for grassland LAI estimation based on statistical and radiation transfer modeling is analyzed, and the achieved accuracy and robustness of the two approaches is compared. The objectives were an ecosystem-adapted radiation transfer model set-up and an optimized LAI derivation in mountainous grassland areas. Multi-temporal LAI in situ measurements as well as time series of RapidEye data from 2011 and 2012 over the catchment of the River Ammer in the Bavarian alpine upland were used. In order to obtain accurate in situ data, a comparison of the LAI derivation algorithms implemented in the LAI-2000 PCA instrument with destructively measured LAI was performed first. For optimizing the empirical-statistical approach, it was then analyzed how the selection of vegetation indices and regression models impacts LAI modeling, and how well these models can be transferred to other dates. It was shown that LAI can be derived
with a mean accuracy of 80 % using contemporaneous field data, but that the accuracy decreases to on average 51 % when using these models on remote sensing data from other dates. The combined use of several data sets to create a regression which is used for LAI derivation at different points in time increased the LAI estimation accuracy to on average 65 %. Thus, reduced field measurement labor comes at the cost of LAI error rates being increased by 10 - 30 % as long as at least two campaigns are conducted. Further, it was shown that the use of RapidEye’s red edge channel improves the LAI derivation by on average 5.4 %.
With regard to physical LAI modeling, special interest lay in assessing the accuracy improvements that can be achieved through model set-up and inversion regularization techniques. First, a global sensitivity analysis was applied to the radiation transfer model in order to identify the most important model parameters and most sensitive spectral features. After model parameterization, several inversion regularizations, namely the use of a multiple sample solution, the additional use of vegetation indices, and the addition of noise, were analyzed. Further, an approach to include the local scene’s geometry in the retrieval process was introduced to account for the mountainous topography. LAI modeling accuracies of in average 70 % were achieved using the best combination of regularization techniques, which is in the upper range of accuracies that were achieved in the few existing other grassland studies based on in situ or air-borne measured hyperspectral data. Finally, further physically derived vegetation parameters and inversion uncertainty measures were evaluated in detail to identify challenging modeling conditions, which was mostly neglected in other studies. An increased modeling uncertainty for extremely high and low LAI values was observed. This indicates an insufficiently wide model parameterization and a canopy deviation from model assumptions on some fields. Further, the LAI modeling accuracies varied strongly between the different scenes. From this observation it can be deduced that the radiometric quality of the remote sensing data, which might be reduced by atmospheric effects or unexpected surface reflectances, exerts a high influence on the LAI modeling accuracy.
The major findings of the comparison between the empirical-statistical and physical LAI modeling approaches are the higher accuracies achieved by the empirical-statistical approach as long as contemporaneous field data are available, and the computationally efficiency of the statistical approach. However, when no or temporally unfitting in situ measurements are available, the physical approach achieves comparable or even higher accuracies. Furthermore, radiation transfer modeling enables the derivation of other leaf and canopy variables useful for ecological monitoring and modeling applications, as well as of pixel-wise uncertainty measures indicating the robustness and reliability of the model inversion and LAI derivation procedure. The established look-up tables can be used for further LAI derivation in Central European grassland also in other years.
The use of high spatial resolution remote sensing data for LAI derivation enables a reliable land cover classification and thus a reduced LAI mapping error due to misclassifications. Furthermore, the RapidEye pixels being smaller than individual fields allow for a radiation transfer model inversion over homogeneous canopies in most cases, as canopy gaps or field parcels can be clearly distinguished. However, in case of unexpected local surface conditions such as blooming, litter, or canopy gaps, high spatial resolution data show corresponding strong deviations in reflectance values and hence LAI estimation, which would be reduced using coarser resolution data through the balancing effect of the surrounding surface reflectances. An optimal pixel size with regard to modeling accuracy hence depends on the canopy and landscape structure. Furthermore, a reduced spatial resolution would enable a considerable acceleration of the LAI map derivation.
This illustration of the potential of RapidEye data and of the challenges associated to LAI derivation in heterogeneous grassland areas contributes to the development of robust LAI estimation procedures based on new and upcoming, spatially and temporally high resolution remote sensing imagery such as Landsat 8 and Sentinel-2.
Klimawandelbedingte bzw. potenziell klimawandelbedingte Umweltmigration ist ein sehr komplexes und breites Feld. Es existiert eine Fülle von Studien, die sich in ihrer Herangehensweise unterscheiden, weshalb hier ein Systematisierungsvorschlag aufgezeigt wird. Mittels einer an den Richtlinien der Grounded Theory orientierten Analyse wurden Studien auf zentrale gemeinsame Kategorien hin untersucht und als Modell präsentiert. Dieses stellt jedoch kein abgeschlossenes System dar, sondern dient durch seine Offenheit als Gerüst, das mit Ergebnissen aus weiteren Fallstudien gefestigt werden kann.
The eminent importance of snow cover for climatic, hydrologic, anthropogenic, and economic reasons has been widely discussed in scientific literature. Up to 50% of the Northern Hemisphere is covered by snow at least temporarily, turning snow to the most prevalent land cover types at all. Depending on regular precipitation and temperatures below freezing point it is obvious that a changing climate effects snow cover characteristics fundamentally. Such changes can have severe impacts on local, national, and even global scale. The region of Central Asia is not an exception from this general rule, but are the consequences accompanying past, present, and possible future changes in snow cover parameters of particular importance. Being characterized by continental climate with hot and dry summers most precipitation accumulates during winter and spring months in the form of snow. The population in this 4,000,000 km² vast area is strongly depending on irrigation to facilitate agriculture. Additionally, electricity is often generated by hydroelectric power stations. A large proportion of the employed water originates from snow melt during spring months, implying that changes in snow cover characteristics will automatically affect both the total amount of obtainable water and the time when this water becomes available. The presented thesis explores the question how the spatial extent of snow covered surface has evolved since the year 1986. This investigation is based on the processing of medium resolution remote sensing data originating from daily MODIS and AVHRR sensors, thus forming a unique approach of snow cover analysis in terms of temporal and spatial resolution. Not only duration but also onset and melt of snow coverage are tracked over time, analyzing for systematic changes within this 26 years lasting time span. AVHRR data are processed from raw Level 1B orbit data to Level 3 thematic snow cover products. Both, AVHRR and MODIS snow maps undergo a further post-processing, producing daily full-area mosaics while completely eliminating inherent cloud cover. Snow cover parameters are derived based on these daily and cloud-free time series, allowing for a detailed analysis of current status and changes. The results confirm the predictions made by coarse resolution predictions from climate models: Central Asian snow cover is changing, posing new challenges for the ecosystem and future water supply. The changes, however, are not aimed at only one direction. Regions with decreasing snow cover exist as well as those where the duration of snow cover increases. A shift towards earlier snow cover start and melt can be observed, posing a serious challenge to water management authorities due to a changed runoff regime.
No abstract available.
K-Ar dating on hornblendes and micas from the TepläDomazlice zone revealed a pattern of dates which significantly deviates from the mid-Carboniferous to early Permian one that is found in the adjacent low-pressure metamorphic Moldanubian and Saxothuringian. Especially for the Mariänske Läzne metabasic complex, confirming early Czech determinations, the dates resemble the early Devonian pattern determined for the Münchberg Gneiss Massif and the Erbendorf-Vohenstrauß zone of northeastern Bavaria. This supports the idea that all three units are remnants of a huge complex which suffered a metamorphic overprint under medium-pressure conditions, probably in the early Devonian. Streng rejuvenation is found in the southern part of the Teplä-Domailice zone by which micas and even two hornblendes were reset to mid-Carboniferous ages. According to the geological setting, part of the apparently preDevonian dates may be explained by inherited argon from earlier metamorphic and magmatic events, e.g. the high-pressure metamorphism documented in eclogitic relics. However, excess argon, caused by the mid-Carboniferous overprint cannot be excluded.
Various amphibolites, metagabbros and eclogitic relics of the Mariänske Läzne complex, and amphibolites from the Cernä Hora Massif exhibit an uniform geochemical character which compares weil with modern mid-ocean ridge basalts. Geochemically these metabasites are similar to the amphibolites of the Myto area and to schistose, partly striped amphibolites of the neighbouring Tirschenreuth-Mähring Zone and the Erbendorf-Vohenstrauss Zone (Bavaria). Greenschists and amphibolites from the Domazlice metamorphic complex show an alkaline-basaltic tendency conforming to modern within-plate basalts or basalts from anomalaus midocean ridge segments. In their chemical character, these metabasites compare weil with the flaseramphibolites of the Erbendorf-Vohenstrauss Zone. Fine-grained amphibolites in the Warzenrieth area and (gabbro-) amphibolites in the Blätterberg-Hoher Bogen area show normal MORB character. The metamorphosed gabbroic rocks in the southern part of the Neukirchen-Kdyne (meta-) igneous complex are subalkaline - tholeiitic and exhibit a magmatic differentiation trend. They differ from the neighbouring amphibolites by generally lower contents of incompatible elements.
Dans le Niger oriental, des phénomenes karstiques sont fréquents dans les roches siliceuses: gres, silcretes, croûtes ferrugineuses, roches cristallines. A partir des études géomorphologiques et micromorphologiques, on peut conclure a une kartsification, au sense de production de formes par dissolution. Les résultats permettent de dater du Tertiaire inférieur la principale période de karstification. La répartition régionale des formes induites par cette karstification indique une dépendance probable des conditions paléoclimatiques. Actuellement le karst influe encore sur le développement des autres formes de relief.
A 42 m drilling was pertormed in the depresalon of Bilma, Xawar, NE-Niger. The sediment and pollen records show that after an initial deposition of dune sands there were repeated lake phases which terminated by desiccation and consolidation of spring mounds. The pollen record indicates a continuous presence of savanna vegetation. The record probably covers the period between the Upper Pleistocene and the Late Holocene. The climate was characterised by a monssonal summer rain regime giving effective rain fall of about 450-500 mm per year. Groundwater recharge was possible but estimates of the amount of water resources are difficult because of the karstic system of the escarpment and the nearly unknown hydrogeological situation.
No abstract available
Bewertung und Auswirkungen der Simulationsgüte führender Klimamoden in einem Multi-Modell Ensemble
(2013)
Der rezente und zukünftige Anstieg der atmosphärischen Treibhausgaskonzentration bedeutet für das terrestrische Klimasystem einen grundlegenden Wandel, der für die globale Gesellschaft schwer zu bewältigende Aufgaben und Herausforderungen bereit hält. Eine effektive, rühzeitige Anpassung an diesen Klimawandel profitiert dabei enorm von möglichst genauen Abschätzungen künftiger Klimaänderungen.
Das geeignete Werkzeug hierfür sind Gekoppelte Atmosphäre Ozean Modelle (AOGCMs). Für solche Fragestellungen müssen allerdings weitreichende Annahmen über die zukünftigen klimarelevanten Randbedingungen getroffen werden. Individuelle Fehler dieser Klimamodelle, die aus der nicht perfekten Abbildung der realen Verhältnisse und Prozesse resultieren, erhöhen die Unsicherheit langfristiger Klimaprojektionen. So unterscheiden sich die Aussagen verschiedener AOGCMs im Hinblick auf den zukünftigen Klimawandel insbesondere bei regionaler Betrachtung, deutlich. Als Absicherung gegen Modellfehler werden üblicherweise die Ergebnisse mehrerer AOGCMs, eines Ensembles an Modellen, kombiniert. Um die Abschätzung des Klimawandels zu präzisieren, wird in der vorliegenden Arbeit der Versuch unternommen, eine Bewertung der Modellperformance der 24 AOGCMs, die an der dritten Phase des Vergleichsprojekts für gekoppelte Modelle (CMIP3) teilgenommen haben, zu erstellen. Auf dieser Basis wird dann eine nummerische Gewichtung für die Kombination des Ensembles erstellt. Zunächst werden die von den AOGCMs simulierten Klimatologien für einige
grundlegende Klimaelemente mit den betreffenden klimatologien verschiedener Beobachtungsdatensätze quantitativ abgeglichen. Ein wichtiger methodischer Aspekt
hierbei ist, dass auch die Unsicherheit der Beobachtungen, konkret Unterschiede zwischen verschiedenen Datensätzen, berücksichtigt werden. So zeigt sich, dass die Aussagen, die aus solchen Ansätzen resultieren, von zu vielen Unsicherheiten in den Referenzdaten beeinträchtigt werden, um generelle Aussagen zur Qualität von AOGCMs zu treffen. Die Nutzung der Köppen-Geiger Klassifikation offenbart jedoch, dass die prinzipielle Verteilung der bekannten Klimatypen im kompletten CMIP3 in vergleichbar guter Qualität reproduziert wird. Als Bewertungskriterium wird daher hier die Fähigkeit der AOGCMs die großskalige natürliche Klimavariabilität, konkret die hochkomplexe gekoppelte
El Niño-Southern Oscillation (ENSO), realistisch abzubilden herangezogen. Es kann anhand verschiedener Aspekte des ENSO-Phänomens gezeigt werden, dass nicht alle AOGCMs hierzu mit gleicher Realitätsnähe in der Lage sind. Dies steht im Gegensatz zu den dominierenden Klimamoden der Außertropen, die modellübergreifend überzeugend repräsentiert werden. Die wichtigsten Moden werden, in globaler Betrachtung, in verschiedenen Beobachtungsdaten über einen neuen Ansatz identifiziert. So können für einige bekannte Zirkulationsmuster neue Indexdefinitionen gewonnen werden, die sich sowohl als äquivalent zu den Standardverfahren erweisen und im Vergleich zu diesen zudem eine deutliche Reduzierung
des Rechenaufwandes bedeuten. Andere bekannte Moden werden dagegen als weniger bedeutsame, regionale Zirkulationsmuster eingestuft. Die hier vorgestellte
Methode zur Beurteilung der Simulation von ENSO ist in guter Übereinstimmung mit anderen Ansätzen, ebenso die daraus folgende Bewertung der gesamten Performance
der AOGCMs. Das Spektrum des Southern Oscillation-Index (SOI) stellt somit eine aussagekräftige Kenngröße der Modellqualität dar.
Die Unterschiede in der Fähigkeit, das ENSO-System abzubilden, erweisen sich als signifikante Unsicherheitsquelle im Hinblick auf die zukünftige Entwicklung einiger fundamentaler und bedeutsamer Klimagrößen, konkret der globalen Mitteltemperatur,
des SOIs selbst, sowie des indischen Monsuns. Ebenso zeigen sich signifikante Unterschiede für regionale Klimaänderungen zwischen zwei Teilensembles des CMIP3, die auf Grundlage der entwickelten Bewertungsfunktion eingeteilt werden. Jedoch sind diese Effekte im Allgemeinen nicht mit den Auswirkungen der
anthropogenen Klimaänderungssignale im Multi-Modell Ensemble vergleichbar, die für die meisten Klimagrößen in einem robusten multivariaten Ansatz detektiert und
quantifiziert werden können. Entsprechend sind die effektiven Klimaänderungen, die sich bei der Kombination aller Simulationen als grundlegende Aussage des
CMIP3 unter den speziellen Randbedingungen ergeben nahezu unabhängig davon, ob alle Läufe mit dem gleichen Einfluss berücksichtigt werden, oder ob die erstellte nummerische Gewichtung verwendet wird. Als eine wesentliche Begründung hierfür kann die Spannbreite der Entwicklung des ENSO-Systems identifiziert werden. Dies
bedeutet größere Schwankungen in den Ergebnissen der Modelle mit funktionierendem ENSO, was den Stellenwert der natürlichen Variabilität als Unsicherheitsquelle
in Fragen des Klimawandels unterstreicht. Sowohl bei Betrachtung der Teilensembles als auch der Gewichtung wirken sich dadurch gegenläufige Trends im SOI
ausgleichend auf die Entwicklung anderer Klimagrößen aus, was insbesondere bei letzterem Vorgehen signifikante mittlere Effekte des Ansatzes, verglichen mit der
Verwendung des üblichen arithmetischen Multi-Modell Mittelwert, verhindert.
Increasing urbanisation is one of the biggest pressures to vegetation in the City of Cape Town. The growth of the city dramatically reduced the area under indigenous Fynbos vegetation, which remains in isolated fragments. These are subject to a number of threats including atmospheric deposition, atypical fire cycles and invasion by exotic plant and animal species. Especially the Port Jackson willow (Acacia saligna) extensively suppresses the indigenous Fynbos vegetation with its rapid growth.
The main objective of this study was to investigate indicators for a quick and early prediction of the health of the remaining Fynbos fragments in the City of Cape Town with help of remote sensing.
First, the productivity of the vegetation in response to rainfall was determined. For this purpose, the Enhanced Vegetation Index (EVI), derived from Terra MODIS data with a spatial resolution of 250m, and precipitation data of 19 rainfall stations for the period from 2000 till 2008 were used. Within the scope of a flexible regression between the EVI data and the precipitation data, different lags of the vegetation response to rainfall were analysed. Furthermore, residual trends (RESTREND) were calculated, which result from the difference between observed EVI and the one predicted by precipitation. Negative trends may suggest a degradation of the habitats. In addition, the so-called Rain-use Efficiency (RUE) was tested in this context. It is defined as the ratio between net primary production (NPP) – represented by the annual sum of EVI – and the annual rainfall sum. These indicators were analysed for their suitability to determine the health of the indigenous Fynbos vegetation.
Furthermore, the degree of dispersal of invasive species especially the Acacia saligna was investigated. With the specific characteristics of the tested indicators and the spectral signature of Acacia saligna, i.e. its unique reflectance over the course of the year, the dispersal was estimated. Since the growth of invasive species dramatically reduces the biodiversity of the fragments, their presence is an important factor for the condition of ecosystem health.
This work focused on 11 test sites with an average size of 200ha, distributed over the whole area of the City of Cape Town. Five of these fragments are under conservation and the others shall be protected in the near future, too, which makes them of special interest. In January 2010, fieldwork was undertaken in order to investigate the state and composition of the local vegetation.
The results show promising indicators for the assessment of ecosystem health. The coefficients of determination of the EVI-rainfall regression for Fynbos are minor, because the reaction of this vegetation type to rainfall is considerably lower than the one of the invasive species. Thus, a good distinction between indigenous and alien vegetation is possible on the basis of this regression. On the other hand, the RESTREND method, for which the regression forms the basis, is only of limited use, since the significance of these trends is not given for Fynbos vegetation. Furthermore, the RUE has considerable potential for the assessment of ecosystem health in the study area. The Port Jackson willow has an explicitly higher EVI than the Fynbos vegetation and thus its RUE is more efficient for a similar amount of rainfall. However, it has to be used with caution, because local and temporal variability cannot be extinguished in the study area over the rather short MODIS time series.
These results display that the interpretation of the indicators has to be conducted differently from the literature, because the element of invasive species was not considered in most of the previous papers. An increase in productivity is not necessarily equivalent with an improvement in health of the fragment, but can indicate a dispersal of Acacia saligna. This shows the general problem of the term ‘degradation’ which in most publications so far is only measured by productivity and other factors like invasive species are disregarded.
On the basis of the EVI-rainfall regression and statistical measures of the EVI, the distribution of invasive species could be delineated. Generally, a strong invasion of the Port Jackson willow was discovered on the test sites. The results display that a reasoned and sustainable management of the fragments is essential in order to prevent the suppression of the indigenous Fynbos vegetation by Acacia saligna. For this purpose, remote sensing can give an indication which areas changed so that specific field surveys can be undertaken and subsequent management measures can be determined.
The discontinuous mountain permafrost zone is characterized by its heterogeneous distribution of frozen ground and a small-scale variability of the ground thermal regime. Large parts of these areas are covered by glacial till and sediments that were exposed after the recession of the glaciers since the 19th century. As response to changed climatic conditions permafrost-affected areas will lose their ability as sediment storage and on the contrary, they will act as source areas for unconsolidated debris. Along with modified precipitation patterns the degradation of the discontinuous mountain permafrost zone will (temporarily)
increase its predisposition for mass movement processes and thus has to be monitored in a differentiated way.
Therefore, the spatio-temporal dynamics of frozen ground are assessed in this study based on results obtained in three glacier forefields in the Engadin (Swiss Alps) and at the Zugspitze (German Alps). Sophisticated techniques are required to uncover structural differences in the subsurface. Thus, the applicability of advanced geophysical methods is tested for alpine environments and proved by the good 3D-delineation of a permafrost body and by the detection of detailed processes in the active layer during snow melt. Electrical resistivity tomography (ERT) approaches (quasi-3D, daily monitoring) reveal
their capabilities to detect subsurface resistivity changes both, in space and time. Processes and changes in regard to liquid water content and ice content are observed to exist at short distances even though the active layer is not subject to a considerable thickening
over the past 7 years. The stability of the active layer is verified by borehole temperature data. No synchronous
trend is recognized in permafrost temperatures and together with multi-annual electrical resistivity data they indicate degradation and aggradation processes to occur at the same time. Different heat transfer mechanisms, especially during winter, are recognized by means of temperature sensors above, at, and beneath the surface. Based on surface and borehole temperature data the snow cover is assessed as the major controlling factor for the thermal regime on a local scale. Beyond that, the debris size of the substrate, which modifies the snow cover and regulates air exchange processes above the ground, plays a crucial role as an additional buffer layer. A fundamental control over the stability of local permafrost patches is attributed to the ice-rich transient layer at the base of the active layer. The refreezing of melt water in spring is illustrated with diurnal ERT monitoring data from glacier forefield Murtèl.
Based on these ERT and borehole temperature data a conceptual model of active layer processes between autumn and spring is developed. The latent heat that is inherent in the transient layer protects the permafrost beneath from additional energy input from the surface as long as the refreezing of melt water in spring prevails and sufficient ice is build up each spring. Permafrost sites without a transient layer show considerably higher
temperatures at their table and are more prone to degradation in the years and decades ahead. As main investigation area a glacier forefield beneath the summits of Piz Murtèl and Piz Corvatsch in the Swiss Engadin was chosen. It is located west of the well-known
rock glacier Murtèl. Here, a permafrost body inside and adjacent to the lateral moraine was investigated and could be delineated very well. In the surrounding glacier forefield no further indications of permafrost occurrence could be made. Geophysical data and temperature values from the surface and from a permafrost borehole were compared with long-term data from proximate glacier forefield Muragl (Engadin). Results from both
sites show a considerable stability of the active layer depth in summer while at the same time geophysical data demonstrate annual changes in the amount of liquid water content and ice content in the course of years.
A third investigation area is located in the German Alps. The Zugspitzplatt is a high mountain valley with considerably more precipitation and thicker snow cover compared to both Swiss sites. In close proximity to the present glacier and at a large talus slope beneath the summit crest ground ice could be observed. The high subsurface resistivity values and comparable data from existing studies at the Zugspitze may indicate the presence of sedimentary ice in the subsurface of the karstified Zugspitzplatt. Based on these complementary data from geophysical and temperature measurements as
well as geomorphological field mapping the development of permafrost in glacier forefields under climate change conditions is analyzed with cooperation partners from the SPCC project. Ground temperature simulations forced with long-term climatological data are modeled to assess future permafrost development in glacier forefield Murtèl. Results suggest that permafrost is stable as long as the ice-rich layer between the active layer and
the permafrost table exists. After a tipping point is reached, the disintegration of frozen ground starts to proceed rapidly from the top.
In the central Alps permafrost can be expected above 2300 m a.s.l., at altitudes where mean annual air temperatures are below -1 °C. Isolated permafrost occurrences can be detected in north-exposed talus slopes, far below the timberline, where mean annual air temperatures are positive. Driving factors are assumed to be a low income of solar radiation, a thick organic layer with high insulation capacities as well as the thermally induced chimney effect.
Aim of this study is to achieve a deeper understanding of the factors determining the site-specific thermal regime, as well as the spatially limited and temporally highly variable permafrost occurrences in vegetated talus slopes.
Three supercooled talus slopes in the Swiss Alps were chosen for investigation. Substantially different characteristics were a central criterion in the selection of study sites. Located in the Upper Engadin, climatic conditions, altitude as well as dimensions of the talus slopes are comparable for the study sites Val Bever and Val Susauna; major differences are rooted in the nature of talus substrate and in humus- and vegetation distribution. Characteristics of the Brüeltobel site, located in the Appenzeller Alps, diverge with regard to climatic conditions, altitude and dimensions of the talus slope; humus- and vegetation compositions are comparable to the Val Susauna site.
Confirmation and characterisation of ground ice is accomplished by the application of electrical resistivity and seismic refraction tomography. The estimation of the spatial permafrost distribution is based on quasi-3D resistivity imaging. For the confirmation of permafrost and the analysis of its temporal variability electrical resistivity monitoring arrays were constructed and installed at all study sites, to allow year-round measurements. In addition to resistivity monitoring, the – up to now – first seismic refraction tomography winter monitoring was conducted at the Val Susauna to analyse the permafrost evolution during the winter half-year. Investigations of the ground thermal regime were based on the analysis of temperature logger data. Besides recording air- and ground surface temperatures, focus was set on the temperature evolution in vents and in the organic layer. To analyse the relationship between permafrost distribution on the one hand and humus- and vegetation distribution on the other hand, an extensive mapping of humus characteristics and vegetation composition was conducted at Val Susauna.
The existence of permafrost could be proven at all study sites. Spatially, permafrost bodies show a narrow transition to neighbouring, unfrozen areas. As observed at Val Susauna, the permafrost distribution strongly correlates with areas with exceptionally thick organic layer, high percentages of mosses and lichens in the undergrowth and dwarf grown trees. The temporal variability of permafrost has proven to be exceptionally high, with the magnitude of seasonal variations distinctly exceeding intra-annual changes. Thereby, the winter season is characterised by a significant supercooling. During snowmelt a growth in volumetric ice content is induced by refreezing of percolating meltwater on the supercooled talus.
The results confirmed the fundamental influence of the chimney effect on the existence and temporal variability of permafrost in talus slopes. Divergences in the effectiveness of the thermal regime were detected between the study sites. These are based on differences in the nature of talus material, humus characteristics and vegetation composition.
During summer, the organic material is usually dry at the daytime, inducing a high insulation capability and a protection of the subsurface against high atmospheric temperatures. Bouldery talus slopes typically show an organic layer that is fragmented by large boulders, which induces a strongly reduced insulation capability and allows an efficient heat exchange by convective airflow and percolating precipitation water. In the winter half-year, the thermal conductivity of the organic layer increases massively under moist or frozen conditions, allowing an efficient, conductive cooling of the talus material. The convective cooling in bouldery talus slopes affects an earlier onset and a higher magnitude of supercooling than under consistent humus conditions. Here, conductive heat flow is dominant and the cooling in autumn is buffered by a prolonged zero curtain. The snow cover has proven to be incapable of prohibiting an efficient supercooling of the talus slope in winter, almost independent from thickness.
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no abstract available
This thesis on the “Impacts of extreme hydro-meteorological events on electricity generation and possible adaptation measures – a GIS-based approach for corporate risk management and enhanced climate mitigation concepts in Germany” presents an identification of hydro-meteorological extreme events in Germany and their effects on electricity generating units, i.e. on conventional thermal and nuclear power plants as well as on installations of the renewable energies of hydropower, wind energy and photovoltaic installations. In addition, adaptation measures and strategies are named that help power plant operators to prepare for a changing climate. Due to the different requirements of large facility operators and local planners and owners of renewable energies, the work contains the two approaches of corporate risk management and climate mitigation concepts. A changing climate not only consists of a shift in mean values of weather parameters such as global and regional air temperature and precipitation, but may also result in more frequent and more severe single events such as extreme precipitation, tornadoes and thunderstorms. In two case studies, these findings are implemented into an adjusted general risk management structure. This is enhanced by the use of Geographical Information Systems (GIS) to accomplish a localisation of events and infrastructure. The first example gives insight into the consequences of ice throw from wind turbines and how climate mitigation concepts can act as a framework for an adapted, sustainable energy planning. The second example on the other hand highlights a GIS-based flood risk management for thermal power plants and the benefits of an adjusted corporate risk management cycle. The described approach leads to an integrated management of extreme hydro-meteorological events at power plant site respectively district level by combining two cycles of site-related and local planning in addition to GIS-based analyses. This is demonstrated as an example by the comparison of two districts in Germany. The practical outcome is a comprehensive support for decision-making processes.
Seit dem Jahr 2000 ist die Anzahl an installierten Photovoltaik-Anlagen in Deutschland – dank günstiger politischer Rahmenbedingungen – rasant von 76 MWp auf 24.820 MWp in 2011 gestiegen. Trotz bundesweit einheitlicher finanzieller Förderbedingungen durch das Erneuerbare-Energien-Gesetz existieren jedoch räumliche Unterschiede in der Anzahl an installierten Photovoltaik-Anlagen pro Einwohner, sowohl auf Ebene der Bundesländer, als auch zwischen einzelnen Gemeinden einer Region. In der vorliegenden Arbeit wird die räumliche Diffusion von Photovoltaik-Anlagen in Baden-Württemberg untersucht. Ziel ist zum einen die Ursachen für die räumlichen Unterschiede in der Photovoltaik-Diffusion aufzudecken. Zum anderen ist das Ziel zu überprüfen, ob ein Nachbarschaftseffekt der Photovoltaik-Diffusion existiert. Dies wird mit Hilfe quantitativer und qualitativer Methoden untersucht. Mit Hilfe der räumlichen Autokorrelationsanalyse wird gezeigt, dass sich die Anzahl an Photovoltaik-Anlagen pro Einwohner in den Gemeinden Baden-Württembergs signifikant unterscheidet. Es existieren Cluster von Gemeinden mit besonders hoher Photovoltaik-Nutzung (Hot Spots) und Cluster von Gemeinden mit besonders niedriger Photovoltaik-Nutzung (Cold Spots). Hot Spot-Gemeinden befinden sich zu 95% im ländlichen Raum und Cold Spot-Gemeinden zu 85% im Verdichtungsraum. Die Ergebnisse der räumlichen Regressionsanalyse und der Fallstudie in der Region Heilbronn-Franken zeigen, dass die Unterschiede in der Dichte der Photovoltaik-Anlagen pro Einwohner erstens auf Unterschiede in der Siedlungsstruktur zurückzuführen sind (Anteil an Ein- und Zweifamilienhäusern, Anteil an Neubauten, Anzahl an Viehbetrieben pro Einwohner), zweitens auf Unterschiede im Sozialgefüge (Anteil an Familien) sowie drittens auf den Nachbarschaftseffekt der Diffusion. Aus den Experteninterviews geht hervor, dass zudem weitere lokale Voraussetzungen gegeben sein müssen, damit es zu einer schnellen Photovoltaik-Diffusion kommt. Eine wichtige Rolle spielen die Landwirte, die häufig als Innovatoren auftraten, sowie sog. Change Agents, die den Diffusionsprozess anstoßen und bewusst fördern. Zu letzteren zählen auf lokaler Ebene aktive Bürgermeister, Solarvereine, Photovoltaik-Unternehmer oder Elektroinstallateure, auf regionaler Ebene Maschinenringe und Energieagenturen. Die Modellierung und Analyse der Photovoltaik-Diffusion in den einzelnen Gemeinden von 2000 bis 2030 zeigt für das Jahr 2009, dass die Gemeinden einer Raumkategorie unterschiedliche Diffusionsprofile aufweisen. Je ländlicher eine Gemeinde ist, desto weiter ist tendenziell der Diffusionsprozess fortgeschritten: In Gemeinden des ländlichen Raums befindet sich die Photovoltaik-Diffusion meist bereits im Early Majority-Stadium, in Gemeinden des Verdichtungsraums ist die Photovoltaik-Diffusion dagegen überwiegend erst am Ende des Early Adopter-Stadiums angelangt. Der Innovationseffekt, der angibt, wie stark die Anzahl an Photovoltaik-Anlagen unabhängig von den bereits installierten Anlagen zunimmt, ist im suburbanen Raum und im ländlichen Raum am höchsten. Der Imitationseffekt, der angibt, wie stark die Zunahme neu installierter Photovoltaik-Anlagen von bestehenden Anlagen in einer Gemeinde abhängt, steigt dagegen von der Stadt zum Land an. Durch den Vergleich der Hot Spot-Gemeinden mit den übrigen Gemeinden des ländlichen Raums wird deutlich, dass die Imitation in den Hot Spot-Gemeinden höher liegt. Dies lässt darauf schließen, dass ein Nachbarschaftseffekt der Photovoltaik-Diffusion zwischen den Gemeinden existiert, da die Lage innerhalb eines Hot Spots zu einer erhöhten Wahrnehmung von Photovoltaik-Anlagen und einem häufigeren Austausch mit Photovoltaik-Besitzern führt und damit die Photovoltaik-Diffusion fördert. Vor dem Hintergrund des Klimawandels und der knapper werdenden fossilen Ressourcen gilt in Deutschland das Ziel, die Nutzung erneuerbarer Energien und damit auch der Photovoltaik weiter voranzutreiben. Diese Arbeit zeigt, dass lokale Einflussfaktoren entscheidend für das Entstehen räumlicher Unterschiede in der Photovoltaik-Nutzung sind. Die Kenntnisse dieser Unterschiede, deren Ursachen sowie die Bedeutung des Nachbarschaftseffekts können eine Grundlage für gezielte Förderung oder Marketingmaßnahmen zur weiteren Diffusion von Photovoltaik-Anlagen bieten.
A completely revised and enhanced version of the water balance model MODBIL of the regional water balance dynamics of Cyprus was developed for this study. The model is based on a physical, process-oriented, spatially distributed concept and is applied for the calculation of all important water balance components of the island for the time period of 1961-2004. The calibrated results are statistically analysed and visualised for the whole island area, and evaluated with respect to the renewability of natural water resources. Climate variability and changes of the past decades are analysed with regard to their influence on water balances. A further part of the study focusses on the simulation of impacts of potential climate change. The water balances are simulated under changing climatic conditions on the base of theoretical precipitation, temperature and relative humidity changes and the revealed impacts on the water balances and renewable resources are discussed. Furthermore, a first principal water balance scenario is developed for the assessment of the regional hydrological changes expected for Cyprus by the end of the 21st century. The scenarios are based on recently calculated climate change assessments for this part of the Mediterranean, under an assumed further increase of greenhouse gasses in the atmosphere.
Aufgrund der weltweit steigenden Energienachfrage und den gleichzeitig knapper werdenden natürlichen Ressourcen, muss Energie in Zukunft effizienter genutzt werden. Auch im Sektor der privaten Haushalte stellt sich deshalb die Frage, von welchen Faktoren der Energieverbrauch abhängt. Der Einfluss von technischen Faktoren wie Wärmedämmung von Gebäuden oder der Effizienzklasse von elektrischen Geräten auf den Heizenergie- bzw. Stromverbrauch in privaten Haushalten ist bereits bekannt. Interessant zu wissen ist jedoch auch, welchen Einfluss unterschiedliche Eigenschaften und Verhaltensweisen der Bewohner und damit welchen Einfluss der Lebensstil auf den Energieverbrauch hat. Um den Einfluss des Lebensstils auf den Energieverbrauch in privaten Haushalten im Bereich Wohnen zu untersuchen, wurden Daten anhand einer schriftlichen Haushaltsbefragung in ausgewählten Stadtvierteln in Stuttgart erhoben. Bei der Befragung kam ein bereichsspezifischer Lebensstilansatz zur Anwendung d.h. es wurden Fragen zu den einzelnen Lebensstilbereichen „Lebensform“, „Sozialstruktur“, „Energiesparverhalten“ und „Umwelt- und Energiebewusstsein“ gestellt. Anhand ausgewählter Variablen dieser Lebensstilbereiche wurden die Haushalte mit Hilfe der Clusteranalyse in Lebensstilgruppen des Strom- und Heizenergieverbrauchs eingeteilt. Ein Vergleich der Lebensstilgruppen des Stromverbrauchs zeigte, dass der Unterschied im Stromverbrauch v.a. durch die Anzahl der Personen im Haushalt bedingt ist. Die anderen Lebensstilbereiche wirken sich zwar auch auf den Stromverbrauch aus, sie rufen jedoch nur zwischen wenigen Gruppen signifikante Unterschiede im Stromverbrauch hervor. Bei den Lebensstilgruppen des Heizenergieverbrauchs zeichnet sich ein Einfluss des Lebensstilbereichs des „Energiesparverhaltens“ auf den Heizenergieverbrauch ab. Aufgrund der geringen Fallzahlen konnten die Unterschiede im Heizenergieverbrauch zwischen den Gruppen jedoch nicht auf Signifikanz getestet werden. Aus den Ergebnissen der Untersuchung wird deutlich, dass der Lebensstil einen Einfluss auf den Energieverbrauch in privaten Haushalten im Bereich Wohnen hat. Eine Einteilung der Haushalte in Lebensstilgruppen könnte somit Ansatzpunkte für ein Lebensstil-spezifisches Energiesparmarketing bieten. Um den Einfluss des Lebensstils auf den Energieverbrauch tiefergehend zu untersuchen, sollte der Einfluss von technischen Faktoren ganz ausgeschlossen und die einzelnen Lebensstilbereiche (v.a. das Energiesparverhalten) in den Analysen mit mehr Variablen berücksichtigt werden.
The overarching goal of this research was to explore accurate methods of mapping irrigated crops, where digital cadastre information is unavailable: (a) Boundary separation by object-oriented image segmentation using very high spatial resolution (2.5–5 m) data was followed by (b) identification of crops and crop rotations by means of phenology, tasselled cap, and rule-based classification using high resolution (15–30 m) bi-temporal data. The extensive irrigated cotton production system of the Khorezm province in Uzbekistan, Central Asia, was selected as a study region. Image segmentation was carried out on pan-sharpened SPOT data. Varying combinations of segmentation parameters (shape, compactness, and color) were tested for optimized boundary separation. The resulting geometry was validated against polygons digitized from the data and cadastre maps, analysing similarity (size, shape) and congruence. The parameters shape and compactness were decisive for segmentation accuracy. Differences between crop phenologies were analyzed at field level using bi-temporal ASTER data. A rule set based on the tasselled cap indices greenness and brightness allowed for classifying crop rotations of cotton, winter-wheat and rice, resulting in an overall accuracy of 80 %. The proposed field-based crop classification method can be an important tool for use in water demand estimations, crop yield simulations, or economic models in agricultural systems similar to Khorezm.
Wetlands in West Africa are among the most vulnerable ecosystems to climate change. West African wetlands are often freshwater transfer mechanisms from wetter climate regions to dryer areas, providing an array of ecosystem services and functions. Often wetland-specific data in Africa is only available on a per country basis or as point data. Since wetlands are challenging to map, their accuracies are not well considered in global land cover products. In this paper we describe a methodology to map wetlands using well-corrected 250-meter MODIS time-series data for the year 2002 and over a 360,000 km2 large study area in western Burkina Faso and southern Mali (West Africa). A MODIS-based spectral index table is used to map basic wetland morphology classes. The index uses the wet season near infrared (NIR) metrics as a surrogate for flooding, as a function of the dry season chlorophyll activity metrics (as NDVI). Topographic features such as sinks and streamline areas were used to mask areas where wetlands can potentially occur, and minimize spectral confusion. 30-m Landsat trajectories from the same year, over two reference sites, were used for accuracy assessment, which considered the area-proportion of each class mapped in Landsat for every MODIS cell. We were able to map a total of five wetland categories. Aerial extend of all mapped wetlands (class “Wetland”) is 9,350 km2, corresponding to 4.3% of the total study area size. The classes “No wetland”/“Wetland” could be separated with very high certainty; the overall agreement (KHAT) was 84.2% (0.67) and 97.9% (0.59) for the two reference sites, respectively. The methodology described herein can be employed to render wide area base line information on wetland distributions in semi-arid West Africa, as a data-scarce region. The results can provide (spatially) interoperable information feeds for inter-zonal as well as local scale water assessments.
Current changes of biodiversity result almost exclusively from human activities. This anthropogenic conversion of natural ecosystems during the last decades has led to the so-called ‘biodiversity crisis’, which comprises the loss of species as well as changes in the global distribution patterns of organisms. Species richness is unevenly distributed worldwide. Altogether, 17 so-called ‘megadiverse’ nations cover less than 10% of the earth’s land surface but support nearly 70% of global species richness. Mexico, the study area of this thesis, is one of those countries. However, due to Mexico’s large extent and geographical complexity, it is impossible to conduct reliable and spatially explicit assessments of species distribution ranges based on these collection data and field work alone. In the last two decades, Species distribution models (SDMs) have been established as important tools for extrapolating such in situ observations. SDMs analyze empirical correlations between geo-referenced species occurrence data and environmental variables to obtain spatially explicit surfaces indicating the probability of species occurrence. Remote sensing can provide such variables which describe biophysical land surface characteristics with high effective spatial resolutions. Especially during the last three to five years, the number of studies making use of remote sensing data for modeling species distributions has therefore multiplied. Due to the novelty of this field of research, the published literature consists mostly of selective case studies. A systematic framework for modeling species distributions by means of remote sensing is still missing. This research gap was taken up by this thesis and specific studies were designed which addressed the combination of climate and remote sensing data in SDMs, the suitability of continuous remote sensing variables in comparison with categorical land cover classification data, the criteria for selecting appropriate remote sensing data depending on species characteristics, and the effects of inter-annual variability in remotely sensed time series on the performance of species distribution models. The corresponding novel analyses were conducted with the Maximum Entropy algorithm developed by Phillips et al. (2004). In this thesis, a more comprehensive set of remote sensing predictors than in the existing literature was utilized for species distribution modeling. The products were selected based on their ecological relevance for characterizing species distributions. Two 1 km Terra-MODIS Land 16-day composite standard products including the Enhanced Vegetation Index (EVI), Reflectance Data, and Land Surface Temperature (LST) were assembled into enhanced time series for the time period of 2001 to 2009. These high-dimensional time series data were then transformed into 18 phenological and 35 statistical metrics that were selected based on an extensive literature review. Spatial distributions of twelve tree species were modeled in a hierarchical framework which integrated climate (WorldClim) and MODIS remote sensing data. The species are representative of the major Mexican forest types and cover a variety of ecological traits, such as range size and biotope specificity. Trees were selected because they have a high probability of detection in the field and since mapping vegetation has a long tradition in remote sensing. The result of this thesis showed that the integration of remote sensing data into species distribution models has a significant potential for improving and both spatial detail and accuracy of the model predictions.
U.S. and German Approaches to Regulating Retail Development: Urban Planning Tools and Local Policies
(2012)
This dissertation examines retail development regulation in the U.S. and in Germany, comparing the various urban planning tools and policies in use by municipal governments. These similarities and differences are explored through research into three case study cities in each country, with special attention paid to how these governments regulate large-scale or "big box" retail.
Bildung für nachhaltige Entwicklung setzt einen systematischen Ansatz voraus, der sozioökonomische Umweltaspekte in enge Beziehung zueinander setzt. Bildung für nachhaltige Entwicklung bedeutet also, die Komplexität von Phänomenen und deren Beziehung zueinander zu begreifen lernen und Schlüsselkompetenzen zu entwickeln, um aktiv, bewusst, verantwortungsvoll und kritisch an der Gestaltung der Gegenwart und der Zukunft teilzuhaben. Gegenstand vorliegender Forschungsarbeit ist die Bildung für nachhaltige Entwicklung (BNE) aus Sicht der Geographie und im internationalen Vergleich zwischen der italienischen Stadt Padua in der Region Venetien und Würzburg in Bayern. Im Mittelpunkt stehen Aktivitäten und Projekte, die im formalen Bereich, d.h. in Kindergärten und Grundschulen, und im non-formalen Bereich, wie in Vereinen, Einrichtungen, lokale Körperschaften, durchgeführt wurden. Damit war die Voraussetzung geschaffen, das gesamte Spektrum an Angeboten und Möglichkeiten der Zusammenarbeit im Bereich BNE in den für die Fallstudie gewählten Städten zu erfassen, also einschließlich der Angebote von und der Angebote an die Schulen. Dem Forschungsverfahren liegt ein Fragebogen über die Wertesysteme und Wertvorstellungen von Erziehern und Lehrern in Bezug auf geographische Bildung zugrunde. Dabei stellt sich unter anderem heraus, dass der Zusammenhang zwischen BNE und geographischer Bildung kaum wahrgenommen wird. Diese Feststellung bestätigt sich im weiteren Verlauf des Untersuchungsverfahrens, das sich auf die Auswertung von dreizehn, aus der Fachliteratur und aus internationalen Dokumenten ausgewählten und behandelten BNE-Themen konzentriert. Die Ergebnisse zeigen, dass es in beiden Städten und in beiden Bereichen, im formalen wie im non-formalen, “ BNE-Best Practice” gibt und dass Themen mit Bezug zu Bildung zu Nachhaltigkeit gegenüber Themen mit Bezug zu entwicklungsbezogener Bildung der Vorzug gegeben wird. Weiter geht daraus hervor, dass in erster Linie Umweltaspekte behandelt werden, gefolgt von sozialen, während ökonomische Aspekte das Schlusslicht bilden. In Bezug auf das, was nachhaltige Entwicklung und BNE bedeuten, herrscht bei den Interviewpartnern ziemliche Unklarheit und ein geringes Bewusstsein. Im non-formalen Bereich Tätige wissen über die Grundlagen nachhaltiger Entwicklung Bescheid, bevorzugen jedoch die Bezeichnung “Umwelterziehung”, weil dieser Begriff für die Allgemeinheit angeblich besser verständlich ist. Die Mehrheit der Erzieher und Lehrer hingegen erkennt keinen Unterschied zwischen BNE und Umwelterziehung. Auch die staatlichen Lehrpläne und Richtlinien geben kaum Aufschluss darüber, was BNE ist. Manchmal wird BNE mit Umwelterziehung gleichgesetzt, dann ist sie wieder Teil davon, andere Male wird sie als Orientierungshilfe für Umwelterziehung empfohlen. Jedenfalls wird darin nichts anderes als Umwelterziehung damit in Verbindung gebracht. Die befragten Personen sind wesentlich mehr auf die “ Praxis” als auf die “ Theorie” bedacht. Sie führen interessante Projekte und Aktivitäten durch, sind sich aber des theoretischen Ansatzes, der BNE zugrunde liegt und der mit dem der Geographie in gar einigen Punkten konvergent ist, nicht wirklich bewusst. In diesem Sinne erschließt vorliegende Forschungsarbeit das Potential an Synergien von BNE und geographischer Bildung. Denn einerseits könnte die Geographie aufschlussreiche theoretische Überlegungen und Impulse liefern, andererseits könnte BNE den Anstoß zur Erneuerung geographischer Bildung geben und sie damit aus der gesellschaftlichen Isolation führen. Solche Grundüberlegungen sollten selbstverständlich auch in den Curricula – in Form der zur Verfügung stehenden Stundenzahl – ihren Niederschlag finden.
Diese Dissertationsarbeit liefert einen Beitrag zur Erfassung und Bewertung von Degradationsprozessen im semi-humiden Süden Spaniens. Der erste Teil der Arbeit widmet sich der detaillierten physisch-geographischen Charakterisierung des Großraumes, um danach in dem kleinräumigen Einzugsgebiet des Arroyo del Alforzo, einem Tributär des Río Turón, zwei unterschiedliche Ansätze zur Erfassung von die degradationsbeeinflussenden Fatoren wie Landnutzungswechsel und Starkniederschlagsereignissen in diesem Raum zu untersuchen. Anhand von drei Satellitenbildern wurde der Landnutzungswechsel ermittelt und im Untersuchungsgebiet die Abhängigkeit zu den Hangneigungen untersucht. Vor dem Hintergrund, daß unterschiedlich starke Hangneigungen einen unterschiedlich starken Einfluss auf die Abtragsdynamik bei Niederschlägen hat, wurden anhand der Landnutzungsklassifizierungen in Kombination mit den Hangneigungnen sensible Räume ermittelt. Ein weiterer Ansatz ist die Untersuchung von Tagesniederschlagsdaten auf Starkniederschlagsereignisse, mit dem Ziel, diese zu separieren. Es galt die Annahme, daß diese Starkniederschlagsereignisse im Einzugsgebiet des Arroyo del Alforzo oberflächlichen Abfluss generieren und somit ein bedeutender Sedimenteintrag aus den sensiblen Bereichen des Untersuchungsgebiet in den Stausee Conde de Guadalhorce stattfindet. Mittels sedimentstratigraphischer Untersuchungen an den Sedimenten des 2006 gewonnenen Bohrkerns aus dem Mündungsbereich des Arroyo del Alforzo in den Stausee Conde de Guadalhorce sollte dieser Sedimenteintrag identifierziert werden und somit ein zeitlicher und räumlicher Rückschluss auf die die Abtragung beeinflussenden faktoren Landnutzungswechsel, Hangneigung und Niederschlag efolgen. Die Annahme, dass sich diese Rückschlüsse ziehen lassen können auf der Grundlage des Bindeglieds „Sedimentbohrung“ erwies sich jedoch als zu eng. In einer abschliessenden Bewertung wurde erläutert, daß durch eine gezielte methodische Ergänzung jedoch die Möglichkeit besteht, die Unsicherheiten, die durch eine räumlich wie zeitlich inkonsistente Datenlage der Niederschlagsdaten und die in einem Stausee herrschende spezielle Akkumulationsdynamik hervorgerufen wurde, beseitigt werden kann.
The mineralogical and chemical characteristics of fulgurites ( = natural glasses forrned by lightning strikes to the ground) from the southern Centrat Sahara (Niger) are presented. The fulgurites are indicators of thunderstorms. The northernmost important fulgurite formation in the study area reached up to about l8°N, with decreasing fulgurite concentration from south to north. Their distribution pattern and the relative dating of their formation in relation to Iandscape history from the Late Pleistocene onwards (e.g., palaeolakes, palaeosols), and to Neolithic settlement reveals their value as palaeoenvironmental indicators. They indicate: (1) local palaeoenvironmental conditions depending on the topographical situation in a complex dune relief; (2) climatic change during the mid-Holocene from northerly rains to southerly rains; and (3) the northernmost Iimit of important thunderstorrns and rainfall activity since this time in the southern Centrat Sahara.
Es existieren regionale Unterschiede in der Nutzung von Photovoltaik-Anlagen (PV) in Baden-Württemberg. Die Bedeutung von Raumstruktur und Globalstrahlung für diese Unterschiede wurde großräumig untersucht. Es zeigte sich, dass die PV-Nutzung im ländlichen Raum Baden-Württembergs höher ist als im urbanen Raum. Dieser Zusammenhang gewann in den letzten Jahren an Bedeutung. Die Bedeutung der Globalstrahlung für die PV-Nutzung sank auf ein sehr niedriges Niveau. Weitere Untersuchungen wurden im Nordosten Baden-Württembergs durchgeführt, wo die Raumstruktur ländlich und die PV-Nutzung überdurchschnittlich hoch ist. Um die Ursachen der regionalen Unterschiede in der PV-Nutzung näher zu untersuchen, wurden qualitative Experteninterviews, Korrelationsanalysen und schriftliche Haushaltsbefragungen durchgeführt. Durch Experteninterviews wurden die Hauptakteure für die Diffusion von PV in der Untersuchungsregion identifiziert. Neben PV-Unternehmen sind dies Landwirte, Gemeinderäte und Bürgermeister sowie Energieagenturen. Landwirte nehmen eine Schlüsselrolle ein, da es für sie relativ leicht ist PV-Anlagen zu realisieren. Gemeinderäte und ihre Bürgermeister können PV-Anlagen auf öffentlichen Gebäuden realisieren. Energieagenturen bilden Diffusionsnetzwerke zwischen verschiedenen Akteuren. Eine Korrelationsanalyse deckte einige Faktoren auf, die mit den PV-Anlagen je Einwohner und Kommune in Heilbronn-Franken korrelieren. Diese Faktoren sind (i) Anteil der unter 18 Jährigen, (ii) Anteil der Einfamilienhäuser an den Wohngebäuden, (iii) Anteil der sozialversicherungspflichtigen Beschäftigten mit abgeschlossener Ausbildung, (iv) landwirtschaftliche Betriebe mit Viehhaltung je Einwohner, (v) Anteil der Mehrfamilien-häuser an den Wohngebäuden und (vi) Anteil der sozialversicherungspflichtig Beschäftigten mit Hochschulabschluss. Durch eine Haushaltsbefragung wurden signifikante Unterschiede zwischen PV-Eigentümern und Nicht-Eigentümern aufgedeckt (Alter, Familienverhältnisse, Energieverhalten, PV-Informationskanäle, Einstellung zu PV). Bei formaler Bildung und Einkommen gab es keine signifikanten Unterschiede. Außerdem wurden signifikante Unterschiede zwischen einer Gemeinde mit hoher und einer mit niedriger PV-Nutzung erkannt (Energieverhalten, Notwendigkeit ökologischen Handels, Einstellung zu PV, lokale PV-Akteure). Andere Aspekte wiesen keine signifikanten Unterschiede auf (PV-Informationskanäle, Hinderungsgründe für den Kauf). Außerdem zeigte sich, dass die Diffusion von PV einen wichtigen lokalen Charakter hat (PV-Informationskanäle, lokale Märkte).