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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.