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Growing populations, continued economic development, and limited natural resources are critical factors affecting sustainable development. These factors are particularly pertinent in developing countries in which large parts of the population live at a subsistence level and options for sustainable development are limited. Therefore, addressing sustainable land use strategies in such contexts requires that decision makers have access to evidence-based impact assessment tools that can help in policy design and implementation. Ex-ante impact assessment is an emerging field poised at the science-policy interface and is used to assess the potential impacts of policy while also exploring trade-offs between economic, social and environmental sustainability targets. The objective of this study was to operationalise the impact assessment of land use scenarios in the context of developing countries that are characterised by limited data availability and quality. The Framework for Participatory Impact Assessment (FoPIA) was selected for this study because it allows for the integration of various sustainability dimensions, the handling of complexity, and the incorporation of local stakeholder perceptions. FoPIA, which was originally developed for the European context, was adapted to the conditions of developing countries, and its implementation was demonstrated in five selected case studies. In each case study, different land use options were assessed, including (i) alternative spatial planning policies aimed at the controlled expansion of rural-urban development in the Yogyakarta region (Indonesia), (ii) the expansion of soil and water conservation measures in the Oum Zessar watershed (Tunisia), (iii) the use of land conversion and the afforestation of agricultural areas to reduce soil erosion in Guyuan district (China), (iv) agricultural intensification and the potential for organic agriculture in Bijapur district (India), and (v) land division and privatisation in Narok district (Kenya). The FoPIA method was effectively adapted by dividing the assessment into three conceptual steps: (i) scenario development; (ii) specification of the sustainability context; and (iii) scenario impact assessment. A new methodological approach was developed for communicating alternative land use scenarios to local stakeholders and experts and for identifying recommendations for future land use strategies. Stakeholder and expert knowledge was used as the main sources of information for the impact assessment and was complemented by available quantitative data. Based on the findings from the five case studies, FoPIA was found to be suitable for implementing the impact assessment at case study level while ensuring a high level of transparency. FoPIA supports the identification of causal relationships underlying regional land use problems, facilitates communication among stakeholders and illustrates the effects of alternative decision options with respect to all three dimensions of sustainable development. Overall, FoPIA is an appropriate tool for performing preliminary assessments but cannot replace a comprehensive quantitative impact assessment, and FoPIA should, whenever possible, be accompanied by evidence from monitoring data or analytical tools. When using FoPIA for a policy oriented impact assessment, it is recommended that the process should follow an integrated, complementary approach that combines quantitative models, scenario techniques, and participatory methods.
The past climate in central Asia, and especially on the Tibetan Plateau (TP), is of great importance for an understanding of global climate processes and for predicting the future climate. As a major influence on the climate in this region, the Asian Summer Monsoon (ASM) and its evolutionary history are of vital importance for accurate predictions. However, neither the evolutionary pattern of the summer monsoon nor the driving mechanisms behind it are yet clearly understood. For this research, I first synthesized previously published Late Glacial to Holocene climatic records from monsoonal central Asia in order to extract the general climate signals and the associated summer monsoon intensities. New climate and vegetation sequences were then established using improved quantitative methods, focusing on fossil pollen records recovered from Tibetan lakes and also incorporating new modern datasets. The pollen-vegetation and vegetation-climate relationships on the TP were also evaluated in order to achieve a better understanding of fossil pollen records. The synthesis of previously published moisture-related palaeoclimate records in monsoonal central Asia revealed generally different temporal patterns for the two monsoonal subsystems, i.e. the Indian Summer Monsoon (ISM) and East Asian Summer Monsoon (EASM). The ISM appears to have experienced maximum wet conditions during the early Holocene, while many records from the area affected by the EASM indicate relatively dry conditions at that time, particularly in north-central China where the maximum moisture levels occurred during the middle Holocene. A detailed consideration of possible driving factors affecting the summer monsoon, including summer solar insolation and sea surface temperatures, revealed that the ISM was primarily driven by variations in northern hemisphere solar insolation, and that the EASM may have been constrained by the ISM resulting in asynchronous patterns of evolution for these two subsystems. This hypothesis is further supported by modern monsoon indices estimated using the NCEP/NCAR Reanalysis data from the last 50 years, which indicate a significant negative correlation between the two summer monsoon subsystems. By analogy with the early Holocene, intensification of the ISM during coming decades could lead to increased aridification elsewhere as a result of the asynchronous nature of the monsoon subsystems, as can already be observed in the meteorological data from the last 15 years. A quantitative climate reconstruction using fossil pollen records was achieved through analysis of sediment core recovered from Lake Donggi Cona (in the north-eastern part of the TP) which has been dated back to the Last Glacial Maximum (LGM). A new data-set of modern pollen collected from large lakes in arid to semi-arid regions of central Asia is also presented herein. The concept of "pollen source area" was introduced to modern climate calibration based on pollen from large lakes, and was applied to the fossil pollen sequence from Lake Donggi Cona. Extremely dry conditions were found to have dominated the LGM, and a subsequent gradually increasing trend in moisture during the Late Glacial period was terminated by an abrupt reversion to a dry phase that lasted for about 1000 years and coincided with the first Heinrich Event of the northern Atlantic region. Subsequent periods corresponding to the warm Bølling-Allerød period and the Younger Dryas cold event were followed by moist conditions during the early Holocene, with annual precipitation of up to about 400 mm. A slightly drier trend after 9 cal ka BP was then followed by a second wet phase during the middle Holocene that lasted until 4.5 cal ka BP. Relatively steady conditions with only slight fluctuations then dominated the late Holocene, resulting in the present climatic conditions. In order to investigate the relationship between vegetation and climate, temporal variations in the possible driving factors for vegetation change on the northern TP were examined using a high resolution late Holocene pollen record from Lake Kusai. Moving-window Redundancy Analyses (RDAs) were used to evaluate the correlations between pollen assemblages and individual sedimentary proxies. These analyses have revealed frequent fluctuations in the relative abundances of alpine steppe and alpine desert components, and in particular a decrease in the total vegetation cover at around 1500 cal a BP. The climate was found to have had an important influence on vegetation changes when conditions were relatively wet and stable. However, after the 1500 cal a BP threshold in vegetation cover was crossed the vegetation appears to have been affected more by extreme events such as dust storms or fluvial erosion than by the general climatic trends. In addition, pollen spectra over the last 600 years have been revealed by Procrustes analysis to be significantly different from those recovered from older samples, which is attributed to an increased human impact that resulted in unprecedented changes to the composition of the vegetation. Theoretical models that have been developed and widely applied to the European area (i.e. the Extended R-Value (ERV) model and the Regional Estimates of Vegetation Abundance from Large Sites (REVEALS) model) have been applied to the high alpine TP ecosystems in order to investigate the pollen-vegetation relationships, as well as for quantitative reconstructions of vegetation abundance. The modern pollen–vegetation relationships for four common pollen species on the TP have been investigated using Poaceae as the reference taxa. The ERV Submodel 2 yielded relatively high PPEs for the steppe and desert taxa (Artemisia Chenopodiaceae), and low PPEs for the Cyperaceae that are characteristic of the alpine Kobresia meadows. The plant abundances on the central and north-eastern TP were quantified by applying these PPEs to four post-Late Glacial fossil pollen sequences. The reconstructed vegetation assemblages for the four pollen sequences always yielded smaller compositional species turnovers than suggested by the pollen spectra, indicating that the strength of the previously-reported vegetation changes may therefore have been overestimated. In summary, the key findings of this thesis are that (a) the two ASM subsystems show asynchronous patterns during both the Holocene and modern time periods, (b) fossil pollen records from large lakes reflect regional signals for which the pollen source areas need to be taken into account, (c) climate is not always the main driver for vegetation change, and (d) previously reported vegetation changes on the TP may have been overestimated because they ignored inter-species variations in pollen productivity.
Tectonic and geological processes on Earth often result in structural anisotropy of the subsurface, which can be imaged by various geophysical methods. In order to achieve appropriate and realistic Earth models for interpretation, inversion algorithms have to allow for an anisotropic subsurface. Within the framework of this thesis, I analyzed a magnetotelluric (MT) data set taken from the Cape Fold Belt in South Africa. This data set exhibited strong indications for crustal anisotropy, e.g. MT phases out of the expected quadrant, which are beyond of fitting and interpreting with standard isotropic inversion algorithms. To overcome this obstacle, I have developed a two-dimensional inversion method for reconstructing anisotropic electrical conductivity distributions. The MT inverse problem represents in general a non-linear and ill-posed minimization problem with many degrees of freedom: In isotropic case, we have to assign an electrical conductivity value to each cell of a large grid to assimilate the Earth's subsurface, e.g. a grid with 100 x 50 cells results in 5000 unknown model parameters in an isotropic case; in contrast, we have the sixfold in an anisotropic scenario where the single value of electrical conductivity becomes a symmetric, real-valued tensor while the number of the data remains unchanged. In order to successfully invert for anisotropic conductivities and to overcome the non-uniqueness of the solution of the inverse problem it is necessary to use appropriate constraints on the class of allowed models. This becomes even more important as MT data is not equally sensitive to all anisotropic parameters. In this thesis, I have developed an algorithm through which the solution of the anisotropic inversion problem is calculated by minimization of a global penalty functional consisting of three entries: the data misfit, the model roughness constraint and the anisotropy constraint. For comparison, in an isotropic approach only the first two entries are minimized. The newly defined anisotropy term is measured by the sum of the square difference of the principal conductivity values of the model. The basic idea of this constraint is straightforward. If an isotropic model is already adequate to explain the data, there is no need to introduce electrical anisotropy at all. In order to ensure successful inversion, appropriate trade-off parameters, also known as regularization parameters, have to be chosen for the different model constraints. Synthetic tests show that using fixed trade-off parameters usually causes the inversion to end up by either a smooth model with large RMS error or a rough model with small RMS error. Using of a relaxation approach on the regularization parameters after each successful inversion iteration will result in smoother inversion model and a better convergence. This approach seems to be a sophisticated way for the selection of trade-off parameters. In general, the proposed inversion method is adequate for resolving the principal conductivities defined in horizontal plane. Once none of the principal directions of the anisotropic structure is coincided with the predefined strike direction, only the corresponding effective conductivities, which is the projection of the principal conductivities onto the model coordinate axes direction, can be resolved and the information about the rotation angles is lost. In the end the MT data from the Cape Fold Belt in South Africa has been analyzed. The MT data exhibits an area (> 10 km) where MT phases over 90 degrees occur. This part of data cannot be modeled by standard isotropic modeling procedures and hence can not be properly interpreted. The proposed inversion method, however, could not reproduce the anomalous large phases as desired because of losing the information about rotation angles. MT phases outside the first quadrant are usually obtained by different anisotropic anomalies with oblique anisotropy strike. In order to achieve this challenge, the algorithm needs further developments. However, forward modeling studies with the MT data have shown that surface highly conductive heterogeneity in combination with a mid-crustal electrically anisotropic zone are required to fit the data. According to known geological and tectonic information the mid-crustal zone is interpreted as a deep aquifer related to the fractured Table Mountain Group rocks in the Cape Fold Belt.
Current climate warming is affecting arctic regions at a faster rate than the rest of the world. This has profound effects on permafrost that underlies most of the arctic land area. Permafrost thawing can lead to the liberation of considerable amounts of greenhouse gases as well as to significant changes in the geomorphology, hydrology, and ecology of the corresponding landscapes, which may in turn act as a positive feedback to the climate system. Vast areas of the east Siberian lowlands, which are underlain by permafrost of the Yedoma-type Ice Complex, are particularly sensitive to climate warming because of the high ice content of these permafrost deposits. Thermokarst and thermal erosion are two major types of permafrost degradation in periglacial landscapes. The associated landforms are prominent indicators of climate-induced environmental variations on the regional scale. Thermokarst lakes and basins (alasses) as well as thermo-erosional valleys are widely distributed in the coastal lowlands adjacent to the Laptev Sea. This thesis investigates the spatial distribution and morphometric properties of these degradational features to reconstruct their evolutionary conditions during the Holocene and to deduce information on the potential impact of future permafrost degradation under the projected climate warming. The methodological approach is a combination of remote sensing, geoinformation, and field investigations, which integrates analyses on local to regional spatial scales. Thermokarst and thermal erosion have affected the study region to a great extent. In the Ice Complex area of the Lena River Delta, thermokarst basins cover a much larger area than do present thermokarst lakes on Yedoma uplands (20.0 and 2.2 %, respectively), which indicates that the conditions for large-area thermokarst development were more suitable in the past. This is supported by the reconstruction of the development of an individual alas in the Lena River Delta, which reveals a prolonged phase of high thermokarst activity since the Pleistocene/Holocene transition that created a large and deep basin. After the drainage of the primary thermokarst lake during the mid-Holocene, permafrost aggradation and degradation have occurred in parallel and in shorter alternating stages within the alas, resulting in a complex thermokarst landscape. Though more dynamic than during the first phase, late Holocene thermokarst activity in the alas was not capable of degrading large portions of Pleistocene Ice Complex deposits and substantially altering the Yedoma relief. Further thermokarst development in existing alasses is restricted to thin layers of Holocene ice-rich alas sediments, because the Ice Complex deposits underneath the large primary thermokarst lakes have thawed completely and the underlying deposits are ice-poor fluvial sands. Thermokarst processes on undisturbed Yedoma uplands have the highest impact on the alteration of Ice Complex deposits, but will be limited to smaller areal extents in the future because of the reduced availability of large undisturbed upland surfaces with poor drainage. On Kurungnakh Island in the central Lena River Delta, the area of Yedoma uplands available for future thermokarst development amounts to only 33.7 %. The increasing proximity of newly developing thermokarst lakes on Yedoma uplands to existing degradational features and other topographic lows decreases the possibility for thermokarst lakes to reach large sizes before drainage occurs. Drainage of thermokarst lakes due to thermal erosion is common in the study region, but thermo-erosional valleys also provide water to thermokarst lakes and alasses. Besides these direct hydrological interactions between thermokarst and thermal erosion on the local scale, an interdependence between both processes exists on the regional scale. A regional analysis of extensive networks of thermo-erosional valleys in three lowland regions of the Laptev Sea with a total study area of 5,800 km² found that these features are more common in areas with higher slopes and relief gradients, whereas thermokarst development is more pronounced in flat lowlands with lower relief gradients. The combined results of this thesis highlight the need for comprehensive analyses of both, thermokarst and thermal erosion, in order to assess past and future impacts and feedbacks of the degradation of ice-rich permafrost on hydrology and climate of a certain region.
Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, lambda=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.% for the soil moisture (range of in situ values: 1-46vol.%) and of 0.37-0.45cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.
Modelling of environmental change impacts on water resources and hydrological extremes in Germany
(2012)
Water resources, in terms of quantity and quality, are significantly influenced by environmental changes, especially by climate and land use changes. The main objective of the present study is to project climate change impacts on the seasonal dynamics of water fluxes, spatial changes in water balance components as well as the future flood and low flow conditions in Germany. This study is based on the modeling results of the process-based eco-hydrological model SWIM (Soil and Water Integrated Model) driven by various regional climate scenarios on one hand. On the other hand, it is supported by statistical analysis on long-term trends of observed and simulated time series. In addition, this study evaluates the impacts of potential land use changes on water quality in terms of NO3-N load in selected sub-regions of the Elbe basin. In the context of climate change, the actual evapotransipration is likely to increase in most parts of Germany, while total runoff generation may decrease in south and east regions in the scenario period 2051-2060. Water discharge in all six studied large rivers (Ems, Weser, Saale, Danube, Main and Neckar) would be 8 – 30% lower in summer and autumn compared to the reference period (1961 – 1990), and the strongest decline is expected for the Saale, Danube and Neckar. The 50-year low flow is likely to occur more frequently in western, southern and central Germany after 2061 as suggested by more than 80% of the model runs. The current low flow period (from August to September) may be extended until the late autumn at the end of this century. Higher winter flow is expected in all of these rivers, and the increase is most significant for the Ems (about 18%). No general pattern of changes in flood directions can be concluded according to the results driven by different RCMs, emission scenarios and multi-realizations. An optimal agricultural land use and management are essential for the reduction in nutrient loads and improvement of water quality. In the Weiße Elster and Unstrut sub-basins (Elbe), an increase of 10% in the winter rape area can result in 12-19% more NO3-N load in rivers. In contrast, another energy plant, maize, has a moderate effect on the water environment. Mineral fertilizers have a much stronger effect on the NO3-N load than organic fertilizers. Cover crops, which play an important role in the reduction of nitrate losses from fields, should be maintained on cropland. The uncertainty in estimating future high flows and, in particular, extreme floods remain high due to different RCM structures, emission scenarios and multi-realizations. In contrast, the projection of low flows under warmer climate conditions appears to be more pronounced and consistent. The largest source of uncertainty related to NO3-N modelling originates from the input data on the agricultural management.
One of the major problems for the implementation of water resources planning and management in arid and semi-arid environments is the scarcity of hydrological data and, consequently, research studies. In this thesis, the hydrology of dryland river systems was analyzed and a semi-distributed hydrological model and a forecasting approach were developed for flow transmission processes in river-systems with a focus on semi-arid conditions. Three different sources of hydrological data (streamflow series, groundwater level series and multi-temporal satellite data) were combined in order to analyze the channel transmission losses of a large reach of the Jaguaribe River in NE Brazil. A perceptual model of this reach was derived suggesting that the application of models, which were developed for sub-humid and temperate regions, may be more suitable for this reach than classical models, which were developed for arid and semi-arid regions. Summarily, it was shown that this river reach is hydraulically connected with groundwater and shifts from being a losing river at the dry and beginning of rainy seasons to become a losing/gaining (mostly losing) river at the middle and end of rainy seasons. A new semi-distributed channel transmission losses model was developed, which was based primarily on the capability of simulation in very different dryland environments and flexible model structures for testing hypotheses on the dominant hydrological processes of rivers. This model was successfully tested in a large reach of the Jaguaribe River in NE Brazil and a small stream in the Walnut Gulch Experimental Watershed in the SW USA. Hypotheses on the dominant processes of the channel transmission losses (different model structures) in the Jaguaribe river were evaluated, showing that both lateral (stream-)aquifer water fluxes and ground-water flow in the underlying alluvium parallel to the river course are necessary to predict streamflow and channel transmission losses, the former process being more relevant than the latter. This procedure not only reduced model structure uncertainties, but also reported modelling failures rejecting model structure hypotheses, namely streamflow without river-aquifer interaction and stream-aquifer flow without groundwater flow parallel to the river course. The application of the model to different dryland environments enabled learning about the model itself from differences in channel reach responses. For example, the parameters related to the unsaturated part of the model, which were active for the small reach in the USA, presented a much greater variation in the sensitivity coefficients than those which drove the saturated part of the model, which were active for the large reach in Brazil. Moreover, a nonparametric approach, which dealt with both deterministic evolution and inherent fluctuations in river discharge data, was developed based on a qualitative dynamical system-based criterion, which involved a learning process about the structure of the time series, instead of a fitting procedure only. This approach, which was based only on the discharge time series itself, was applied to a headwater catchment in Germany, in which runoff are induced by either convective rainfall during the summer or snow melt in the spring. The application showed the following important features: • the differences between runoff measurements were more suitable than the actual runoff measurements when using regression models; • the catchment runoff system shifted from being a possible dynamical system contaminated with noise to a linear random process when the interval time of the discharge time series increased; • and runoff underestimation can be expected for rising limbs and overestimation for falling limbs. This nonparametric approach was compared with a distributed hydrological model designed for real-time flood forecasting, with both presenting similar results on average. Finally, a benchmark for hydrological research using semi-distributed modelling was proposed, based on the aforementioned analysis, modelling and forecasting of flow transmission processes. The aim of this benchmark was not to describe a blue-print for hydrological modelling design, but rather to propose a scientific method to improve hydrological knowledge using semi-distributed hydrological modelling. Following the application of the proposed benchmark to a case study, the actual state of its hydrological knowledge and its predictive uncertainty can be determined, primarily through rejected hypotheses on the dominant hydrological processes and differences in catchment/variables responses.
Sediment records of three European lakes were investigated in order to reconstruct the regional climate development during the Lateglacial and Holocene, to investigate the response of local ecosystems to climatic fluctuations and human impact and to relate regional peculiarities of past climate development to climatic changes on a larger spatial scale. The Lake Hańcza (NE Poland) sediment record was studied with a focus on reconstructing the early Holocene climate development and identifying possible differences to Western Europe. Following the initial Holocene climatic improvement, a further climatic improvement occurred between 10 000 and 9000 cal. a BP. Apparently, relatively cold and dry climate conditions persisted in NE Poland during the first ca. 1500 years of the Holocene, most likely due to a specific regional atmospheric circulation pattern. Prevailing anticyclonic circulation linked to a high-pressure cell above the remaining Scandinavian Ice Sheet (SIS) might have blocked the eastward propagation of warm and moist Westerlies and thus attenuated the early Holocene climatic amelioration in this region until the final decay of the SIS, a pattern different from climate development in Western Europe. The Lateglacial sediment record of Lake Mondsee (Upper Austria) was investigated in order to study the regional climate development and the environmental response to rapid climatic fluctuations. While the temperature rise and environmental response at the onset of the Holocene took place quasi-synchronously, major leads and lags in proxy responses characterize the onset of the Lateglacial Interstadial. In particular, the spread of coniferous woodlands and the reduction of detrital flux lagged the initial Lateglacial warming by ca. 500–750 years. Major cooling at the onset of the Younger Dryas took place synchronously with a change in vegetation, while the increase of detrital matter flux was delayed by about 150–300 years. Complex proxy responses are also detected for short-term Lateglacial climatic fluctuations. In summary, periods of abrupt climatic changes are characterized by complex and temporally variable proxy responses, mainly controlled by ecosystem inertia and the environmental preconditions. A second study on the Lake Mondsee sediment record focused on two small-scale climate deteriorations around 8200 and 9100 cal. a BP, which have been triggered by freshwater discharges to the North Atlantic, causing a shutdown of the Atlantic meridional overturning circulation (MOC). Combining microscopic varve counting and AMS 14C dating yielded a precise duration estimate (ca. 150 years) and absolute dating of the 8.2 ka cold event, both being in good agreement with results from other palaeoclimate records. Moreover, a sudden temperature overshoot after the 8.2 ka cold event was identified, also seen in other proxy records around the North Atlantic. This was most likely caused by enhanced resumption of the MOC, which also initiated substantial shifts of oceanic and atmospheric front systems. Although there is also evidence from other proxy records for pronounced recovery of the MOC and atmospheric circulation changes after the 9.1 ka cold event, no temperature overshoot is seen in the Lake Mondsee record, indicating the complex behaviour of the global climate system. The Holocene sediment record of Lake Iseo (northern Italy) was studied to shed light on regional earthquake activity and the influence of climate variability and anthropogenic impact on catchment erosion and detrital flux into the lake. Frequent small-scale detrital layers within the sediments reflect allochthonous sediment supply by extreme surface runoff events. During the early to mid-Holocene, increased detrital flux coincides with periods of cold and wet climate conditions, thus apparently being mainly controlled by climate variability. In contrast, intervals of high detrital flux during the late Holocene partly also correlate with phases of increased human impact, reflecting the complex influences on catchment erosion processes. Five large-scale event layers within the sediments, which are composed of mass-wasting deposits and turbidites, are supposed to have been triggered by strong local earthquakes. While the uppermost of these event layers is assigned to a documented adjacent earthquake in AD 1222, the four other layers are supposed to be related to previously undocumented prehistorical earthquakes.
Dryland vulnerability : typical patterns and dynamics in support of vulnerability reduction efforts
(2011)
The pronounced constraints on ecosystem functioning and human livelihoods in drylands are frequently exacerbated by natural and socio-economic stresses, including weather extremes and inequitable trade conditions. Therefore, a better understanding of the relation between these stresses and the socio-ecological systems is important for advancing dryland development. The concept of vulnerability as applied in this dissertation describes this relation as encompassing the exposure to climate, market and other stresses as well as the sensitivity of the systems to these stresses and their capacity to adapt. With regard to the interest in improving environmental and living conditions in drylands, this dissertation aims at a meaningful generalisation of heterogeneous vulnerability situations. A pattern recognition approach based on clustering revealed typical vulnerability-creating mechanisms at global and local scales. One study presents the first analysis of dryland vulnerability with global coverage at a sub-national resolution. The cluster analysis resulted in seven typical patterns of vulnerability according to quantitative indication of poverty, water stress, soil degradation, natural agro-constraints and isolation. Independent case studies served to validate the identified patterns and to prove the transferability of vulnerability-reducing approaches. Due to their worldwide coverage, the global results allow the evaluation of a specific system’s vulnerability in its wider context, even in poorly-documented areas. Moreover, climate vulnerability of smallholders was investigated with regard to their food security in the Peruvian Altiplano. Four typical groups of households were identified in this local dryland context using indicators for harvest failure risk, agricultural resources, education and non-agricultural income. An elaborate validation relying on independently acquired information demonstrated the clear correlation between weather-related damages and the identified clusters. It also showed that household-specific causes of vulnerability were consistent with the mechanisms implied by the corresponding patterns. The synthesis of the local study provides valuable insights into the tailoring of interventions that reflect the heterogeneity within the social group of smallholders. The conditions necessary to identify typical vulnerability patterns were summarised in five methodological steps. They aim to motivate and to facilitate the application of the selected pattern recognition approach in future vulnerability analyses. The five steps outline the elicitation of relevant cause-effect hypotheses and the quantitative indication of mechanisms as well as an evaluation of robustness, a validation and a ranking of the identified patterns. The precise definition of the hypotheses is essential to appropriately quantify the basic processes as well as to consistently interpret, validate and rank the clusters. In particular, the five steps reflect scale-dependent opportunities, such as the outcome-oriented aspect of validation in the local study. Furthermore, the clusters identified in Northeast Brazil were assessed in the light of important endogenous processes in the smallholder systems which dominate this region. In order to capture these processes, a qualitative dynamic model was developed using generalised rules of labour allocation, yield extraction, budget constitution and the dynamics of natural and technological resources. The model resulted in a cyclic trajectory encompassing four states with differing degree of criticality. The joint assessment revealed aggravating conditions in major parts of the study region due to the overuse of natural resources and the potential for impoverishment. The changes in vulnerability-creating mechanisms identified in Northeast Brazil are well-suited to informing local adjustments to large-scale intervention programmes, such as “Avança Brasil”. Overall, the categorisation of a limited number of typical patterns and dynamics presents an efficient approach to improving our understanding of dryland vulnerability. Appropriate decision-making for sustainable dryland development through vulnerability reduction can be significantly enhanced by pattern-specific entry points combined with insights into changing hotspots of vulnerability and the transferability of successful adaptation strategies.
The impact of global warming on human water resources is attracting increasing attention. No other region in this world is so strongly affected by changes in water supply than the tropics. Especially in Africa, the availability and access to water is more crucial to existence (basic livelihoods and economic growth) than anywhere else on Earth. In East Africa, rainfall is mainly influenced by the migration of the Inter-Tropical Convergence Zone (ITCZ) and by the El Niño Southern Oscillation (ENSO) with more rain and floods during El Niño and severe droughts during La Niña. The forecasting of East African rainfall in a warming world requires a better understanding of the response of ENSO-driven variability to mean climate. Unfortunately, existing meteorological data sets are too short or incomplete to establish a precise evaluation of future climate. From Lake Challa near Mount Kilimanjaro, we report records from a laminated lake sediment core spanning the last 25,000 years. Analyzing a monthly cleared sediment trap confirms the annual origin of the laminations and demonstrates that the varve-thicknesses are strongly linked to the duration and strength of the windy season. Given the modern control of seasonal ITCZ location on wind and rain in this region and the inverse relation between the two, thicker varves represent windier and thus drier years. El Niño (La Niña) events are associated with wetter (drier) conditions in east Africa and decreased (increased) surface wind speeds. Based on this fact, the thickness of the varves can be used as a tool to reconstruct a) annual rainfall b) wind season strength, and c) ENSO variability. Within this thesis, I found evidence for centennialscale changes in ENSO-related rainfall variability during the last three millennia, abrupt changes in variability during the Medieval Climate Anomaly and the Little Ice Age, and an overall reduction in East African rainfall and its variability during the Last Glacial period. Climate model simulations support forward extrapolation from these lake-sediment data, indicating that a future Indian Ocean warming will enhance East Africa’s hydrological cycle and its interannual variability in rainfall. Furthermore, I compared geochemical analyses from the sediment trap samples with a broad range of limnological, meteorological, and geological parameters to characterize the impact of sedimentation processes from the in-situ rocks to the deposited sediments. As a result an excellent calibration for existing μXRF data from Lake Challa over the entire 25,000 year long profile was provided. The climate development during the last 25,000 years as reconstructed from the Lake Challa sediments is in good agreement with other studies and highlights the complex interactions between long-term orbital forcing, atmosphere, ocean and land surface conditions. My findings help to understand how abrupt climate changes occur and how these changes correlate with climate changes elsewhere on Earth.