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Semi-arid areas are, due to their climatic setting, characterized by small water resources. An increasing water demand as a consequence of population growth and economic development as well as a decreasing water availability in the course of possible climate change may aggravate water scarcity in future, which often exists already for present-day conditions in these areas. Understanding the mechanisms and feedbacks of complex natural and human systems, together with the quantitative assessment of future changes in volume, timing and quality of water resources are a prerequisite for the development of sustainable measures of water management to enhance the adaptive capacity of these regions. For this task, dynamic integrated models, containing a hydrological model as one component, are indispensable tools. The main objective of this study is to develop a hydrological model for the quantification of water availability in view of environmental change over a large geographic domain of semi-arid environments. The study area is the Federal State of Ceará (150 000 km2) in the semi-arid north-east of Brazil. Mean annual precipitation in this area is 850 mm, falling in a rainy season with duration of about five months. Being mainly characterized by crystalline bedrock and shallow soils, surface water provides the largest part of the water supply. The area has recurrently been affected by droughts which caused serious economic losses and social impacts like migration from the rural regions. The hydrological model Wasa (Model of Water Availability in Semi-Arid Environments) developed in this study is a deterministic, spatially distributed model being composed of conceptual, process-based approaches. Water availability (river discharge, storage volumes in reservoirs, soil moisture) is determined with daily resolution. Sub-basins, grid cells or administrative units (municipalities) can be chosen as spatial target units. The administrative units enable the coupling of Wasa in the framework of an integrated model which contains modules that do not work on the basis of natural spatial units. The target units mentioned above are disaggregated in Wasa into smaller modelling units within a new multi-scale, hierarchical approach. The landscape units defined in this scheme capture in particular the effect of structured variability of terrain, soil and vegetation characteristics along toposequences on soil moisture and runoff generation. Lateral hydrological processes at the hillslope scale, as reinfiltration of surface runoff, being of particular importance in semi-arid environments, can thus be represented also within the large-scale model in a simplified form. Depending on the resolution of available data, small-scale variability is not represented explicitly with geographic reference in Wasa, but by the distribution of sub-scale units and by statistical transition frequencies for lateral fluxes between these units. Further model components of Wasa which respect specific features of semi-arid hydrology are: (1) A two-layer model for evapotranspiration comprises energy transfer at the soil surface (including soil evaporation), which is of importance in view of the mainly sparse vegetation cover. Additionally, vegetation parameters are differentiated in space and time in dependence on the occurrence of the rainy season. (2) The infiltration module represents in particular infiltration-excess surface runoff as the dominant runoff component. (3) For the aggregate description of the water balance of reservoirs that cannot be represented explicitly in the model, a storage approach respecting different reservoirs size classes and their interaction via the river network is applied. (4) A model for the quantification of water withdrawal by water use in different sectors is coupled to Wasa. (5) A cascade model for the temporal disaggregation of precipitation time series, adapted to the specific characteristics of tropical convective rainfall, is applied for the generating rainfall time series of higher temporal resolution. All model parameters of Wasa can be derived from physiographic information of the study area. Thus, model calibration is primarily not required. Model applications of Wasa for historical time series generally results in a good model performance when comparing the simulation results of river discharge and reservoir storage volumes with observed data for river basins of various sizes. The mean water balance as well as the high interannual and intra-annual variability is reasonably represented by the model. Limitations of the modelling concept are most markedly seen for sub-basins with a runoff component from deep groundwater bodies of which the dynamics cannot be satisfactorily represented without calibration. Further results of model applications are: (1) Lateral processes of redistribution of runoff and soil moisture at the hillslope scale, in particular reinfiltration of surface runoff, lead to markedly smaller discharge volumes at the basin scale than the simple sum of runoff of the individual sub-areas. Thus, these processes are to be captured also in large-scale models. The different relevance of these processes for different conditions is demonstrated by a larger percentage decrease of discharge volumes in dry as compared to wet years. (2) Precipitation characteristics have a major impact on the hydrological response of semi-arid environments. In particular, underestimated rainfall intensities in the rainfall input due to the rough temporal resolution of the model and due to interpolation effects and, consequently, underestimated runoff volumes have to be compensated in the model. A scaling factor in the infiltration module or the use of disaggregated hourly rainfall data show good results in this respect. The simulation results of Wasa are characterized by large uncertainties. These are, on the one hand, due to uncertainties of the model structure to adequately represent the relevant hydrological processes. On the other hand, they are due to uncertainties of input data and parameters particularly in view of the low data availability. Of major importance is: (1) The uncertainty of rainfall data with regard to their spatial and temporal pattern has, due to the strong non-linear hydrological response, a large impact on the simulation results. (2) The uncertainty of soil parameters is in general of larger importance on model uncertainty than uncertainty of vegetation or topographic parameters. (3) The effect of uncertainty of individual model components or parameters is usually different for years with rainfall volumes being above or below the average, because individual hydrological processes are of different relevance in both cases. Thus, the uncertainty of individual model components or parameters is of different importance for the uncertainty of scenario simulations with increasing or decreasing precipitation trends. (4) The most important factor of uncertainty for scenarios of water availability in the study area is the uncertainty in the results of global climate models on which the regional climate scenarios are based. Both a marked increase or a decrease in precipitation can be assumed for the given data. Results of model simulations for climate scenarios until the year 2050 show that a possible future change in precipitation volumes causes a larger percentage change in runoff volumes by a factor of two to three. In the case of a decreasing precipitation trend, the efficiency of new reservoirs for securing water availability tends to decrease in the study area because of the interaction of the large number of reservoirs in retaining the overall decreasing runoff volumes.
Durch die Stilllegung der Kali-Gewinnung und -Produktion zwischen 1990 und 1993 sowie die begonnene Rekultivierung der Kali-Rückstandshalden haben sich die Salzfrachteintragsbedingungen für die Fließgwewässer im "Südharz-Kalirevier" in Thüringen zum Teil deutlich verändert. Aufgrund erheblich geringerer Salzeinträge in die Vorfluter Wipper und Bode ist es möglich geworden, zu einer ökologisch verträglichen Salzfrachtsteuerung überzugehen. Die Komplexität der zugrunde liegenden Stofftransportprozesse im Einzugsgebiet der Wipper macht es jedoch unumgänglich, den Steuerungsvorgang nicht nur durch reine Bilanzierungsvorgänge auf der betrachteten Steuerstrecke zu erfassen (so wie bisher praktiziert), sondern auch die Abflussdynamik im Fließgewässer und den Wasserhaushalt im Gebiet mit einzubeziehen. Die Ergebnisse dieser Arbeit dienen zum einen einer Vertiefung der Prozessverständnisse und der Interaktion von Wasserhaushalt, Abflussbildung sowie Stofftransport in bergbaubeeinflussten Einzugsgebieten am Beispiel der Unstrut bzw. ihrer relevanten Nebenflüsse. Zum anderen sollen sie zur Analyse und Bewertung eines Bewirtschaftungsplanes für die genannten Fließgewässer herangezogen werden können. Ziel dieser Arbeit ist die Erstellung eines prognosetauglichen Steuerungsinstrumentes, das für die Bewirtschaftung von Flusseinzugsgebieten unterschiedlicher Größe genutzt und unter den Rahmenbedingungen der bergbaubedingten salinaren Einträge effektiv zur Steuerung der anthropogenen Frachten eingesetzt werden kann. Die Quellen der anthropogen eingeleiteten Salzfracht sind vor allem die Rückstandshalden der stillgelegten Kaliwerke. Durch Niederschläge entstehen salzhaltige Haldenabwässer, die zum Teil ungesteuert über oberflächennahe Ausbreitungsvorgänge direkt in die Vorfluter gelangen, ein anderer Teil wird über die Speichereinrichtungen gefasst und gezielt abgestoßen. Durch Undichtigkeiten des Laugenstapelbeckens in Wipperdorf gelangen ebenfalls ungesteuerte Frachteinträge in die Wipper. Ein weiterer Eintragspfad ist zudem die geogene Belastung. Mit Hilfe detaillierter Angaben zu den oben genannten Eintragspfaden konnten Modellrechnungen im Zeitraum von 1992 bis 2003 durchgeführt werden. Durch die Ausarbeitung eines neuartigen Steuerungskonzeptes für das Laugenstapelbecken Wipperdorf, war es nun möglich, die gefasste Haldenlauge entsprechend der aktuellen Abflusssituation gezielt abstoßen zu können. Neben der modelltechnischen Erfassung der aktuellen hydrologischen Situation und der Vorgabe eines Chlorid-Konzentrationssteuerzieles für den Pegel Hachelbich, mussten dabei weitere Randbedingungen (Beckenkapazität, Beckenfüllstand, Mindestfüllstand, Kapazität des Ableitungskanals, usw.) berücksichtigt werden. Es zeigte sich, dass unter Anwendung des Steuerungskonzeptes die Schwankungsbreite der Chloridkonzentration insgesamt gesehen deutlich verringert werden konnte. Die Überschreitungshäufigkeiten bezüglich eines Grenzwertes von 2 g Chlorid/l am Pegel Hachelbich fielen deutlich, und auch die maximale Dauer einer solchen Periode konnte stark verkürzt werden. Kritische Situationen bei der modelltechnischen Frachtzusteuerung traten nur dann auf, wenn Niedrigwasserverhältnisse durch die Simulationsberechnungen noch unterschätzt wurden. Dies hatte deutliche Überschreitungen der Zielvorgaben für den Pegel Hachelbich zur Folge. Mit Hilfe des Steuerungsalgorithmus konnten desweiteren auch Szenarienberechnungen durchgeführt werden, um die Auswirkungen zukünftig zu erwartender Salzfrachten näher spezifizieren zu können. Dabei konnte festgestellt werden, dass Abdichtungsmaßnahmen der Haldenkörper sich direkt positiv auf die Entwicklung der Konzentration in Hachelbich auswirkten. Durch zusätzlich durchgeführte Langzeitszenarien konnte darüber hinaus nachgewiesen werden, dass langfristig eine Grenzwertfestlegung auf 1,5 g Chlorid/l in Hachelbich möglich ist, und die Stapelkapazitäten dazu ausreichend bemessen sind.
The scope of this study is to investigate the environmental change in the German part of the Elbe river basin, whereby the focus is on two water related problems: having too little water and having water of poor quality. The Elbe region is representative of humid to semi-humid landscapes in central Europe, where water availability during the summer season is the limiting factor for plant growth and crop yields, especially in the loess areas, where the annual precipitation is lower than 500 mm. It is most likely that water quantity problems will accelerate in future, because both the observed and the projected climate trend show an increase in temperature and a decrease in annual precipitation, especially in the summer. Another problem is nutrient pollution of rivers and lakes. In the early 1990s, the Elbe was one of the most heavily polluted rivers in Europe. Even though nutrient emissions from point sources have notably decreased in the basin due to reduction of industrial sources and introduction of new and improved sewage treatment facilities, the diffuse sources of pollution are still not sufficiently controlled. The investigations have been done using the eco-hydrological model SWIM (Soil and Water Integrated Model), which has been embedded in a model framework of climate and agro-economic models. A global scenario of climate and agro-economic change has been regionalized to generate transient climate forcing data and land use boundary conditions for the model. The model was used to transform the climate and land use changes into altered evapotranspiration, groundwater recharge, crop yields and river discharge, and to investigate the development of water quality in the river basin. Particular emphasis was given to assessing the significance of the impacts on the hydrology, taking into account in the analysis the inherent uncertainty of the regional climate change as well as the uncertainty in the results of the model. The average trend of the regional climate change scenario indicates a decrease in mean annual precipitation up to 2055 of about 1.5 %, but with high uncertainty (covering the range from -15.3 % to +14.8 %), and a less uncertain increase in temperature of approximately 1.4 K. The relatively small change in precipitation in conjunction with the change in temperature leads to severe impacts on groundwater recharge and river flow. Increasing temperature induces longer vegetation periods, and the seasonality of the flow regime changes towards longer low flow spells in summer. As a results the water availability will decrease on average of the scenario simulations by approximately 15 %. The increase in temperatures will improve the growth conditions for temperature limited crops like maize. The uncertainty of the climate trend is particularly high in regions where the change is the highest. The simulation results for the Nuthe subbasin of the Elbe indicate that retention processes in groundwater, wetlands and riparian zones have a high potential to reduce the nitrate concentrations of rivers and lakes in the basin, because they are located at the interface between catchment area and surface water bodies, where they are controlling the diffuse nutrient inputs. The relatively high retention of nitrate in the Nuthe basin is due to the long residence time of water in the subsurface (about 40 years), with good conditions for denitrification, and due to nitrate retention and plant uptake in wetlands and riparian zones. The concluding result of the study is that the natural environment and communities in parts of Central Europe will have considerably lower water resources under scenario conditions. The water quality will improve, but due to the long residence time of water and nutrients in the subsurface, this improvement will be slower in areas where the conditions for nutrient turn-over in the subsurface are poor.
Complete protection against flood risks by structural measures is impossible. Therefore flood prediction is important for flood risk management. Good explanatory power of flood models requires a meaningful representation of bio-physical processes. Therefore great interest exists to improve the process representation. Progress in hydrological process understanding is achieved through a learning cycle including critical assessment of an existing model for a given catchment as a first step. The assessment will highlight deficiencies of the model, from which useful additional data requirements are derived, giving a guideline for new measurements. These new measurements may in turn lead to improved process concepts. The improved process concepts are finally summarized in an updated hydrological model. In this thesis I demonstrate such a learning cycle, focusing on the advancement of model evaluation methods and more cost effective measurements. For a successful model evaluation, I propose that three questions should be answered: 1) when is a model reproducing observations in a satisfactory way? 2) If model results deviate, of what nature is the difference? And 3) what are most likely the relevant model components affecting these differences? To answer the first two questions, I developed a new method to assess the temporal dynamics of model performance (or TIGER - TIme series of Grouped Errors). This method is powerful in highlighting recurrent patterns of insufficient model behaviour for long simulation periods. I answered the third question with the analysis of the temporal dynamics of parameter sensitivity (TEDPAS). For calculating TEDPAS, an efficient method for sensitivity analysis is necessary. I used such an efficient method called Fourier Amplitude Sensitivity Test, which has a smart sampling scheme. Combining the two methods TIGER and TEDPAS provided a powerful tool for model assessment. With WaSiM-ETH applied to the Weisseritz catchment as a case study, I found insufficient process descriptions for the snow dynamics and for the recession during dry periods in late summer and fall. Focusing on snow dynamics, reasons for poor model performance can either be a poor representation of snow processes in the model, or poor data on snow cover, or both. To obtain an improved data set on snow cover, time series of snow height and temperatures were collected with a cost efficient method based on temperature measurements on multiple levels at each location. An algorithm was developed to simultaneously estimate snow height and cold content from these measurements. Both, snow height and cold content are relevant quantities for spring flood forecasting. Spatial variability was observed at the local and the catchment scale with an adjusted sampling design. At the local scale, samples were collected on two perpendicular transects of 60 m length and analysed with geostatistical methods. The range determined from fitted theoretical variograms was within the range of the sampling design for 80% of the plots. No patterns were found, that would explain the random variability and spatial correlation at the local scale. At the watershed scale, locations of the extensive field campaign were selected according to a stratified sample design to capture the combined effects of elevation, aspect and land use. The snow height is mainly affected by the plot elevation. The expected influence of aspect and land use was not observed. To better understand the deficiencies of the snow module in WaSiM-ETH, the same approach, a simple degree day model was checked for its capability to reproduce the data. The degree day model was capable to explain the temporal variability for plots with a continuous snow pack over the entire snow season, if parameters were estimated for single plots. However, processes described in the simple model are not sufficient to represent multiple accumulation-melt-cycles, as observed for the lower catchment. Thus, the combined spatio-temporal variability at the watershed scale is not captured by the model. Further tests on improved concepts for the representation of snow dynamics at the Weißeritz are required. From the data I suggest to include at least rain on snow and redistribution by wind as additional processes to better describe spatio-temporal variability. Alternatively an energy balance snow model could be tested. Overall, the proposed learning cycle is a useful framework for targeted model improvement. The advanced model diagnostics is valuable to identify model deficiencies and to guide field measurements. The additional data collected throughout this work helps to get a deepened understanding of the processes in the Weisseritz catchment.