@phdthesis{Reusser2011,
  author    = {Reusser, Dominik Edwin},
  title     = {Combining smart model diagnostics and effective data collection for snow catchments},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-52574},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Francke2009,
  author    = {Francke, Till},
  title     = {Measurement and modelling of water and sediment fluxes in meso-scale dryland catchments},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-31525},
  school      = {Universit{\"a}t Potsdam},
  year      = {2009},
  abstract  = {Water shortage is a serious threat for many societies worldwide. In drylands, water management measures like the construction of reservoirs are affected by eroded sediments transported in the rivers. Thus, the capability of assessing water and sediment fluxes at the river basin scale is of vital importance to support management decisions and policy making. This subject was addressed by the DFG-funded SESAM-project (Sediment Export from large Semi-Arid catchments: Measurements and Modelling). As a part of this project, this thesis focuses on (1) the development and implementation of an erosion module for a meso-scale catchment model, (2) the development of upscaling and generalization methods for the parameterization of such model, (3) the execution of measurements to obtain data required for the modelling and (4) the application of the model to different study areas and its evaluation. The research was carried out in two meso-scale dryland catchments in NE-Spain: Ribera Salada (200 km²) and Is{\´a}bena (450 km²). Adressing objective 1, WASA-SED, a spatially semi-distributed model for water and sediment transport at the meso-scale was developed. The model simulates runoff and erosion processes at the hillslope scale, transport processes of suspended and bedload fluxes in the river reaches, and retention and remobilisation processes of sediments in reservoirs. This thesis introduces the model concept, presents current model applications and discusses its capabilities and limitations. Modelling at larger scales faces the dilemma of describing relevant processes while maintaining a manageable demand for input data and computation time. WASA-SED addresses this challenge by employing an innovative catena-based upscaling approach: the landscape is represented by characteristic toposequences. For deriving these toposequences with regard to multiple attributes (eg. topography, soils, vegetation) the LUMP-algorithm (Landscape Unit Mapping Program) was developed and related to objective 2. It incorporates an algorithm to retrieve representative catenas and their attributes, based on a Digital Elevation Model and supplemental spatial data. These catenas are classified to provide the discretization for the WASA-SED model. For objective 3, water and sediment fluxes were monitored at the catchment outlet of the Is{\´a}bena and some of its sub-catchments. For sediment yield estimation, the intermittent measurements of suspended sediment concentration (SSC) had to be interpolated. This thesis presents a comparison of traditional sediment rating curves (SRCs), generalized linear models (GLMs) and non-parametric regression using Random Forests (RF) and Quantile Regression Forests (QRF). The observed SSCs are highly variable and range over six orders of magnitude. For these data, traditional SRCs performed poorly, as did GLMs, despite including other relevant process variables (e.g. rainfall intensities, discharge characteristics). RF and QRF proved to be very robust and performed favourably for reproducing sediment dynamics. QRF additionally excels in providing estimates on the accuracy of the predictions. Subsequent analysis showed that most of the sediment was exported during intense storms of late summer. Later floods yielded successively less sediment. Comparing sediment generation to yield at the outlet suggested considerable storage effects within the river channel. Addressing objective 4, the WASA-SED model was parameterized for the two study areas in NE Spain and applied with different foci. For Ribera Salada, the uncalibrated model yielded reasonable results for runoff and sediment. It provided quantitative measures of the change in runoff and sediment yield for different land-uses. Additional land management scenarios were presented and compared to impacts caused by climate change projections. In contrast, the application for the Is{\´a}bena focussed on exploring the full potential of the model's predictive capabilities. The calibrated model achieved an acceptable performance for the validation period in terms of water and sediment fluxes. The inadequate representation of the lower sub-catchments inflicted considerable reductions on model performance, while results for the headwater catchments showed good agreement despite stark contrasts in sediment yield. In summary, the application of WASA-SED to three catchments proved the model framework to be a practicable multi-scale approach. It successfully links the hillslope to the catchment scale and integrates the three components hillslope, river and reservoir in one model. Thus, it provides a feasible approach for tackling issues of water and sediment yield at the meso-scale. The crucial role of processes like transmission losses and sediment storage in the river has been identified. Further advances can be expected when the representation of connectivity of water and sediment fluxes (intra-hillslope, hillslope-river, intra-river) is refined and input data improves.},
  language  = {en}
}
@phdthesis{Kneis2007,
  author    = {Kneis, David},
  title     = {A water quality model for shallow river-lake systems and its application in river basin management},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-14647},
  school      = {Universit{\"a}t Potsdam},
  year      = {2007},
  abstract  = {This work documents the development and application of a new model for simulating mass transport and turnover in rivers and shallow lakes. The simulation tool called 'TRAM' is intended to complement mesoscale eco-hydrological catchment models in studies on river basin management. TRAM aims at describing the water quality of individual water bodies, using problem- and scale-adequate approaches for representing their hydrological and ecological characteristics. The need for such flexible water quality analysis and prediction tools is expected to further increase during the implementation of the European Water Framework Directive (WFD) as well as in the context of climate change research. The developed simulation tool consists of a transport and a reaction module with the latter being highly flexible with respect to the description of turnover processes in the aquatic environment. Therefore, simulation approaches of different complexity can easily be tested and model formulations can be chosen in consideration of the problem at hand, knowledge of process functioning, and data availability. Consequently, TRAM is suitable for both heavily simplified engineering applications as well as scientific ecosystem studies involving a large number of state variables, interactions, and boundary conditions. TRAM can easily be linked to catchment models off-line and it requires the use of external hydrodynamic simulation software. Parametrization of the model and visualization of simulation results are facilitated by the use of geographical information systems as well as specific pre- and post-processors. TRAM has been developed within the research project 'Management Options for the Havel River Basin' funded by the German Ministry of Education and Research. The project focused on the analysis of different options for reducing the nutrient load of surface waters. It was intended to support the implementation of the WFD in the lowland catchment of the Havel River located in North-East Germany. Within the above-mentioned study TRAM was applied with two goals in mind. In a first step, the model was used for identifying the magnitude as well as spatial and temporal patterns of nitrogen retention and sediment phosphorus release in a 100~km stretch of the highly eutrophic Lower Havel River. From the system analysis, strongly simplified conceptual approaches for modeling N-retention and P-remobilization in the studied river-lake system were obtained. In a second step, the impact of reduced external nutrient loading on the nitrogen and phosphorus concentrations of the Havel River was simulated (scenario analysis) taking into account internal retention/release. The boundary conditions for the scenario analysis such as runoff and nutrient emissions from river basins were computed by project partners using the catchment models SWIM and ArcEGMO-Urban. Based on the output of TRAM, the considered options of emission control could finally be evaluated using a site-specific assessment scale which is compatible with the requirements of the WFD. Uncertainties in the model predictions were also examined. According to simulation results, the target of the WFD -- with respect to total phosphorus concentrations in the Lower Havel River -- could be achieved in the medium-term, if the full potential for reducing point and non-point emissions was tapped. Furthermore, model results suggest that internal phosphorus loading will ease off noticeably until 2015 due to a declining pool of sedimentary mobile phosphate. Mass balance calculations revealed that the lakes of the Lower Havel River are an important nitrogen sink. This natural retention effect contributes significantly to the efforts aimed at reducing the river's nitrogen load. If a sustainable improvement of the river system's water quality is to be achieved, enhanced measures to further reduce the immissions of both phosphorus and nitrogen are required.},
  language  = {en}
}
@phdthesis{Hattermann2005,
  author    = {Hattermann, Fred Fokko},
  title     = {Integrated modelling of Global Change impacts in the German Elbe River Basin},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-6052},
  school      = {Universit{\"a}t Potsdam},
  year      = {2005},
  abstract  = {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.},
  subject      = {Hydrologie},
  language  = {en}
}
@phdthesis{Zaehle2005,
  author    = {Zaehle, S{\"o}nke},
  title     = {Process-based simulation of the terrestrial biosphere : an evaluation of present-day and future terrestrial carbon balance estimates and their uncertainty},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-5263},
  school      = {Universit{\"a}t Potsdam},
  year      = {2005},
  abstract  = {At present, carbon sequestration in terrestrial ecosystems slows the growth rate of atmospheric CO2 concentrations, and thereby reduces the impact of anthropogenic fossil fuel emissions on the climate system. Changes in climate and land use affect terrestrial biosphere structure and functioning at present, and will likely impact on the terrestrial carbon balance during the coming decades - potentially providing a positive feedback to the climate system due to soil carbon releases under a warmer climate. Quantifying changes, and the associated uncertainties, in regional terrestrial carbon budgets resulting from these effects is relevant for the scientific understanding of the Earth system and for long-term climate mitigation strategies. A model describing the relevant processes that govern the terrestrial carbon cycle is a necessary tool to project regional carbon budgets into the future. This study (1) provides an extensive evaluation of the parameter-based uncertainty in model results of a leading terrestrial biosphere model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from theoretical and experimental evidence, and introduces the most promising hypothesis into the model; (3) demonstrates how forest statistics can be successfully integrated with process-based modelling to provide long-term constraints on regional-scale forest carbon budget estimates for a European forest case-study; and (4) elucidates the combined effects of land-use and climate changes on the present-day and future terrestrial carbon balance over Europe for four illustrative scenarios - implemented by four general circulation models - using a comprehensive description of different land-use types within the framework of LPJ-DGVM. This study presents a way to assess and reduce uncertainty in process-based terrestrial carbon estimates on a regional scale. The results of this study demonstrate that simulated present-day land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in modelled net primary production. Process-based terrestrial modelling and forest statistics are successfully combined to improve model-based estimates of vegetation carbon stocks and their change over time. Application of the advanced model for 77 European provinces shows that model-based estimates of biomass development with stand age compare favourably with forest inventory-based estimates for different tree species. Driven by historic changes in climate, atmospheric CO2 concentration, forest area and wood demand between 1948 and 2000, the model predicts European-scale, present-day age structure of forests, ratio of biomass removals to increment, and vegetation carbon sequestration rates that are consistent with inventory-based estimates. Alternative scenarios of climate and land-use change in the 21<sup>st century suggest carbon sequestration in the European terrestrial biosphere during the coming decades will likely be on magnitudes relevant to climate mitigation strategies. However, the uptake rates are small in comparison to the European emissions from fossil fuel combustion, and will likely decline towards the end of the century. Uncertainty in climate change projections is a key driver for uncertainty in simulated land-atmosphere carbon fluxes and needs to be accounted for in mitigation studies of the terrestrial biosphere.},
  subject      = {Terrestrische {\"O}kologie},
  language  = {en}
}
@phdthesis{Wriedt2004,
  author    = {Wriedt, Gunter},
  title     = {Modelling of nitrogen transport and turnover during soil and groundwater passage in a small lowland catchment of Northern Germany},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0001307},
  school      = {Universit{\"a}t Potsdam},
  year      = {2004},
  abstract  = {Stoffumsatzreaktionen und hydraulische Prozesse im Boden und Grundwasser k{\"o}nnen in Tieflandeinzugsgebieten zu einer Nitratretention f{\"u}hren. Die Untersuchung dieser Prozesse in Raum und Zeit kann mit Hilfe geeigneter Modelle erfolgen. Ziele dieser Arbeit sind: i) die Entwicklung eines geeigneten Modellansatzes durch Kombination von Teilmodellen zur Simulation des N-Transportes im Boden und Grundwasser von Tieflandeinzugsgebieten und ii) die Untersuchung von Wechselwirkungen zwischen Gebietseigenschaften und N-Transport unter besonderer Ber{\"u}cksichtigung der potentiellen N-Zufuhr in die Oberfl{\"a}chengew{\"a}sser. Der Modellansatz basiert auf der Kombination verschiedener Teilmodelle: das Bodenwasser- und -stickstoffmodell mRISK-N, das Grundwassermodell MODFLOW und das Stofftransportmodell RT3D. Zur Untersuchung der Wechselwirkungen mit den Gebietseigenschaften muss die Verteilung und Verf{\"u}gbarkeit von Reaktionspartnern ber{\"u}cksichtigt werden. Dazu wurde ein Reaktionsmodul entwickelt, welches chemische Prozesse im Grundwasser simuliert. Hierzu geh{\"o}ren die Mineralisation organischer Substanz durch Sauerstoff, Nitrat und Sulfat sowie die Pyritoxidation durch Sauerstoff und Nitrat. Der Modellansatz wurde in verschiedenen Einzelstudien angewandt, wobei jeweils bestimmte Teilmodelle im Vordergrund stehen. Alle Modellstudien basieren auf Daten aus dem Schaugrabeneinzugsgebiet (ca. 25 km\&\#178;), in der N{\"a}he von Osterburg(Altmark) im Norden Sachsen-Anhalts. Die folgenden Einzelstudien wurden durchgef{\"u}hrt: i) Evaluation des Bodenmodells anhand von Lysimeterdaten, ii) Modellierung eines Tracerexperimentes im Feldmaßstab als eine erste Anwendung des Reaktionsmoduls, iii) Untersuchung hydraulisch-chemischer Wechselwirkungen an einem 2D-Grundwassertransekt, iv) Fl{\"a}chenverteilte Modellierung von Grundwasserneubildung und Bodenstickstoffaustrag im Untersuchungsgebiet als Eingangsdaten f{\"u}r nachfolgende Grundwassersimulationen, und v) Untersuchung der Ausbreitung von Nitrat im Grundwasser und des Durchbruchs in die Oberfl{\"a}chengew{\"a}sser im Untersuchungsgebiet auf Basis einer 3D-Modellierung von Grundwasserstr{\"o}mung und reaktivem Stofftransport. Die Modellstudien zeigen, dass der Modellansatz geeignet ist, die Wechselwirkungen zwischen Stofftransport und \&ndash;umsatz und den hydraulisch-chemischen Gebietseigenschaften zu modellieren. Die Ausbreitung von Nitrat im Sediment wird wesentlich von der Verf{\"u}gbarkeit reaktiver Substanzen sowie der Verweilzeit im Grundwasserleiter bestimmt. Bei der Simulation des Untersuchungsgebietes wurde erst nach 70 Jahren eine der gegebenen Eintragssitutation entsprechende Nitratkonzentration im Grundwasserzustrom zum Grabensystem erreicht (konservativer Transport). Die Ber{\"u}cksichtigung von reaktivem Stofftransport f{\"u}hrt zu einer deutlichen Reduktion der Nitratkonzentrationen. Die Modellergebnisse zeigen, dass der Grundwasserzustrom die beobachtete Nitratbelastung im Grabensystem nicht erkl{\"a}ren kann, da der Großteil des Nitrates durch Denitrifikation verloren geht. Andere Quellen, wie direkte Eintr{\"a}ge oder Dr{\"a}nagenzufl{\"u}sse m{\"u}ssen ebenfalls in Betracht gezogen werden. Die Prognosef{\"a}higkeit des Modells f{\"u}r das Untersuchungsgebiet wird durch die Datenunsicherheiten und die Sch{\"a}tzung der Modellparameter eingeschr{\"a}nkt. Dennoch ist der Modellansatz eine wertvolle Hilfe bei der Identifizierung von belastungsrelevanten Teilfl{\"a}chen (Stoffquellen und -senken) sowie bei der Modellierung der Auswirkungen von Managementmaßnahmen oder Landnutzungsver{\"a}nderungen auf Grundlage von Szenario-Simulationen. Der Modellansatz unterst{\"u}tzt auch die Interpretation von Beobachtungsdaten, da so die lokalen Informationen in einen r{\"a}umlichen und zeitlichen Zusammenhang gestellt werden k{\"o}nnen.},
  language  = {en}
}