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The reanalysis products and derived products, ERA5 (Copernicus Climate Change Service, 2018) and W5E5 (WATCH Forcing Data (WFD) methodology applied to ERA5) (LANGE ET AL., 2021) have been recently published initiating a new phase of scientific research utilizing these datasets. ERA5 and W5E5 offer the possibility to reduce insecurities in model results through their improved quality compared to previous climate reanalyses (CUCCHI ET AL., 2020). The suitability of either climate forcing as input for the hydrological model WaterGAP and the influence of the models specific calibration routine has been evaluated with four model experiments. The model was validated by analysing the models ability to produce reasonable values for global water balance components and to reproduce observed discharge in 1427 basins as well as total water storage anomalies in 143 basins using well established efficiency metrics. Bias correction of W5E5 was found to lead to more global realistic mean precipitation and consequently discharge and AET values. In an uncalibrated model setup ERA5 results in better performances across all efficiency metrics. Model results produced with W5E5 as climate input were strongly improved through calibration ultimately leading to the best performances out of all four model experiments. However, model performances considerably improved through calibration with both climate forcings hence calibration was found to have the strongest effect on model performance. Furthermore, spatial differences in performance of either forcing were identified. Snow-dominated regions show an overall better performance with ERA5, while wetter and warmer regions are better represented with W5E5. Finally, it can be concluded that W5E5 should be preferred as climate input for impact modelling; however, depending on the spatial scale and region ERA5 should at least be considered, in particular for snow-dominated regions.
In the past sixty years, excessive water consumption and dam construction have significantly influenced natural flow regimes and surface freshwater ecosystems throughout China, and thus resulted in serious environmental problems. In order to balance the competing water demands between human and environment and provide knowledge on sustainable water management, assessments on anthropogenic flow alterations and their impacts on aquatic and riparian ecosystems in China are needed.
In this study, the first evaluation on quantitative relationships between anthropogenic flow alterations and ecological responses in eleven river basins and watersheds in China was performed based on the data that could be obtained from published case studies. Quantitative relationships between changes in average annual discharge, seasonal low flow and seasonal high flow and changes in ecological indicators (fish diversity, fish catch and vegetation cover, etc.) were analyzed. The results showed that changes in riparian vegetation cover as well as changes in fish diversity and fish catch were strongly correlated with the changes in flow magnitude (r = 0.77, 0.66), especially with changes in average annual river discharge. In addition, more than half of the variations in vegetation cover could be explained by changes in average annual river discharge (r² = 0.63) and roughly 50 % changes in fish catch in arid and semi-arid region and 60% changes of fish catch in humid region could be related to alterations in average annual river discharge (r² = 0.53, 0.58).
In a supplementary analysis of this study, the first estimation on quantitative relationships between decreases in native fish species richness and anthropogenic flow alterations in 34 river basins and sub-basins in China was conducted. Linear relationships between losses of native fish species and five ecologically relevant flow indicators were analyzed by single and multiple regression models. For the single regression analysis, significant linear relationships were detected for the indicators of long-term average annual discharge (ILTA) and statistical low flow Q90 (IQ90). For the multiple regressions, no indicator other than ILTA has significant relationships with changes in number of fish species mainly due to collinearity. Two conclusions emerged from the analysis: 1) losses of fish species were positively correlated with changes in ILTA in China and 2) indicator of ILTA was dominant over other flow indicators included in this research for the given dataset. These results provide a guideline for the sustainable water resources management in rivers with high risk of fish extinction in China.
Floodplains and other wetlands depend on seasonal river flooding and play an important role in the terrestrial water cycle. They influence evapotranspiration, water storage and river discharge dynamics, and they are the habitat of a large number of animals and plants. Thus, to assess the Earth’s system and its changes, a robust understanding of the dynamics of floodplain wetlands including inundated areas, water storages, and water flows is required.
This PhD thesis aims at improving the modeling of large floodplains and wetlands within the global-scale hydrological model WaterGAP, in order to better estimate water flows and water storage variations in different storage compartments. Within the scope of this thesis, I have developed a new approach to simulate dynamic floodplain inundation on a global-scale. This approach introduces an algorithm into WaterGAP, which has a spatial resolution of 0.5 degree (longitude and latitude) globally. The new approach uses subgrid-scale topography, based on high-resolution digital elevation models, to describe the floodplain elevation profile within each grid cell by applying a hypsographic curve. The approach comprises the modeling of a two-way river-floodplain interaction, the separate downstream water transport within the river and the floodplain – both with temporally and spatially different variable flow velocities – and the floodplain-groundwater interactions. The WaterGAP version that includes the floodplain algorithm, WaterGAP 2.2b_fpl, estimates floodplain and river water storage, inundated area and water table elevation, and also simulates backwater effects.
WaterGAP 2.2b_fpl was applied to model river discharge, river flow velocity, water storages, water heights and surface water extent on a global-scale. Model results were comprehensively validated against ground observations and remote sensing data. Overall, the modeled and observed data are in agreement. In comparison to the former version WaterGAP 2.2b, the model performance has improved significantly. The improvements are most remarkable in the Amazon River basin. However, the seasonal variation of surface water extent and total water storage anomalies are still too low in many regions on the globe when compared to observations. A detailed analysis of the simulated results suggests that in the Amazon River basin the introduction of backwater effects is important for realistically simulating water storages and surface water extent. Future efforts should focus on the simulation of water levels in order to better model the flow routing according to water slope. To further improve the model performance in specific regions, I recommend that the globally constant model parameters that affect inundation initiation, river-floodplain interaction, DEM correction for vegetation, and backwater amount at basin or subbasin-scale be adjusted.
Bayesian Networks are computer-based environmental models that are frequently used to support decision-making under uncertainty. Under data scarce conditions, Bayesian Networks can be developed, parameterized, and run based on expert knowledge only. However, the efficiency of expert-based Bayesian Network modeling is limited by the difficulty in deriving model inputs in the time available during expert workshops. This thesis therefore aimed at developing a simple and robust method for deriving conditional probability tables from expert estimates in a time-efficient way. The design and application of this new elicitation and conversion method is demonstrated using a case study in Xinjiang, Northwest China. The key characteristics of this method are its time-efficiency and the approach to use different conversion tables based on varying levels of confidence. Although the method has its limitations, e.g. it can only be applied for variables with one conditioning variable; it provides the opportunity to support the parameterization of Bayesian Networks which would otherwise remain half-finished due to time constraints. In addition, a case study in the Murray-Darling Basin, Australia, is used to compare Bayesian Network types and software to improve the presentation clarity of large Bayesian Networks. Both case studies aimed at gaining insights on how to improve the applicability of Bayesian Networks to support environmental management.
Agriculture of crops provides more than 85% of the energy in human diet, while also securing income of more than 2.6 billion people. To investigate past, present and future changes in the domain of food security, water resources and water use, nutrient cycles, and land management it is required to know the agricultural land use, in particular which crop grows where and when. The current global land use or land cover data sets are based on remote sensing and agricultural census statistics. In general, these only contain one or very few classes of agricultural land use. When crop-specific areas are given, no distinction of irrigated and rainfed areas is made, whereas it is necessary to distinguish rainfed and irrigated crops, because crop productivity and water use differ significantly between them.
To support global-scale assessments that are sensitive to agricultural land use, the global data set of Monthly Irrigated and Rainfed Crop Areas around the year 2000 (MIRCA2000) was developed by the author. With a spatial resolution of 5 arc-minutes (approximately 9.2 km at the equator), MIRCA2000 provides for the first time, spatially explicit irrigated and rainfed crop areas separately for each of the 26 crop classes for each month of the year, and includes multi-cropping. The data set covers all major food crops as well as cotton, while the remaining crops are grouped into three categories (perennial, annual and fodder grasses). Also for the first time, crop calendars on national or sub-national level were consistently linked to annual values of harvested area at the 5 arc-minutes grid cell level, such that monthly growing areas could be computed that are representative for the time period 1998 to 2002.
The downscaling algorithm maximizes the consistency to the grid-based input data of cropland extent [Ramankutty et al., 2008], crop-specific total annual harvested area [Monfreda et al., 2008], and area equipped for irrigation [Siebert et al., 2007]. In addition to the methodology, this dissertation describes differences to other datasets and standard scaling methods, as well as some applications. For quality assessment independent datasets and newly developed quality parameters are used, and scale effects are discussed.
Supplementary Appendices document crop calendars for irrigated and rainfed crops for each of the 402 spatial units (Appendix I), data sources of harvested area and of cropping periods for irrigated crops, country by country (Appendix K), as well as data quality parameters (Appendix L, including spreadsheet files).
Long-term average groundwater recharge representing the sustainable groundwater resources is modeled as a 0.5° by 0.5° grid on global scale by the WaterGAP Global Hydrology Model. Due to uncertainties of estimating groundwater recharge, especially in semiarid and arid regions, independent estimates are used for calibrating the model. This work compiled a new set of independent groundwater recharge estimates based on a work of Scanlon et al. (2006). The 59 independent estimates, together with an already existing independent estimates compilation, are used for the evaluation of two WGHM variants; one variant is modeling with an improved more realistically distributed daily precipitation dataset.
The objective of this thesis is the evaluation of the modeled data of the WaterGAP Global Hydrology Model (WGHM). The analysis of the impact of the new Watch Forcing Data (WFD) precipitation dataset on the modeled groundwater recharge tends to result in lower values in humid and higher values in (semi-)arid regions compared to the WGHM standard variant. Comparing both WGHM variants to the independent estimates compilations, representing (semi-)arid regions, the WGHM variant shows over- and underestimations especially of the low values and the WGHM WFD variant shows a bias toward overestimation especially for values below 4 mm/yr. The analysis of texture, hydrogeology and vegetation/ land cover could not give satisfying explanations for the discrepancies, but derived from the groundwater recharge measurement methods analysis indirect/ localized recharge seems to be a significant factor causing underestimations, as resulted in the comparison of the independent estimates based on Scanlon et al. 2006 with the WGHM variants.
The estimation of water balance components as well as water-related indicators on the land surface by means of global hydrological models have evolved in recent decades. Results of such models are frequently used in global- and continental-scale assessments of the current and future state of the terrestrial water cycle and provide a valuable data basis, e.g., for the Intergovernmental Panel on Climate Change. The Water – Global Assessment and Prognosis (WaterGAP) model is one of the state-of-the-art models in that field and has been in development and application for around 20 years. The evaluation, modification and application of WaterGAP is the subject of this thesis. In particular, the sensitivity of climate input data on radiation calculation and simulated water fluxes and storages is evaluated in the first part. Effects of model modification such as updated spatial input datasets, improved process representation or an alternative calibration scheme are the focus of the second part. Finally, three applications of WaterGAP give insight into the capabilities of that model, namely an estimate of global and continental water balance components, an assessment of groundwater depletion and the impact of climate change on river flow regimes. Model experiments, which are described in six journal papers as well as the appendices, were used as the basis for answering the total of 13 research questions. One of the major foci was to quantify the sensitivity of simulated water fluxes and storages to alternative climate input data. It was found that the handling of precipitation undercatch leads to the greatest difference in water balance components, especially in those areas where WaterGAP is not calibrated due to a lack of river discharge observations. The modifications of WaterGAP in the last few decades has led in general to an improved simulation of monthly river discharge, but process representation in semi-arid and arid regions still requires improvements. With the most current model version, WaterGAP 2.2b, and for the time period 1971–2000, river discharge to the oceans and inland sinks is estimated to be 40 000 km3 yr-1, whereas actual evapotranspiration is simulated as 70 500 km3 yr-1. Future research needs for WaterGAP in particular but also for the global hydrological model community in general are defined, promoting a community-driven effort for a robust assessment of the continental water cycle.
140 Liter Wasser werden für die Herstellung einer Tasse Kaffee benötigt, 1.300 Liter Wasser für ein Kilo Gerste und 3.400 Liter Wasser für ein Kilo Reis. Diese Zahlen mögen im ersten Moment unglaubwürdig erscheinen, doch sie entsprechen der Wirklichkeit. Für die Herstellung von nahezu allen Produkten wird Wasser in teils sogar sehr großen Mengen benötigt. In dem Endprodukt jedoch findet sich meist nur ein kleiner Teil des ursprünglich eingesetzten Wassers in seiner physischen Form wieder. Der überwiegende Anteil wurde während des Produktionsprozesses verdunstet oder zur Kühlung eingesetzt und wird daher als „virtuelles Wasser“ bezeichnet. Aufgrund des Exports und Imports von Produkten im Zuge des internationalen Handels kommt es somit auch zu Strömen von virtuellem Wasser zwischen den einzelnen Ländern. In dieser Bachelorarbeit wird der virtuelle Wasserhandel mit 23 verschiedenen Feldfrüchten mit dem Fokus auf Deutschland für den Zeitraum von 1998 bis 2002 untersucht. In die Berechnung dieser virtuellen Wasserströme ist ein neuartiges Modell eingegangen, das Global Crop Water Model (GCWM), welches den virtuellen Wassergehalt für unterschiedliche Feldfruchtgruppen global für jede 5-Minuten-Zelle auf Basis detaillierter Daten berechnet. Dank dieses Modells ist es möglich, eine Trennung zwischen dem virtuellen Wasser, welches aus der Nutzung des Niederschlagswassers und dem virtuellen Wasser, welches aus der Bewässerung von Ackerflächen resultiert, vorzunehmen und diese getrennt von einander zu analysieren. Mittels der Verwendung der Handelsstatistik Comtrade der Vereinten Nationen lässt sich aus den Ergebnissen des GCWM der virtuelle Wasserhandel darstellen. Es zeigt sich, dass Deutschland das meiste Wasser in seiner virtuellen Form nach Algerien, Saudi-Arabien, Belgien und in die Niederlande exportiert, wohingegen aus Brasilien, den USA, Frankreich und der Elfenbeinküste die größten virtuellen Wassermengen importiert werden.
In situ rainwater harvesting has a long history in arid and semi-arid regions of the world buffering water shortages for human consumption and agriculture. In the context of an Integrated Water Resource Management (IWRM) in the Cuvelai Basin in northern Namibia, roof top rainwater harvesting is being introduced to a rural community for the irrigation of household scale gardens for the cultivation of horticulture products. This study elaborates how harvested rainwater can be used for garden irrigation in a sustainable manner evaluating ecologic, economic and social implications. Considering local conditions eight cropping scenarios were designed, including different criteria as well as one and two annual planting seasons. These schemes were tested under present climate conditions and under three future climate change scenarios for 2050 with the help of a tank model designed to model monthly tank inflows and outflows. Special attention was laid on risk and uncertainty aspects of varying inter-annual and interseasonal precipitation and future climate change. A framework for the assessment of sustainability was adapted to the purposes of this study and indicators have been developed in order to assess the cropping and irrigation schemes for sustainability.
The study found that with the given tank size of 30 m³, depending on crop scenario, under optimized conditions a garden area of 60 to 90 m³ can be irrigated. The choice of crops highly impacts water use efficiency and economic profitability, compared to the considerably lower impact of amount of annual planting seasons and future climate change. In the case of worsening future climate conditions, adaptation measures need to be taken as especially the economic as well as the environmental situation are expected to exacerbate due to expected decreases in yields and revenues. Already under present conditions however, the economic dimension represents the most limiting factor to sustainability, particularly due to the excessive investment costs of the rainwater harvesting and gardening facility. Nonetheless, rainwater harvesting in combination with gardening can be regarded as successful in securing household nutrition, providing sufficient horticulture products for household consumption or market sale. At the same time with the optimal choice of crops the investment costs can be recovered within the end of the lifespan of the facility.
Water is scarce in semi-arid and arid regions. Using alternative water sources (i.e. non-conventional water sources), such as municipal reuse water and harvested rain, contributes to using existing water resources more efficiently and productively. The aim of this study is to evaluate the two alternative water sources reuse water and harvested rain for the irrigation of small-holder agriculture from a system perspective. This helps decision and policy makers to have proper information about which system and technology to adopt under local conditions. For this, the evaluation included ecologic, societal, economic, institutional and political as well as technical aspects. For the evaluation, the study area in central-northern Namibia was chosen in the frame of the research and development project CuveWaters. The main methods used include a mathematical material flow analysis, the computation and modelling of crop requirements, a multi-criteria decision analysis using the Analytical Hierarchy Process (AHP) method and a financial cost-benefit analysis. From a systemic perspective, the proposed novel systems were compared to the exciting conventional infrastructure. The results showed that both water reuse and rainwater harvesting systems for the irrigation of small-holder horticulture offer numerous technological, ecologic, economic, societal, institutional and political benefits. Rainwater harvesting based gardens have a positive benefit-cost ratio under favorable conditions. Government programs could fund the infrastructure investment costs, while the micro-entrepreneur can assume a micro-credit to finance operation and maintenance costs. Installing sanitation in informal settlements and reusing municipal water for irrigation reduces the overall water demand of households and agriculture by 39%, compared to improving sanitation facilities in informal settlements without reusing the water for agriculture. Given that water is the limiting factor for crop fertigation, the generated nutrient-rich reuse water is sufficient to annually irrigate about 10 m2 to 13 m2 per sanitation user. Compared to crop nutrient requirements, there are too many nutrients in the reuse water. Thus when using nutrient-rich reuse water, no use of fertilizers and a careful salt management is necessary. When comparing this novel system with improved sanitation, advanced wastewater treatment and nutrient-rich water reuse to the conventional and to two adapted systems, results showed that the novel CuveWaters system is the best option for the given context in a semi-arid developing country. Therefore, the results of this study suggest a further roll-out of the novel CuveWaters system. The methodology developed and the results of this study demonstrated that taking sanitation users into consideration plays a major role for the planning of an integrated water reuse infrastructure because they are the determinant factor for the amount of available nutrient-rich reuse water. In addition, it could be shown that water reuse and rainwater harvesting systems for the irrigation of small-scale gardens provide a wide range of benefits and can be key to using scarce water resources more efficiently and to contributing to the Sustainable Development Goals.
