Abstract. WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well as water flows and water storage and thus water resources on all land areas of the Earth. Since 1996, it has served to assess water resources and water stress both historically and in the future, in particular under climate change. It has improved our understanding of continental water storage variations, with a focus on overexploitation and depletion of water resources. In this paper, we describe the most recent model version WaterGAP 2.2d, including the water use models, the linking model that computes net abstractions from groundwater and surface water and the WaterGAP Global Hydrology Model (WGHM). Standard model output variables that are freely available at a data repository are explained. In addition, the most requested model outputs, total water storage anomalies, streamflow and water use, are evaluated against observation data. Finally, we show examples of assessments of the global freshwater system that can be achieved with WaterGAP 2.2d model output.
Urmia Lake, the world second largest hypersaline lake, has decreased in size over recent decades primarily because inflow has diminished. This has caused serious socio-environmental consequences similar to those of the Aral Sea disaster. By using the Variable Infiltration Capacity (VIC) model, this study estimates the relative contributions of climate change and water resources development -which includes construction of reservoirs and expansion of irrigated areas -to changes in Urmia Lake inflow over the period . The model results show that decreases in inflow generally follow observed decreases in precipitation, though the variability in inflow is more pronounced than the variability in precipitation. The results also suggest that water use for irrigation has increased pressure on the basin's water availability and has caused flows to decrease by as much as 40% during dry years. On the other hand, the presence of reservoirs positively contributed to water availability during relatively dry years and did not significantly reduce lake inflow. By accelerating irrigation expansion in the basin, reservoirs have, however indirectly, contributed to inflow reduction. Our results show that annual inflow to Urmia Lake has dropped by 48% over the study period. About three fifths of this change was caused by climate change and about two fifths was caused by water resources development. The results of this study show that to prevent further desiccation of Urmia Lake it will be necessary both to develop national plans to reduce irrigation water use and to develop international plans to address climate change.
Abstract. Urmia Lake, the world second largest hypersaline lake, has been largely desiccated over the last two decades resulting in socio-environmental consequences similar or even larger than the Aral Sea disaster. To rescue the lake a new water management plan has been proposed, a rapid 40% decline in irrigation water use replacing a former plan which intended to develop reservoirs and irrigation. However, none of these water management plans, which have large socio-economic impacts, have been assessed under future changes in climate and water availability. By adapting a method of environmental flow requirements (EFRs) for hypersaline lakes, we estimated annually 3.7•10 9 m 3 water is needed to preserve Urmia Lake. Then, the Variable Infiltration Capacity (VIC) hydrological model was forced with bias-corrected climate model outputs for both the lowest (RCP2.6) and highest (RCP8.5) greenhouse-gas concentration scenarios to estimate future water availability and impacts of water management strategies. Results showed a 10% decline in future water availability in the basin under RCP2.6 and 27% under RCP8.5. Our results showed that if future climate change is highly limited (RCP2.6) inflow can be just enough to meet the EFRs by implementing the reduction irrigation plan. However, under more rapid climate change scenario (RCP8.5) reducing irrigation water use will not be enough to save the lake and more drastic measures are needed. Our results showed that future water management plans are not robust under climate change in this region. Therefore, an integrated approach of future land-water use planning and climate change adaptation is therefore needed to improve future water security and to reduce the desiccating of this hypersaline lake.
<p>Freshwater availability is of vital importance for humans, freshwater biota and ecosystem functions. In the past decades, global hydrological models (GHMs) were developed to improve understanding of the global freshwater situation in a globalized word, by filling gaps in observational coverage and assessing scenarios of the future under consideration of different socioeconomic developments and climate change. The Water Global Assessment and Prognosis (WaterGAP) model was one of the first GHMs developed to evaluate freshwater resources and their use for both historical and future conditions. It consists of five water use models (for irrigation, domestic, cooling of thermal power plants, manufacturing, and livestock sectors) and the WaterGAP Global Hydrology Model (WGHM). Recently, the latest model version, WaterGAP 2.2d, was finalized, containing a number of enhancements and revisions such as a river storage-based flow velocity approach, improvements in modelling groundwater recharge in dry environments and integration of historical development of irrigated areas.</p><p>This presentation provides an overview about the WaterGAP 2.2d scheme and features, assesses global freshwater resources (runoff and streamflow) and water balance components, and provides insights to evaluation results against observed streamflow, GRACE total water storage and the AQUASTAT database.</p>
Increases in water demand often result in unsustainable water use, leaving insufficient amounts of water for the environment. Therefore, water-saving strategies have been introduced to the environmental policy agenda in many (semi)-arid regions. As many such interventions failed to reach their objectives, a comprehensive tool is needed to assess them. We introduced a constructive framework to assess the proposed strategies by estimating five key components of the water balance in an area: (1) Demand; (2) Availability; (3) Withdrawal; (4) Depletion and (5) Outflow. The framework was applied to assess the Urmia Lake Restoration Program (ULRP) which aimed to increase the basin outflow to the lake to reach 3.1 × 109 m3 yr−1. Results suggested that ULRP could help to increase the Outflow by up to 57%. However, successful implementation of the ULRP was foreseen to be impeded because of three main reasons: (i) decreasing return flows; (ii) increased Depletion; (iii) the impact of climate change. Decreasing return flows and increasing Depletion were expected due to the introduction of technologies that increase irrigation efficiency, while climate change could decrease future water availability by an estimated 3–15%. We suggest that to reach the intervention target, strategies need to focus on reducing water depletion rather than water withdrawals. The framework can be used to comprehensively assess water-saving strategies, particularly in water-stressed basins.
Farmers have to make decisions to adapt to climate change and reduce environmental vulnerability. If these decisions are made incorrectly, irreversible changes can take place that threaten environmental, social and economic sustainability of agriculture. This study applies a land use change model to guide regional agricultural land use planning, with a focus on the case of the south basin of the Urmia Lake, NW Iran, using data from Landsat images, statistics, questionnaire and checklist. The findings indicate the significant changes in the five factors, namely rainfall, humidity, minimum temperature, average temperature and maximum temperature. For example, the rainfall decreased more than 10 mm and the average temperature has increased by 3.5 °C in the last 30 years. The results of factor analysis showed that the studied variables were grouped into eight factors. These factors explained 57.4% of the variance of the determinant factors of farmers' behavior on climate change in the study area. The results obtained from supervised classification showed that all land uses have undergone many changes. The irrigated agriculture and rainfed agriculture have increased 79.43% and 82.5%, respectively, while water bodies, dense grass and woodlands, and sparse grass have declined sharply in the south basin of Urmia Lake. The forecasted results for the year 2027 show that if the existing situation continues, more crises will be faced in terms of land use change, since irrigated agriculture and rainfed agriculture are expected to grow by nearly 9000 ha and more than 1000 ha, respectively.
<p><span>Global hydrological models simulate water storages and fluxes of the water cycle, </span><span>motivated to assess water problems such as water scarcity, high flows and more generally the impact of anthropogenic change on the global water system. </span><span>However, the models include many uncertainties due to the model inputs (e.g. climate forcing data), model parameters, and model structure </span><span>which can lead</span> <span>to</span><span> disagreements </span><span>when simulation results are compared to</span><span> observations. To reduce </span><span>and quantify</span><span> these uncertainties, </span><span>some of </span><span>the models are calibrated against in-situ </span><span>streamflow</span><span> observations or compared against </span><span>total water storage anomalies (TWSA) derived from the Gravity Recovery And Climate Experiment (GRACE) satellite mission. In recent years, TWSA data are integrated into some models via data assimilation </span><span>to directly improve the realism of the models</span><span>.</span></p><p><span>In this study, we present our framework for jointly assimilating satellite and in-situ observations into the WaterGAP Global Hydrological Model (WGHM). </span><span>In addition to GRACE TWSA maps, for the first time here we experimentally jointly assimilate in-situ streamflow observations from gauge stations. </span><span>This</span> <span>is in preparation for the</span><span> Surface Water and Ocean Topography (SWOT) satellite, which will be launched this year and is expected to allow the derivation of streamflow observations globally for rivers wider than 50-100m. </span></p><p><span>GRACE assimilation strongly improves </span><span>the TWSA simulations in the Mississippi River Basin, e.g. the correlation increases to 91%, with which our results are consistent with previous studies. However, we find in this case that the streamflow simulation deteriorat</span><span>es</span><span>, f</span><span>or example, correlation reduces from 92% to 61% at the most downstream gauge station. In contrast, joint</span><span>ly assimilating GRACE data and streamflow observations from GRDC gauge stations improves the streamflow observations by up to 33% in terms of e.g. RMSE and correlation while maintaining the good TWSA simulati</span><span>ons. </span><span>In view of the upcoming SWOT mission, our data suggest that the </span><span>SWOT</span><span> data will help to further improve the structure and simulations of global hydrological models. </span></p>
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