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.

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 done with WaterGAP2.2d model output.

In a developing Country like Sri Lanka, it is very important to plan and manage its land development programmes to attract investments to develop land resources. In this context special emphasis should be given to urban areas.The prevailing systems of issuing preliminary land development clearance by the Urban Development Authority (UDA) which is based on a manual filing system consumes significant time and is unable to provide alternative solutions to prospective developers. Most of the countries use Geographic Information Systems (GIS) for similar land management work.A study was carried out, selecting Thimbirigasyaya ward of Colombo Municipal Council (CMC) to develop a GIS based lajid data management system in order to carry out the management of the land clearances in an efficient manner.Land parcel information obtained from CMC and UDA were scanned, spatial data were georeferenced and a mosaic was constructed. Input data were subjected to accuracy checks and were verified. Accuracies of data duplication, length, extent etc., were found satisfactory and adequate for UDA land clearance work. The database also incorporates the UDA conditions stipulated for location, zone and regulations enabling the checking of applications. The developed land information system was designed to include all functional aspects in the previous systems and additional capability to provide alternative solutions. The system developed using GIS was verified for computational accuracy using manual calculations. Adequacy checks were done with respect to the approved regulations.

<p>Unlike global climate models, hydrological models cannot simulate the feedbacks among atmospheric processes, vegetation, water, and energy exchange at the land surface. This severely limits their ability to quantify the impact of climate change and the concurrent increase of atmospheric CO<sub>2</sub> concentrations on evapotranspiration and thus runoff. Hydrological models generally calculate actual evapotranspiration as a fraction of potential evapotranspiration (PET), which is computed as a function of temperature and net radiation and sometimes of humidity and wind speed. Almost no hydrological model takes into account that PET changes because the vegetation responds to changing CO<sub>2</sub> and climate. This active vegetation response consists of three components. With higher CO<sub>2</sub> concentrations, 1) plant stomata close, reducing transpiration (physiological effect) and 2) plants may grow better, with more leaves, increasing transpiration (structural effect), while 3) climatic changes lead to changes in plants growth and even biome shifts, changing evapotranspiration. Global climate models, which include dynamic vegetation models, simulate all these processes, albeit with a high uncertainty, and take into account the feedbacks to the atmosphere.</p><p>Milly and Dunne (2016) (MD) found that in the case of RCP8.5 the change of PET (computed using the Penman-Monteith equation) between 1981- 2000 and 2081-2100 is much higher than the change of non-water-stressed evapotranspiration (NWSET) computed by an ensemble of global climate models. This overestimation is partially due to the neglect of active vegetation response and partially due to the neglected feedbacks between the atmosphere and the land surface.</p><p>The objective of this paper is to present a simple approach for hydrological models that enables them to mimic the effect of active vegetation on potential evapotranspiration under climate change, thus improving computation of freshwater-related climate change hazards by hydrological models. MD proposed an alternative approach to estimate changes in PET for impact studies that is only a function of the changes in energy and not of temperature and achieves a good fit to the ensemble mean change of evapotranspiration computed by the ensemble of global climate models in months and grid cells without water stress. We developed an implementation of the MD idea for hydrological models using the Priestley-Taylor equation (PET-PT) to estimate PET as a function of net radiation and temperature. With PET-PT, an increasing temperature trend leads to strong increases in PET. Our proposed methodology (PET-MD) helps to remove this effect, retaining the impact of temperature on PET but not on long-term PET change.</p><p>We implemented the PET-MD approach in the global hydrological model WaterGAP2.2d. and computed daily time series of PET between 1981 and 2099 using bias-adjusted climate data of four global climate models for RCP 8.5. We evaluated, computed PET-PT and PET-MD at the grid cell level and globally, comparing also to the results of the Milly-Dunne study. The global analysis suggests that the application of PET-MD reduces the PET change until the end of this century from 3.341 mm/day according to PET-PT to 3.087 mm/day (ensemble mean over the four global climate models).</p><p>Milly, P.C.D., Dunne K.A. (2016). DOI:10.1038/nclimate3046.</p>

<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>