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Global water models (GWMs) simulate the terrestrial water cycle on the global scale and are used to assess the impacts of climate change on freshwater systems. GWMs are developed within different modelling frameworks and consider different underlying hydrological processes, leading to varied model structures. Furthermore, the equations used to describe various processes take different forms and are generally accessible only from within the individual model codes. These factors have hindered a holistic and detailed understanding of how different models operate, yet such an understanding is crucial for explaining the results of model evaluation studies, understanding inter-model differences in their simulations, and identifying areas for future model development. This study provides a comprehensive overview of how 16 state-of-the-art GWMs are designed. We analyse water storage compartments, water flows, and human water use sectors included in models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). We develop a standard writing style for the model equations to enhance model intercomparison, improvement, and communication. In this study, WaterGAP2 used the highest number of water storage compartments, 11, and CWatM used 10 compartments. Six models used six compartments, while four models (DBH, JULES-W1, Mac-PDM.20, and VIC) used the lowest number, three compartments. WaterGAP2 simulates five human water use sectors, while four models (CLM4.5, CLM5.0, LPJmL, and MPI-HM) simulate only water for the irrigation sector. We conclude that, even though hydrological processes are often based on similar equations for various processes, in the end these equations have been adjusted or models have used different values for specific parameters or specific variables. The similarities and differences found among the models analysed in this study are expected to enable us to reduce the uncertainty in multi-model ensembles, improve existing hydrological processes, and integrate new processes.
The accurate knowledge of the groundwater storage variation (ΔGWS) is essential for reliable water resource assessment, particularly in arid and semi-arid environments (e.g., Australia, the North China Plain (NCP)) where water storage is significantly affected by human activities and spatiotemporal climate variations. The large-scale ΔGWS can be simulated from a land surface model (LSM), but the high model uncertainty is a major drawback that reduces the reliability of the estimates. The evaluation of the model estimate is then very important to assess its accuracy. To improve the model performance, the terrestrial water storage variation derived from the Gravity Recovery And Climate Experiment (GRACE) satellite mission is commonly assimilated into LSMs to enhance the accuracy of the ΔGWS estimate. This study assimilates GRACE data into the PCRaster Global Water Balance (PCR-GLOBWB) model. The GRACE data assimilation (DA) is developed based on the three-dimensional ensemble Kalman smoother (EnKS 3D), which considers the statistical correlation of all extents (spatial, temporal, vertical) in the DA process. The ΔGWS estimates from GRACE DA and four LSM simulations (PCR-GLOBWB, the Community Atmosphere Biosphere Land Exchange (CABLE), the Water Global Assessment and Prognosis Global Hydrology Model (WGHM), and World-Wide Water (W3)) are validated against the in situ groundwater data. The evaluation is conducted in terms of temporal correlation, seasonality, long-term trend, and detection of groundwater depletion. The GRACE DA estimate shows a significant improvement in all measures, notably the correlation coefficients (respect to the in situ data) are always higher than the values obtained from model simulations alone (e.g., ~0.15 greater in Australia, and ~0.1 greater in the NCP). GRACE DA also improves the estimation of groundwater depletion that the models cannot accurately capture due to the incorrect information of the groundwater demand (in, e.g., PCR-GLOBWB, WGHM) or the unavailability of a groundwater consumption routine (in, e.g., CABLE, W3). In addition, this study conducts the inter-comparison between four model simulations and reveals that PCR-GLOBWB and CABLE provide a more accurate ΔGWS estimate in Australia (subject to the calibrated parameter) while PCR-GLOBWB and WGHM are more accurate in the NCP (subject to the inclusion of anthropogenic factors). The analysis can be used to declare the status of the ΔGWS estimate, as well as itemize the possible improvements of the future model development.
The assessment of water balance components using global hydrological models is subject to climate forcing uncertainty as well as to an increasing intensity of human water use within the 20th century. The uncertainty of five state-of-the-art climate forcings and the resulting range of cell runoff that is simulated by the global hydrological model WaterGAP is presented. On the global land surface, about 62 % of precipitation evapotranspires, whereas 38 % discharges into oceans and inland sinks. During 1971–2000, evapotranspiration due to human water use amounted to almost 1 % of precipitation, while this anthropogenic water flow increased by a factor of approximately 5 between 1901 and 2010. Deviation of estimated global discharge from the ensemble mean due to climate forcing uncertainty is approximately 4 %. Precipitation uncertainty is the most important reason for the uncertainty of discharge and evapotranspiration, followed by shortwave downward radiation. At continental levels, deviations of water balance components due to uncertain climate forcing are higher, with the highest discharge deviations occurring for river discharge in Africa (−6 to 11 % from the ensemble mean). Uncertain climate forcings also affect the estimation of irrigation water use and thus the estimated human impact of river discharge. The uncertainty range of global irrigation water consumption amounts to approximately 50 % of the global sum of water consumption in the other water use sector.
Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of large-scale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human–water interface in hydrological models.
We performed an intercomparison of river discharge regulated by dams under four meteorological forcings among five global hydrological models for a historical period by simulation. This is the first global multimodel intercomparison study on dam-regulated river flow. Although the simulations were conducted globally, the Missouri–Mississippi and Green–Colorado Rivers were chosen as case-study sites in this study. The hydrological models incorporate generic schemes of dam operation, not specific to a certain dam. We examined river discharge on a longitudinal section of river channels to investigate the effects of dams on simulated discharge, especially at the seasonal time scale. We found that the magnitude of dam regulation differed considerably among the hydrological models. The difference was attributable not only to dam operation schemes but also to the magnitude of simulated river discharge flowing into dams. That is, although a similar algorithm of dam operation schemes was incorporated in different hydrological models, the magnitude of dam regulation substantially differed among the models. Intermodel discrepancies tended to decrease toward the lower reaches of these river basins, which means model dependence is less significant toward lower reaches. These case-study results imply that, intermodel comparisons of river discharge should be made at different locations along the river's course to critically examine the performance of hydrological models because the performance can vary with the locations.
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.