Rens van Beek

Human activities, including domestic water use, agriculture, and energy generation, cause increasing challenges in meeting water demands, not only due to water shortages, but also poor water quality. Nevertheless, there remains limited understanding of how water quality influences the allocation of water per source across different sectors at a large scale. Here we show, for the first time, that water quality strongly affects both water source allocation and sectoral water use competition in river basins globally. We developed a new sectoral water use and allocation model, which accounts for water quality requirements (i.e., suitability thresholds) for the main water use sectors (i.e., domestic, irrigation, livestock, manufacturing and energy). Our results show that the sole inclusion of surface water quality leads to a substantial decrease of surface water withdrawal (17% globally) and an increase in groundwater dependence, with Latin America, the Middle East and North Africa exhibiting the largest responses. In addition, the inclusion of water quality requirements leads to improved estimates of total surface water used in most regions and should therefore be systematically integrated into sectoral water use modeling to provide more meaningful estimates supporting water use management and decision making.

Farmers face increasing challenges in maintaining stable crop production as climate change alters growing conditions through higher temperatures, variable rainfall, and extreme weather events. To adapt, farmers often select new crop varieties and adjust planting dates before changing crops, as these strategies involve lower costs and risks. To support assessments of future crop production under climate change, we developed a global gridded dataset that provides simulated yields and consumptive water use for multiple crop varieties and sowing dates for maize, soybean, winter wheat, spring wheat, and rice. The dataset is based on simulations with the WOrld FOod STudies crop growth model under five global climate models and three greenhouse gas concentration scenarios, at a spatial resolution of 0.5 by 0.5 degrees (~55 km at the equator), covering the years 1961 to 2100. It can help identify suitable crop varieties and planting dates that sustain yields and optimize water use. This dataset is intended for use in crop modelling, climate impact assessments, and agricultural adaptation planning.

Solifluction is an important geomorphological process, mainly driven by seasonal freeze–thaw cycles that mobilize the upper soil layers and contribute significantly to landscape evolution. Despite its relevance, there is currently no numerical package available for simulating solifluction in a physically based manner. In this study, we present a new three-dimensional numerical model, soli3d, developed to simulate this phenomenon by deriving the governing physical partial differential equations and explicitly solving them using numerical discretization.The model integrates mass conservation, momentum conservation, and heat transfer. The thawed soil layer is treated as a viscous fluid, and the corresponding momentum equations are derived following principles from fluid mechanics. Topographic evolution is tracked using a Volume of Fluid (VOF) method. Soil temperature profiles are computed by solving the heat transfer equation in the vertical direction. The viscosity of the thawed soil is assumed to depend on temperature, soil and vegetation properties. The soli3d software package uses the finite difference method (FDM) to discretize and solve the governing equations. The vertical domain is represented by multiple layers, while the horizontal plane is discretized using uniform, structured rectangular grids. The soli3d model (see soli3d link [https://github.com/computationalgeography/soli3d]) is available as an open-source Python implementation utilizing the LUE environmental modelling framework (see link [https://zenodo.org/records/16792016]) for efficient parallel and distributed computing.To assess the model performance, soli3d is validated using a set of benchmark test cases. The results demonstrate the capability of the model to reproduce key characteristics of solifluction processes and provide a foundation for future applications.

Individual hydrological and crop growth models often oversimplify underlying processes, reducing the accuracy of both simulated hydrology and crop growth dynamics. While crop models tend to generalize soil moisture processes, most hydrological models commonly use constant vegetation parameters and prescribed phenologies, neglecting the dynamic nature of crop growth. Despite some studies that have coupled hydrological and crop models, a limited understanding exists regarding the feedbacks between hydrology and crop growth. Our objective is to quantify the feedback between crop systems and hydrology on a fine-grained spatiotemporal level. To this end, the PCR-GLOBWB 2 hydrological model was coupled with the WOFOST crop growth model to quantify both the one-way and two-way interactions between hydrology and crop growth on a daily time step and at 5 arcmin (∼ 10 km) resolution. Our study spans the contiguous United States (CONUS) region and covers the period from 1979 to 2019, allowing a comprehensive evaluation of the feedback between hydrology and crop growth dynamics. We compare individual (stand-alone) as well as one-way and two-way coupled WOFOST and PCR-GLOBWB 2 model runs and evaluate the average crop yield and its interannual variability for rainfed and irrigated crops as well as simulated irrigation water withdrawal for maize, wheat, and soybean. Our results reveal distinct patterns in the temporal and spatial variation of crop yield depending on the included interactions between hydrology and crop systems. Evaluating the model results against reported yield and water use data demonstrates the efficacy of the coupled framework in replicating observed irrigated and rainfed crop yields. Our results show that two-way coupling, with its dynamic feedback mechanisms, outperforms one-way coupling for rainfed crops. This improved performance stems from the feedback of WOFOST crop phenology to the crop parameters in the hydrological model. Our results suggest that when crop models are combined with hydrological models, a two-way coupling is needed to capture the impact of interannual climate variability on food production.

Water temperature is a key abiotic factor influencing aquatic ecosystem health and the services provided to both nature and humans. Global water temperature models offer possibilities to improve our understanding of water temperature regimes, which is increasingly important against the backdrop of climate change. Yet, existing studies have predominantly relied on a single model, which can lead to an incomplete representation of uncertainty and potential biases, in addition to limited insight into the range of possible future conditions, which ultimately reduces the robustness of climate impact assessments. Here, we provide a comprehensive assessment of surface freshwater temperature changes from various river and lake models for both past conditions and under future scenarios of climate change. Global models consistently simulate that surface water temperatures are currently 0.5 °C–0.8 °C higher than at the turn of the century (i.e. 1981–2000), and that warming will extend and intensify with future global change throughout the 21st century. While the strength of warming is highly sensitive to the different water temperature models, emissions scenarios and global climate models, our multi-model ensemble shows a global average annual water temperature rise of between +1.3 °C and +4.1 °C by the end of the century. To illustrate a potential societal impact of our results, we evaluate how future changes in discharge and water temperature may affect existing thermoelectric power plants, estimating average annual reductions of 1.5%–6% in global usable capacity by the end of the century. However, with river water temperatures projected to exhibit more pronounced seasonal patterns in the future—especially under the more extreme climate change scenarios and during summer months in the Northern Hemisphere—intra-annual reductions in usable capacity can be much more severe. Given the challenges associated with (large-scale) adaptation to control water temperature regimes, strong climate change mitigation is crucial for minimising water temperature rises and its associated negative impacts on humankind and ecosystems.

Human activities strongly rely on the availability of sufficient water and of adequate quality, yet water use sectors (e.g. irrigation, domestic, industry and energy), already experience clean water scarcity. Additionally, the availability of clean water is further compromised by increasing water demand of the growing population, deterioration of water quality due to pollution by emissions by the different sections, and by more frequent and intense hydroclimatic extremes (e.g. droughts, heatwaves, and compound events). These developments increase the cross-sectoral competition for the available water (Cárdenas Belleza et al, 2023). Current research on large-scale water scarcity related to insufficient water of good quality has provided limited understanding of the sector-specific impacts. This limits our understanding of how water quality affects water sources allocation to different water use sectors and how such responses will impact sector-specific and total water scarcity under global change.The main objective of this research is to assess cross-sectoral water scarcity due to sectoral competition for limited clean water resources, explicitly considering water quantity and water quality requirements under global change. To address this, we developed a new globally applicable sectoral water use and allocation model, QUAlloc v1.0, that incorporates water quality requirements across main water use sectors (domestic, irrigation, livestock, manufacturing, and energy). QUAlloc v1.0 is linked to the PCR‑GLOBWB 2 hydrological model (Sutanudjaja et al, 2018) and the DynQual v1.0 global surface water quality model (Jones et al, 2023), forming a sectoral water quality, use and allocation modelling framework.Our results show that present surface water quality strongly affects both water source allocation and sectoral water use competition in river basins globally, resulting in a significant reduction in global surface water withdrawals (by 17%) and an increased dependence on groundwater (e.g., Latin America, the Middle East, North Africa). Additionally, we show that sectors with less stringent water quality requirements, namely livestock and manufacturing, benefit by the reduced surface water withdrawal from other sectors (i.e., domestic, irrigation), enabling to increase its withdrawal. Projections of sector-specific water scarcity under climate change and socio-economic changes for the whole 21st century suggest that these inter-sectoral impacts will become increasingly stronger in the future. Our study is the first in exploring the impacts of present and future water quality in the cross-sectoral water use competition and their effects on sector-specific water scarcity globally.References:Cárdenas B., G.A., Bierkens, M.F.P., van Vliet, M.T.H.: Sectoral water use responses to droughts and heatwaves: analyses from local to global scales for 1990-2019. Environ. Res. Lett. 18 104008. https://doi.org/10.1088/1748-9326/acf82e, 2023.Sutanudjaja, E.H., van Beek, L.P.H., de Jong, S.M., van Geer, F.C., and Bierkens, M.F.P.: Calibrating a large-extent high-resolution coupled groundwater-land surface model using soil moisture and discharge data, Water Resour. https://doi.org/10.5194/gmd-11-2429-2018, 2018.Jones, E.R., Bierkens, M.F.P., Wanders, N., Sutanudjaja, E.H., van Beek, L.P.H., and van Vliet, M.T.H.: DynQual v1.0: a high-resolution global surface water quality model, Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, 2023.

Land surface characteristics play an important role in shaping hydrological response and groundwater-surface water interactions. It is therefore paramount to model the terrestrial hydrological at cycle spatial resolutions which incorporate appropriate land surface heterogeneities.Our objective is to enable modelling of the global terrestrial hydrological cycle at very high spatial resolution. As a first step towards this goal, we present the first global application of PCR-GLOBWB at 30 arcseconds (~1 km) resolution. In this global 30 arcseconds PCR-GLOBWB model we implement a new statistical downscaling routine for meteorological forcing that relies on CHELSA high resolution climatologies to provide an improved spatial distributions of precipitation, temperature and reference evapotranspiration. To better capture snow and ice dynamics, we have embedded an improved snow and ice distribution scheme, which is critital for high mountain regions. Finally, we improve on the method of parralisation used when running the model at a global scale to overcome computational limitations.We simulated the global terrestrial hydrological cycle from 1985 – 2019 at the daily timestep and validate simulated river discharge, evaporation, total water storage anomalies and snow cover against observed data. The model outputs are also compared to previous more coarse scale global PCR-GLOBWB model at 5 arcminute and 30 arcminute resolutions as well as simulations with the lower resolution meteorological forcing to separately quantify the impact of increasing the spatial resolution in the land surface and meteorological forcing. Furthermore, we discuss the computational challenges encountered along the way and outline future directions and opportunities in high-resolution global hydrological modelling.

We revisit the classic problem of determining economically optimal groundwater withdrawal rates for irrigation. The novelty compared to previous mathematical analyses is the inclusion of non-linear groundwater-surface water interaction that allows for incorporating the impact of capture, i.e. the fact that all or part of the pumped groundwater comes out of reduced surface water flow or increased recharge. We additionally included the option to internalize environmental externalities (e.g. streamflow depletion) and maximize social welfare rather than farmer’s profit. This analysis results in a fixed optimal groundwater withdrawal rate qopt when withdrawal q remains smaller than some critical withdrawal rate (maximum capture) qcrit and provides depletion trajectories, either under competition or optimal control, if q is larger than qcrit. Based on the relative value of q, qcrit and qopt it also yields four quadrants of distinct withdrawal strategies. Using global hydrogeological and hydroeconomic datasets we map the global occurrence of these four quadrants and provide global estimates of optimal groundwater withdrawal rates and depletion trajectories. For the quadrants with groundwater depletion (q >qcrit) we derive and compare depletion trajectories under competition, optimal control and optimal control including environmental externalities, and assessed globally where the differences between these depletion modes are small, which is known as the Gisser-Sánchez effect. We find that the Gisser-Sánchez effect is globally ubiquitous, but only if environmental externalities are ignored. The inclusion of environmental externalities in optimal control withdrawal result in notably reduced groundwater decline and larger values of social welfare in many of the major depletion areas.

Drought-heatwave events increase water use mainly for domestic and irrigation water use sectors (Cárdenas et al., 2023). Moreover, water quality deterioration caused by human activities is exacerbated by more frequent and longer-lasting extreme hydro-climatic events, such as droughts and heatwaves. These circumstances challenge the supply of water of suitable quality and increase the cross-sectoral competition forclean water.Water use models are useful in estimating responses in water demand and use ‑in terms of consumption and withdrawals‑ of the main water use sectors (i.e., irrigation, livestock, domestic, energy and manufacturing); however, there are few water use models that account for both water quantity and quality dimensions simultaneously. The main objective of our research is to assess the cross-sectoral water deficit due to sectoral competition for limited clean water resources, explicitly considering water quantity and water quality requirements.To address this objective a new sectoral water use model framework has been developed, that evaluates simultaneously water quantity and water quality requirements for the main water use sectors. This globally applicable model framework builds on the PCR-GLOBWB 2 hydrological model (Sutanudjaja et al, 2018) and DynQual v1.0 global surface water quality model (Jones et al, 2023), which simulates surface water temperature, salinity as indicated by total dissolved solids (TDS), organic pollution as indicated by biochemical oxygen demand (BOD), and pathogen pollution as indicated by faecal coliform (FC).Preliminary results show that high salinity (TDS) is the predominant water quality constituent limiting water use for irrigation most of the year; while for the domestic sector it is organic pollution, particularly in regions with limited water treatment capacities. For such sectors, accounting for water quality requirements lead to substantial reductions in surface water withdrawals over the Conterminous United States when compared to results obtained from only water quantity-based models.This modelling framework provides the basis for an integrated water scarcity assessment driven by changes in water quantity and quality under current and future droughts and heatwaves.ReferencesCárdenas B., G.A., Bierkens, M.F.P., van Vliet, M.T.H.: Sectoral water use responses to droughts and heatwaves: analyses from local to global scales for 1990-2019. Environ. Res. Lett. 18 104008. https://doi.org/10.1088/1748-9326/acf82e, 2023.Sutanudjaja, E. H., van Beek, L. P. H., de Jong, S. M., van Geer, F. C., and Bierkens, M. F. P.: Calibrating a large-extent high-resolution coupled groundwater-land surface model using soil moisture and discharge data, Water Resour. https://doi.org/10.5194/gmd-11-2429-2018, 2018.Jones, E. R., Bierkens, M. F. P., Wanders, N., Sutanudjaja, E. H., van Beek, L. P. H., and van Vliet, M. T. H.: DynQual v1.0: a high-resolution global surface water quality model, Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, 2023.

Offshore freshened groundwater reserves have been identified in numerous regions worldwide. These reserves were often deposited during past sea level lowstands and are therefore non-renewable and slowly salinized by infiltrating seawater. However, in some cases these offshore freshened groundwater reserves can be connected to inland groundwater systems and can be recharged by fresh groundwater inflow from the landward direction. It has recently been suggested that these offshore freshened groundwater reserves could provide an additional source of fresh (and brackish) water for coastal communities that often face increasing fresh water stress. The feasibility, both economic and physical, of offshore freshened groundwater extraction is investigated in this study. To assess this feasibility from a physical point of view we built a set of 3D semi-conceptual groundwater flow models using the imod-wq code which allows us to estimate the offshore groundwater salinity development over large time scales (i.e. one glacial-interglacial cycle). The result of these large time scale models can be interpreted as estimations of the current offshore groundwater salinity conditions and thus provide a better picture of the current presence and magnitude of the offshore freshened groundwater resources in the model domain. In the next modelling stress period we introduce a set of pumping wells into the offshore domain and simulate several offshore freshened groundwater extraction scenarios. In such way we can evaluate the time it takes for these offshore freshened groundwater reserves to be fully salinized and exhausted. Additionally, we can also assess any potential negative impacts on the groundwater system in the coastal hinterland such as decreasing groundwater levels and/or increased salinization.In the second part of our study we evaluate the economic feasibility of the offshore freshened groundwater pumping and use as additional fresh water resource for coastal communities. Several coastal areas located in south and south-east Asia (e.g. Pearl River delta) were selected since this region is identified as a region with high possibility and magnitude of offshore freshened groundwater resources. The economic parameters that are taken into account as favourable for offshore freshened groundwater exploration are (i) the overall economic development (e.g. GDP, HDI), (ii) the presence of groundwater pumping and desalination plants inland meaning the technology is already present in the region and (iii) costs of fresh water and groundwater pumping and desalination infrastructure in the region. Our study is only the first step in assessing the feasibility of offshore freshened groundwater exploration and hopefully our approach will be improved and tested in other coastal regions around the world to evaluate the full potential of these still untapped fresh groundwater resources.