Articles | Volume 29, issue 22
https://doi.org/10.5194/hess-29-6499-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-6499-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Nov 2025
Research article |
| 19 Nov 2025
| 19 Nov 2025
Data derived reservoir operations simulated in a global hydrologic model
Department of Physical Geography, Utrecht University, Princetonlaan 8a, Utrecht, the Netherlands
Edwin H. Sutanudjaja
Department of Physical Geography, Utrecht University, Princetonlaan 8a, Utrecht, the Netherlands
Marc Bierkens
Department of Physical Geography, Utrecht University, Princetonlaan 8a, Utrecht, the Netherlands
Deltares, Unit D Subsurface and Groundwater Systems, Utrecht, the Netherlands
Niko Wanders
Department of Physical Geography, Utrecht University, Princetonlaan 8a, Utrecht, the Netherlands
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Marc F. P. Bierkens, Edwin H. Sutanudjaja, and Niko Wanders
Hydrol. Earth Syst. Sci., 25, 5859–5878, https://doi.org/10.5194/hess-25-5859-2021, https://doi.org/10.5194/hess-25-5859-2021, 2021
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We introduce a simple analytical framework that allows us to estimate to what extent large-scale groundwater withdrawal affects groundwater levels and streamflow. It also calculates which part of the groundwater withdrawal comes out of groundwater storage and which part from a reduction in streamflow. Global depletion rates obtained with the framework are compared with estimates from satellites, from global- and continental-scale groundwater models, and from in situ datasets.
Jan L. Gunnink, Hung Van Pham, Gualbert H. P. Oude Essink, and Marc F. P. Bierkens
Earth Syst. Sci. Data, 13, 3297–3319, https://doi.org/10.5194/essd-13-3297-2021, https://doi.org/10.5194/essd-13-3297-2021, 2021
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Camelia-Eliza Telteu, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, Lauren Seaby Andersen, Manolis Grillakis, Simon Newland Gosling, Yusuke Satoh, Oldrich Rakovec, Tobias Stacke, Jinfeng Chang, Niko Wanders, Harsh Lovekumar Shah, Tim Trautmann, Ganquan Mao, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Luis Samaniego, Yoshihide Wada, Vimal Mishra, Junguo Liu, Petra Döll, Fang Zhao, Anne Gädeke, Sam S. Rabin, and Florian Herz
Geosci. Model Dev., 14, 3843–3878, https://doi.org/10.5194/gmd-14-3843-2021, https://doi.org/10.5194/gmd-14-3843-2021, 2021
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We analyse water storage compartments, water flows, and human water use sectors included in 16 global water models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b. We develop a standard writing style for the model equations. We conclude that even though hydrologic processes are often based on similar equations, in the end these equations have been adjusted, or the models have used different values for specific parameters or specific variables.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
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Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
Edward R. Jones, Michelle T. H. van Vliet, Manzoor Qadir, and Marc F. P. Bierkens
Earth Syst. Sci. Data, 13, 237–254, https://doi.org/10.5194/essd-13-237-2021, https://doi.org/10.5194/essd-13-237-2021, 2021
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Continually improving and affordable wastewater management provides opportunities for both pollution reduction and clean water supply augmentation. This study provides a global outlook on the state of domestic and industrial wastewater production, collection, treatment and reuse. Our results can serve as a baseline in evaluating progress towards policy goals (e.g. Sustainable Development Goals) and as input data in large-scale water resource assessments (e.g. water quality modelling).
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
Earth Syst. Dynam., 12, 17–35, https://doi.org/10.5194/esd-12-17-2021, https://doi.org/10.5194/esd-12-17-2021, 2021
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Motivated by the possible influence of rising temperatures, this study synthesises results from observations and climate models to explore trends (1900–2018) in eastern African (EA) drought measures. However, no discernible trends are found in annual soil moisture or precipitation. Positive trends in potential evaporation indicate that for irrigated regions more water is now required to counteract increased evaporation. Precipitation deficit is, however, the most useful indicator of EA drought.
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Short summary
Using machine learning techniques and remotely sensed reservoir data, we develop a workflow to derive reservoir storage bounds. We put these bounds in a global hydrologic model, PCR-GLOBWB 2, and evaluate the difference between generalized operations (the schemes typically in global models) and this data derived method. We find that modelled storage is more accurate in the data derived operations. We also find that generalized operations over estimate storage and can underestimate water gaps.
Using machine learning techniques and remotely sensed reservoir data, we develop a workflow to...
