Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-5029-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-5029-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
27 Oct 2020
Development and technical paper |
| 27 Oct 2020
| 27 Oct 2020
Simulating human impacts on global water resources using VIC-5
Water Systems and Global Change Group, Department of Environmental Sciences, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Wietse H. P. Franssen
Water Systems and Global Change Group, Department of Environmental Sciences, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Michelle T. H. van Vliet
Department of Physical Geography, Utrecht University, P.O. Box 80115, 3508 TC Utrecht, the Netherlands
Bart Nijssen
Computational Hydrology Group, Department of Civil and Environmental Engineering, University of Washington, P.O. Box 352700, 98195-2700, Seattle, USA
Fulco Ludwig
Water Systems and Global Change Group, Department of Environmental Sciences, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Related authors
Barry van Jaarsveld, Niko Wanders, Edwin H. Sutanudjaja, Jannis Hoch, Bram Droppers, Joren Janzing, Rens L. P. H. van Beek, and Marc F. P. Bierkens
EGUsphere, https://doi.org/10.5194/egusphere-2024-1025, https://doi.org/10.5194/egusphere-2024-1025, 2024
Short summary
Short summary
Policy makers use global hydrological models to develop water management strategies and policies. However, if these models provided information at higher resolutions that would be better. We present a first of its kind, truly global hyper-resolution model and show that hyper-resolution brings about better estimates of river discharge and this is especially true for smaller catchments. Our results also suggest future hyper-resolution model need to include more detailed landcover information.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
Short summary
Short summary
Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Hordur Bragi Helgason and Bart Nijssen
Earth Syst. Sci. Data, 16, 2741–2771, https://doi.org/10.5194/essd-16-2741-2024, https://doi.org/10.5194/essd-16-2741-2024, 2024
Short summary
Short summary
LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Nicole Gyakowah Otoo, Edwin H. Sutanudjaja, Michelle T. H. van Vliet, Aafke M. Schipper, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-112, https://doi.org/10.5194/hess-2024-112, 2024
Preprint under review for HESS
Short summary
Short summary
The contribution of groundwater to groundwater dependent ecosystems (GDEs) is declining as a result of an increase in groundwater abstractions and climate change. This may lead to loss of habitat and biodiversity. This proposed framework enables the mapping and understanding of the temporal and spatial dynamics of GDEs on a large scale. The next step is to assess the global impacts of climate change and water use on GDEs' extent and health.
Barry van Jaarsveld, Niko Wanders, Edwin H. Sutanudjaja, Jannis Hoch, Bram Droppers, Joren Janzing, Rens L. P. H. van Beek, and Marc F. P. Bierkens
EGUsphere, https://doi.org/10.5194/egusphere-2024-1025, https://doi.org/10.5194/egusphere-2024-1025, 2024
Short summary
Short summary
Policy makers use global hydrological models to develop water management strategies and policies. However, if these models provided information at higher resolutions that would be better. We present a first of its kind, truly global hyper-resolution model and show that hyper-resolution brings about better estimates of river discharge and this is especially true for smaller catchments. Our results also suggest future hyper-resolution model need to include more detailed landcover information.
Sneha Chevuru, Rens L. P. H. van Beek, Michelle T. H. van Vliet, Jerom P. M. Aerts, and Marc F. P. Bierkens
EGUsphere, https://doi.org/10.5194/egusphere-2024-465, https://doi.org/10.5194/egusphere-2024-465, 2024
Short summary
Short summary
This paper integrates PCR-GLOBWB 2 hydrological model with WOFOST crop growth model to analyze mutual feedbacks between hydrology and crop growth. It quantifies one-way and two-way feedbacks between hydrology and crop growth, revealing patterns in crop yield and irrigation water use. Dynamic interactions enhance understanding of climate variability impacts on food production, highlighting the importance of two-way model coupling for accurate assessments.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
Short summary
Short summary
DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Veit Blauhut, Michael Stoelzle, Lauri Ahopelto, Manuela I. Brunner, Claudia Teutschbein, Doris E. Wendt, Vytautas Akstinas, Sigrid J. Bakke, Lucy J. Barker, Lenka Bartošová, Agrita Briede, Carmelo Cammalleri, Ksenija Cindrić Kalin, Lucia De Stefano, Miriam Fendeková, David C. Finger, Marijke Huysmans, Mirjana Ivanov, Jaak Jaagus, Jiří Jakubínský, Svitlana Krakovska, Gregor Laaha, Monika Lakatos, Kiril Manevski, Mathias Neumann Andersen, Nina Nikolova, Marzena Osuch, Pieter van Oel, Kalina Radeva, Renata J. Romanowicz, Elena Toth, Mirek Trnka, Marko Urošev, Julia Urquijo Reguera, Eric Sauquet, Aleksandra Stevkov, Lena M. Tallaksen, Iryna Trofimova, Anne F. Van Loon, Michelle T. H. van Vliet, Jean-Philippe Vidal, Niko Wanders, Micha Werner, Patrick Willems, and Nenad Živković
Nat. Hazards Earth Syst. Sci., 22, 2201–2217, https://doi.org/10.5194/nhess-22-2201-2022, https://doi.org/10.5194/nhess-22-2201-2022, 2022
Short summary
Short summary
Recent drought events caused enormous damage in Europe. We therefore questioned the existence and effect of current drought management strategies on the actual impacts and how drought is perceived by relevant stakeholders. Over 700 participants from 28 European countries provided insights into drought hazard and impact perception and current management strategies. The study concludes with an urgent need to collectively combat drought risk via a European macro-level drought governance approach.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
Short summary
Short summary
Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Wouter J. Smolenaars, Sanita Dhaubanjar, Muhammad K. Jamil, Arthur Lutz, Walter Immerzeel, Fulco Ludwig, and Hester Biemans
Hydrol. Earth Syst. Sci., 26, 861–883, https://doi.org/10.5194/hess-26-861-2022, https://doi.org/10.5194/hess-26-861-2022, 2022
Short summary
Short summary
The arid plains of the lower Indus Basin rely heavily on the water provided by the mountainous upper Indus. Rapid population growth in the upper Indus is expected to increase the water that is consumed there. This will subsequently reduce the water that is available for the downstream plains, where the population and water demand are also expected to grow. In future, this may aggravate tensions over the division of water between the countries that share the Indus Basin.
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
Short summary
Short summary
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).
Laura E. Queen, Philip W. Mote, David E. Rupp, Oriana Chegwidden, and Bart Nijssen
Hydrol. Earth Syst. Sci., 25, 257–272, https://doi.org/10.5194/hess-25-257-2021, https://doi.org/10.5194/hess-25-257-2021, 2021
Short summary
Short summary
Using a large ensemble of simulated flows throughout the northwestern USA, we compare daily flood statistics in the past (1950–1999) and future (2050–1999) periods and find that nearly all locations will experience an increase in flood magnitudes. The flood season expands significantly in many currently snow-dominant rivers, moving from only spring to both winter and spring. These results, properly extended, may help inform flood risk management and negotiations of the Columbia River Treaty.
Yixin Mao, Wade T. Crow, and Bart Nijssen
Hydrol. Earth Syst. Sci., 24, 615–631, https://doi.org/10.5194/hess-24-615-2020, https://doi.org/10.5194/hess-24-615-2020, 2020
Short summary
Short summary
The new generation of satellite soil moisture observations are used to correct the streamflow in a regional-scale river basin simulated by a mathematical model. The correction is done via both the direct updating of soil moisture and correction of rainfall input. Results show some streamflow improvement, but the magnitude is small. A larger improvement will need future generations of even higher-quality satellite soil moisture data and better process representation in the mathematical model.
John R. Yearsley, Ning Sun, Marisa Baptiste, and Bart Nijssen
Hydrol. Earth Syst. Sci., 23, 4491–4508, https://doi.org/10.5194/hess-23-4491-2019, https://doi.org/10.5194/hess-23-4491-2019, 2019
Short summary
Short summary
This study investigates the impact of dam-induced hydrologic alterations and modification of riparian buffers on stream temperatures and thermal habitat for aquatic species. We enhanced and applied a model system (DHSVM-RBM) that couples a distributed hydrologic model, DHSVM, with the distributed stream temperature model, RBM, in the Farmington River basin in the Connecticut River system, which includes varying types of watershed development (e.g., deforestation and reservoirs).
Andrew R. Bennett, Joseph J. Hamman, and Bart Nijssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-179, https://doi.org/10.5194/gmd-2019-179, 2019
Preprint withdrawn
Short summary
Short summary
MetSim is a software package for simulating meteorologic processes, and aims to be applied in the environmental and Earth sciences. It can simulate processes such as solar and thermal radiation, specific humidity, and vapor pressure across large spatial areas in an efficient manner. This paper describes the software and analyzes it's ability to be used in large simulations. We describe how MetSim can be used and provide details on the various options that are available.
Wouter Greuell, Wietse H. P. Franssen, and Ronald W. A. Hutjes
Hydrol. Earth Syst. Sci., 23, 371–391, https://doi.org/10.5194/hess-23-371-2019, https://doi.org/10.5194/hess-23-371-2019, 2019
Short summary
Short summary
This paper explains why forecasts of river flow in Europe for a time between 1 and 7 months have skill. The forecasts were produced with a water model. The model reacts to forecasts of weather variables like precipitation, which tend to have little skill and hence hardly contribute to the skill in the forecasts of river flow. The paper shows when and where these forecasts have skill; this is mostly due to knowledge of the amount of water in the soil at the time the forecasts are made.
Michael A. Brunke, John J. Cassano, Nicholas Dawson, Alice K. DuVivier, William J. Gutowski Jr., Joseph Hamman, Wieslaw Maslowski, Bart Nijssen, J. E. Jack Reeves Eyre, José C. Renteria, Andrew Roberts, and Xubin Zeng
Geosci. Model Dev., 11, 4817–4841, https://doi.org/10.5194/gmd-11-4817-2018, https://doi.org/10.5194/gmd-11-4817-2018, 2018
Short summary
Short summary
The Regional Arctic System Model version 1 (RASM1) was recently developed for high-resolution simulation of the coupled atmosphere–ocean–sea ice–land system in the Arctic. Its simulation of the atmosphere–land–ocean–sea ice interface is evaluated by using the spread in recent reanalyses and a global Earth system model as baselines. Such comparisons reveal that RASM1 simulates precipitation well and improves the simulation of surface fluxes over sea ice.
Joseph J. Hamman, Bart Nijssen, Theodore J. Bohn, Diana R. Gergel, and Yixin Mao
Geosci. Model Dev., 11, 3481–3496, https://doi.org/10.5194/gmd-11-3481-2018, https://doi.org/10.5194/gmd-11-3481-2018, 2018
Short summary
Short summary
Variable Infiltration Capacity (VIC) is a widely used hydrologic model. This paper documents the development of VIC version 5, which includes a reconfiguration of the model source code to support a wider range of modeling applications. It also represents a significant step forward for the VIC user community in terms of support for a range of modeling applications, reproducibility, and scientific robustness.
Wouter Greuell, Wietse H. P. Franssen, Hester Biemans, and Ronald W. A. Hutjes
Hydrol. Earth Syst. Sci., 22, 3453–3472, https://doi.org/10.5194/hess-22-3453-2018, https://doi.org/10.5194/hess-22-3453-2018, 2018
Short summary
Short summary
This paper presents the development and skill analysis of WUSHP, a system that makes hydrological forecasts for time horizons up to 7 months. Hot spots of significant skill in river discharge were identified in Fennoscandia (from January to October), the southern part of the Mediterranean (from June to August), Poland, north Germany, Romania and Bulgaria (mainly from November to January), and west France (from December to May). Some skill is left at the end of the forecasts.
Dung Duc Tran, Gerardo van Halsema, Petra J. G. J. Hellegers, Long Phi Hoang, Tho Quang Tran, Matti Kummu, and Fulco Ludwig
Hydrol. Earth Syst. Sci., 22, 1875–1896, https://doi.org/10.5194/hess-22-1875-2018, https://doi.org/10.5194/hess-22-1875-2018, 2018
Short summary
Short summary
We modeled hydrological changes under impacts of large-scale dike constructions for intensive rice production in the floodplain of the Vietnamese Mekong Delta. Four scenarios show a significant increase in peak water levels in the upstream rivers, but very few water level changes are found downstream. Water balance calculations show where the floodwater goes under four dike construction scenarios. Its impacts on the tidal areas need to be clarified in the future with a 3-D hydraulic model.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
Short summary
Short summary
This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Abraham Endalamaw, W. Robert Bolton, Jessica M. Young-Robertson, Don Morton, Larry Hinzman, and Bart Nijssen
Hydrol. Earth Syst. Sci., 21, 4663–4680, https://doi.org/10.5194/hess-21-4663-2017, https://doi.org/10.5194/hess-21-4663-2017, 2017
Short summary
Short summary
This study applies plot-scale and hill-slope knowledge to a process-based mesoscale model to improve the skill of distributed hydrological models to simulate the spatially and basin-integrated hydrological processes of complex ecosystems in the sub-arctic boreal forest. We developed a sub-grid parameterization method to parameterize the surface heterogeneity of interior Alaskan discontinuous permafrost watersheds.
Pablo A. Mendoza, Andrew W. Wood, Elizabeth Clark, Eric Rothwell, Martyn P. Clark, Bart Nijssen, Levi D. Brekke, and Jeffrey R. Arnold
Hydrol. Earth Syst. Sci., 21, 3915–3935, https://doi.org/10.5194/hess-21-3915-2017, https://doi.org/10.5194/hess-21-3915-2017, 2017
Short summary
Short summary
Water supply forecasts are critical to support water resources operations and planning. The skill of such forecasts depends on our knowledge of (i) future meteorological conditions and (ii) the amount of water stored in a basin. We address this problem by testing several approaches that make use of these sources of predictability, either separately or in a combined fashion. The main goal is to understand the marginal benefits of both information and methodological complexity in forecast skill.
Long Phi Hoang, Hannu Lauri, Matti Kummu, Jorma Koponen, Michelle T. H. van Vliet, Iwan Supit, Rik Leemans, Pavel Kabat, and Fulco Ludwig
Hydrol. Earth Syst. Sci., 20, 3027–3041, https://doi.org/10.5194/hess-20-3027-2016, https://doi.org/10.5194/hess-20-3027-2016, 2016
Short summary
Short summary
We modelled hydrological changes under climate change in the Mekong River, focusing on extreme events. The scenario ensemble shows an intensification of the hydrological cycle under climate change. Annual river flow increases between 5 and 16 % depending on locations. Extreme high flows increase substantially in both magnitude and frequency, posing threats to flood safety in the basin. Extreme low-flow events are projected to reduce as a result of increased river flow during the dry season.
Naoki Mizukami, Martyn P. Clark, Kevin Sampson, Bart Nijssen, Yixin Mao, Hilary McMillan, Roland J. Viger, Steve L. Markstrom, Lauren E. Hay, Ross Woods, Jeffrey R. Arnold, and Levi D. Brekke
Geosci. Model Dev., 9, 2223–2238, https://doi.org/10.5194/gmd-9-2223-2016, https://doi.org/10.5194/gmd-9-2223-2016, 2016
Short summary
Short summary
mizuRoute version 1 is a stand-alone runoff routing tool that post-processes runoff outputs from any distributed hydrologic models to produce streamflow estimates in large-scale river network. mizuRoute is flexible to river network representation and includes two different river routing schemes. This paper demonstrates mizuRoute's capability of multi-decadal streamflow estimations in the river networks over the entire contiguous Unites States, which contains over 54 000 river segments.
W. Greuell, J. C. M. Andersson, C. Donnelly, L. Feyen, D. Gerten, F. Ludwig, G. Pisacane, P. Roudier, and S. Schaphoff
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-10289-2015, https://doi.org/10.5194/hessd-12-10289-2015, 2015
Revised manuscript has not been submitted
Short summary
Short summary
The main aims of this paper are the evaluation of five large-scale hydrological models across Europe and the assessment of the suitability of the models for making projections under climate change. While we found large inter-model differences in biases, the skill to simulate interannual variability in discharge did not differ much between the models. Assuming that the skill of a model to simulate interannual variability provides a measure for the model’s ability to make projections under climate
A. V. Pastor, F. Ludwig, H. Biemans, H. Hoff, and P. Kabat
Hydrol. Earth Syst. Sci., 18, 5041–5059, https://doi.org/10.5194/hess-18-5041-2014, https://doi.org/10.5194/hess-18-5041-2014, 2014
Short summary
Short summary
Freshwater ecosystems encompass the most threatened species on earth. Environmental flow requirements need to be addressed globally to provide sufficient water for humans and nature. We present a comparison of five environmental flow methods validated with locally calculated EFRs. We showed that methods based on monthly average flow such as the variable monthly flow method are more reliable than methods based on annual thresholds. A range of EFRs was calculated for large river basins.
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
S. Hagemann, C. Chen, D. B. Clark, S. Folwell, S. N. Gosling, I. Haddeland, N. Hanasaki, J. Heinke, F. Ludwig, F. Voss, and A. J. Wiltshire
Earth Syst. Dynam., 4, 129–144, https://doi.org/10.5194/esd-4-129-2013, https://doi.org/10.5194/esd-4-129-2013, 2013
Related subject area
Hydrology
Generalised drought index: a novel multi-scale daily approach for drought assessment
Development and performance of a high-resolution surface wave and storm surge forecast model: application to a large lake
Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models (δHBV-globe1.0-hydroDL)
PyEt v1.3.1: a Python package for the estimation of potential evapotranspiration
Prediction of hysteretic matric potential dynamics using artificial intelligence: application of autoencoder neural networks
Regionalization in global hydrological models and its impact on runoff simulations: a case study using WaterGAP3 (v 1.0.0)
STORM v.2: A simple, stochastic rainfall model for exploring the impacts of climate and climate change at and near the land surface in gauged watersheds
Fluvial flood inundation and socio-economic impact model based on open data
RoGeR v3.0.5 – a process-based hydrological toolbox model in Python
Coupling a large-scale glacier and hydrological model (OGGM v1.5.3 and CWatM V1.08) – towards an improved representation of mountain water resources in global assessments
An open-source refactoring of the Canadian Small Lakes Model for estimates of evaporation from medium-sized reservoirs
EvalHyd v0.1.2: a polyglot tool for the evaluation of deterministic and probabilistic streamflow predictions
Modelling water quantity and quality for integrated water cycle management with the Water Systems Integrated Modelling framework (WSIMOD) software
HGS-PDAF (version 1.0): a modular data assimilation framework for an integrated surface and subsurface hydrological model
Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications
Reservoir Assessment Tool version 3.0: a scalable and user-friendly software platform to mobilize the global water management community
HydroFATE (v1): a high-resolution contaminant fate model for the global river system
Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2
GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications
GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers
mesas.py v1.0: a flexible Python package for modeling solute transport and transit times using StorAge Selection functions
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model
Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)
The global water resources and use model WaterGAP v2.2e: description and evaluation of modifications and new features
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information
Representing the impact of Rhizophora mangroves on flow in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification
Enhancing the representation of water management in global hydrological models
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
Simulation of crop yield using the global hydrological model H08 (crp.v1)
How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
GEB v0.1: a large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe
Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python
Basin-scale gyres and mesoscale eddies in large lakes: a novel procedure for their detection and characterization, assessed in Lake Geneva
João António Martins Careto, Rita Margarida Cardoso, Ana Russo, Daniela Catarina André Lima, and Pedro Miguel Matos Soares
Geosci. Model Dev., 17, 8115–8139, https://doi.org/10.5194/gmd-17-8115-2024, https://doi.org/10.5194/gmd-17-8115-2024, 2024
Short summary
Short summary
This study proposes a new daily drought index, the generalised drought index (GDI). The GDI not only identifies the same events as established indices but is also capable of improving their results. The index is empirically based and easy to compute, not requiring fitting the data to a probability distribution. The GDI can detect flash droughts and longer-term events, making it a versatile tool for drought monitoring.
Laura L. Swatridge, Ryan P. Mulligan, Leon Boegman, and Shiliang Shan
Geosci. Model Dev., 17, 7751–7766, https://doi.org/10.5194/gmd-17-7751-2024, https://doi.org/10.5194/gmd-17-7751-2024, 2024
Short summary
Short summary
We develop an operational forecast system, Coastlines-LO, that can simulate water levels and surface waves in Lake Ontario driven by forecasts of wind speeds and pressure fields from an atmospheric model. The model has relatively low computational requirements, and results compare well with near-real-time observations, as well as with results from other existing forecast systems. Results show that with shorter forecast lengths, storm surge and wave predictions can improve in accuracy.
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 17, 7181–7198, https://doi.org/10.5194/gmd-17-7181-2024, https://doi.org/10.5194/gmd-17-7181-2024, 2024
Short summary
Short summary
Accurate hydrologic modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall–runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional modeling approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
Matevž Vremec, Raoul A. Collenteur, and Steffen Birk
Geosci. Model Dev., 17, 7083–7103, https://doi.org/10.5194/gmd-17-7083-2024, https://doi.org/10.5194/gmd-17-7083-2024, 2024
Short summary
Short summary
Geoscientists commonly use various potential evapotranpiration (PET) formulas for environmental studies, which can be prone to errors and sensitive to climate change. PyEt, a tested and open-source Python package, simplifies the application of 20 PET methods for both time series and gridded data, ensuring accurate and consistent PET estimations suitable for a wide range of environmental applications.
Nedal Aqel, Lea Reusser, Stephan Margreth, Andrea Carminati, and Peter Lehmann
Geosci. Model Dev., 17, 6949–6966, https://doi.org/10.5194/gmd-17-6949-2024, https://doi.org/10.5194/gmd-17-6949-2024, 2024
Short summary
Short summary
The soil water potential (SWP) determines various soil water processes. Since remote sensing techniques cannot measure it directly, it is often deduced from volumetric water content (VWC) information. However, under dynamic field conditions, the relationship between SWP and VWC is highly ambiguous due to different factors that cannot be modeled with the classical approach. Applying a deep neural network with an autoencoder enables the prediction of the dynamic SWP.
Jenny Kupzig, Nina Kupzig, and Martina Flörke
Geosci. Model Dev., 17, 6819–6846, https://doi.org/10.5194/gmd-17-6819-2024, https://doi.org/10.5194/gmd-17-6819-2024, 2024
Short summary
Short summary
Valid simulation results from global hydrological models (GHMs) are essential, e.g., to studying climate change impacts. Adapting GHMs to ungauged basins requires regionalization, enabling valid simulations. In this study, we highlight the impact of regionalization of GHMs on runoff simulations using an ensemble of regionalization methods for WaterGAP3. We have found that regionalization leads to temporally and spatially varying uncertainty, potentially reaching up to inter-model differences.
Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev., 17, 5387–5412, https://doi.org/10.5194/gmd-17-5387-2024, https://doi.org/10.5194/gmd-17-5387-2024, 2024
Short summary
Short summary
STORM v.2 (short for STOchastic Rainfall Model version 2.0) is an open-source and user-friendly modelling framework for simulating rainfall fields over a basin. It also allows simulating the impact of plausible climate change either on the total seasonal rainfall or the storm’s maximum intensity.
Lukas Riedel, Thomas Röösli, Thomas Vogt, and David N. Bresch
Geosci. Model Dev., 17, 5291–5308, https://doi.org/10.5194/gmd-17-5291-2024, https://doi.org/10.5194/gmd-17-5291-2024, 2024
Short summary
Short summary
River floods are among the most devastating natural hazards. We propose a flood model with a statistical approach based on openly available data. The model is integrated in a framework for estimating impacts of physical hazards. Although the model only agrees moderately with satellite-detected flood extents, we show that it can be used for forecasting the magnitude of flood events in terms of socio-economic impacts and for comparing these with past events.
Robin Schwemmle, Hannes Leistert, Andreas Steinbrich, and Markus Weiler
Geosci. Model Dev., 17, 5249–5262, https://doi.org/10.5194/gmd-17-5249-2024, https://doi.org/10.5194/gmd-17-5249-2024, 2024
Short summary
Short summary
The new process-based hydrological toolbox model, RoGeR (https://roger.readthedocs.io/), can be used to estimate the components of the hydrological cycle and the related travel times of pollutants through parts of the hydrological cycle. These estimations may contribute to effective water resources management. This paper presents the toolbox concept and provides a simple example of providing estimations to water resources management.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
Short summary
Short summary
This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
M. Graham Clark and Sean K. Carey
Geosci. Model Dev., 17, 4911–4922, https://doi.org/10.5194/gmd-17-4911-2024, https://doi.org/10.5194/gmd-17-4911-2024, 2024
Short summary
Short summary
This paper provides validation of the Canadian Small Lakes Model (CSLM) for estimating evaporation rates from reservoirs and a refactoring of the original FORTRAN code into MATLAB and Python, which are now stored in GitHub repositories. Here we provide direct observations of the surface energy exchange obtained with an eddy covariance system to validate the CSLM. There was good agreement between observations and estimations except under specific atmospheric conditions when evaporation is low.
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
Short summary
Short summary
The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Barnaby Dobson, Leyang Liu, and Ana Mijic
Geosci. Model Dev., 17, 4495–4513, https://doi.org/10.5194/gmd-17-4495-2024, https://doi.org/10.5194/gmd-17-4495-2024, 2024
Short summary
Short summary
Water management is challenging when models don't capture the entire water cycle. We propose that using integrated models facilitates management and improves understanding. We introduce a software tool designed for this task. We discuss its foundation, how it simulates water system components and their interactions, and its customisation. We provide a flexible way to represent water systems, and we hope it will inspire more research and practical applications for sustainable water management.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev., 17, 3559–3578, https://doi.org/10.5194/gmd-17-3559-2024, https://doi.org/10.5194/gmd-17-3559-2024, 2024
Short summary
Short summary
We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model; its large selection of different assimilation algorithms; and its modularity with respect to the combination of different types of observations, states and parameters.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
Short summary
Short summary
We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
Short summary
Short summary
The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
Geosci. Model Dev., 17, 2877–2899, https://doi.org/10.5194/gmd-17-2877-2024, https://doi.org/10.5194/gmd-17-2877-2024, 2024
Short summary
Short summary
Treated and untreated wastewaters are sources of contaminants of emerging concern. HydroFATE, a new global model, estimates their concentrations in surface waters, identifying streams that are most at risk and guiding monitoring/mitigation efforts to safeguard aquatic ecosystems and human health. Model predictions were validated against field measurements of the antibiotic sulfamethoxazole, with predicted concentrations exceeding ecological thresholds in more than 400 000 km of rivers worldwide.
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024, https://doi.org/10.5194/gmd-17-2141-2024, 2024
Short summary
Short summary
We show a new irrigation scheme included in the ORCHIDEE land surface model. The new irrigation scheme restrains irrigation due to water shortage, includes water adduction, and represents environmental limits and facilities to access water, due to representing infrastructure in a simple way. Our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, even if there are difficulties due to shortcomings and limited information.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
Short summary
Short summary
Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
Short summary
Short summary
We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024, https://doi.org/10.5194/gmd-17-477-2024, 2024
Short summary
Short summary
Over the last 10 years, scientists have developed StorAge Selection: a new way of modeling how material is transported through complex systems. Here, we present some new, easy-to-use, flexible, and very accurate code for implementing this method. We show that, in cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other codes to the right answer in an important way: it conserves mass.
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
Short summary
Short summary
Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
Short summary
Short summary
This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
Short summary
Short summary
We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Hannes Müller Schmied, Tim Trautmann, Sebastian Ackermann, Denise Cáceres, Martina Flörke, Helena Gerdener, Ellen Kynast, Thedini Asali Peiris, Leonie Schiebener, Maike Schumacher, and Petra Döll
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-213, https://doi.org/10.5194/gmd-2023-213, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Assessing water availability and water use at the global scale is challenging but essential for a range of purposes. We describe the newest version of the global hydrological model WaterGAP which has been used for numerous water resources assessments since 1996. We show the effects of new model features and model evaluations against observed streamflow and water storage anomalies as well as water abstractions statistics. The publically available model output for several variants is described.
Daniel Boateng and Sebastian G. Mutz
Geosci. Model Dev., 16, 6479–6514, https://doi.org/10.5194/gmd-16-6479-2023, https://doi.org/10.5194/gmd-16-6479-2023, 2023
Short summary
Short summary
We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
Short summary
Short summary
Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
Short summary
Short summary
Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
Short summary
Short summary
Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
Short summary
Short summary
NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
Short summary
Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
Short summary
Short summary
Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
Short summary
Short summary
DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
Short summary
Short summary
Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Zhipin Ai and Naota Hanasaki
Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, https://doi.org/10.5194/gmd-16-3275-2023, 2023
Short summary
Short summary
Simultaneously simulating food production and the requirements and availability of water resources in a spatially explicit manner within a single framework remains challenging on a global scale. Here, we successfully enhanced the global hydrological model H08 that considers human water use and management to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. Our improved model will be beneficial for advancing global food–water nexus studies in the future.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev., 16, 3137–3163, https://doi.org/10.5194/gmd-16-3137-2023, https://doi.org/10.5194/gmd-16-3137-2023, 2023
Short summary
Short summary
Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows us to select the most influential input parameters, but it has to be adapted to spatial modelling. This study will identify relevant methods that can be transposed to any hydrological and water quality model and improve the fate of pesticide knowledge.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
Short summary
Short summary
In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
Jens A. de Bruijn, Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide Wada, and Jeroen C. J. H. Aerts
Geosci. Model Dev., 16, 2437–2454, https://doi.org/10.5194/gmd-16-2437-2023, https://doi.org/10.5194/gmd-16-2437-2023, 2023
Short summary
Short summary
We present a computer simulation model of the hydrological system and human system, which can simulate the behaviour of individual farmers and their interactions with the water system at basin scale to assess how the systems have evolved and are projected to evolve in the future. For example, we can simulate the effect of subsidies provided on investment in adaptation measures and subsequent effects in the hydrological system, such as a lowering of the groundwater table or reservoir level.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
Short summary
Short summary
During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
Short summary
Short summary
It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
Short summary
Short summary
Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
Short summary
Short summary
This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
Short summary
Short summary
Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
Short summary
Short summary
Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
Short summary
Short summary
Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
Short summary
Short summary
A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
Short summary
Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
Shuqi Lin, Donald C. Pierson, and Jorrit P. Mesman
Geosci. Model Dev., 16, 35–46, https://doi.org/10.5194/gmd-16-35-2023, https://doi.org/10.5194/gmd-16-35-2023, 2023
Short summary
Short summary
The risks brought by the proliferation of algal blooms motivate the improvement of bloom forecasting tools, but algal blooms are complexly controlled and difficult to predict. Given rapid growth of monitoring data and advances in computation, machine learning offers an alternative prediction methodology. This study tested various machine learning workflows in a dimictic mesotrophic lake and gave promising predictions of the seasonal variations and the timing of algal blooms.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
Short summary
Short summary
A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Seyed Mahmood Hamze-Ziabari, Ulrich Lemmin, Frédéric Soulignac, Mehrshad Foroughan, and David Andrew Barry
Geosci. Model Dev., 15, 8785–8807, https://doi.org/10.5194/gmd-15-8785-2022, https://doi.org/10.5194/gmd-15-8785-2022, 2022
Short summary
Short summary
A procedure combining numerical simulations, remote sensing, and statistical analyses is developed to detect large-scale current systems in large lakes. By applying this novel procedure in Lake Geneva, strategies for detailed transect field studies of the gyres and eddies were developed. Unambiguous field evidence of 3D gyre/eddy structures in full agreement with predictions confirmed the robustness of the proposed procedure.
Cited articles
Abdulla, F. A., Lettenmaier, D. P., Wood, E. F., and Smith, J. A.:
Application of a macroscale hydrologic model to estimate the water balance of the Arkansas Red River basin,
J. Geophys. Res.-Atmos.,
101, 7449–7459, https://doi.org/10.1029/95jd02416, 1996.
Alcamo, J., Döll, P., Kaspar, F., and Siebert, S.:
Global change and global scenarios of water use and availability: an application of WaterGAP1.0, Center for environmental systems research,
University of Kassel, Kassel, Germany, 96, 1997.
Alcamo, J., Döll, P., Henrichs, T., Kaspar, F., Lehner, B., Rosch, T., and Siebert, S.:
Development and testing of the WaterGAP 2 global model of water use and availability,
Hydrolog. Sci. J.,
48, 317–337, https://doi.org/10.1623/hysj.48.3.317.45290, 2003.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.:
Crop Evapotranspiration – Guidelines for computing crop water requirements,
Food and Agricultural Organisation, Rome, Italy, 326, 1998.
Andreadis, K. M., Storck, P., and Lettenmaier, D. P.:
Modeling snow accumulation and ablation processes in forested environments,
Water Resour. Res.,
45, W05429, https://doi.org/10.1029/2008wr007042, 2009.
Arthington, A. H., Bhaduri, A., Bunn, S. E., Jackson, S. E., Tharme, R. E., Tickner, D., Young, B., Acreman, M., Baker, N., Capon, S., Horne, A. C., Kendy, E., McClain, M. E., Poff, N. L., Richter, B. D., and Ward, S.: The Brisbane Declaration and Global Action Agenda on Environmental Flows, Front. Environ. Sci., 6, 45, https://doi.org/10.3389/fenvs.2018.00045, 2018.
Babel, M. S., Das Gupta, A., and Pradhan, P.:
A multivariate econometric approach for domestic water demand modeling: An application to Kathmandu, Nepal,
Water Resour. Manag.,
21, 573–589, https://doi.org/10.1007/s11269-006-9030-6, 2007.
Bazilian, M., Rogner, H., Howells, M., Hermann, S., Arent, D., Gielen, D., Steduto, P., Mueller, A., Komor, P., Tol, R. S. J., and Yumkella, K. K.:
Considering the energy, water and food nexus: Towards an integrated modelling approach,
Energ. Policy,
39, 7896–7906, https://doi.org/10.1016/j.enpol.2011.09.039, 2011.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Biemans, H., Haddeland, I., Kabat, P., Ludwig, F., Hutjes, R. W. A., Heinke, J., von Bloh, W., and Gerten, D.:
Impact of reservoirs on river discharge and irrigation water supply during the 20th century,
Water Resour. Res.,
47, W03509, https://doi.org/10.1029/2009wr008929, 2011.
Bijl, D. L., Bogaart, P. W., Dekker, S. C., and van Vuuren, D. P.:
Unpacking the nexus: Different spatial scales for water, food and energy,
Global Environ. Chang.,
48, 22–31, https://doi.org/10.1016/j.gloenvcha.2017.11.005, 2018.
Bolt, J., Inklaar, R., de Jong, H., and van Zanden, J. L.:
Rebasing “Maddison”: New income comparisons and the shape of long-run economic developments,
University of Groningen, Groningen, the Netherlands, 1–67, 2018.
Bondeau, A., Smith, P. C., Zaehle, S., Schaphoff, S., Lucht, W., Cramer, W., Gerten, D., Lotze-Campen, H., Muller, C., Reichstein, M., and Smith, B.:
Modelling the role of agriculture for the 20th century global terrestrial carbon balance,
Glob. Change Biol.,
13, 679–706, https://doi.org/10.1111/j.1365-2486.2006.01305.x, 2007.
Bowling, L. C., Pomeroy, J. W., and Lettenmaier, D. P.:
Parameterization of blowing-snow sublimation in a macroscale hydrology model,
J. Hydrometeorol.,
5, 745–762, https://doi.org/10.1175/1525-7541(2004)005<0745:Pobsia>2.0.Co;2, 2004.
Brooks, R. H. and Corey, A. T.:
Hydraulic properties of porous media,
Colorado State University, Fort Collins, Colorado, 27 pp., 1964.
Brouwer, C., Prins, K., and Heibloem, M.:
Irrigation water management: Irrigation scheduling,
Food and Agricultural Organisation, Rome, Italy, 1989.
Calder, I. R.:
Hydrologic effects of land use change,
in: Handbook of hydrology,
edited by: Maidment, D. R.,
McGraw-Hill, New York, 471–515, 1993.
Carpenter, S. R., Stanley, E. H., and Vander Zanden, M. J.:
State of the World's Freshwater Ecosystems: Physical, Chemical, and Biological Changes,
Annu. Rev. Env. Resour.,
36, 75–99, https://doi.org/10.1146/annurev-environ-021810-094524, 2011.
Carter, A. J. and Scholes, R. J.:
Generating a global database of soil properties,
IGBP Data and Information Services, Potsdam, Germany, 10 pp., 1999.
Chateau, J., Dellink, R., and Lanzi, E.:
An overview of the OECD ENV-linkages model,
Organisation for Economic Co-operation and Development, 1–29, 2014.
Chegwidden, O. S., Nijssen, B., Rupp, D. E., Arnold, J. R., Clark, M. P., Hamman, J. J., Kao, S.-C., Mao, Y., Mizukami, N., Mote, P. W., Pan, M., Pytlak, E., and Xiao, M.:
How Do Modeling Decisions Affect the Spread Among Hydrologic Climate Change Projections? Exploring a Large Ensemble of Simulations Across a Diversity of Hydroclimates,
Earths Future,
7, 623–637, https://doi.org/10.1029/2018ef001047, 2019.
Cherkauer, K. A. and Lettenmaier, D. P.:
Hydrologic effects of frozen soils in the upper Mississippi River basin,
J. Geophys. Res.-Atmos.,
104, 19599–19610, https://doi.org/10.1029/1999jd900337, 1999.
Cherkauer, K. A. and Lettenmaier, D. P.:
Simulation of spatial variability in snow and frozen soil,
J. Geophys. Res.-Atmos.,
108, 8858, https://doi.org/10.1029/2003jd003575, 2003.
Connor, R.:
Water for a sustainable world, United Nations Educational,
Scientific and Cultural Organisation, Paris, France, 122 pp., 2015.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A
Statistical Exploration of the Relationships of Soil-Moisture Characteristics to the Physical-Properties of Soils,
Water Resour. Res.,
20, 682–690, https://doi.org/10.1029/WR020i006p00682, 1984.
Deardorff, J. W.:
Efficient Prediction of Ground Surface-Temperature and Moisture, with Inclusion of a Layer of Vegetation,
J. Geophys. Res.-Oceans,
83, 1889–1903, https://doi.org/10.1029/JC083iC04p01889, 1978.
de Graaf, I. E. M., van Beek, R. L. P. H., Gleeson, T., Moosdorf, N., Schmitz, O., Sutanudjaja, E. H., and Bierkens, M. F. P.:
A global-scale two-layer transient groundwater model: Development and application to groundwater depletion,
Adv. Water Resour.,
102, 53–67, https://doi.org/10.1016/j.advwatres.2017.01.011, 2017.
Döll, P., Fiedler, K., and Zhang, J.: Global-scale analysis of river flow alterations due to water withdrawals and reservoirs, Hydrol. Earth Syst. Sci., 13, 2413–2432, https://doi.org/10.5194/hess-13-2413-2009, 2009.
Döll, P., Hoffmann-Dobrev, H., Portmann, F. T., Siebert, S., Eicker, A., Rodell, M., Strassberg, G., and Scanlon, B. R.:
Impact of water withdrawals from groundwater and surface water on continental water storage variations,
J. Geodyn.,
59–60, 143–156, https://doi.org/10.1016/j.jog.2011.05.001, 2012.
Döll, P., Müller Schmied, H., Schuh, C., Portmann, F. T., and Eicker, A.:
Global-scale assessment of groundwater depletion and related groundwater abstractions: Combining hydrological modeling with information from well observations and GRACE satellites,
Water Resour. Res.,
50, 5698–5720, https://doi.org/10.1002/2014wr015595, 2014.
Döll, P., Douville, H., Guntner, A., Muller Schmied, H., and Wada, Y.:
Modelling Freshwater Resources at the Global Scale: Challenges and Prospects,
Surv. Geophys.,
37, 195–221, https://doi.org/10.1007/s10712-015-9343-1, 2016.
Droppers, B.: BramDr/VIC_support: Support for VIC-WUR version 2.1.0 (Version VIC-WUR.2.1.0), Zenodo, https://doi.org/10.5281/zenodo.3934363, 2020.
Droppers, B., Franssen, W. H. P., van Vliet, M. H. T., Nijssen, B., and Ludwig, F.: BramDr/VIC: VIC-WUR version 2.1.0 (Version VIC-WUR.2.1.0), Zenodo, https://doi.org/10.5281/zenodo.3934325, 2020.
Ducoudre, N. I., Laval, K., and Perrier, A.:
Sechiba, a New Set of Parameterizations of the Hydrologic Exchanges at the Land Atmosphere Interface within the Lmd Atmospheric General-Circulation Model,
J. Climate,
6, 248–273, https://doi.org/10.1175/1520-0442(1993)006<0248:Sansop>2.0.Co;2, 1993.
EC: EUROSTAT, European Commission, available at: https://ec.europa.eu/eurostat, last access: June 2019.
EIA: EIA,
U.S. Energy Information Administration, available at: https://www.eia.gov (last access: June 2019), 2013.
Famiglietti, J. S.:
The global groundwater crisis,
Nat. Clim. Change,
4, 945–948, https://doi.org/10.1038/nclimate2425, 2014.
FAO:
AQUASTAT,
Food and Agricultural Organisation, available at: http://www.fao.org/aquastat (last access: June 2019), 2016.
Feenstra, R. C., Inklaar, R., and Timmer, M. P.:
The Next Generation of the Penn World Table,
Am. Econ. Rev.,
105, 3150–3182, https://doi.org/10.1257/aer.20130954, 2015.
Flörke, M. and Alcamo, J.:
European outlook on water use,
Centre for Environmental Systems Research, Kassel, 86 pp., 2004.
Flörke, M., Kynast, E., Barlund, I., Eisner, S., Wimmer, F., and Alcamo, J.:
Domestic and industrial water uses of the past 60 years as a mirror of socio-economic development: A global simulation study,
Global Environ. Chang.,
23, 144–156, https://doi.org/10.1016/j.gloenvcha.2012.10.018, 2013.
Franchini, M. and Pacciani, M.:
Comparative-Analysis of Several Conceptual Rainfall Runoff Models,
J. Hydrol.,
122, 161–219, https://doi.org/10.1016/0022-1694(91)90178-K, 1991.
Frenken, K. and Gillet, V.:
Irrigation water requirement and water withdrawal by country,
Food and Agricultural Organisation, Rome, Italy, 264 pp., 2012.
Gerten, D., Hoff, H., Rockstrom, J., Jagermeyr, J., Kummu, M., and Pastor, A. V.:
Towards a revised planetary boundary for consumptive freshwater use: role of environmental flow requirements,
Curr. Opin. Env. Sust.,
5, 551–558, https://doi.org/10.1016/j.cosust.2013.11.001, 2013.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S. O., Wint, G. R. W., and Robinson, T. P.:
Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010,
Sci. Data,
5, 180227, https://doi.org/10.1038/sdata.2018.227, 2018.
Gleeson, T. and Richter, B.:
How much groundwater can we pump and protect environmental flows through time? Presumptive standards for conjunctive management of aquifers and rivers,
River Res. Appl.,
34, 83–92, https://doi.org/10.1002/rra.3185, 2018.
Gleick, P. H., Cooley, H., Katz, D., Lee, E., Morrison, J., Meena, P., Samulon, A., and Wolff, G. H.:
The world's water 2006–2007: The biennial report on freshwater resources,
Island Press, Washington, 392 pp., 2013.
Goldstein, R. and Smith, W.:
U.S. water consumption for power production – the next half century,
Electric Power Research Institute, California, USA, 57, 2002.
GRDC:
GRDC,
The Global Runoff Data Centre, available at: https://www.bafg.de/GRDC (last access: March 2019), 2003.
Grill, G., Lehner, B., Thieme, M., Geenen, B., Tickner, D., Antonelli, F., Babu, S., Borrelli, P., Cheng, L., Crochetiere, H., Macedo, H. E., Filgueiras, R., Goichot, M., Higgins, J., Hogan, Z., Lip, B., McClain, M. E., Meng, J., Mulligan, M., Nilsson, C., Olden, J. D., Opperman, J. J., Petry, P., Liermann, C. R., Saenz, L., Salinas-Rodriguez, S., Schelle, P., Schmitt, R. J. P., Snider, J., Tan, F., Tockner, K., Valdujo, P. H., van Soesbergen, A., and Zarfl, C.:
Mapping the world's free-flowing rivers,
Nature,
569, 215–221, https://doi.org/10.1038/s41586-019-1111-9, 2019.
Grobicki, A., Huidobro, P., Galloni, S., Asano, T., and Delgau, K. F.:
Water, a shared responsibility (chapter 8),
United Nations Educational, Scientific and Cultural Organisation, Paris, France, 276–303, 2005.
Haddeland, I., Lettenmaier, D. P., and Skaugen, T.:
Effects of irrigation on the water and energy balances of the Colorado and Mekong river basins,
J. Hydrol.,
324, 210–223, https://doi.org/10.1016/j.jhydrol.2005.09.028, 2006a.
Haddeland, I., Skaugen, T., and Lettenmaier, D. P.:
Anthropogenic impacts on continental surface water fluxes,
Geophys. Res. Lett.,
33, L08406, https://doi.org/10.1029/2006gl026047, 2006b.
Hagemann, S. and Gates, L. D.:
Validation of the hydrological cycle of ECMWF and NCEP reanalyses using the MPI hydrological discharge model,
J. Geophys. Res.-Atmos.,
106, 1503–1510, https://doi.org/10.1029/2000jd900568, 2001.
Hamlet, A. F. and Lettenmaier, D. P.:
Effects of climate change on hydrology and water resources in the Columbia River basin,
J. Am. Water Resour. As.,
35, 1597–1623, https://doi.org/10.1111/j.1752-1688.1999.tb04240.x, 1999.
Hamman, J., Nijssen, B., Brunke, M., Cassano, J., Craig, A., DuVivier, A., Hughes, M., Lettenmaier, D. P., Maslowski, W., Osinski, R., Roberts, A., and Zeng, X. B.:
Land Surface Climate in the Regional Arctic System Model,
J. Climate,
29, 6543–6562, https://doi.org/10.1175/Jcli-D-15-0415.1, 2016.
Hamman, J., Nijssen, B., Roberts, A., Craig, A., Maslowski, W., and Osinski, R.:
The coastal streamflow flux in the Regional Arctic System Model,
J. Geophys. Res.-Oceans,
122, 1683–1701, https://doi.org/10.1002/2016jc012323, 2017a.
Hamman, J., Nijssen, B., Bohn, T., Franssen, W., Yixinmao, and Gergel, D.: UW-Hydro/VIC: VIC 5.0.1 (Version VIC.5.0.1), Zenodo, https://doi.org/10.5281/zenodo.267178, 2017b.
Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y.: The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481–3496, https://doi.org/10.5194/gmd-11-3481-2018, 2018.
Hanasaki, N., Kanae, S., and Oki, T.:
A reservoir operation scheme for global river routing models,
J. Hydrol.,
327, 22–41, https://doi.org/10.1016/j.jhydrol.2005.11.011, 2006.
Hanasaki, N., Kanae, S., Oki, T., Masuda, K., Motoya, K., Shirakawa, N., Shen, Y., and Tanaka, K.: An integrated model for the assessment of global water resources – Part 2: Applications and assessments, Hydrol. Earth Syst. Sci., 12, 1027–1037, https://doi.org/10.5194/hess-12-1027-2008, 2008a.
Hanasaki, N., Kanae, S., Oki, T., Masuda, K., Motoya, K., Shirakawa, N., Shen, Y., and Tanaka, K.: An integrated model for the assessment of global water resources – Part 1: Model description and input meteorological forcing, Hydrol. Earth Syst. Sci., 12, 1007–1025, https://doi.org/10.5194/hess-12-1007-2008, 2008b.
Hanasaki, N., Fujimori, S., Yamamoto, T., Yoshikawa, S., Masaki, Y., Hijioka, Y., Kainuma, M., Kanamori, Y., Masui, T., Takahashi, K., and Kanae, S.: A global water scarcity assessment under Shared Socio-economic Pathways – Part 1: Water use, Hydrol. Earth Syst. Sci., 17, 2375–2391, https://doi.org/10.5194/hess-17-2375-2013, 2013.
Hanasaki, N., Yoshikawa, S., Pokhrel, Y., and Kanae, S.: A global hydrological simulation to specify the sources of water used by humans, Hydrol. Earth Syst. Sci., 22, 789–817, https://doi.org/10.5194/hess-22-789-2018, 2018.
Hansen, M. C., Defries, R. S., Townshend, J. R. G., and Sohlberg, R.:
Global land cover classification at 1km spatial resolution using a classification tree approach,
Int. J. Remote Sens.,
21, 1331–1364, https://doi.org/10.1080/014311600210209, 2000.
Harding, R., Best, M., Blyth, E., Hagemann, S., Kabat, P., Tallaksen, L. M., Warnaars, T., Wiberg, D., Weedon, G. P., van Lanen, H., Ludwig, F., and Haddeland, I.:
WATCH: Current Knowledge of the Terrestrial Global Water Cycle,
J. Hydrometeorol.,
12, 1149–1156, https://doi.org/10.1175/jhm-d-11-024.1, 2011.
Hejazi, M., Edmonds, J., Clarke, L., Kyle, P., Davies, E., Chaturvedi, V., Wise, M., Patel, P., Eom, J., Calvin, K., Moss, R., and Kim, S.:
Long-term global water projections using six socioeconomic scenarios in an integrated assessment modeling framework,
Technol. Forecast. Soc.,
81, 205–226, https://doi.org/10.1016/j.techfore.2013.05.006, 2014.
Huang, Z., Hejazi, M., Li, X., Tang, Q., Vernon, C., Leng, G., Liu, Y., Döll, P., Eisner, S., Gerten, D., Hanasaki, N., and Wada, Y.: Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns, Hydrol. Earth Syst. Sci., 22, 2117–2133, https://doi.org/10.5194/hess-22-2117-2018, 2018.
Jägermeyr, J., Pastor, A., Biemans, H., and Gerten, D.:
Reconciling irrigated food production with environmental flows for Sustainable Development Goals implementation,
Nat. Commun.,
8, 15900, https://doi.org/10.1038/ncomms15900, 2017.
Kim, S. H., Hejazi, M., Liu, L., Calvin, K., Clarke, L., Edmonds, J., Kyle, P., Patel, P., Wise, M., and Davies, E.:
Balancing global water availability and use at basin scale in an integrated assessment model,
Climatic Change,
136, 217–231, https://doi.org/10.1007/s10584-016-1604-6, 2016.
Klein Goldewijk, K., Beusen, A., Doelman, J., and Stehfest, E.: Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953, https://doi.org/10.5194/essd-9-927-2017, 2017.
Konikow, L. F.:
Contribution of global groundwater depletion since 1900 to sea-level rise,
Geophys. Res. Lett.,
38, L17401, https://doi.org/10.1029/2011gl048604, 2011.
Krinner, G., Viovy, N., de Noblet-Ducoudre, N., Ogee, J., Polcher, J., Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.:
A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system,
Global Biogeochem. Cy.,
19, GB1015, https://doi.org/10.1029/2003gb002199, 2005.
Lehner, B., Liermann, C. R., Revenga, C., Vorosmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J. C., Rodel, R., Sindorf, N., and Wisser, D.:
High-resolution mapping of the world's reservoirs and dams for sustainable river-flow management,
Front. Ecol. Environ.,
9, 494–502, https://doi.org/10.1890/100125, 2011.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.:
A Simple Hydrologically Based Model of Land-Surface Water and Energy Fluxes for General-Circulation Models,
J. Geophys. Res.-Atmos.,
99, 14415–14428, https://doi.org/10.1029/94jd00483, 1994.
Lohmann, D., NolteHolube, R., and Raschke, E.:
A large-scale horizontal routing model to be coupled to land surface parametrization schemes,
Tellus A,
48, 708–721, https://doi.org/10.1034/j.1600-0870.1996.t01-3-00009.x, 1996.
Lohmann, D., Raschke, E., Nijssen, B., and Lettenmaier, D. P.:
Regional scale hydrology: II. Application of the VIC-2L model to the Weser River, Germany,
Hydrolog. Sci. J.,
43, 143–158, https://doi.org/10.1080/02626669809492108, 1998a.
Lohmann, D., Raschke, E., Nijssen, B., and Lettenmaier, D. P.:
Regional scale hydrology: I. Formulation of the VIC-2L model coupled to a routing model,
Hydrolog. Sci. J.,
43, 131–141, https://doi.org/10.1080/02626669809492107, 1998b.
Long, D., Yang, Y., Wada, Y., Hong, Y., Liang, W., Chen, Y., Yong, B., Hou, A., Wei, J., and Chen, L.:
Deriving scaling factors using a global hydrological model to restore GRACE total water storage changes for China's Yangtze River Basin,
Remote Sens. Environ.,
168, 177–193, https://doi.org/10.1016/j.rse.2015.07.003, 2015.
Masaki, Y., Hanasaki, N., Takahashi, K., and Hijioka, Y.:
Consequences of implementing a reservoir operation algorithm in a global hydrological model under multiple meteorological forcing,
Hydrolog. Sci. J.,
63, 1047–1061, https://doi.org/10.1080/02626667.2018.1473872, 2018.
Mekonnen, M. M. and Hoekstra, A. Y.:
Four billion people facing severe water scarcity,
Sci. Adv.,
2, e1500323, https://doi.org/10.1126/sciadv.1500323, 2016.
Mo, K. C.:
Model-Based Drought Indices over the United States,
J. Hydrometeorol.,
9, 1212–1230, https://doi.org/10.1175/2008jhm1002.1, 2008.
Myneni, R. B., Nemani, R. R., and Running, S. W.:
Estimation of global leaf area index and absorbed par using radiative transfer models,
IEEE T. Geosci. Remote,
35, 1380–1393, https://doi.org/10.1109/36.649788, 1997.
NASA: GRACE, National Aeronautics and Space Administration, available at: https://grace.jpl.nasa.gov (last access: September 2019), 2002.
Nazemi, A. and Wheater, H. S.: On inclusion of water resource management in Earth system models – Part 2: Representation of water supply and allocation and opportunities for improved modeling, Hydrol. Earth Syst. Sci., 19, 63–90, https://doi.org/10.5194/hess-19-63-2015, 2015a.
Nazemi, A. and Wheater, H. S.: On inclusion of water resource management in Earth system models – Part 1: Problem definition and representation of water demand, Hydrol. Earth Syst. Sci., 19, 33–61, https://doi.org/10.5194/hess-19-33-2015, 2015b.
Nijssen, B., Lettenmaier, D. P., Liang, X., Wetzel, S. W., and Wood, E. F.:
Streamflow simulation for continental-scale river basins,
Water Resour. Res.,
33, 711–724, https://doi.org/10.1029/96wr03517, 1997.
Nijssen, B., O'Donnell, G. M., Hamlet, A. F., and Lettenmaier, D. P.:
Hydrologic sensitivity of global rivers to climate change,
Climatic Change,
50, 143–175, https://doi.org/10.1023/A:1010616428763, 2001a.
Nijssen, B., O'Donnell, G. M., Lettenmaier, D. P., Lohmann, D., and Wood, E. F.:
Predicting the discharge of global rivers,
J. Climate,
14, 3307–3323, https://doi.org/10.1175/1520-0442(2001)014<3307:Ptdogr>2.0.Co;2, 2001b.
Nijssen, B., Schnur, R., and Lettenmaier, D. P.:
Global retrospective estimation of soil moisture using the variable infiltration capacity land surface model, 1980–93,
J. Climate,
14, 1790–1808, https://doi.org/10.1175/1520-0442(2001)014<1790:Greosm>2.0.Co;2, 2001c.
Nilsson, C., Reidy, C. A., Dynesius, M., and Revenga, C.:
Fragmentation and flow regulation of the world's large river systems,
Science,
308, 405–408, https://doi.org/10.1126/science.1107887, 2005.
Oki, T. and Kanae, S.:
Global hydrological cycles and world water resources,
Science,
313, 1068–1072, https://doi.org/10.1126/science.1128845, 2006.
Oki, T., Musiake, K., Matsuyama, H., and Masuda, K.:
Global Atmospheric Water-Balance and Runoff from Large River Basins,
Hydrol. Process.,
9, 655–678, https://doi.org/10.1002/hyp.3360090513, 1995.
Pastor, A. V., Ludwig, F., Biemans, H., Hoff, H., and Kabat, P.: Accounting for environmental flow requirements in global water assessments, Hydrol. Earth Syst. Sci., 18, 5041–5059, https://doi.org/10.5194/hess-18-5041-2014, 2014.
Pastor, A. V., Palazzo, A., Havlik, P., Biemans, H., Wada, Y., Obersteiner, M., Kabat, P., and Ludwig, F.:
The global nexus of food–trade–water sustaining environmental flows by 2050,
Nature Sustainability,
2, 499–507, https://doi.org/10.1038/s41893-019-0287-1, 2019.
Poff, N. L., Richter, B. D., Arthington, A. H., Bunn, S. E., Naiman, R. J., Kendy, E., Acreman, M., Apse, C., Bledsoe, B. P., Freeman, M. C., Henriksen, J., Jacobson, R. B., Kennen, J. G., Merritt, D. M., O'Keeffe, J. H., Olden, J. D., Rogers, K., Tharme, R. E., and Warner, A.:
The ecological limits of hydrologic alteration (ELOHA): a new framework for developing regional environmental flow standards,
Freshwater Biol.,
55, 147–170, https://doi.org/10.1111/j.1365-2427.2009.02204.x, 2010.
Pokhrel, Y., Hanasaki, N., Koirala, S., Cho, J., Yeh, P. J.-F., Kim, H., Kanae, S., and Oki, T.:
Incorporating Anthropogenic Water Regulation Modules into a Land Surface Model,
J. Hydrometeorol.,
13, 255–269, https://doi.org/10.1175/jhm-d-11-013.1, 2012.
Pokhrel, Y. N., Koirala, S., Yeh, P. J.-F., Hanasaki, N., Longuevergne, L., Kanae, S., and Oki, T.:
Incorporation of groundwater pumping in a global Land Surface Model with the representation of human impacts,
Water Resour. Res.,
51, 78–96, https://doi.org/10.1002/2014wr015602, 2015.
Pokhrel, Y. N., Hanasaki, N., Wada, Y., and Kim, H.:
Recent progresses in incorporating human land-water management into global land surface models toward their integration into Earth system models,
WIREs Water,
3, 548–574, https://doi.org/10.1002/wat2.1150, 2016.
Portmann, F. T., Siebert, S., and Döll, P.:
MIRCA2000-Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling,
Global Biogeochem. Cy.,
24, GB1011, https://doi.org/10.1029/2008gb003435, 2010.
Postel, S. L., Daily, G. C., and Ehrlich, P. R.:
Human appropriation of renewable fresh water,
Science,
271, 785–788, https://doi.org/10.1126/science.271.5250.785, 1996.
Reed, B. and Reed, B.:
How much water is needed in emergencies,
Water, Engineering and Development Centre, Leicestershire, 2013.
Richter, B. D., Davis, M. M., Apse, C., and Konrad, C.:
A Presumptive Standard for Environmental Flow Protection,
River Res. Appl.,
28, 1312–1321, https://doi.org/10.1002/rra.1511, 2012.
Rodell, M., Velicogna, I., and Famiglietti, J. S.:
Satellite-based estimates of groundwater depletion in India,
Nature,
460, 999-U980, https://doi.org/10.1038/nature08238, 2009.
Roman, M. O., Wang, Z. S., Sun, Q. S., Kalb, V., Miller, S. D., Molthan, A., Schultz, L., Bell, J., Stokes, E. C., Pandey, B., Seto, K. C., Hall, D., Oda, T., Wolfe, R. E., Lin, G., Golpayegani, N., Devadiga, S., Davidson, C., Sarkar, S., Praderas, C., Schmaltz, J., Boller, R., Stevens, J., Gonzalez, O. M. R., Padilla, E., Alonso, J., Detres, Y., Armstrong, R., Miranda, I., Conte, Y., Marrero, N., MacManus, K., Esch, T., and Masuoka, E. J.:
NASA's Black Marble nighttime lights product suite,
Remote Sens. Environ.,
210, 113–143, https://doi.org/10.1016/j.rse.2018.03.017, 2018.
Rost, S., Gerten, D., Bondeau, A., Lucht, W., Rohwer, J., and Schaphoff, S.:
Agricultural green and blue water consumption and its influence on the global water system,
Water Resour. Res.,
44, W09405, https://doi.org/10.1029/2007wr006331, 2008.
Rougé, C., Reed, P. M., Grogan, D. S., Zuidema, S., Prusevich, A., Glidden, S., Lamontagne, J. R., and Lammers, R. B.: Coordination and Control: Limits in Standard Representations of Multi-Reservoir Operations in Hydrological Modeling, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-589, in review, 2019.
Sellers, P. J., Tucker, C. J., Collatz, G. J., Los, S. O., Justice, C. O., Dazlich, D. A., and Randall, D. A.:
A Global 1∘ by 1∘ NDVI Data Set for Climate Studies. Part 2. The Generation of Global Fields of Terrestrial Biophysical Parameters from the NDVI,
Int. J. Remote Sens.,
15, 3519–3545, https://doi.org/10.1080/01431169408954343, 1994.
Shen, Y., Oki, T., Utsumi, N., Kanae, S., and Hanasaki, N.:
Projection of future world water resources under SRES scenarios: water withdrawal/Projection des ressources en eau mondiales futures selon les scénarios du RSSE: prélèvement d'eau,
Hydrolog. Sci. J.,
53, 11–33, https://doi.org/10.1080/02626667.2013.862338, 2008.
Shiklomanov, I. A.:
Appraisal and assessment of world water resources,
Water Int.,
25, 11–32, https://doi.org/10.1080/02508060008686794, 2000.
Shuttleworth, W. J.:
Evaporation, in: Handbook of Hydrology,
edited by: Maidment, D. R., McGraw-Hill, New York, 98–144, 1993.
Smakhtin, V., Revenga, C., and Döll, P.:
A pilot global assessment of environmental water requirements and scarcity,
Water Int.,
29, 307–317, https://doi.org/10.1080/02508060408691785, 2004.
Smith, M.:
CROPWAT: A computer program for irrigation planning and management, FAO irrigation and drainage paper,
Food and Agricultural Organisation, Rome, Italy, 127 pp., 1996.
Steinfeld, H., Gerber, P., Wassenaar, T. D., Castel, V., Rosales, M., and De Haan, C.:
Livestock's long shadow: environmental issues and options,
Food and Agricultural Organisation, Rome, Italy, 416 pp., 2006.
Sutanudjaja, E. H., van Beek, R., Wanders, N., Wada, Y., Bosmans, J. H. C., Drost, N., van der Ent, R. J., de Graaf, I. E. M., Hoch, J. M., de Jong, K., Karssenberg, D., López López, P., Peßenteiner, S., Schmitz, O., Straatsma, M. W., Vannametee, E., Wisser, D., and Bierkens, M. F. P.: PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model, Geosci. Model Dev., 11, 2429–2453, https://doi.org/10.5194/gmd-11-2429-2018, 2018.
Takata, K., Emori, S., and Watanabe, T.:
Development of the minimal advanced treatments of surface interaction and runoff,
Global Planet. Change,
38, 209–222, https://doi.org/10.1016/S0921-8181(03)00030-4, 2003.
Tessler, Z. D., Vorosmarty, C. J., Grossberg, M., Gladkova, I., Aizenman, H., Syvitski, J. P. M., and Foufoula-Georgiou, E.:
Profiling risk and sustainability in coastal deltas of the world,
Science,
349, 638–643, https://doi.org/10.1126/science.aab3574, 2015.
Turner, S. W. D., Hejazi, M., Yonkofski, C., Kim, S. H., and Kyle, P.:
Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals Over the Twenty-First Century,
Earths Future,
7, 123–135, https://doi.org/10.1029/2018ef001105, 2019.
van Beek, L. P. H., and Bierkens, M. F. P.: The global hydrological model PCR-GLOBWB: conceptualization, parameterization and verification, Departement of physical geography, Utrecht university, Utrecht, The Netherlands, 54 pp., 2009.
van Vliet, M. T. H., Wiberg, D., Leduc, S., and Riahi, K.: Power-generation system vulnerability and adaptation to changes in climate and water resources,
Nat. Clim. Change,
6, 375–380, https://doi.org/10.1038/Nclimate2903, 2016.
Vassolo, S. and Döll, P.:
Global-scale gridded estimates of thermoelectric power and manufacturing water use,
Water Resour. Res.,
41, W04010, https://doi.org/10.1029/2004wr003360, 2005.
Voisin, N., Li, H., Ward, D., Huang, M., Wigmosta, M., and Leung, L. R.: On an improved sub-regional water resources management representation for integration into earth system models, Hydrol. Earth Syst. Sci., 17, 3605–3622, https://doi.org/10.5194/hess-17-3605-2013, 2013.
Voisin, N., Hejazi, M. I., Leung, L. R., Liu, L., Huang, M. Y., Li, H. Y., and Tesfa, T.: Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model,
Water Resour. Res.,
53, 4253–4270, https://doi.org/10.1002/2016wr019767, 2017.
Voisin, N., Kintner-Meyer, M., Wu, D., Skaggs, R., Fu, T., Zhou, T., Nguyen, T., and Kraucunas, I.:
Opportunities for Joint Water–Energy Management Sensitivity of the 2010 Western US Electricity Grid Operations to Climate Oscillations,
B. Am. Meteorol. Soc.,
99, 299–312, https://doi.org/10.1175/Bams-D-16-0253.1, 2018.
Vorosmarty, C. J., McIntyre, P. B., Gessner, M. O., Dudgeon, D., Prusevich, A., Green, P., Glidden, S., Bunn, S. E., Sullivan, C. A., Liermann, C. R., and Davies, P. M.:
Global threats to human water security and river biodiversity,
Nature,
467, 555–561, https://doi.org/10.1038/nature09440, 2010.
Voß, F. and Flörke, M.:
Spatially explicit estimates of past and present manufacturing and energy water use,
Center for Environmental Systems Research, Kassel, 16 pp., 2010.
Wada, Y. and Bierkens, M. F. P.:
Sustainability of global water use: past reconstruction and future projections,
Environ. Res. Lett.,
9, 104003, https://doi.org/10.1088/1748-9326/9/10/104003, 2014.
Wada, Y., van Beek, L. P. H., and Bierkens, M. F. P.: Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability, Hydrol. Earth Syst. Sci., 15, 3785–3808, https://doi.org/10.5194/hess-15-3785-2011, 2011a.
Wada, Y., van Beek, L. P. H., Viviroli, D., Durr, H. H., Weingartner, R., and Bierkens, M. F. P.:
Global monthly water stress: 2. Water demand and severity of water stress,
Water Resour. Res.,
47, W07518, https://doi.org/10.1029/2010wr009792, 2011b.
Wada, Y., Wisser, D., and Bierkens, M. F. P.: Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources, Earth Syst. Dynam., 5, 15–40, https://doi.org/10.5194/esd-5-15-2014, 2014.
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and Viterbo, P.:
The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data,
Water Resour. Res.,
50, 7505–7514, https://doi.org/10.1002/2014wr015638, 2014.
Wisser, D., Fekete, B. M., Vörösmarty, C. J., and Schumann, A. H.: Reconstructing 20th century global hydrography: a contribution to the Global Terrestrial Network- Hydrology (GTN-H), Hydrol. Earth Syst. Sci., 14, 1–24, https://doi.org/10.5194/hess-14-1-2010, 2010.
Wood, A. W. and Lettenmaier, D. P.:
A test bed for new seasonal hydrologic forecasting approaches in the western United States,
B. Am. Meteorol. Soc.,
87, 1699–1712, https://doi.org/10.1175/Bams-87-12-1699, 2006.
World Bank:
World bank development indicators, available at: https://databank.worldbank.org/source/world-development-indicators (last access: April 2019),
World Bank, 2010.
Yassin, F., Razavi, S., Elshamy, M., Davison, B., Sapriza-Azuri, G., and Wheater, H.: Representation and improved parameterization of reservoir operation in hydrological and land-surface models, Hydrol. Earth Syst. Sci., 23, 3735–3764, https://doi.org/10.5194/hess-23-3735-2019, 2019.
Zhao, G., Gao, H. L., Naz, B. S., Kao, S. C., and Voisin, N.:
Integrating a reservoir regulation scheme into a spatially distributed hydrological model,
Adv. Water Resour.,
98, 16–31, https://doi.org/10.1016/j.advwatres.2016.10.014, 2016.
Zhou, T., Haddeland, I., Nijssen, B., and Lettenmaier, D. P.:
Human induced changes in the global water cycle,
AGU Geophysical Monograph Series,
https://doi.org/10.1002/9781118971772.ch4, 2015.
Zhou, T., Nijssen, B., Gao, H. L., and Lettenmaier, D. P.:
The Contribution of Reservoirs to Global Land Surface Water Storage Variations,
J. Hydrometeorol.,
17, 309–325, https://doi.org/10.1175/Jhm-D-15-0002.1, 2016.
Zhou, T., Voisin, N., Leng, G. Y., Huang, M. Y., and Kraucunas, I.:
Sensitivity of Regulated Flow Regimes to Climate Change in the Western United States,
J. Hydrometeorol.,
19, 499–515, https://doi.org/10.1175/Jhm-D-17-0095.1, 2018.
Zhu, C. M., Leung, L. R., Gochis, D., Qian, Y., and Lettenmaier, D. P.:
Evaluating the Influence of Antecedent Soil Moisture on Variability of the North American Monsoon Precipitation in the Coupled MM5/VIC Modeling System,
J. Adv. Model. Earth. Sy.,
1, 13, https://doi.org/10.3894/James.2009.1.13, 2009.
Short summary
Our study aims to include both both societal and natural water requirements and uses into a hydrological model in order to enable worldwide assessments of sustainable water use. The model was extended to include irrigation, domestic, industrial, energy, and livestock water uses as well as minimum flow requirements for natural systems. Initial results showed competition for water resources between society and nature, especially with respect to groundwater withdrawals.
Our study aims to include both both societal and natural water requirements and uses into a...
