Articles | Volume 16, issue 18
https://doi.org/10.5194/gmd-16-5449-2023
© Author(s) 2023. 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-16-5449-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Enhancing the representation of water management in global hydrological models
Guta Wakbulcho Abeshu
Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA
Fuqiang Tian
Department of Hydraulic Engineering, Tsinghua University, Beijing
100084, China
Thomas Wild
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
Mengqi Zhao
Pacific Northwest National Laboratory, Richland, WA 99354, USA
Sean Turner
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
A. F. M. Kamal Chowdhury
Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, MD 20740, USA
Chris R. Vernon
Pacific Northwest National Laboratory, Richland, WA 99354, USA
Hongchang Hu
Department of Hydraulic Engineering, Tsinghua University, Beijing
100084, China
Yuan Zhuang
Department of Hydraulic Engineering, Tsinghua University, Beijing
100084, China
Mohamad Hejazi
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
now at: King Abdullah Petroleum Studies and Research Center
(KAPSARC), Riyadh, Saudi Arabia
Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA
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Geosci. Model Dev., 17, 5587–5617, https://doi.org/10.5194/gmd-17-5587-2024, https://doi.org/10.5194/gmd-17-5587-2024, 2024
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The Global Change Analysis Model (GCAM) simulates the world’s climate–land–energy–water system interactions , but its reservoir representation is limited. We developed the GLObal Reservoir Yield (GLORY) model to provide GCAM with information on the cost of supplying water based on reservoir construction costs, climate and demand conditions, and reservoir expansion potential. GLORY enhances our understanding of future reservoir capacity needs to meet human demands in a changing climate.
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
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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.
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Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, https://doi.org/10.5194/essd-14-929-2022, 2022
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Existing riverbed sediment particle size data are sparsely available at individual sites. We develop a continuous map of median riverbed sediment particle size over the contiguous US corresponding to millions of river segments based on the existing observations and machine learning methods. This map is useful for research in large-scale river sediment using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc.
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Hydrol. Earth Syst. Sci., 26, 665–688, https://doi.org/10.5194/hess-26-665-2022, https://doi.org/10.5194/hess-26-665-2022, 2022
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Hydrol. Earth Syst. Sci., 29, 2633–2654, https://doi.org/10.5194/hess-29-2633-2025, https://doi.org/10.5194/hess-29-2633-2025, 2025
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Earth Syst. Sci. Data, 17, 2713–2733, https://doi.org/10.5194/essd-17-2713-2025, https://doi.org/10.5194/essd-17-2713-2025, 2025
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Zhen Cui and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 2275–2291, https://doi.org/10.5194/hess-29-2275-2025, https://doi.org/10.5194/hess-29-2275-2025, 2025
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Keer Zhang and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2025-1126, https://doi.org/10.5194/egusphere-2025-1126, 2025
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Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025, https://doi.org/10.5194/hess-29-1919-2025, 2025
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Hydrol. Earth Syst. Sci., 29, 1847–1864, https://doi.org/10.5194/hess-29-1847-2025, https://doi.org/10.5194/hess-29-1847-2025, 2025
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Hydrol. Earth Syst. Sci., 29, 1033–1060, https://doi.org/10.5194/hess-29-1033-2025, https://doi.org/10.5194/hess-29-1033-2025, 2025
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Hydrol. Earth Syst. Sci., 28, 5133–5147, https://doi.org/10.5194/hess-28-5133-2024, https://doi.org/10.5194/hess-28-5133-2024, 2024
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Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
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Hydrol. Earth Syst. Sci., 28, 3613–3632, https://doi.org/10.5194/hess-28-3613-2024, https://doi.org/10.5194/hess-28-3613-2024, 2024
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Mengqi Zhao, Thomas B. Wild, Neal T. Graham, Son H. Kim, Matthew Binsted, A. F. M. Kamal Chowdhury, Siwa Msangi, Pralit L. Patel, Chris R. Vernon, Hassan Niazi, Hong-Yi Li, and Guta W. Abeshu
Geosci. Model Dev., 17, 5587–5617, https://doi.org/10.5194/gmd-17-5587-2024, https://doi.org/10.5194/gmd-17-5587-2024, 2024
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The Global Change Analysis Model (GCAM) simulates the world’s climate–land–energy–water system interactions , but its reservoir representation is limited. We developed the GLObal Reservoir Yield (GLORY) model to provide GCAM with information on the cost of supplying water based on reservoir construction costs, climate and demand conditions, and reservoir expansion potential. GLORY enhances our understanding of future reservoir capacity needs to meet human demands in a changing climate.
Stephen B. Ferencz, Ning Sun, Sean W. D. Turner, Brian A. Smith, and Jennie S. Rice
Nat. Hazards Earth Syst. Sci., 24, 1871–1896, https://doi.org/10.5194/nhess-24-1871-2024, https://doi.org/10.5194/nhess-24-1871-2024, 2024
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Drought has long posed an existential threat to society. Population growth, economic development, and the potential for more extreme and prolonged droughts due to climate change pose significant water security challenges. Better understanding the impacts and adaptive responses resulting from extreme drought can aid adaptive planning. The 2008–2015 record drought in the Colorado Basin, Texas, United States, is used as a case study to assess impacts and responses to severe drought.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
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This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
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
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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.
Ruidong Li, Ting Sun, Fuqiang Tian, and Guang-Heng Ni
Geosci. Model Dev., 16, 751–778, https://doi.org/10.5194/gmd-16-751-2023, https://doi.org/10.5194/gmd-16-751-2023, 2023
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We developed SHAFTS (Simultaneous building Height And FootprinT extraction from Sentinel imagery), a multi-task deep-learning-based Python package, to estimate average building height and footprint from Sentinel imagery. Evaluation in 46 cities worldwide shows that SHAFTS achieves significant improvement over existing machine-learning-based methods.
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 5473–5491, https://doi.org/10.5194/hess-26-5473-2022, https://doi.org/10.5194/hess-26-5473-2022, 2022
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Sea level rise, storm surge and river discharge can cause coastal backwater effects in downstream sections of rivers, creating critical flood risks. This study simulates the backwater effects using a large-scale river model on a coastal-refined computational mesh. By decomposing the backwater drivers, we revealed their relative importance and long-term variations. Our analysis highlights the increasing strength of backwater effects due to sea level rise and more frequent storm surge.
Taher Chegini and Hong-Yi Li
Hydrol. Earth Syst. Sci., 26, 4279–4300, https://doi.org/10.5194/hess-26-4279-2022, https://doi.org/10.5194/hess-26-4279-2022, 2022
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Belowground urban stormwater networks (BUSNs) play a critical and irreplaceable role in preventing or mitigating urban floods. However, they are often not available for urban flood modeling at regional or larger scales. We develop a novel algorithm to estimate existing BUSNs using ubiquitously available aboveground data at large scales based on graph theory. The algorithm has been validated in different urban areas; thus, it is well transferable.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 26, 4147–4167, https://doi.org/10.5194/hess-26-4147-2022, https://doi.org/10.5194/hess-26-4147-2022, 2022
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Tracer-aided hydrological models are useful tool to reduce uncertainty of hydrological modeling in cold basins, but there is little guidance on the sampling strategy for isotope analysis, which is important for large mountainous basins. This study evaluated the reliance of the tracer-aided modeling performance on the availability of isotope data in the Yarlung Tsangpo river basin, and provides implications for collecting water isotope data for running tracer-aided hydrological models.
Yongping Wei, Jing Wei, Gen Li, Shuanglei Wu, David Yu, Mohammad Ghoreishi, You Lu, Felipe Augusto Arguello Souza, Murugesu Sivapalan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 26, 2131–2146, https://doi.org/10.5194/hess-26-2131-2022, https://doi.org/10.5194/hess-26-2131-2022, 2022
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There is increasing tension among the riparian countries of transboundary rivers. This article proposes a socio-hydrological framework that incorporates the slow and less visible societal processes into existing hydro-economic models, revealing the slow and hidden feedbacks between societal and hydrological processes. This framework will contribute to process-based understanding of the complex mechanism that drives conflict and cooperation in transboundary river management.
Matthew Binsted, Gokul Iyer, Pralit Patel, Neal T. Graham, Yang Ou, Zarrar Khan, Nazar Kholod, Kanishka Narayan, Mohamad Hejazi, Son Kim, Katherine Calvin, and Marshall Wise
Geosci. Model Dev., 15, 2533–2559, https://doi.org/10.5194/gmd-15-2533-2022, https://doi.org/10.5194/gmd-15-2533-2022, 2022
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GCAM-USA v5.3_water_dispatch is an open-source model that represents key interactions across economic, energy, water, and land systems in a global framework, with subnational detail in the United States. GCAM-USA can be used to explore future changes in demand for (and production of) energy, water, and crops at the state and regional level in the US. This paper describes GCAM-USA and provides four illustrative scenarios to demonstrate the model's capabilities and potential applications.
Liying Guo, Jing Wei, Keer Zhang, Jiale Wang, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 26, 1165–1185, https://doi.org/10.5194/hess-26-1165-2022, https://doi.org/10.5194/hess-26-1165-2022, 2022
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Data support is crucial for the research of conflict and cooperation on transboundary rivers. Conventional, manual constructions of datasets cannot meet the requirements for fast updates in the big data era. This study brings up a revised methodological framework, based on the conventional method, and a toolkit for the news media dataset tracking of conflict and cooperation dynamics on transboundary rivers. A dataset with good tradeoffs between data relevance and coverage is generated.
Guta Wakbulcho Abeshu, Hong-Yi Li, Zhenduo Zhu, Zeli Tan, and L. Ruby Leung
Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, https://doi.org/10.5194/essd-14-929-2022, 2022
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Existing riverbed sediment particle size data are sparsely available at individual sites. We develop a continuous map of median riverbed sediment particle size over the contiguous US corresponding to millions of river segments based on the existing observations and machine learning methods. This map is useful for research in large-scale river sediment using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc.
Hong-Yi Li, Zeli Tan, Hongbo Ma, Zhenduo Zhu, Guta Wakbulcho Abeshu, Senlin Zhu, Sagy Cohen, Tian Zhou, Donghui Xu, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 665–688, https://doi.org/10.5194/hess-26-665-2022, https://doi.org/10.5194/hess-26-665-2022, 2022
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We introduce a new multi-process river sediment module for Earth system models. Application and validation over the contiguous US indicate a satisfactory model performance over large river systems, including those heavily regulated by reservoirs. This new sediment module enables future modeling of the transportation and transformation of carbon and nutrients carried by the fine sediment along the river–ocean continuum to close the global carbon and nutrient cycles.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 25, 6151–6172, https://doi.org/10.5194/hess-25-6151-2021, https://doi.org/10.5194/hess-25-6151-2021, 2021
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Hydrological modeling has large problems of uncertainty in cold regions. Tracer-aided hydrological models are increasingly used to reduce uncertainty and refine the parameterizations of hydrological processes, with limited application in large basins due to the unavailability of spatially distributed precipitation isotopes. This study explored the utility of isotopic general circulation models in driving a tracer-aided hydrological model in a large basin on the Tibetan Plateau.
Kunbiao Li, Fuqiang Tian, Mohd Yawar Ali Khan, Ran Xu, Zhihua He, Long Yang, Hui Lu, and Yingzhao Ma
Earth Syst. Sci. Data, 13, 5455–5467, https://doi.org/10.5194/essd-13-5455-2021, https://doi.org/10.5194/essd-13-5455-2021, 2021
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Due to complex climate and topography, there is still a lack of a high-quality rainfall dataset for hydrological modeling over the Tibetan Plateau. This study aims to establish a high-accuracy daily rainfall product over the southern Tibetan Plateau through merging satellite rainfall estimates based on a high-density rainfall gauge network. Statistical and hydrological evaluation indicated that the new dataset outperforms the raw satellite estimates and several other products of similar types.
Yi Nan, Lide Tian, Zhihua He, Fuqiang Tian, and Lili Shao
Hydrol. Earth Syst. Sci., 25, 3653–3673, https://doi.org/10.5194/hess-25-3653-2021, https://doi.org/10.5194/hess-25-3653-2021, 2021
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This study integrated a water isotope module into the hydrological model THREW. The isotope-aided model was subsequently applied for process understanding in the glacierized watershed of Karuxung river on the Tibetan Plateau. The model was used to quantify the contribution of runoff component and estimate the water travel time in the catchment. Model uncertainties were significantly constrained by using additional isotopic data, improving the process understanding in the catchment.
You Lu, Fuqiang Tian, Liying Guo, Iolanda Borzì, Rupesh Patil, Jing Wei, Dengfeng Liu, Yongping Wei, David J. Yu, and Murugesu Sivapalan
Hydrol. Earth Syst. Sci., 25, 1883–1903, https://doi.org/10.5194/hess-25-1883-2021, https://doi.org/10.5194/hess-25-1883-2021, 2021
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The upstream countries in the transboundary Lancang–Mekong basin build dams for hydropower, while downstream ones gain irrigation and fishery benefits. Dam operation changes the seasonality of runoff downstream, resulting in their concerns. Upstream countries may cooperate and change their regulations of dams to gain indirect political benefits. The socio-hydrological model couples hydrology, reservoir, economy, and cooperation and reproduces the phenomena, providing a useful model framework.
Jing Wei, Yongping Wei, Fuqiang Tian, Natalie Nott, Claire de Wit, Liying Guo, and You Lu
Hydrol. Earth Syst. Sci., 25, 1603–1615, https://doi.org/10.5194/hess-25-1603-2021, https://doi.org/10.5194/hess-25-1603-2021, 2021
Liming Wang, Songjun Han, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 25, 375–386, https://doi.org/10.5194/hess-25-375-2021, https://doi.org/10.5194/hess-25-375-2021, 2021
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It remains unclear at which timescale the complementary principle performs best in estimating evaporation. In this study, evaporation estimation was assessed over 88 eddy covariance monitoring sites at multiple timescales. The results indicate that the generalized complementary functions perform best in estimating evaporation at the monthly scale. This study provides a reference for choosing a suitable time step for evaporation estimations in relevant studies.
Cited articles
Abeshu, G. W.: Abeshu-etal_2023_GMD: Model Input and Output data, Zenodo [data set], https://doi.org/10.5281/zenodo.7557403, 2023a.
Abeshu, G. W.: gutabeshu/Abeshu-etal_2023_GMD: Xanthos-wm (v1.01), Zenodo [code], https://doi.org/10.5281/zenodo.7557380, 2023b.
Abeshu, G. W.: gutabeshu/xanthos-wm: Xanthos-wm-v1.02 (Xanthos-wm-v1.02). Zenodo [code], https://doi.org/10.5281/zenodo.8267343, 2023c.
Abeshu, G. W., Li, H.-Y., Zhu, Z., Tan, Z., and Leung, L. R.: Median bed-material sediment particle size across rivers in the contiguous US, Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, 2022.
Arango-Aramburo, S., Turner, S. W. D., Daenzer, K., Ríos-Ocampo, J. P.,
Hejazi, M. I., Kober, T., Álvarez-Espinosa, A. C., Romero-Otalora, G.
D., and van der Zwaan, B.: Climate impacts on hydropower in Colombia: A
multi-model assessment of power sector adaptation pathways, Energ. Policy,
128, 179–188, https://doi.org/10.1016/j.enpol.2018.12.057, 2019.
Belletti, B., Garcia de Leaniz, C., Jones, J., Bizzi, S., Börger, L.,
Segura, G., Castelletti, A., van de Bund, W., Aarestrup, K., Barry, J.,
Belka, K., Berkhuysen, A., Birnie-Gauvin, K., Bussettini, M., Carolli, M.,
Consuegra, S., Dopico, E., Feierfeil, T., Fernández, S., Fernandez
Garrido, P., Garcia-Vazquez, E., Garrido, S., Giannico, G., Gough, P.,
Jepsen, N., Jones, P. E., Kemp, P., Kerr, J., King, J., Łapińska, M.,
Lázaro, G., Lucas, M. C., Marcello, L., Martin, P., McGinnity, P.,
O'Hanley, J., Olivo del Amo, R., Parasiewicz, P., Pusch, M., Rincon, G.,
Rodriguez, C., Royte, J., Schneider, C. T., Tummers, J. S., Vallesi, S.,
Vowles, A., Verspoor, E., Wanningen, H., Wantzen, K. M., Wildman, L., and
Zalewski, M.: More than one million barriers fragment Europe's rivers,
Nature, 588, 436–441, https://doi.org/10.1038/s41586-020-3005-2, 2020.
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.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36,
https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Beven, K.: Parameter Estimation and Predictive Uncertainty, in:
Rainfall-Runoff Modelling, Wiley, 231–287,
https://doi.org/10.1002/9781119951001.ch7, 2012.
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,
1–15, https://doi.org/10.1029/2009WR008929, 2011.
Birnbaum, A., Lamontagne, J., Wild, T., Dolan, F., and Yarlagadda, B.:
Drivers of Future Physical Water Scarcity and Its Economic Impacts in Latin
America and the Caribbean, Earth's Future, 10, 1–21,
https://doi.org/10.1029/2022EF002764, 2022.
Boulange, J., Hanasaki, N., Yamazaki, D., and Pokhrel, Y.: Role of dams in
reducing global flood exposure under climate change, Nat. Commun., 12, 1–7,
https://doi.org/10.1038/s41467-020-20704-0, 2021.
Braun, C., Vernon, C., Link, R., Evanoff, J., and zarrarkhan: JGCRI/xanthos: v2.4.1 Xanthos (v2.4.1), Zenodo [code], https://doi.org/10.5281/zenodo.5177210, 2021.
Branstetter, M. L. and Erickson, D. J.: Continental runoff dynamics in the
Community Climate System Model 2 (CCSM2) control simulation, J. Geophys.
Res.-Atmos., 108, 1–17, https://doi.org/10.1029/2002jd003212, 2003.
Burek, P., Satoh, Y., Kahil, T., Tang, T., Greve, P., Smilovic, M., Guillaumot, L., Zhao, F., and Wada, Y.: Development of the Community Water Model (CWatM v1.04) – a high-resolution hydrological model for global and regional assessment of integrated water resources management, Geosci. Model Dev., 13, 3267–3298, https://doi.org/10.5194/gmd-13-3267-2020, 2020.
Calvin, K., Patel, P., Clarke, L., Asrar, G., Bond-Lamberty, B., Cui, R. Y., Di Vittorio, A., Dorheim, K., Edmonds, J., Hartin, C., Hejazi, M., Horowitz, R., Iyer, G., Kyle, P., Kim, S., Link, R., McJeon, H., Smith, S. J., Snyder, A., Waldhoff, S., and Wise, M.: GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems, Geosci. Model Dev., 12, 677–698, https://doi.org/10.5194/gmd-12-677-2019, 2019.
De Roo, A. P. J., Wesseling, C. G., and Van Deursen, W. P. A.: Physically
based river basin modelling within a GIS: The LISFLOOD model, Hydrol.
Process., 14, 1981–1992,
https://doi.org/10.1002/1099-1085(20000815/30)14:11/12<1981::aid-hyp49>3.0.co;2-f, 2000.
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.
Gleeson, T., Wagener, T., Döll, P., Zipper, S. C., West, C., Wada, Y., Taylor, R., Scanlon, B., Rosolem, R., Rahman, S., Oshinlaja, N., Maxwell, R., Lo, M.-H., Kim, H., Hill, M., Hartmann, A., Fogg, G., Famiglietti, J. S., Ducharne, A., de Graaf, I., Cuthbert, M., Condon, L., Bresciani, E., and Bierkens, M. F. P.: GMD perspective: The quest to improve the evaluation of groundwater representation in continental- to global-scale models, Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, 2021.
Graham, N. T., Hejazi, M. I., Chen, M., Davies, E. G. R., Edmonds, J. A.,
Kim, S. H., Turner, S. W. D., Li, X., Vernon, C. R., Calvin, K.,
Miralles-Wilhelm, F., Clarke, L., Kyle, P., Link, R., Patel, P., Snyder, A.
C., and Wise, M. A.: Humans drive future water scarcity changes across all
Shared Socioeconomic Pathways, Environ. Res. Lett., 15, 014007,
https://doi.org/10.1088/1748-9326/ab639b, 2020.
Grill, G., Lehner, B., Thieme, M., Geenen, B., Tickner, D., Antonelli, F.,
Babu, S., Borrelli, P., Cheng, L., Crochetiere, H., Ehalt Macedo, H.,
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., Reidy Liermann, C., Sáenz, L., Salinas-Rodríguez, 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.
Grogan, D. S., Zuidema, S., Prusevich, A., Wollheim, W. M., Glidden, S., and Lammers, R. B.: Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality, Geosci. Model Dev., 15, 7287–7323, https://doi.org/10.5194/gmd-15-7287-2022, 2022.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition
of the mean squared error and NSE performance criteria: Implications for
improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Haddeland, I., Skaugen, T., and Lettenmaier, D. P.: Anthropogenic impacts on
continental surface water fluxes, Geophys. Res. Lett., 33, 2–5,
https://doi.org/10.1029/2006GL026047, 2006.
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 1: Model description and input meteorological forcing, Hydrol. Earth Syst. Sci., 12, 1007–1025, https://doi.org/10.5194/hess-12-1007-2008, 2008.
Hejazi, M. I., Edmonds, J., Clarke, L., Kyle, P., Davies, E., Chaturvedi, V., Eom, J., Wise, M., Patel, P., and Calvin, K.: Integrated assessment of global water scarcity over the 21st century – Part 2: Climate change mitigation policies, Hydrol. Earth Syst. Sci. Discuss., 10, 3383–3425, https://doi.org/10.5194/hessd-10-3383-2013, 2013.
Hejazi, M. I., Edmonds, J., Clarke, L., Kyle, P., Davies, E., Chaturvedi, V., Wise, M., Patel, P., Eom, J., and Calvin, K.: Integrated assessment of global water scarcity over the 21st century under multiple climate change mitigation policies, Hydrol. Earth Syst. Sci., 18, 2859–2883, https://doi.org/10.5194/hess-18-2859-2014, 2014.
Hirpa, F. A., Salamon, P., Beck, H. E., Lorini, V., Alfieri, L., Zsoter, E.,
and Dadson, S. J.: Calibration of the Global Flood Awareness System (GloFAS)
using daily streamflow data, J. Hydrol., 566, 595–606,
https://doi.org/10.1016/j.jhydrol.2018.09.052, 2018.
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.: Global
gridded monthly sectoral water use dataset for 1971–2010: v2, Zenodo [data set]
https://doi.org/10.5281/zenodo.1209296,
2018a.
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, 2018b.
Khan, Z., Wild, T. B., Silva Carrazzone, M. E., Gaudioso, R., Mascari, M.
P., Bianchi, F., Weinstein, F., Pérez, F., Pérez, W.,
Miralles-Wilhelm, F., Clarke, L., Hejazi, M., Vernon, C. R., Kyle, P.,
Edmonds, J., and Muoz Castillo, R.: Integrated energy-water-land nexus
planning to guide national policy: An example from Uruguay, Environ. Res.
Lett., 15, 094014, https://doi.org/10.1088/1748-9326/ab9389, 2020.
Knoben, W. J. M., Freer, J. E., and Woods, R. A.: Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, 2019.
Lehner, B., Liermann, C. R., Revenga, C., Vörömsmarty, C., Fekete,
B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J.,
Nilsson, C., Robertson, J. C., Rödel, 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.
Li, H., Huang, M., Wigmosta, M. S., Ke, Y., Coleman, A. M., Leung, L. R.,
Wang, A., and Ricciuto, D. M.: Evaluating runoff simulations from the
Community Land Model 4.0 using observations from flux towers and a
mountainous watershed, J. Geophys. Res.-Atmos., 116, D24120,
https://doi.org/10.1029/2011JD016276, 2011.
Li, H., Abeshu, G., Zhu, Z., Tan, Z., and Leung, L. R.: A national map of
riverine median bed-material particle size over CONUS(1.1), Zenodo [data set],
https://doi.org/10.5281/zenodo.4921987, 2021.
Li, H. Y., Leung, L. R., Getirana, A., Huang, M., Wu, H., Xu, Y., Guo, J.,
and Voisin, N.: Evaluating global streamflow simulations by a physically
based routing model coupled with the community land model, J.
Hydrometeorol., 16, 948–971, https://doi.org/10.1175/JHM-D-14-0079.1, 2015.
Li, X., Vernon, C. R., Hejazi, M. I., Link, R. P., Feng, L., Liu, Y., and
Rauchenstein, L. T.: Xanthos – A Global Hydrologic Model, J. Open Res.
Softw., 5, 21, https://doi.org/10.5334/jors.181, 2017.
Liu, Y., Hejazi, M., Li, H., Zhang, X., and Leng, G.: A hydrological emulator for global applications – HE v1.0.0, Geosci. Model Dev., 11, 1077–1092, https://doi.org/10.5194/gmd-11-1077-2018, 2018.
López, J. and Francés, F.: Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates, Hydrol. Earth Syst. Sci., 17, 3189–3203, https://doi.org/10.5194/hess-17-3189-2013, 2013.
Loucks, D. P., Beek, E. van, Stedinger, J. R., Dijkman, J. P. M., and
Villars, M. T.: Water resource systems planning and management: An
introduction to methods, models, and applications, Springer International
Publishing, Cham, 1–624, https://doi.org/10.1007/978-3-319-44234-1,
2017.
Mahmood, K.: Reservoir sedimentation: impact, extent, and mitigation,
Technical Report, International Bank for Reconstruction and Development,
Washington, DC (USA), Report Number: PB-88-113964/XAB, WORLD-BANK-TP-71, 1987.
Martinez, G. F. and Gupta, H. V.: Toward improved identification of
hydrological models: A diagnostic evaluation of the “abcd” monthly water
balance model for the conterminous United States, Water Resour. Res., 46,
1–21, https://doi.org/10.1029/2009WR008294, 2010.
Martinez, G. F. and Gupta, H. V.: Hydrologic consistency as a basis for
assessing complexity of monthly water balance models for the continental
United States, Water Resour. Res., 47, 1–18,
https://doi.org/10.1029/2011WR011229, 2011.
McKay, M. D., Beckman, R. J., and Conover, W. J.: Comparison of Three
Methods for Selecting Values of Input Variables in the Analysis of Output
from a Computer Code, Technometrics, 21, 239–245,
https://doi.org/10.1080/00401706.1979.10489755, 1979.
Moges, E., Demissie, Y., Larsen, L., and Yassin, F.: Review: Sources of
hydrological model uncertainties and advances in their analysis, Water, 13, 1–23, https://doi.org/10.3390/w13010028, 2021.
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D.,
and Veith, T. L.: Model Evaluation Guidelines for Systematic Quantification
of Accuracy in Watershed Simulations, T. ASABE, 50, 885–900,
https://doi.org/10.13031/2013.23153, 2007.
Müller Schmied, H., Cáceres, D., Eisner, S., Flörke, M., Herbert, C., Niemann, C., Peiris, T. A., Popat, E., Portmann, F. T., Reinecke, R., Schumacher, M., Shadkam, S., Telteu, C.-E., Trautmann, T., and Döll, P.: The global water resources and use model WaterGAP v2.2d: model description and evaluation, Geosci. Model Dev., 14, 1037–1079, https://doi.org/10.5194/gmd-14-1037-2021, 2021.
Piccardi, C. and Soncini-Sessa, R.: Stochastic dynamic programming for
reservoir optimal control: Dense discretization and inflow correlation
assumption made possible by parallel computing, Water Resour. Res., 27,
729–741, https://doi.org/10.1029/90WR02766, 1991.
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.
Santos da Silva, S. R., Hejazi, M. I., Iyer, G., Wild, T. B., Binsted, M.,
Miralles-Wilhelm, F., Patel, P., Snyder, A. C., and Vernon, C. R.: Power
sector investment implications of climate impacts on renewable resources in
Latin America and the Caribbean, Nat. Commun., 12, 1–12,
https://doi.org/10.1038/s41467-021-21502-y, 2021.
Schaphoff, S., von Bloh, W., Rammig, A., Thonicke, K., Biemans, H., Forkel, M., Gerten, D., Heinke, J., Jägermeyr, J., Knauer, J., Langerwisch, F., Lucht, W., Müller, C., Rolinski, S., and Waha, K.: LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description, Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018, 2018.
Stedinger, J. R., Sule, B. F., and Loucks, D. P.: Stochastic dynamic programming models for reservoir operation optimization, Water Resour. Res., 20, 14991505, https://doi.org/10.1029/WR020i011p01499, 1984.
Shen, Y., Ruijsch, J., Lu, M., Sutanudjaja, E. H., and Karssenberg, D.:
Random forests-based error-correction of streamflow from a large-scale
hydrological model: Using model state variables to estimate error terms,
Comput. Geosci., 159, 105019, https://doi.org/10.1016/j.cageo.2021.105019,
2022.
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.
Telteu, C.-E., Müller Schmied, H., Thiery, W., Leng, G., Burek, P., Liu, X., Boulange, J. E. S., Andersen, L. S., Grillakis, M., Gosling, S. N., Satoh, Y., Rakovec, O., Stacke, T., Chang, J., Wanders, N., Shah, H. L., Trautmann, T., Mao, G., Hanasaki, N., Koutroulis, A., Pokhrel, Y., Samaniego, L., Wada, Y., Mishra, V., Liu, J., Döll, P., Zhao, F., Gädeke, A., Rabin, S. S., and Herz, F.: Understanding each other's models: an introduction and a standard representation of 16 global water models to support intercomparison, improvement, and communication, Geosci. Model Dev., 14, 3843–3878, https://doi.org/10.5194/gmd-14-3843-2021, 2021.
Tennant, D. L.: Instream Flow Regimens for Fish, Wildlife, Recreation and
Related Environmental Resources, Fisheries, 1, 6–10,
https://doi.org/10.1577/1548-8446(1976)001<0006:IFRFFW>2.0.CO;2, 1976.
Thomas, H. A.: Improved Methods for National tvater Assessment, U.S. Geol.
Surv. Water Resour., 44, Water Resources Contract: WR15249270, 1981.
Turner, S. W. D.: Reservoir (Tools for Analysis, Design, and Operation of
Water Supply Storages),
https://geomodeling.njnu.edu.cn/modelItem/074783d2-6218-4b9d-b1e2-d93132d3b030 (last access: 1 August 2022),
2016.
Turner, S. W. D., Ng, J. Y., and Galelli, S.: Examining global electricity
supply vulnerability to climate change using a high-fidelity hydropower dam
model, Sci. Total Environ., 590–591, 663–675,
https://doi.org/10.1016/j.scitotenv.2017.03.022, 2017.
van der Knijff, J. M., Younis, J., and de Roo, A. P. J.: LISFLOOD: A
GIS-based distributed model for river basin scale water balance and flood
simulation, Int. J. Geogr. Inf. Sci., 24, 189–212,
https://doi.org/10.1080/13658810802549154, 2010.
Vernon, C. R., Hejazi, M. I., Turner, S. W. D., Liu, Y., Braun, C. J., Li,
X., and Link, R. P.: A global hydrologic framework to accelerate scientific
discovery, J. Open Res. Softw., 7, 1–7, https://doi.org/10.5334/jors.245,
2019.
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.
Votruba, L. and Broza, V.: Flood-control Function of Reservoirs, in: Water
Management in Reservoirs, 295–296,
https://doi.org/10.1016/S0167-5648(08)70640-3, 1989.
Walsh, R. P. D. and Lawler, D. M.: Rainfall seasonality: Description,
spatial patterns and change through time, Weather, 36, 201–208,
https://doi.org/10.1002/j.1477-8696.1981.tb05400.x, 1981.
Wan, W., Zhao, J., Li, H. Y., Mishra, A., Ruby Leung, L., Hejazi, M., Wang,
W., Lu, H., Deng, Z., Demissisie, Y., and Wang, H.: Hydrological Drought in
the Anthropocene: Impacts of Local Water Extraction and Reservoir Regulation
in the U.S., J. Geophys. Res.-Atmos., 122, 11313–11328,
https://doi.org/10.1002/2017JD026899, 2017.
Wan, W., Zhao, J., Li, H. Y., Mishra, A., Hejazi, M., Lu, H., Demissie, Y.,
and Wang, H.: A Holistic View of Water Management Impacts on Future
Droughts: A Global Multimodel Analysis, J. Geophys. Res.-Atmos., 123,
5947–5972, https://doi.org/10.1029/2017JD027825, 2018.
Wang, W., Li, H. Y., Leung, L. R., Yigzaw, W., Zhao, J., Lu, H., Deng, Z.,
Demisie, Y., and Blöschl, G.: Nonlinear Filtering Effects of Reservoirs
on Flood Frequency Curves at the Regional Scale, Water Resour. Res., 53,
8277–8292, https://doi.org/10.1002/2017WR020871, 2017.
Weedon, G. P., Gomes, S., Viterbo, P., Shuttleworth, W. J., Blyth, E.,
Österle, H., Adam, J. C., Bellouin, N., Boucher, O., and Best, M.:
Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional
Reference Crop Evaporation over Land during the Twentieth Century, J.
Hydrometeorol., 12, 823–848, https://doi.org/10.1175/2011JHM1369.1, 2011.
White, R.: Evacuation of sediments from reservoirs, Thomas Telford
Publishing, https://doi.org/10.1680/eosfr.29538, 2001.
Wild, T. B., Birnbaum, A. N., Reed, P. M., and Loucks, D. P.: An open source
reservoir and sediment simulation framework for identifying and evaluating
siting, design, and operation alternatives, Environ. Model. Softw., 136,
104947, https://doi.org/10.1016/j.envsoft.2020.104947, 2021a.
Wild, T. B., Khan, Z., Clarke, L., Hejazi, M., Bereslawski, J. L., Suriano,
M., Roberts, P., Casado, J., Miralles-Wilhelm, F., Gavino-Novillo, M.,
Muñoz-Castillo, R., Moreda, F., Zhao, M., Yarlagadda, B., Lamontagne,
J., and Birnbaum, A.: Integrated energy-water-land nexus planning in the
Colorado River Basin (Argentina), Reg. Environ. Change, 21, 62,
https://doi.org/10.1007/s10113-021-01775-1, 2021b.
Wild, T. B., Khan, Z., Zhao, M., Suriano, M., Bereslawski, J. L., Roberts,
P., Casado, J., Gaviño-Novillo, M., Clarke, L., Hejazi, M.,
Miralles-Wilhelm, F., Muñoz-Castillo, R., Vernon, C., Snyder, A.,
Yarlagadda, B., Birnbaum, A., Lamontagne, J., White, D., and Ojeda-Matos,
G.: The Implications of Global Change for the Co-Evolution of Argentina's
Integrated Energy-Water-Land Systems, Earth's Future, 9, e2020EF001970,
https://doi.org/10.1029/2020EF001970, 2021c.
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.
Wu, H., Kimball, J. S., Mantua, N., and Stanford, J.: Automated upscaling of
river networks for macroscale hydrological modeling, Water Resour. Res., 47,
1–18, https://doi.org/10.1029/2009WR008871, 2011.
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.
Ye, S., Li, H. Y., Huang, M., Ali, M., Leng, G., Leung, L. R., Wang, S. W.,
and Sivapalan, M.: Regionalization of subsurface stormflow parameters of
hydrologic models: Derivation from regional analysis of streamflow recession
curves, J. Hydrol., 519, 670–682,
https://doi.org/10.1016/j.jhydrol.2014.07.017, 2014.
Yoshida, T., Hanasaki, N., Nishina, K., Boulange, J., Okada, M., and Troch,
P. A.: Inference of Parameters for a Global Hydrological Model:
Identifiability and Predictive Uncertainties of Climate-Based Parameters,
Water Resour. Res., 58, e2021WR030660, https://doi.org/10.1029/2021WR030660, 2022.
Zarfl, C., Lumsdon, A. E., Berlekamp, J., Tydecks, L., and Tockner, K.: A global boom in hydropower dam construction, Aquat. Sci., 77, 161170, https://doi.org/10.1007/s00027-014-0377-0, 2015.
Zeng, X., Hu, T., Cai, X., Zhou, Y., and Wang, X.: Improved dynamic
programming for parallel reservoir system operation optimization, Adv. Water
Resour., 131, 103373, https://doi.org/10.1016/j.advwatres.2019.07.003, 2019.Please provide article number or page range.
Zhang, X., Li, H.-Y., Deng, Z. D., Ringler, C., Gao, Y., Hejazi, M. I., and
Leung, L. R.: Impacts of climate change, policy and Water-Energy-Food nexus
on hydropower development, Renew. Energ., 116, 827–834,
https://doi.org/10.1016/j.renene.2017.10.030, 2018.
Zhang, X., Li, H. Y., Deng, Z. D., Leung, L. R., Skalski, J. R., and Cooke,
S. J.: On the variable effects of climate change on Pacific salmon, Ecol.
Modell., 397, 95–106, https://doi.org/10.1016/j.ecolmodel.2019.02.002,
2019.
Zhang, X., Li, H. Y., Leung, L. R., Liu, L., Hejazi, M. I., Forman, B. A.,
and Yigzaw, W.: River Regulation Alleviates the Impacts of Climate Change on
U.S. Thermoelectricity Production, J. Geophys. Res.-Atmos., 125, e2019JD031618,
https://doi.org/10.1029/2019JD031618, 2020.
Zhou, T., Leung, L. R., Leng, G., Voisin, N., Li, H. Y., Craig, A. P.,
Tesfa, T., and Mao, Y.: Global Irrigation Characteristics and Effects
Simulated by Fully Coupled Land Surface, River, and Water Management Models
in E3SM, J. Adv. Model. Earth Sy., 12, 1–18,
https://doi.org/10.1029/2020MS002069, 2020.
Zhou, Y., Hejazi, M., Smith, S., Edmonds, J., Li, H., Clarke, L., Calvin,
K., and Thomson, A.: A comprehensive view of global potential for
hydro-generated electricity, Energ. Environ. Sci., 8, 2622–2633,
https://doi.org/10.1039/C5EE00888C, 2015.
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.
Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are...