Articles | Volume 25, issue 3
https://doi.org/10.5194/hess-25-1365-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-1365-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Mar 2021
Research article |
| 19 Mar 2021
| 19 Mar 2021
Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling
Department of Civil and Structural Engineering, University of Sheffield, Sheffield, United Kingdom
School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, United States
Patrick M. Reed
School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, United States
Danielle S. Grogan
Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, United States
Shan Zuidema
Water Systems Analysis Group, University of New Hampshire, Durham, NH, United States
Alexander Prusevich
Water Systems Analysis Group, University of New Hampshire, Durham, NH, United States
Stanley Glidden
Water Systems Analysis Group, University of New Hampshire, Durham, NH, United States
Jonathan R. Lamontagne
Department of Civil and Environmental Engineering, Tufts University, Medford, MA, United States
Richard B. Lammers
Water Systems Analysis Group, University of New Hampshire, Durham, NH, United States
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The proposed approach is based on the parameterisation of flow duration curves (FDCs) to generate hypothetical streamflow futures. (1) We sample a broad range of future climates with modified values of three key streamflow statistics. (2) We generate an FDC for each hydro-climate future. (3) The resulting ensemble is ready to support robustness assessments in a changing climate. Our approach seamlessly represents a large range of futures with increased frequencies of both high and low flows.
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Hydrol. Earth Syst. Sci., 25, 551–564, https://doi.org/10.5194/hess-25-551-2021, https://doi.org/10.5194/hess-25-551-2021, 2021
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In our case study we find that increasing the efficiency of irrigation technology will have unintended consequences like reducing water available for aquifer replenishment or for other irrigators. The amount of water needed to stabilize regional aquifers exceeds the amount that could be saved by improving irrigation efficiency. Since users depend upon local groundwater storage, which is more sensitive to management decisions than river flow, comanagement of surface and groundwater is critical.
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Hydrol. Earth Syst. Sci., 17, 2893–2903, https://doi.org/10.5194/hess-17-2893-2013, https://doi.org/10.5194/hess-17-2893-2013, 2013
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Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
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This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
Mauricio Lima, Katherine Deck, Oliver R. A. Dunbar, and Tapio Schneider
EGUsphere, https://doi.org/10.48550/arXiv.2404.14212, https://doi.org/10.48550/arXiv.2404.14212, 2024
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Machine learning is playing an increasingly important role in hydrological modeling. In this paper, we introduce an adaptation of existing machine learning models forecasting streamflow in river basins, redesigning them with the goal of integrating them into climate models. We demonstrate the effectiveness of our adapted model by showing that it outperforms a physics-based river model. These results motivate further studies of the use of machine learning based river models inside climate models.
Fransje van Oorschot, Ruud J. van der Ent, Andrea Alessandri, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 2313–2328, https://doi.org/10.5194/hess-28-2313-2024, https://doi.org/10.5194/hess-28-2313-2024, 2024
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Vegetation plays a crucial role in regulating the water cycle by transporting water from the subsurface to the atmosphere via roots; this transport depends on the extent of the root system. In this study, we quantified the effect of irrigation on roots at a global scale. Our results emphasize the importance of accounting for irrigation in estimating the vegetation root extent, which is essential to adequately represent the water cycle in hydrological and climate models.
Omar V. Müller, Patrick C. McGuire, Pier Luigi Vidale, and Ed Hawkins
Hydrol. Earth Syst. Sci., 28, 2179–2201, https://doi.org/10.5194/hess-28-2179-2024, https://doi.org/10.5194/hess-28-2179-2024, 2024
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This work evaluates how rivers are projected to change in the near future compared to the recent past in the context of a warming world. We show that important rivers of the world will notably change their flows, mainly during peaks, exceeding the variations that rivers used to exhibit. Such large changes may produce more frequent floods, alter hydropower generation, and potentially affect the ocean's circulation.
Mugni Hadi Hariadi, Gerard van der Schrier, Gert-Jan Steeneveld, Samuel J. Sutanto, Edwin Sutanudjaja, Dian Nur Ratri, Ardhasena Sopaheluwakan, and Albert Klein Tank
Hydrol. Earth Syst. Sci., 28, 1935–1956, https://doi.org/10.5194/hess-28-1935-2024, https://doi.org/10.5194/hess-28-1935-2024, 2024
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We utilize the high-resolution CMIP6 for extreme rainfall and streamflow projection over Southeast Asia. This region will experience an increase in both dry and wet extremes in the near future. We found a more extreme low flow and high flow, along with an increasing probability of low-flow and high-flow events. We reveal that the changes in low-flow events and their probabilities are not only influenced by extremely dry climates but also by the catchment characteristics.
Ayenew D. Ayalew, Paul D. Wagner, Dejene Sahlu, and Nicola Fohrer
Hydrol. Earth Syst. Sci., 28, 1853–1872, https://doi.org/10.5194/hess-28-1853-2024, https://doi.org/10.5194/hess-28-1853-2024, 2024
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The study presents a pioneering comprehensive integrated approach to unravel hydrological complexities in data-scarce regions. By integrating diverse data sources and advanced analytics, we offer a holistic understanding of water systems, unveiling hidden patterns and driving factors. This innovative method holds immense promise for informed decision-making and sustainable water resource management, addressing a critical need in hydrological science.
Juliette Godet, Eric Gaume, Pierre Javelle, Pierre Nicolle, and Olivier Payrastre
Hydrol. Earth Syst. Sci., 28, 1403–1413, https://doi.org/10.5194/hess-28-1403-2024, https://doi.org/10.5194/hess-28-1403-2024, 2024
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This work was performed in order to precisely address a point that is often neglected by hydrologists: the allocation of points located on a river network to grid cells, which is often a mandatory step for hydrological modelling.
Jim Yoon, Nathalie Voisin, Christian Klassert, Travis Thurber, and Wenwei Xu
Hydrol. Earth Syst. Sci., 28, 899–916, https://doi.org/10.5194/hess-28-899-2024, https://doi.org/10.5194/hess-28-899-2024, 2024
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Global and regional models used to evaluate water shortages typically neglect the possibility that irrigated crop areas may change in response to future hydrological conditions, such as the fallowing of crops in response to drought. Here, we enhance a model used for water shortage analysis with farmer agents that dynamically adapt their irrigated crop areas based on simulated hydrological conditions. Results indicate that such cropping adaptation can strongly alter simulated water shortages.
Celray James Chawanda, Albert Nkwasa, Wim Thiery, and Ann van Griensven
Hydrol. Earth Syst. Sci., 28, 117–138, https://doi.org/10.5194/hess-28-117-2024, https://doi.org/10.5194/hess-28-117-2024, 2024
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Africa's water resources are being negatively impacted by climate change and land-use change. The SWAT+ hydrological model was used to simulate the hydrological cycle in Africa, and results show likely decreases in river flows in the Zambezi and Congo rivers and highest flows in the Niger River basins due to climate change. Land cover change had the biggest impact in the Congo River basin, emphasizing the importance of including land-use change in studies.
Tom Kimpson, Margarita Choulga, Matthew Chantry, Gianpaolo Balsamo, Souhail Boussetta, Peter Dueben, and Tim Palmer
Hydrol. Earth Syst. Sci., 27, 4661–4685, https://doi.org/10.5194/hess-27-4661-2023, https://doi.org/10.5194/hess-27-4661-2023, 2023
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Lakes play an important role when we try to explain and predict the weather. More accurate and up-to-date description of lakes all around the world for numerical models is a continuous task. However, it is difficult to assess the impact of updated lake description within a weather prediction system. In this work, we develop a method to quickly and automatically define how, where, and when updated lake description affects weather prediction.
Haiyang Shi, Geping Luo, Olaf Hellwich, Xiufeng He, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 27, 4551–4562, https://doi.org/10.5194/hess-27-4551-2023, https://doi.org/10.5194/hess-27-4551-2023, 2023
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Using evidence from meteorological stations, this study assessed the climatic, hydrological, and ecological aridity changes in global drylands and their associated mechanisms. A decoupling between atmospheric, hydrological, and vegetation aridity was found. This highlights the added value of using station-scale data to assess dryland change as a complement to results based on coarse-resolution reanalysis data and land surface models.
En Ning Lai, Lan Wang-Erlandsson, Vili Virkki, Miina Porkka, and Ruud J. van der Ent
Hydrol. Earth Syst. Sci., 27, 3999–4018, https://doi.org/10.5194/hess-27-3999-2023, https://doi.org/10.5194/hess-27-3999-2023, 2023
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This research scrutinized predicted changes in root zone soil moisture dynamics across different climate scenarios and different climate regions globally between 2021 and 2100. The Mediterranean and most of South America stood out as regions that will likely experience permanently drier conditions, with greater severity observed in the no-climate-policy scenarios. These findings underscore the impact that possible future climates can have on green water resources.
Julia Pfeffer, Anny Cazenave, Alejandro Blazquez, Bertrand Decharme, Simon Munier, and Anne Barnoud
Hydrol. Earth Syst. Sci., 27, 3743–3768, https://doi.org/10.5194/hess-27-3743-2023, https://doi.org/10.5194/hess-27-3743-2023, 2023
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The GRACE (Gravity Recovery And Climate Experiment) satellite mission enabled the quantification of water mass redistributions from 2002 to 2017. The analysis of GRACE satellite data shows here that slow changes in terrestrial water storage occurring over a few years to a decade are severely underestimated by global hydrological models. Several sources of errors may explain such biases, likely including the inaccurate representation of groundwater storage changes.
Thedini Asali Peiris and Petra Döll
Hydrol. Earth Syst. Sci., 27, 3663–3686, https://doi.org/10.5194/hess-27-3663-2023, https://doi.org/10.5194/hess-27-3663-2023, 2023
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Hydrological models often overlook vegetation's response to CO2 and climate, impairing their ability to forecast impacts on evapotranspiration and water resources. To address this, we suggest involving two model variants: (1) the standard method and (2) a modified approach (proposed here) based on the Priestley–Taylor equation (PT-MA). While not universally applicable, a dual approach helps consider uncertainties related to vegetation responses to climate change, enhancing model representation.
Samah Larabi, Juliane Mai, Markus Schnorbus, Bryan A. Tolson, and Francis Zwiers
Hydrol. Earth Syst. Sci., 27, 3241–3263, https://doi.org/10.5194/hess-27-3241-2023, https://doi.org/10.5194/hess-27-3241-2023, 2023
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The computational cost of sensitivity analysis (SA) becomes prohibitive for large hydrologic modeling domains. Here, using a large-scale Variable Infiltration Capacity (VIC) deployment, we show that watershed classification helps identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. Findings reveal the opportunity to leverage climate and land cover attributes to reduce the cost of SA and facilitate more rapid deployment of large-scale land surface models.
Tanja Denager, Torben O. Sonnenborg, Majken C. Looms, Heye Bogena, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 27, 2827–2845, https://doi.org/10.5194/hess-27-2827-2023, https://doi.org/10.5194/hess-27-2827-2023, 2023
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This study contributes to improvements in the model characterization of water and energy fluxes. The results show that multi-objective autocalibration in combination with mathematical regularization is a powerful tool to improve land surface models. Using the direct measurement of turbulent fluxes as the target variable, parameter optimization matches simulations and observations of latent heat, whereas sensible heat is clearly biased.
Yuki Kimura, Yukiko Hirabayashi, Yuki Kita, Xudong Zhou, and Dai Yamazaki
Hydrol. Earth Syst. Sci., 27, 1627–1644, https://doi.org/10.5194/hess-27-1627-2023, https://doi.org/10.5194/hess-27-1627-2023, 2023
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Since both the frequency and magnitude of flood will increase by climate change, information on spatial distributions of potential inundation depths (i.e., flood-hazard map) is required. We developed a method for constructing realistic future flood-hazard maps which addresses issues due to biases in climate models. A larger population is estimated to face risk in the future flood-hazard map, suggesting that only focusing on flood-frequency change could cause underestimation of future risk.
Hoontaek Lee, Martin Jung, Nuno Carvalhais, Tina Trautmann, Basil Kraft, Markus Reichstein, Matthias Forkel, and Sujan Koirala
Hydrol. Earth Syst. Sci., 27, 1531–1563, https://doi.org/10.5194/hess-27-1531-2023, https://doi.org/10.5194/hess-27-1531-2023, 2023
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We spatially attribute the variance in global terrestrial water storage (TWS) interannual variability (IAV) and its modeling error with two data-driven hydrological models. We find error hotspot regions that show a disproportionately large significance in the global mismatch and the association of the error regions with a smaller-scale lateral convergence of water. Our findings imply that TWS IAV modeling can be efficiently improved by focusing on model representations for the error hotspots.
Jannis M. Hoch, Edwin H. Sutanudjaja, Niko Wanders, Rens L. P. H. van Beek, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 27, 1383–1401, https://doi.org/10.5194/hess-27-1383-2023, https://doi.org/10.5194/hess-27-1383-2023, 2023
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To facilitate locally relevant simulations over large areas, global hydrological models (GHMs) have moved towards ever finer spatial resolutions. After a decade-long quest for hyper-resolution (i.e. equal to or smaller than 1 km), the presented work is a first application of a GHM at 1 km resolution over Europe. This not only shows that hyper-resolution can be achieved but also allows for a thorough evaluation of model results at unprecedented detail and the formulation of future research.
Chinchu Mohan, Tom Gleeson, James S. Famiglietti, Vili Virkki, Matti Kummu, Miina Porkka, Lan Wang-Erlandsson, Xander Huggins, Dieter Gerten, and Sonja C. Jähnig
Hydrol. Earth Syst. Sci., 26, 6247–6262, https://doi.org/10.5194/hess-26-6247-2022, https://doi.org/10.5194/hess-26-6247-2022, 2022
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The relationship between environmental flow violations and freshwater biodiversity at a large scale is not well explored. This study intended to carry out an exploratory evaluation of this relationship at a large scale. While our results suggest that streamflow and EF may not be the only determinants of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods or with other biodiversity data or metrics.
Zhaofei Liu
Hydrol. Earth Syst. Sci., 26, 6207–6226, https://doi.org/10.5194/hess-26-6207-2022, https://doi.org/10.5194/hess-26-6207-2022, 2022
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Ground heat flux (G) accounts for a significant fraction of the surface energy balance (SEB), but there is insufficient research on these models compared with other flux. The accuracy of G simulation methods in the SEB-based remote sensing evapotranspiration models is evaluated. Results show that the accuracy of each method varied significantly at different sites and at half-hour intervals. Further improvement of G simulations is recommended for the remote sensing evapotranspiration modelers.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022, https://doi.org/10.5194/hess-26-5971-2022, 2022
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We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
Feng Zhong, Shanhu Jiang, Albert I. J. M. van Dijk, Liliang Ren, Jaap Schellekens, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 26, 5647–5667, https://doi.org/10.5194/hess-26-5647-2022, https://doi.org/10.5194/hess-26-5647-2022, 2022
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A synthesis of rainfall interception data from past field campaigns is performed, including 166 forests and 17 agricultural plots distributed worldwide. These site data are used to constrain and validate an interception model that considers sub-grid heterogeneity and vegetation dynamics. A global, 40-year (1980–2019) interception dataset is generated at a daily temporal and 0.1° spatial resolution. This dataset will serve as a benchmark for future investigations of the global hydrological cycle.
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.
Kieran M. R. Hunt, Gwyneth R. Matthews, Florian Pappenberger, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 5449–5472, https://doi.org/10.5194/hess-26-5449-2022, https://doi.org/10.5194/hess-26-5449-2022, 2022
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In this study, we use three models to forecast river streamflow operationally for 13 months (September 2020 to October 2021) at 10 gauges in the western US. The first model is a state-of-the-art physics-based streamflow model (GloFAS). The second applies a bias-correction technique to GloFAS. The third is a type of neural network (an LSTM). We find that all three are capable of producing skilful forecasts but that the LSTM performs the best, with skilful 5 d forecasts at nine stations.
Tongtiegang Zhao, Haoling Chen, Yu Tian, Denghua Yan, Weixin Xu, Huayang Cai, Jiabiao Wang, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 26, 4233–4249, https://doi.org/10.5194/hess-26-4233-2022, https://doi.org/10.5194/hess-26-4233-2022, 2022
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This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts).
Vili Virkki, Elina Alanärä, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu
Hydrol. Earth Syst. Sci., 26, 3315–3336, https://doi.org/10.5194/hess-26-3315-2022, https://doi.org/10.5194/hess-26-3315-2022, 2022
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Direct and indirect human actions have altered streamflow across the world since pre-industrial times. Here, we apply a method of environmental flow envelopes (EFEs) that develops the existing global environmental flow assessments by methodological advances and better consideration of uncertainty. By assessing the violations of the EFE, we comprehensively quantify the frequency, severity, and trends of flow alteration during the past decades, illustrating anthropogenic effects on streamflow.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
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Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Jawairia A. Ahmad, Barton A. Forman, and Sujay V. Kumar
Hydrol. Earth Syst. Sci., 26, 2221–2243, https://doi.org/10.5194/hess-26-2221-2022, https://doi.org/10.5194/hess-26-2221-2022, 2022
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Assimilation of remotely sensed data into a land surface model to improve the spatiotemporal estimation of soil moisture across South Asia exhibits potential. Satellite retrieval assimilation corrects biases that are generated due to an unmodeled hydrologic phenomenon, i.e., irrigation. The improvements in fine-scale, modeled soil moisture estimates by assimilating coarse-scale retrievals indicates the utility of the described methodology for data-scarce regions.
Naota Hanasaki, Hikari Matsuda, Masashi Fujiwara, Yukiko Hirabayashi, Shinta Seto, Shinjiro Kanae, and Taikan Oki
Hydrol. Earth Syst. Sci., 26, 1953–1975, https://doi.org/10.5194/hess-26-1953-2022, https://doi.org/10.5194/hess-26-1953-2022, 2022
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Global hydrological models (GHMs) are usually applied with a spatial resolution of about 50 km, but this time we applied the H08 model, one of the most advanced GHMs, with a high resolution of 2 km to Kyushu island, Japan. Since the model was not accurate as it was, we incorporated local information and improved the model, which revealed detailed water stress in subregions that were not visible with the previous resolution.
Basil Kraft, Martin Jung, Marco Körner, Sujan Koirala, and Markus Reichstein
Hydrol. Earth Syst. Sci., 26, 1579–1614, https://doi.org/10.5194/hess-26-1579-2022, https://doi.org/10.5194/hess-26-1579-2022, 2022
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We present a physics-aware machine learning model of the global hydrological cycle. As the model uses neural networks under the hood, the simulations of the water cycle are learned from data, and yet they are informed and constrained by physical knowledge. The simulated patterns lie within the range of existing hydrological models and are plausible. The hybrid modeling approach has the potential to tackle key environmental questions from a novel perspective.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung
Hydrol. Earth Syst. Sci., 26, 1089–1109, https://doi.org/10.5194/hess-26-1089-2022, https://doi.org/10.5194/hess-26-1089-2022, 2022
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We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare two experiments, one with globally uniform and one with vegetation parameters that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting the important role of the interaction between groundwater–soil moisture–vegetation in understanding TWS variations.
Marc F. P. Bierkens, Edwin H. Sutanudjaja, and Niko Wanders
Hydrol. Earth Syst. Sci., 25, 5859–5878, https://doi.org/10.5194/hess-25-5859-2021, https://doi.org/10.5194/hess-25-5859-2021, 2021
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We introduce a simple analytical framework that allows us to estimate to what extent large-scale groundwater withdrawal affects groundwater levels and streamflow. It also calculates which part of the groundwater withdrawal comes out of groundwater storage and which part from a reduction in streamflow. Global depletion rates obtained with the framework are compared with estimates from satellites, from global- and continental-scale groundwater models, and from in situ datasets.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, https://doi.org/10.5194/hess-25-5287-2021, 2021
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Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
Jérôme Kopp, Pauline Rivoire, S. Mubashshir Ali, Yannick Barton, and Olivia Martius
Hydrol. Earth Syst. Sci., 25, 5153–5174, https://doi.org/10.5194/hess-25-5153-2021, https://doi.org/10.5194/hess-25-5153-2021, 2021
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Episodes of extreme rainfall events happening in close temporal succession can lead to floods with dramatic impacts. We developed a novel method to individually identify those episodes and deduced the regions where they occur frequently and where their impact is substantial. Those regions are the east and northeast of the Asian continent, central Canada and the south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and north of Argentina and south of Bolivia.
Alyssa J. DeVincentis, Hervé Guillon, Romina Díaz Gómez, Noelle K. Patterson, Francine van den Brandeler, Arthur Koehl, J. Pablo Ortiz-Partida, Laura E. Garza-Díaz, Jennifer Gamez-Rodríguez, Erfan Goharian, and Samuel Sandoval Solis
Hydrol. Earth Syst. Sci., 25, 4631–4650, https://doi.org/10.5194/hess-25-4631-2021, https://doi.org/10.5194/hess-25-4631-2021, 2021
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Latin America and the Caribbean face many water-related stresses which are expected to worsen with climate change. To assess the vulnerability, we reviewed over 20 000 multilingual research articles using machine learning and an understanding of the regional landscape. Results reveal that the region’s inherent vulnerability is compounded by research blind spots in niche topics (reservoirs and risk assessment) and subregions (Caribbean nations), as well as by its reliance on one country (Brazil).
Michiel Maertens, Gabriëlle J. M. De Lannoy, Sebastian Apers, Sujay V. Kumar, and Sarith P. P. Mahanama
Hydrol. Earth Syst. Sci., 25, 4099–4125, https://doi.org/10.5194/hess-25-4099-2021, https://doi.org/10.5194/hess-25-4099-2021, 2021
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In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.
Louise J. Slater, Bailey Anderson, Marcus Buechel, Simon Dadson, Shasha Han, Shaun Harrigan, Timo Kelder, Katie Kowal, Thomas Lees, Tom Matthews, Conor Murphy, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 3897–3935, https://doi.org/10.5194/hess-25-3897-2021, https://doi.org/10.5194/hess-25-3897-2021, 2021
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Weather and water extremes have devastating effects each year. One of the principal challenges for society is understanding how extremes are likely to evolve under the influence of changes in climate, land cover, and other human impacts. This paper provides a review of the methods and challenges associated with the detection, attribution, management, and projection of nonstationary weather and water extremes.
Cited articles
Abatzoglou, J. T.: Development of gridded surface meteorological data for ecological applications and modelling, Int. J. Climatol., 33, 121–131, https://doi.org/10.1002/joc.3413, 2013. a
Adam, J. C., Haddeland, I., Su, F., and Lettenmaier, D. P.: Simulation of reservoir influences on annual and seasonal streamflow changes for the Lena, Yenisei, and Ob' rivers, J. Geophys. Res.-Atmos., 112, D24114, https://doi.org/10.1029/2007JD008525, 2007. a, b, c
Ahmadalipour, A. and Moradkhani, H.: Analyzing the uncertainty of ensemble-based gridded observations in land surface simulations and drought assessment, J. Hydrol., 555, 557–568, https://doi.org/10.1016/j.jhydrol.2017.10.059, 2017. a
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration-Guidelines for computing crop water requirements – FAO Irrigation and drainage paper 56, FAO, Rome, 326 pp., 1998. a
Avisse, N., Tilmant, A., Müller, M. F., and Zhang, H.: Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas, Hydrol. Earth Syst. Sci., 21, 6445–6459, https://doi.org/10.5194/hess-21-6445-2017, 2017. a
Bierkens, M. F. P.: Global hydrology 2015: State, trends, and directions, Water Resour. Res., 51, 4923–4947, https://doi.org/10.1002/2015WR017173, 2015. a
Bierkens, M. F. P., Bell, V. A., Burek, P., Chaney, N., Condon, L. E., David, C. H., de Roo, A., Döll, P., Drost, N., Famiglietti, J. S., Flörke, M., Gochis, D. J., Houser, P., Hut, R., Keune, J., Kollet, S., Maxwell, R. M., Reager, J. T., Samaniego, L., Sudicky, E., Sutanudjaja, E. H., van de Giesen, N., Winsemius, H., and Wood, E. F.: Hyper-resolution global hydrological modelling: what is next?, Hydrol. Process., 29, 310–320, https://doi.org/10.1002/hyp.10391, 2015. a
Bierkens, M. F. P., Reinhard, S., de Bruijn, J. A., Veninga, W., and Wada, Y.: The Shadow Price of Irrigation Water in Major Groundwater-Depleting Countries, Water Resour. Res., 55, 4266–4287, https://doi.org/10.1029/2018WR023086, 2019. a
Burek, P. A., Roo, A. D., and van der Knijff, J.: LISFLOOD - Distributed Water Balance and Flood Simulation Model – Revised User Manual, Tech. Rep., Publications Office of the European Union, Directorate-General Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy, 2013. a, b
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Model. Softw., 22, 1509–1518, https://doi.org/10.1016/j.envsoft.2006.10.004, 2007. a, b
Center For International Earth Science Information Network – CIESIN – Columbia University: Gridded Population of the World, Version 4 (GPWv4): Population Density, NASA Socioeconomic Data and Applications Center (SEDAC), Palisades, NY, USA, 2016. a
Coe, M. T.: Modeling Terrestrial Hydrological Systems at the Continental Scale: Testing the Accuracy of an Atmospheric GCM, J. Climate, 13, 686–704, https://doi.org/10.1175/1520-0442(2000)013<0686:MTHSAT>2.0.CO;2, 2000. a
Coerver, H. M., Rutten, M. M., and van de Giesen, N. C.: Deduction of reservoir operating rules for application in global hydrological models, Hydrol. Earth Syst. Sci., 22, 831–851, https://doi.org/10.5194/hess-22-831-2018, 2018. a, b
Dang, T. D., Chowdhury, A. F. M. K., and Galelli, S.: On the representation of water reservoir storage and operations in large-scale hydrological models: implications on model parameterization and climate change impact assessments, Hydrol. Earth Syst. Sci., 24, 397–416, https://doi.org/10.5194/hess-24-397-2020, 2020. a
Dieter, C. A., Maupin, M. A., Caldwell, R. R., Harris, M. A., Ivahnenko, T. I., Lovelace, J. K., Barber, N. L., and Linsey, K. S.: Estimated use of water in the United States in 2015, USGS Numbered Series 1441, iP-090439, US Geological Survey, Reston, VA, available at: http://pubs.er.usgs.gov/publication/cir1441, last access: 13 November 2018. a
Döll, P., Kaspar, F., and Lehner, B.: A global hydrological model for deriving water availability indicators: model tuning and validation, J. Hydrol., 270, 105–134, https://doi.org/10.1016/S0022-1694(02)00283-4, 2003. a
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. a, b
Dynesius, M. and Nilsson, C.: Fragmentation and Flow Regulation of River Systems in the Northern Third of the World, Science, 266, 753–762, https://doi.org/10.1126/science.266.5186.753, 1994. a
Ehsani, N., Fekete, B. M., Vörösmarty, C. J., and Tessler, Z. D.: A neural network based general reservoir operation scheme, Stoch. Environ. Res. Risk A., 30, 1151–1166, https://doi.org/10.1007/s00477-015-1147-9, 2016. a, b, c
Ehsani, N., Vörösmarty, C. J., Fekete, B. M., and Stakhiv, E. Z.: Reservoir operations under climate change: Storage capacity options to mitigate risk, J. Hydrol., 555, 435–446, https://doi.org/10.1016/j.jhydrol.2017.09.008, 2017. a
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017. a
Gilmore, S.: Assessing the Adaptive Capacity of Idaho's Magic Valley As a Complex Social-Ecological System, MS thesis, University of Idaho, Moscow, ID, 2019. a
Giuliani, M. and Herman, J. D.: Modeling the behavior of water reservoir operators via eigenbehavior analysis, Adv. Water Resour., 122, 228–237, https://doi.org/10.1016/j.advwatres.2018.10.021, 2018. a
Giuliani, M., Herman, J. D., Castelletti, A., and Reed, P.: Many-objective reservoir policy identification and refinement to reduce policy inertia and myopia in water management, Water Resour. Res., 50, 3355–3377, https://doi.org/10.1002/2013WR014700, 2014. a
Giuliani, M., Castelletti, A., Pianosi, F., Mason, E., and Reed, P. M.: Curses, Tradeoffs, and Scalable Management: Advancing Evolutionary Multiobjective Direct Policy Search to Improve Water Reservoir Operations, J. Water Resour. Plan. Manage., 142, 04015050, https://doi.org/10.1061/(ASCE)WR.1943-5452.0000570, 2016. a
Grill, G., lehner, B., Thieme, M., Geenen, B., Tickner, D., Antonelli, F., Babu, S., Borrelli, P., l. Cheng, 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., l. S/'aenz, Salinas-Rodr/'iguez, S., Schelle, P., Schmitt, R. J. P., Snider, J., anf K. Tockner, F. T., 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. a
Grogan, D. S.: Global and regional assessments of unsustainable groundwater use in irrigated agriculture, PhD thesis, University of New Hampshire, USA, available at: http://scholars.unh.edu/dissertation/2 (last access: 21 May 2019), 2016. a
Grogan, D. S., Zhang, F., Prusevich, A., Lammers, R. B., Wisser, D., Glidden, S., Li, C., and Frolking, S.: Quantifying the link between crop production and mined groundwater irrigation in China, Sci. Total Environ., 511, 161–175, https://doi.org/10.1016/j.scitotenv.2014.11.076, 2015. a, b, c
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. a
Guse, B., Reusser, D. E., and Fohrer, N.: How to improve the representation of hydrological processes in SWAT for a lowland catchment – temporal analysis of parameter sensitivity and model performance, Hydrol. Process., 28, 2651–2670, https://doi.org/10.1002/hyp.9777, 2014. a
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, 2006. a, b, c
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. Assoc., 35, 1597–1623, https://doi.org/10.1111/j.1752-1688.1999.tb04240.x, 1999. a
Han, W., Yang, Z., Di, L., and Mueller, R.: CropScape: A Web service based application for exploring and disseminating US conterminous geospatial cropland data products for decision support, Comput. Electron. Agric., 84, 111–123, https://doi.org/10.1016/j.compag.2012.03.005, 2012. a
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. a
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 2: Water availability and scarcity, Hydrol. Earth Syst. Sci., 17, 2393–2413, https://doi.org/10.5194/hess-17-2393-2013, 2013. a
Hanasaki, N., Yoshikawa, S., Pokhrel, Y., and Kanae, S.: A Quantitative Investigation of the Thresholds for Two Conventional Water Scarcity Indicators Using a State-of-the-Art Global Hydrological Model With Human Activities, Water Resour. Res., 54, 8279–8294, https://doi.org/10.1029/2018WR022931, 2018. a
Hejazi, M. I., Cai, X., and Ruddell, B. L.: The role of hydrologic information in reservoir operation – Learning from historical releases, Adv. Water Resour., 31, 1636–1650, 2008. a
Hejazi, M. I., Voisin, N., Liu, L., Bramer, L. M., Fortin, D. C., Hathaway, J. E., Huang, M., Kyle, P., Leung, L. R., Li, H.-Y., Liu, Y., Patel, P. L., Pulsipher, T. C., Rice, J. S., Tesfa, T. K., Vernon, C. R., and Zhou, Y.: 21st century United States emissions mitigation could increase water stress more than the climate change it is mitigating, P. Natl. Acad. Sci. USA, 112, 10635–10640, https://doi.org/10.1073/pnas.1421675112, 2015. a
Herbert, C. and Döll, P.: Global assessment of current and future groundwater stress with a focus on transboundary aquifers, Water Resour. Res., 55, 4760–4784, https://doi.org/10.1029/2018WR023321, 2019. a
Herman, J. and Usher, W.: SALib: An open-source Python library for Sensitivity Analysis, J. Open Source Softw., 2, 97, https://doi.org/10.21105/joss.00097, 2017. a
Herman, J. D., Kollat, J. B., Reed, P. M., and Wagener, T.: Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models, Hydrol. Earth Syst. Sci., 17, 2893–2903, https://doi.org/10.5194/hess-17-2893-2013, 2013a. a
Herman, J. D., Kollat, J. B., Reed, P. M., and Wagener, T.: From maps to movies: high-resolution time-varying sensitivity analysis for spatially distributed watershed models, Hydrol. Earth Syst. Sci., 17, 5109–5125, https://doi.org/10.5194/hess-17-5109-2013, 2013b. a, b
Hoekema, D. J. and Sridhar, V.: Relating climatic attributes and water resources allocation: A study using surface water supply and soil moisture indices in the Snake River basin, Idaho, Water Resour. Res., 47, W07536, https://doi.org/10.1029/2010WR009697, 2011. a
Independent Panel To Review Cause of Teton Dam Failure: Report to US Department of Interior and State of Idaho on Failure of Teton Dam, Tech. Rep., United States Bureau of Reclamations, available at: https://www.usbr.gov/pn/snakeriver/dams/uppersnake/teton/1976failure.pdf
(last access: 20 May 2018), 1976. a
Iooss, B. and Lemaître, P.: A Review on Global Sensitivity Analysis Methods, Springer US, Boston, MA, 101–122, https://doi.org/10.1007/978-1-4899-7547-8_5, 2015. a
Jägermeyr, J., Gerten, D., Heinke, J., Schaphoff, S., Kummu, M., and Lucht, W.: Water savings potentials of irrigation systems: global simulation of processes and linkages, Hydrol. Earth Syst. Sci., 19, 3073–3091, https://doi.org/10.5194/hess-19-3073-2015, 2015. a
Jägermeyr, J., Gerten, D., Schaphoff, S., Heinke, J., Lucht, W., and Rockström, J.: Integrated crop water management might sustainably halve the global food gap, Environ. Res. Lett., 11, 025002, https://doi.org/10.1088/1748-9326/11/2/025002, 2016. a
Jeuland, M., Baker, J., Bartlett, R., and Lacombe, G.: The costs of uncoordinated infrastructure management in multi-reservoir river basins, Environ. Res. Lett., 9, 105006, https://doi.org/10.1088/1748-9326/9/10/105006, 2014. a
Kliskey, A., Abatzoglou, J., Alessa, L., Kolden, C., Hoekema, D., Moore, B., Gilmore, S., and Austin, G.: Planning for Idaho's waterscapes: A review of historical drivers and outlook for the next 50 years, Environ. Sci. Policy, 94, 191–201, https://doi.org/10.1016/j.envsci.2019.01.009, 2019. a
Kraucunas, I., Clarke, L., Dirks, J., Hathaway, J., Hejazi, M., Hibbard, K., Huang, M., Jin, C., Kintner-Meyer, M., van Dam, K. K., Leung, R., Li, H.-Y., Moss, R., Peterson, M., Rice, J., Scott, M., Thomson, A., Voisin, N., and West, T.: Investigating the nexus of climate, energy, water, and land at decision-relevant scales: the Platform for Regional Integrated Modeling and Analysis (PRIMA), Climatic Change, 129, 573–588, https://doi.org/10.1007/s10584-014-1064-9, 2015. a
Lamontagne, J. R., Reed, P. M., Marangoni, G., Keller, K., and Garner, G. G.: Robust abatement pathways to tolerable climate futures require immediate global action, Nat. Clim. Change, 9, 290–294, https://doi.org/10.1038/s41558-019-0426-8, 2019. a
Latrubesse, E. M., Arima, E. Y., Dunne, T., Park, E., Baker, V. R., d'Horta, F. M., Wight, C., Wittmann, F., Zuanon, J., Baker, P. A., Ribas, C. C., Norgaard, R. B., Filizola, N., Ansar, A., Flyvbjerg, B., and Stevaux, J. C.: Damming the rivers of the Amazon basin, Nature, 546, 363–369, https://doi.org/10.1038/nature22333, 2017. a
Legates, D. R. and McCabe Jr., G. J.: Evaluating the use of “goodness-of-fit” Measures in hydrologic and hydroclimatic model validation, Water Resour. Res., 35, 233–241, https://doi.org/10.1029/1998WR900018, 1999. a
Lehner, B., Verdin, K., and Jarvis, A.: New Global Hydrography Derived From Spaceborne Elevation Data, Eos Tran. AGU, 89, 93–94, https://doi.org/10.1029/2008EO100001, 2008. a
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, 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. a
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. a
Liu, J., Hertel, T. W., Lammers, R. B., Prusevich, A., Baldos, U. L. C., Grogan, D. S., and Frolking, S.: Achieving sustainable irrigation water withdrawals: global impacts on food security and land use, Environ. Res. Lett., 12, 104009, https://doi.org/10.1088/1748-9326/aa88db, 2017. a, b
Liu, X., Liu, W., Yang, H., Tang, Q., Flörke, M., Masaki, Y., Müller Schmied, H., Ostberg, S., Pokhrel, Y., Satoh, Y., and Wada, Y.: Multimodel assessments of human and climate impacts on mean annual streamflow in China, Hydrol. Earth Syst. Sci., 23, 1245–1261, https://doi.org/10.5194/hess-23-1245-2019, 2019. a
Loucks, D. P. and van Beek, E.: Water Resources Systems Planning and Management, UNESCO, Paris, 2005. a
Marques, G. F. and Tilmant, A.: The economic value of coordination in large-scale multireservoir systems: The Parana River case, Water Resour. Res., 49, 7546–7557, https://doi.org/10.1002/2013WR013679, 2013. a
Masaki, Y., Hanasaki, N., Biemans, H., Schmied, H. M., Tang, Q., Wada, Y., Gosling, S. N., Takahashi, K., and Hijioka, Y.: Intercomparison of global river discharge simulations focusing on dam operation – multiple models analysis in two case-study river basins, Missouri-Mississippi and Green-Colorado, Environ. Res. Lett., 12, 055002, https://doi.org/10.1088/1748-9326/aa57a8, 2017. a, b
Mateo, C. M., Hanasaki, N., Komori, D., Tanaka, K., Kiguchi, M., Champathong, A., Sukhapunnaphan, T., Yamazaki, D., and Oki, T.: Assessing the impacts of reservoir operation to floodplain inundation by combining hydrological, reservoir management, and hydrodynamic models, Water Resour. Res., 50, 7245–7266, https://doi.org/10.1002/2013WR014845, 2014. a
Maupin, M. A., Kenny, J. F., Hutson, S. S., Lovelace, J. K., Barber, N. L., and Linsey, K. S.: Estimated use of water in the United States in 2010, no. 1405 in Circular, US Geological Survey, Reston, Virginia, 2014. a
McGuire, M., Wood, A. W., Hamlet, A. F., and Lettenmaier, D. P.: Use of Satellite Data for Streamflow and Reservoir Storage Forecasts in the Snake River Basin, J. Water Resour. Plan. Manage., 132, 97–110, https://doi.org/10.1061/(ASCE)0733-9496(2006)132:2(97), 2006. a
Meigh, J. R., McKenzie, A. A., and Sene, K. J.: A Grid-Based Approach to Water Scarcity Estimates for Eastern and Southern Africa, Water Resour. Manag., 13, 85–115, https://doi.org/10.1023/A:1008025703712, 1999. a
Metin, A. D., Dung, N. V., Schröter, K., Guse, B., Apel, H., Kreibich, H., Vorogushyn, S., and Merz, B.: How do changes along the risk chain affect flood risk?, Nat. Hazards Earth Syst. Sci., 18, 3089–3108, https://doi.org/10.5194/nhess-18-3089-2018, 2018. a
Meza, I., Siebert, S., Döll, P., Kusche, J., Herbert, C., Eyshi Rezaei, E., Nouri, H., Gerdener, H., Popat, E., Frischen, J., Naumann, G., Vogt, J. V., Walz, Y., Sebesvari, Z., and Hagenlocher, M.: Global-scale drought risk assessment for agricultural systems, Nat. Hazards Earth Syst. Sci., 20, 695–712, https://doi.org/10.5194/nhess-20-695-2020, 2020. a
Mishra, V., Aaadhar, S., Shah, H., Kumar, R., Pattanaik, D. R., and Tiwari, A. D.: The Kerala flood of 2018: combined impact of extreme rainfall and reservoir storage, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2018-480, 2018. a
Monteith, J. L.: Evaporation and the Environment in the State and Movement of Water in Living Organisms, in: Proceedings of the Society for Experimental Biology, Symposium No. 19, Cambridge University Press, Cambridge, 205–234, 1965. a
Morris, M. D.: Factorial Sampling Plans for Preliminary Computational Experiments, Technometrics, 33, 161–174, https://doi.org/10.1080/00401706.1991.10484804, 1991. a, b
Müller, M. F., Yoon, J., Gorelick, S. M., Avisse, N., and Tilmant, A.: Impact of the Syrian refugee crisis on land use and transboundary freshwater resources, P. Natl. Acad. Sci. USA, 113, 14932–14937, https://doi.org/10.1073/pnas.1614342113, 2016. a
Musselman, K. N., Lehner, F., Ikeda, K., Clark, M. P., Prein, A. F., Liu, C., Barlage, M., and Rasmussen, R.: Projected increases and shifts in rain-on-snow flood risk over western North America, Nat. Clim. Change, 8, 808–812, https://doi.org/10.1038/s41558-018-0236-4, 2018. a
Najibi, N., Devineni, N., and Lu, M.: Hydroclimate drivers and atmospheric teleconnections of long duration floods: An application to large reservoirs in the Missouri River Basin, Adv. Water Resour., 100, 153–167, https://doi.org/10.1016/j.advwatres.2016.12.004, 2017. a
National Oceanic and Atmospheric Administration: Flooding in Idaho, available at: https://www.weather.gov/safety/flood-states-id, last access: 13 April 2020. a
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, 2015. a
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. a
Oyerinde, G. T., Wisser, D., Hountondji, F. C., Odofin, A. J., Lawin, A. E., Afouda, A., and Diekkrüger, B.: Quantifying Uncertainties in Modeling Climate Change Impacts on Hydropower Production, Climate, 4, 34, https://doi.org/10.3390/cli4030034, 2016. a
Pianosi, F. and Wagener, T.: Understanding the time-varying importance of different uncertainty sources in hydrological modelling using global sensitivity analysis, Hydrol. Process., 30, 3991–4003, https://doi.org/10.1002/hyp.10968, 2016. a
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. a, b
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. a
Qiu, J., Yang, Q., Zhang, X., Huang, M., Adam, J. C., and Malek, K.: Implications of water management representations for watershed hydrologic modeling in the Yakima River basin, Hydrol. Earth Syst. Sci., 23, 35–49, https://doi.org/10.5194/hess-23-35-2019, 2019. a
Quinn, J., Reed, P., Giuliani, M., and Castelletti, A.: What is controlling our control rules? Opening the black box of multi-reservoir operating policies using time-varying sensitivity analysis, Water Resour. Res., 55, 5962–5984, https://doi.org/10.1029/2018WR024177, 2019. a, b, c
Quinn, J. D., Reed, P. M., Giuliani, M., and Castelletti, A.: Rival framings: A framework for discovering how problem formulation uncertainties shape risk management trade-offs in water resources systems, Water Resour. Res., 53, 7208–7233, https://doi.org/10.1002/2017WR020524, 2017. a
Rauscher, S. A., Pal, J. S., Diffenbaugh, N. S., and Benedetti, M. M.: Future changes in snowmelt-driven runoff timing over the western US, Geophys. Res. Lett., 35, L16703, https://doi.org/10.1029/2008GL034424, 2008. a
Reinecke, R., Foglia, L., Mehl, S., Herman, J. D., Wachholz, A., Trautmann, T., and Döll, P.: Spatially distributed sensitivity of simulated global groundwater heads and flows to hydraulic conductivity, groundwater recharge, and surface water body parameterization, Hydrol. Earth Syst. Sci., 23, 4561–4582, https://doi.org/10.5194/hess-23-4561-2019, 2019. a
Reusser, D. E. and Zehe, E.: Inferring model structural deficits by analyzing temporal dynamics of model performance and parameter sensitivity, Water Resour. Res., 47, W07550, https://doi.org/10.1029/2010WR009946, 2011. a
Rougé, C., Reed, P. M., Grogan, D. S., Zuidema, S., Prusevich, A., Glidden, S., Lamontagne, J. R., and Lammers, R. B.: UpperSnakeRiver_reservoirs_WBM, GitHub, available at: https://github.com/charlesrouge/, last access: 15 September 2020. a
Ruano, M., Ribes, J., Seco, A., and Ferrer, J.: An improved sampling strategy based on trajectory design for application of the Morris method to systems with many input factors, Environ. Model. Softw., 37, 103–109, https://doi.org/10.1016/j.envsoft.2012.03.008, 2012. a
Sampson, C. C., Smith, A. M., Bates, P. D., Neal, J. C., Alfieri, L., and Freer, J. E.: A high-resolution global flood hazard model, Water Resour. Res., 51, 7358–7381, https://doi.org/10.1002/2015WR016954, 2015. a
Schmitt, R. J. P., Bizzi, S., Castelletti, A., and Kondolf, G. M.: Improved trade-offs of hydropower and sand connectivity by strategic dam planning in the Mekong, Nat. Sustain., 1, 96–104, https://doi.org/10.1038/s41893-018-0022-3, 2018. a
Schumann, G. J.-P., Stampoulis, D., Smith, A. M., Sampson, C. C., Andreadis, K. M., Neal, J. C., and Bates, P. D.: Rethinking flood hazard at the global scale, Geophys. Res. Lett., 43, 10249–10256, https://doi.org/10.1002/2016GL070260, 2016. a
Shin, S., Pokhrel, Y., and Miguez-Macho, G.: High-Resolution Modeling of Reservoir Release and Storage Dynamics at the Continental Scale, Water Resour. Res., 55, 787–810, https://doi.org/10.1029/2018WR023025, 2019. a, b
Steinfeld, H., Gerber, P., Wassenaar, T., Castel, V., Rosales, M., and de Haan, C.: Livestock's long shadow, Tech. Rep., Food and Agriculture Organisation of the United Nations (UN-FAO), available at: http://www.fao.org/docrep/010/a0701e/a0701e00.HTM (last access: 9 August 2018), 2006. a
Stewart, R., Wollheim, W., Miara, A., Vorosmarty, C., Fekete, B., Lammers, R., and Rosenzweig, B.: Horizontal Cooling Towers: Riverine Ecosystem Services and the Fate of Thermoelectric Heat in the Contemporary Northeast US, Environ. Res. Lett., 8, 025010, https://doi.org/10.1088/1748-9326/8/2/025010, 2013. a
Stewart, R. J., Wollheim, W. M., Gooseff, M. N., Briggs, M. A., Jacobs, J. M., Peterson, B. J., and Hopkinson, C. S.: Separation of river network-scale nitrogen removal among the main channel and two transient storage compartments, Water Resour. Res., 47, W00J10, https://doi.org/10.1029/2010WR009896, 2011. a
Thomas, C. A. and Lamke, R. D.: Floods of February 1962 in Southern Idaho and Northeastern Nevada, Tech. Rep., United States Geological Survey, Washington, D.C., 1962. a
Timpe, K. and Kaplan, D.: The changing hydrology of a dammed Amazon, Sci. Adv., 3, e1700611, https://doi.org/10.1126/sciadv.1700611, 2017. a
Turner, S. W. D., Xu, W., and Voisin, N.: Inferred inflow forecast horizons guiding reservoir release decisions across the United States, Hydrol. Earth Syst. Sci., 24, 1275–1291, https://doi.org/10.5194/hess-24-1275-2020, 2020. a
van Beek, L. P. H., Yoshihide, W., and P., B. M. F.: Global monthly water stress: 1. Water balance and water availability, Water Resour. Res., 47, W07517, https://doi.org/10.1029/2010WR009791, 2011. a
Veldkamp, T. I. E., Zhao, F., Ward, P. J., de Moel, H., Aerts, J. C. J. H., Schmied, H. M., Portmann, F. T., Masaki, Y., Pokhrel, Y., Liu, X., Satoh, Y., Gerten, D., Gosling, S. N., Zaherpour, J., and Wada, Y.: Human impact parameterizations in global hydrological models improve estimates of monthly discharges and hydrological extremes: a multi-model validation study, Environ. Res. Lett., 13, 055008, https://doi.org/10.1088/1748-9326/aab96f, 2018. a
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, 2013a. a, b, c, d
Voisin, N., Liu, L., Hejazi, M., Tesfa, T., Li, H., Huang, M., Liu, Y., and Leung, L. R.: One-way coupling of an integrated assessment model and a water resources model: evaluation and implications of future changes over the US Midwest, Hydrol. Earth Syst. Sci., 17, 4555–4575, https://doi.org/10.5194/hess-17-4555-2013, 2013b. a
Vörösmarty, C. J., Sharma, K. P., Fekete, B. M., Copeland, A. H., Holden, J., Marble, J., and Lough, J. A.: The Storage and Aging of Continental Runoff in Large Reservoir Systems of the World, Ambio, 26, 210–219, 1997. a
Wada, Y., van Beek, L. P. H., Viviroli, D., Dürr, 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, 2011. a
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. a, b
Wada, Y., Bierkens, M. F. P., de Roo, A., Dirmeyer, P. A., Famiglietti, J. S., Hanasaki, N., Konar, M., Liu, J., Müller Schmied, H., Oki, T., Pokhrel, Y., Sivapalan, M., Troy, T. J., van Dijk, A. I. J. M., van Emmerik, T., Va Huijgevoort, M. H. J., Van Lanen, H. A. J., Vörösmarty, C. J., Wanders, N., and Wheater, H.: Human–water interface in hydrological modelling: current status and future directions, Hydrol. Earth Syst. Sci., 21, 4169–4193, https://doi.org/10.5194/hess-21-4169-2017, 2017. a
Wanders, N., van Vliet, M. T. H., Wada, Y., Bierkens, M. F. P., and van Beek, L. P. H. R.: High-Resolution Global Water Temperature Modeling, Water Resour. Res., 55, 2760–2778, https://doi.org/10.1029/2018WR023250, 2019. a
Wang, K., Shi, H., Chen, J., and Li, T.: An improved operation-based reservoir scheme integrated with Variable Infiltration Capacity model for multiyear and multipurpose reservoirs, J. Hydrol., 571, 365–375, https://doi.org/10.1016/j.jhydrol.2019.02.006, 2019. a, b
Willmott, C. J., Rowe, C. M., and Mintz, Y.: Climatology of the terrestrial seasonal water cycle, J. Climatol., 5, 589–606, https://doi.org/10.1002/joc.3370050602, 1985. a
Wise, E. K.: Tree ring record of streamflow and drought in the upper Snake River, Water Resour. Res., 46, W11529, https://doi.org/10.1029/2010WR009282, 2010. a
Wise, E. K.: Hydroclimatology of the US Intermountain West, Prog. Phys. Geogr., 36, 458–479, https://doi.org/10.1177/0309133312446538, 2012. a
Wisser, D., Frolking, S., Douglas, E. M., Fekete, B. M., Vörösmarty, C. J., and Schumann, A. H.: Global irrigation water demand: Variability and uncertainties arising from agricultural and climate data sets, Geophys. Res. Lett., 35, l24408, https://doi.org/10.1029/2008GL035296, 2008. a
Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, L. P. H., Bierkens, M. F. P., Blyth, E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis, D., van de Giesen, N., Houser, P., Jaffé, P. R., Kollet, S., Lehner, B., Lettenmaier, D. P., Peters-Lidard, C., Sivapalan, M., Sheffield, J., Wade, A., and Whitehead, P.: Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water, Water Resour. Res., 47, W05301, https://doi.org/10.1029/2010WR010090, 2011. a, b
Wu, Y. and Chen, J.: An Operation-Based Scheme for a Multiyear and Multipurpose Reservoir to Enhance Macroscale Hydrologic Models, J. Hydrometeorol., 13, 270–283, https://doi.org/10.1175/JHM-D-10-05028.1, 2012. a, b
Yang, T., Gao, X., Sorooshian, S., and Li, X.: Simulating California reservoir operation using the classification and regression-tree algorithm combined with a shuffled cross-validation scheme, Water Resour. Res., 52, 1626–1651, https://doi.org/10.1002/2015WR017394, 2016. a
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. a, b
Yates, D., Sieber, J., Purkey, D., and Huber-Lee, A.: WEAP21 – A Demand-, Priority-, and Preference-Driven Water Planning Model, Water Int., 30, 487–500, https://doi.org/10.1080/02508060508691893, 2005. a
Yoshikawa, S., Cho, J., Yamada, H. G., Hanasaki, N., and Kanae, S.: An assessment of global net irrigation water requirements from various water supply sources to sustain irrigation: rivers and reservoirs (1960–2050), Hydrol. Earth Syst. Sci., 18, 4289–4310, https://doi.org/10.5194/hess-18-4289-2014, 2014.
a, b, c
Zagona, E. A., Fulp, T. J., Shane, R., Magee, T., and Goranflo, H. M.: Riverware: A Generalized Tool for Complex Reservoir System Modeling, J. Am. Water Resour. Assoc., 37, 913–929, https://doi.org/10.1111/j.1752-1688.2001.tb05522.x, 2001. a
Zaherpour, J., Gosling, S. N., Mount, N., Schmied, H. M., Veldkamp, T. I. E., Dankers, R., Eisner, S., Gerten, D., Gudmundsson, L., Haddeland, I., Hanasaki, N., Kim, H., Leng, G., Liu, J., Masaki, Y., Oki, T., Pokhrel, Y., Satoh, Y., Schewe, J., and Wada, Y.: Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts, Environ. Res. Lett., 13, 065015, https://doi.org/10.1088/1748-9326/aac547, 2018. a
Zajac, Z., Revilla-Romero, B., Salamon, P., Burek, P., Hirpa, F. A., and Beck, H.: The impact of lake and reservoir parameterization on global streamflow simulation, J. Hydrol., 548, 552–568, https://doi.org/10.1016/j.jhydrol.2017.03.022, 2017. a, b
Zarfl, C., Lumsdon, A. E., Berlekamp, J., Tydecks, L., and Tockner, K.: A global boom in hydropower dam construction, Aquat. Sci., 77, 161–170, https://doi.org/10.1007/s00027-014-0377-0, 2015. a
Zaveri, E., Grogan, D. S., Fisher-Vanden, K., Frolking, S., Lammers, R. B., Wrenn, D. H., Prusevich, A., and Nicholas, R. E.: Invisible water, visible impact: groundwater use and Indian agriculture under climate change, Environ. Res. Lett., 11, 084005, https://doi.org/10.1088/1748-9326/11/8/084005, 2016. a, b, c, d
Zhao, G., Gao, H., 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. a, b, c
Zuidema, S., Grogan, D., Prusevich, A., Lammers, R., Gilmore, S., and Williams, P.: Interplay of changing irrigation technologies and water reuse: example from the upper Snake River basin, Idaho, USA, Hydrol. Earth Syst. Sci., 24, 5231–5249, https://doi.org/10.5194/hess-24-5231-2020, 2020. a
Short summary
Amid growing interest in using large-scale hydrological models for flood and drought monitoring and forecasting, it is important to evaluate common assumptions these models make. We investigated the representation of reservoirs as separate (non-coordinated) infrastructure. We found that not appropriately representing coordination and control processes can lead a hydrological model to simulate flood and drought events that would not occur given the coordinated emergency response in the basin.
Amid growing interest in using large-scale hydrological models for flood and drought monitoring...
