Articles | Volume 26, issue 1
https://doi.org/10.5194/hess-26-71-2022
© Author(s) 2022. 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-26-71-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
06 Jan 2022
Research article | Highlight paper |
| 06 Jan 2022
| 06 Jan 2022
Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+
Hydrology and Hydraulic Engineering Department, Vrije Universiteit
Brussel (VUB), 1050 Brussels, Belgium
Celray James Chawanda
Hydrology and Hydraulic Engineering Department, Vrije Universiteit
Brussel (VUB), 1050 Brussels, Belgium
Jonas Jägermeyr
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Center for Climate Systems Research, Columbia University, New York,
NY 10025, USA
Climate Resilience, Potsdam Institute for Climate Impact Research
(PIK), Member of the Leibniz Association, 14412, Potsdam, Germany
Ann van Griensven
Hydrology and Hydraulic Engineering Department, Vrije Universiteit
Brussel (VUB), 1050 Brussels, Belgium
Water Science and Engineering Department, IHE Delft Institute for
Water Education, 2611 AX Delft, The Netherlands
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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Hydrol. Earth Syst. Sci., 27, 1683–1693, https://doi.org/10.5194/hess-27-1683-2023, https://doi.org/10.5194/hess-27-1683-2023, 2023
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To facilitate the meaningful participation of stakeholders in water management, model choice is crucial. We show how system dynamics models (SDMs), which are very visual and stakeholder-friendly, can be automatically combined with physically based hydrological models that may be more appropriate for modelling the water processes of a human–water system. This allows building participatory SDMs with stakeholders and delegating hydrological components to an external hydrological model.
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Hydrol. Earth Syst. Sci., 26, 4447–4468, https://doi.org/10.5194/hess-26-4447-2022, https://doi.org/10.5194/hess-26-4447-2022, 2022
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Studies using agro-hydrological models, like the Soil and Water Assessment Tool (SWAT), to map evapotranspiration (ET) do not account for cropping seasons. A comparison between the default SWAT+ set-up (with static land use representation) and a dynamic SWAT+ model set-up (with seasonal land use representation) is made by spatial mapping of the ET. The results show that ET with seasonal representation is closer to remote sensing estimates, giving better performance than ET with static land use.
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Human-controlled reservoirs have a large influence on the global water cycle. However, dam operations are rarely represented in Earth system models. We implement and evaluate a widely used reservoir parametrization in a global river-routing model. Using observations of individual reservoirs, the reservoir scheme outperforms the natural lake scheme. However, both schemes show a similar performance due to biases in runoff timing and magnitude when using simulated runoff.
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Sibyll Schaphoff, Werner von Bloh, Anja Rammig, Kirsten Thonicke, Hester Biemans, Matthias Forkel, Dieter Gerten, Jens Heinke, Jonas Jägermeyr, Jürgen Knauer, Fanny Langerwisch, Wolfgang Lucht, Christoph Müller, Susanne Rolinski, and Katharina Waha
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Tadesse Alemayehu, Ann van Griensven, Befekadu Taddesse Woldegiorgis, and Willy Bauwens
Hydrol. Earth Syst. Sci., 21, 4449–4467, https://doi.org/10.5194/hess-21-4449-2017, https://doi.org/10.5194/hess-21-4449-2017, 2017
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The goal of this paper is to improve the vegetation growth modelling in SWAT for tropical ecosystems. Therefore, we propose a straightforward but robust soil moisture index (SMI) – a quotient of rainfall (P) and reference evapotranspiration (ETr) – to dynamically initiate a new growth cycle within a predefined period. Our results for the Mara Basin (Kenya/Tanzania) show that the simulated LAI corresponds well with the MODIS LAI for for evergreen forest, savanna grassland and shrubland.
Lan T. Ha, Wim G. M. Bastiaanssen, Ann van Griensven, Albert I. J. M. van Dijk, and Gabriel B. Senay
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-251, https://doi.org/10.5194/hess-2017-251, 2017
Preprint withdrawn
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The paper shows a new approach in calibrating hydrological model using remote sensing data from open access sources. The innovation is that the parameters of the soil-vegetation processes were optimized that will make SWAT a useful tool for optimizing water conservation, agricultural outputs, and ecosystem services such as reduced soil erosion, better water quality standards, carbon sequestration, micro-climate cooling and appraising scenarios of green growth.
J. Jägermeyr, D. Gerten, J. Heinke, S. Schaphoff, M. Kummu, and W. Lucht
Hydrol. Earth Syst. Sci., 19, 3073–3091, https://doi.org/10.5194/hess-19-3073-2015, https://doi.org/10.5194/hess-19-3073-2015, 2015
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We present a process-based simulation of global irrigation systems for the world’s major crop types. This study advances the global quantification of irrigation systems while providing a framework for assessing potential future transitions in these systems, a prerequisite for refined simulation of crop yields under climate change. We reveal for many river basins the potential for sizeable water savings and related increases in water productivity through irrigation improvements.
M. Arias-Hidalgo, B. Bhattacharya, A. E. Mynett, and A. van Griensven
Hydrol. Earth Syst. Sci., 17, 2905–2915, https://doi.org/10.5194/hess-17-2905-2013, https://doi.org/10.5194/hess-17-2905-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
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Jean-Luc Martel, François Brissette, Richard Arsenault, Richard Turcotte, Mariana Castañeda-Gonzalez, William Armstrong, Edouard Mailhot, Jasmine Pelletier-Dumont, Gabriel Rondeau-Genesse, and Louis-Philippe Caron
Hydrol. Earth Syst. Sci., 29, 2811–2836, https://doi.org/10.5194/hess-29-2811-2025, https://doi.org/10.5194/hess-29-2811-2025, 2025
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This study compares long short-term memory (LSTM) neural networks with traditional hydrological models to predict future streamflow under climate change. Using data from 148 catchments, it finds that LSTM models, which learn from extensive data sequences, perform differently and often better than traditional hydrological models. The continental LSTM model, which includes data from diverse climate zones, is particularly effective for understanding climate impacts on water resources.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
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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We assessed the value of high-resolution data and parameter transferability across temporal scales based on seven catchments in northern China. We found that higher-resolution data do not always improve model performance, questioning the need for such data. Model parameters are transferable across different data resolutions but not across computational time steps. It is recommended to utilize a smaller computational time step when building hydrological models even without high-resolution data.
Wouter J. M. Knoben, Ashwin Raman, Gaby J. Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, Katie van Werkhoven, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 29, 2361–2375, https://doi.org/10.5194/hess-29-2361-2025, https://doi.org/10.5194/hess-29-2361-2025, 2025
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Hydrologic models are needed to provide simulations of water availability, floods, and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models and thus cannot easily be used to select an appropriate model for a specific place.
Chen Yang, Zitong Jia, Wenjie Xu, Zhongwang Wei, Xiaolang Zhang, Yiguang Zou, Jeffrey McDonnell, Laura Condon, Yongjiu Dai, and Reed Maxwell
Hydrol. Earth Syst. Sci., 29, 2201–2218, https://doi.org/10.5194/hess-29-2201-2025, https://doi.org/10.5194/hess-29-2201-2025, 2025
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We developed the first high-resolution, integrated surface water–groundwater hydrologic model of the entirety of continental China using ParFlow. The model shows good performance in terms of streamflow and water table depth when compared to global data products and observations. It is essential for water resources management and decision-making in China within a consistent framework in the changing world. It also has significant implications for similar modeling in other places in the world.
Haifan Liu, Haochen Yan, and Mingfu Guan
Hydrol. Earth Syst. Sci., 29, 2109–2132, https://doi.org/10.5194/hess-29-2109-2025, https://doi.org/10.5194/hess-29-2109-2025, 2025
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Land changes and landscape features critically impact water systems. Studying two watersheds in China’s Greater Bay Area, we found slope strongly influences water processes in mountainous areas. However, this relationship is weak in the lower regions of steeper watersheds. Urbanization leads to an increase in annual surface runoff, while flatter watersheds exhibit a buffering capacity against this effect. However, this buffering capacity diminishes with increasing annual rainfall intensity.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci., 29, 1981–2002, https://doi.org/10.5194/hess-29-1981-2025, https://doi.org/10.5194/hess-29-1981-2025, 2025
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Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite the fact that they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what they truly reflect in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and timescales for accurate drought characterization and monitoring.
Sebastian Gegenleithner, Manuel Pirker, Clemens Dorfmann, Roman Kern, and Josef Schneider
Hydrol. Earth Syst. Sci., 29, 1939–1962, https://doi.org/10.5194/hess-29-1939-2025, https://doi.org/10.5194/hess-29-1939-2025, 2025
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Accurate early-warning systems are crucial for reducing the damage caused by flooding events. In this study, we explored the potential of long short-term memory networks for enhancing the forecast accuracy of hydrologic models employed in operational flood forecasting. The presented approach elevated the investigated hydrologic model’s forecast accuracy for further ahead predictions and at flood event runoff.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
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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Common intuition holds that higher input data resolution leads to better results. To assess the benefits of high-resolution data, we conduct simulation experiments using data with various temporal resolutions across multiple catchments and find that higher-resolution data do not always improve model performance, challenging the necessity of pursuing such data. In catchments with small areas or significant flow variability, high-resolution data is more valuable.
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025, https://doi.org/10.5194/hess-29-1703-2025, 2025
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The quantification of precipitation into evaporation and runoff is vital for water resources management. The Budyko framework, based on aridity and evaporative indices of a catchment, can be an ideal tool for that. However, recent research highlights deviations of catchments from the expected evaporative index, casting doubt on its reliability. This study quantifies deviations of 2387 catchments, finding them minor and predictable. Integrating these into predictions upholds the framework's efficacy.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025, https://doi.org/10.5194/hess-29-1725-2025, 2025
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In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until we observe overparameterization.
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025, https://doi.org/10.5194/hess-29-1685-2025, 2025
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We generate operational forecasts of daily maximum stream water temperature for 32 consecutive days at 54 stations in Switzerland with our best-performing data-driven model. The average forecast error is 0.38 °C for 1 d ahead and increases to 0.90 °C for 32 d ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1749–1758, https://doi.org/10.5194/hess-29-1749-2025, https://doi.org/10.5194/hess-29-1749-2025, 2025
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Long short-term memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modelling. However, most studies focus on predictions at a daily scale, limiting the benefits of sub-daily (e.g. hourly) predictions in applications like flood forecasting. In this study, we introduce a new architecture, multi-frequency LSTM (MF-LSTM), designed to use inputs of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci., 29, 1615–1636, https://doi.org/10.5194/hess-29-1615-2025, https://doi.org/10.5194/hess-29-1615-2025, 2025
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Our study projects how climate change will affect the drying of river segments and stream networks in Europe, using advanced modelling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent and intense and will start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists for evaluating the ecological health of river ecosystem.
Tariq Aziz, Steven K. Frey, David R. Lapen, Susan Preston, Hazen A. J. Russell, Omar Khader, Andre R. Erler, and Edward A. Sudicky
Hydrol. Earth Syst. Sci., 29, 1549–1568, https://doi.org/10.5194/hess-29-1549-2025, https://doi.org/10.5194/hess-29-1549-2025, 2025
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This study determines the value of subsurface water for ecosystem services' supply in an agricultural watershed in Ontario, Canada. Using a fully integrated water model and an economic valuation approach, the research highlights subsurface water's critical role in maintaining watershed ecosystem services. The study informs on the sustainable use of subsurface water and introduces a new method for managing watershed ecosystem services.
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1277–1294, https://doi.org/10.5194/hess-29-1277-2025, https://doi.org/10.5194/hess-29-1277-2025, 2025
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Data-driven techniques have shown the potential to outperform process-based models in rainfall–runoff simulations. Hybrid models, combining both approaches, aim to enhance accuracy and maintain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions, we test their generalization capabilities for extreme hydrological events.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
Hydrol. Earth Syst. Sci., 29, 1061–1082, https://doi.org/10.5194/hess-29-1061-2025, https://doi.org/10.5194/hess-29-1061-2025, 2025
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This study reconstructs daily runoff in Switzerland (1962–2023) using a deep-learning model, providing a spatially contiguous dataset on a medium-sized catchment grid. The model outperforms traditional hydrological methods, revealing shifts in Swiss water resources, including more frequent dry years and declining summer runoff. The reconstruction is publicly available.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
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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Owing to differences in the existing published results, we conducted a detailed analysis of the runoff components and future trends in the Yarlung Tsangpo River basin and found that the contributions of snowmelt and glacier melt runoff to streamflow (both ~5 %) are limited and much lower than previous results. The streamflow in this area will continuously increase in the future, but the overestimated contribution of glacier melt could lead to an underestimation of this increasing trend.
Moritz Maximilian Heuer, Hadysa Mohajerani, and Markus Christian Casper
EGUsphere, https://doi.org/10.5194/egusphere-2025-636, https://doi.org/10.5194/egusphere-2025-636, 2025
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This study presents a calibration approach for water balance models. The different calibration steps aim at calibrating different hydrological processes: evapotranspiration, the runoff partitioning into surface runoff, interflow and groundwater recharge, as well as the groundwater behaviour. This allows for selection of a model parameterisation that correctly predicts the discharge at catchment outlet and simultaneously correctly depicts the underlying hydrological processes.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025, https://doi.org/10.5194/hess-29-903-2025, 2025
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This study develops an integrated framework based on the novel Driving index for changes in Precipitation–Runoff Relationships (DPRR) to explore the controlling changes in precipitation–runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation–runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025, https://doi.org/10.5194/hess-29-785-2025, 2025
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Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine learning (ML) models are increasingly being applied for flood forecasting. Such models are typically trained on large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets that maximise the spatio-temporal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025, https://doi.org/10.5194/hess-29-753-2025, 2025
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This study presents the first distributed hydrological simulation which confirms claims raised by historians that the eastward diversion project of the Tone River in Japan was conducted 4 centuries ago to increase low flows and subsequent travelling possibilities surrounding the capital, Edo (Tokyo), using inland navigation. We showed that great steps forward can be made for improving quality of life with small human engineering waterworks and small interventions in the regime of natural flows.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025, https://doi.org/10.5194/hess-29-683-2025, 2025
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This work investigates how hydrological models are transferred to a period in which climate conditions are different to the ones of the period in which they were set up. The robustness assessment test built to detect dependencies between model error and climatic drivers was applied to three hydrological models in 352 catchments in Denmark, France and Sweden. Potential issues are seen in a significant number of catchments for the models, even though the catchments differ for each model.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025, https://doi.org/10.5194/hess-29-627-2025, 2025
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Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 29, 447–463, https://doi.org/10.5194/hess-29-447-2025, https://doi.org/10.5194/hess-29-447-2025, 2025
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Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small catchments compared to large catchments, and spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show effects. The results can improve estimations of probabilities of extreme floods.
Ngo Nghi Truyen Huynh, Pierre-André Garambois, Benjamin Renard, François Colleoni, Jérôme Monnier, and Hélène Roux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3665, https://doi.org/10.5194/egusphere-2024-3665, 2025
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Understanding and modeling flash flood-prone areas remains challenging due to limited data and scale-relevant hydrological theory. While machine learning shows promise, its integration with process-based models is difficult. We present an approach incorporating machine learning into a high-resolution hydrological model to correct internal fluxes and transfer parameters between watersheds. Results show improved accuracy, advancing development of learnable and interpretable process-based models.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht H. Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci., 29, 335–360, https://doi.org/10.5194/hess-29-335-2025, https://doi.org/10.5194/hess-29-335-2025, 2025
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Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping to better prepare for and respond to floods.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
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To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their physical realism, which is measured by the ability of the model to reproduce observed system dynamics. Using a model to represent the dynamics of water and nitrate and dissolved organic carbon concentrations in an agricultural catchment, we showed that using solute-concentration data for calibration is useful to improve the hydrological consistency of the model.
Benjamin Guillaume, Adrien Michez, and Aurore Degré
EGUsphere, https://doi.org/10.5194/egusphere-2024-3978, https://doi.org/10.5194/egusphere-2024-3978, 2025
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Nature-based solutions (NbS) can mitigate floods and agricultural droughts by enhancing soil health and restoring hydrological cycles. This study highlights that leveraging soil diversity is key to optimizing NbS performance.
Haley A. Canham, Belize Lane, Colin B. Phillips, and Brendan P. Murphy
Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025, https://doi.org/10.5194/hess-29-27-2025, 2025
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The influence of watershed disturbances has proved challenging to disentangle from natural streamflow variability. This study evaluates the influence of time-varying hydrologic controls on rainfall–runoff in undisturbed and wildfire-disturbed watersheds using a novel time-series event separation method. Across watersheds, water year type and season influenced rainfall–runoff patterns. Accounting for these controls enabled clearer isolation of wildfire effects.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci., 28, 5511–5539, https://doi.org/10.5194/hess-28-5511-2024, https://doi.org/10.5194/hess-28-5511-2024, 2024
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Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
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This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Laia Estrada, Xavier Garcia, Joan Saló-Grau, Rafael Marcé, Antoni Munné, and Vicenç Acuña
Hydrol. Earth Syst. Sci., 28, 5353–5373, https://doi.org/10.5194/hess-28-5353-2024, https://doi.org/10.5194/hess-28-5353-2024, 2024
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Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological model, integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, https://doi.org/10.5194/hess-28-5331-2024, 2024
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Daniel T. Myers, David Jones, Diana Oviedo-Vargas, John Paul Schmit, Darren L. Ficklin, and Xuesong Zhang
Hydrol. Earth Syst. Sci., 28, 5295–5310, https://doi.org/10.5194/hess-28-5295-2024, https://doi.org/10.5194/hess-28-5295-2024, 2024
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We studied how streamflow and water quality models respond to land cover data collected by satellites during the growing season versus the non-growing season. The land cover data showed more trees during the growing season and more built areas during the non-growing season. We next found that the use of non-growing season data resulted in a higher modeled nutrient export to streams. Knowledge of these sensitivities would be particularly important when models inform water resource management.
Hatice Türk, Christine Stumpp, Markus Hrachowitz, Karsten Schulz, Peter Strauss, Günter Blöschl, and Michael Stockinger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-359, https://doi.org/10.5194/hess-2024-359, 2024
Revised manuscript accepted for HESS
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Using advances in transit time estimation and tracer data, we tested if fast-flow transit times are controlled solely by soil moisture or are also controlled by precipitation intensity. We used soil moisture-dependent and precipitation intensity-conditional transfer functions. We showed that significant portion of event water bypasses the soil matrix through fast flow paths (overland flow, tile drains, preferential flow paths) in dry soil conditions for both low and high-intensity precipitation.
Kevin R. Shook, Paul H. Whitfield, Christopher Spence, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 28, 5173–5192, https://doi.org/10.5194/hess-28-5173-2024, https://doi.org/10.5194/hess-28-5173-2024, 2024
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Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Pablo Fernando Dornes and Rocío Noelia Comas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-338, https://doi.org/10.5194/hess-2024-338, 2024
Revised manuscript accepted for HESS
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The Desaguadero-Salado-Chadiluevú-Curacó (DSCC) River is a semiarid river which is severely dammed in its tributaries which collect the snowmelt runoff. This runoff feeds mostly gravitational irrigation systems of very low efficiency. As a result, the DSCC River does not have natural runoff. The proposed Hydrological Regime Index (HRI) is able to discriminate and quantify regime alterations under permanent and non-permanent flow conditions and with low and high impoundment conditions.
Sylvain Payraudeau, Pablo Alvarez-Zaldivar, Paul van Dijk, and Gwenaël Imfeld
EGUsphere, https://doi.org/10.5194/egusphere-2024-2840, https://doi.org/10.5194/egusphere-2024-2840, 2024
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Our study focuses on the rising concern of pesticides damaging aquatic ecosystems, which puts drinking water, the environment, and human health at risk. We provided more accurate estimates of how pesticides break down and spread in small water systems, helping to improve pesticide management practices. By using unique chemical markers in our analysis, we enhanced the accuracy of our predictions, offering important insights for better protection of water sources and natural ecosystems.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
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We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Vishal Thakur, Yannis Markonis, Rohini Kumar, Johanna Ruth Thomson, Mijael Rodrigo Vargas Godoy, Martin Hanel, and Oldrich Rakovec
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-341, https://doi.org/10.5194/hess-2024-341, 2024
Revised manuscript accepted for HESS
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Understanding the changes in water movement in earth is crucial for everyone. To quantify this water movement there are several techniques. We examined how different methods of estimating evaporation impact predictions of various types of water movement across Europe. We found that, while these methods generally agree on whether changes are increasing or decreasing, they differ in magnitude. This means selecting the right evaporation method is crucial for accurate predictions of water movement.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Nan Wu, Ke Zhang, Amir Naghibi, Hossein Hashemi, Zhongrui Ning, Qinuo Zhang, Xuejun Yi, Haijun Wang, Wei Liu, Wei Gao, and Jerker Jarsjö
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-324, https://doi.org/10.5194/hess-2024-324, 2024
Revised manuscript accepted for HESS
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The hydrology of cold regions in the human population is poorly understood due to complex motion and limited data, hindering streamflow analysis. Using existing models, we compared runoff from an extended model with snowmelt and frozen ground, validating its reliability and integration. This study focuses on the effects of snowmelt and frozen ground on runoff, affecting precipitation type, surface-groundwater partitioning, and evapotranspiration.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
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We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
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This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
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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This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Francesco Zignol, William Lidberg, Caroline Greiser, Johannes Larson, Raúl Hoffrén, and Anneli M. Ågren
EGUsphere, https://doi.org/10.5194/egusphere-2024-2909, https://doi.org/10.5194/egusphere-2024-2909, 2024
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We investigated the factors influencing soil moisture variations across a boreal forest catchment in northern Sweden, where data is usually scarce. We found that soil moisture is shaped by topographical features, vegetation and soil characteristics, and weather conditions. The insights presented in this study will help improve models that predict soil moisture over space and time, which is crucial for forest management and nature conservation in the face of climate change and biodiversity loss.
Maria Elenius, Charlotta Pers, Sara Schützer, and Berit Arheimer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-271, https://doi.org/10.5194/hess-2024-271, 2024
Revised manuscript accepted for HESS
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Simulations of peatland rewetting in Sweden under various conditions of climate, local hydrology and rewetting practices showed insubstantial changes in landscape flow extremes due to mixing with runoff from various landcover. The impact on local hydrological extremes are governed by groundwater levels prior to rewetting and reduced tree cover, hence wetland allocation and management practices are crucial if the purpose is to reduce flow extremes in peatland streams.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
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A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
Short summary
Short summary
Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Cited articles
Abaci, O. and Papanicolaou, A. T.: Long-term effects of management practices
on water-driven soil erosion in an intense agricultural sub-watershed:
Monitoring and modelling, Hydrol. Process. Int. J., 23, 2818–2837, 2009.
Alemayehu, T., van Griensven, A., and Bauwens, W.: Evaluating CFSR and WATCH
Data as Input to SWAT for the Estimation of the Potential Evapotranspiration
in a Data-Scarce Eastern-African Catchment, J. Hydrol. Eng., 21, 05015028,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0001305, 2016.
Alemayehu, T., van Griensven, A., Woldegiorgis, B. T., and Bauwens, W.: An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems, Hydrol. Earth Syst. Sci., 21, 4449–4467, https://doi.org/10.5194/hess-21-4449-2017, 2017.
Arnold, J., Bieger, K., White, M., Srinivasan, R., Dunbar, J., and Allen,
P.: Use of decision tables to simulate management in SWAT+, Water, 10,
713, https://doi.org/10.3390/w10060713, 2018.
Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.: Large
Area Hydrologic Modeling and Assessment Part I: Model Development1, JAWRA J.
Am. Water Resour. Assoc., 34, 73–89,
https://doi.org/10.1111/j.1752-1688.1998.tb05961.x, 1998.
Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M.
J., Srinivasan, R., Santhi, C., Harmel, R. D., Van Griensven, A., and Van
Liew, M. W.: SWAT: Model use, calibration, and validation, Trans. ASABE, 55,
1491–1508, 2012.
Arnold, J. G., Kiniry, J. R., Srinivasan, R., Williams, J. R., Haney, E. B.,
and Neitsch, S. L.: SWAT 2012 input/output documentation, Texas Water
Resources Institute, 2013.
Asfaw, A., Simane, B., Hassen, A., and Bantider, A.: Variability and time
series trend analysis of rainfall and temperature in northcentral Ethiopia:
A case study in Woleka sub-basin, Weather Clim. Extrem., 19, 29–41,
https://doi.org/10.1016/j.wace.2017.12.002, 2018.
Bégué, A., Arvor, D., Bellon, B., Betbeder, J., De Abelleyra, D., P.
D. Ferraz, R., Lebourgeois, V., Lelong, C., Simões, M., and R.
Verón, S.: Remote Sensing and Cropping Practices: A Review, Remote
Sens., 10, 99, https://doi.org/10.3390/rs10010099, 2018.
Betrie, G. D., Mohamed, Y. A., van Griensven, A., and Srinivasan, R.: Sediment management modelling in the Blue Nile Basin using SWAT model, Hydrol. Earth Syst. Sci., 15, 807–818, https://doi.org/10.5194/hess-15-807-2011, 2011.
Bieger, K., Arnold, J. G., Rathjens, H., White, M. J., Bosch, D. D., Allen,
P. M., Volk, M., and Srinivasan, R.: Introduction to SWAT+, A Completely
Restructured Version of the Soil and Water Assessment Tool, JAWRA J. Am.
Water Resour. Assoc., 53, 115–130,
https://doi.org/10.1111/1752-1688.12482, 2017.
Burakowski, E., Tawfik, A., Ouimette, A., Lepine, L., Novick, K., Ollinger,
S., Zarzycki, C., and Bonan, G.: The role of surface roughness, albedo, and
Bowen ratio on ecosystem energy balance in the Eastern United States, Agric.
For. Meteorol., 249, 367–376,
https://doi.org/10.1016/j.agrformet.2017.11.030, 2018.
Camberlin, P.: Nile Basin Climates, in: The Nile: Origin, Environments,
Limnology and Human Use, edited by: Dumont, H. J., Springer Netherlands,
Dordrecht, 307–333,
https://doi.org/10.1007/978-1-4020-9726-3_16, 2009.
Chawanda, C. J., Arnold, J., Thiery, W., and Griensven, A. van: Mass balance
calibration and reservoir representations for large-scale hydrological
impact studies using SWAT+, Clim. Change, 163, 1307–1327,
https://doi.org/10.1007/s10584-020-02924-x, 2020.
Chen, F. and Xie, Z.: Effects of crop growth and development on regional
climate: a case study over East Asian monsoon area, Clim. Dyn., 38,
2291–2305, https://doi.org/10.1007/s00382-011-1125-y, 2012.
Eldardiry, H. and Hossain, F.: Understanding Reservoir Operating Rules in
the Transboundary Nile River Basin Using Macroscale Hydrologic Modeling with
Satellite Measurements, J. Hydrometeorol., 20, 2253–2269,
https://doi.org/10.1175/JHM-D-19-0058.1, 2019.
Eltahir, E. A. B.: A Soil Moisture–Rainfall Feedback Mechanism: 1. Theory
and observations, Water Resour. Res., 34, 765–776,
https://doi.org/10.1029/97WR03499, 1998.
Estel, S., Kuemmerle, T., Levers, C., Baumann, M., and Hostert, P.: Mapping
cropland-use intensity across Europe using MODIS NDVI time series, Environ.
Res. Lett., 11, 024015, https://doi.org/10.1088/1748-9326/11/2/024015, 2016.
FAO: Using remote sensing in support of solutions to reduce agricultural
water productivity gaps, Rome, Italy, available
at: https://www.fao.org/3/i7315en/i7315en.pdf (last access: 20 February 2021), 2018.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., and Roth, L.: The shuttle radar
topography mission, Rev. Geophys., 45, https://doi.org/10.1029/2005RG000183 (data available at: https://cgiarcsi.community/data/srtm-90m-digital-elevation-database-v4-1/, last access: 8 January 2021), 2007.
Fisher, J. B., Melton, F., Middleton, E., Hain, C., Anderson, M., Allen, R.,
McCabe, M. F., Hook, S., Baldocchi, D., Townsend, P. A., Kilic, A., Tu, K.,
Miralles, D. D., Perret, J., Lagouarde, J.-P., Waliser, D., Purdy, A. J.,
French, A., Schimel, D., Famiglietti, J. S., Stephens, G., and Wood, E. F.:
The future of evapotranspiration: Global requirements for ecosystem
functioning, carbon and climate feedbacks, agricultural management, and
water resources, Water Resour. Res., 53, 2618–2626,
https://doi.org/10.1002/2016WR020175, 2017.
Gong, T. T., Lei, H. M., Yang, D. W., Jiao, Y., and Yang, H. B.: Effects of vegetation change on evapotranspiration in a semiarid shrubland of the Loess Plateau, China, Hydrol. Earth Syst. Sci. Discuss., 11, 13571–13605, https://doi.org/10.5194/hessd-11-13571-2014, 2014.
Ha, L. T., Bastiaanssen, W. G. M., Van Griensven, A., Van Dijk, A. I. J. M.,
and Senay, G. B.: Calibration of Spatially Distributed Hydrological
Processes and Model Parameters in SWAT Using Remote Sensing Data and an
Auto-Calibration Procedure: A Case Study in a Vietnamese River Basin, Water,
10, 212, https://doi.org/10.3390/w10020212, 2018.
Haregeweyn, N., Tsunekawa, A., Nyssen, J., Poesen, J., Tsubo, M., Tsegaye
Meshesha, D., Schütt, B., Adgo, E., and Tegegne, F.: Soil erosion and
conservation in Ethiopia: A review, Prog. Phys. Geogr. Earth Environ., 39,
750–774, https://doi.org/10.1177/0309133315598725, 2015.
Haregeweyn, N., Tsunekawa, A., Poesen, J., Tsubo, M., Meshesha, D. T.,
Fenta, A. A., Nyssen, J., and Adgo, E.: Comprehensive assessment of soil
erosion risk for better land use planning in river basins: Case study of the
Upper Blue Nile River, Sci. Total Environ., 574, 95–108,
https://doi.org/10.1016/j.scitotenv.2016.09.019, 2017.
Hengl, T., Heuvelink, G. B. M., Kempen, B., Leenaars, J. G. B., Walsh, M.
G., Shepherd, K. D., Sila, A., MacMillan, R. A., Jesus, J. M. de, Tamene,
L., and Tondoh, J. E.: Mapping Soil Properties of Africa at 250 m
Resolution: Random Forests Significantly Improve Current Predictions, PLOS
ONE, 10, e0125814, https://doi.org/10.1371/journal.pone.0125814 (data available at: https://www.isric.org/projects/africa-soil-information-service-afsis, last access: 25 January 2021), 2015.
Hilker, T., Lyapustin, A. I., Tucker, C. J., Hall, F. G., Myneni, R. B.,
Wang, Y., Bi, J., de Moura, Y. M., and Sellers, P. J.: Vegetation dynamics
and rainfall sensitivity of the Amazon, P. Natl. Acad. Sci. USA, 111,
16041–16046, 2014.
Hurni, H.: Erosion-productivity-conservation systems in Ethiopia, Proceedings 4th International Conference on Soil Conservation, Maracay, Venezuela, 654–674, 1985.
Hurtt, G. C., Chini, L., Sahajpal, R., Frolking, S., Bodirsky, B. L., Calvin, K., Doelman, J. C., Fisk, J., Fujimori, S., Klein Goldewijk, K., Hasegawa, T., Havlik, P., Heinimann, A., Humpenöder, F., Jungclaus, J., Kaplan, J. O., Kennedy, J., Krisztin, T., Lawrence, D., Lawrence, P., Ma, L., Mertz, O., Pongratz, J., Popp, A., Poulter, B., Riahi, K., Shevliakova, E., Stehfest, E., Thornton, P., Tubiello, F. N., van Vuuren, D. P., and Zhang, X.: Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6, Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020 (data available at: https://luh.umd.edu/, last access: 31 January 2021), 2020.
Iizumi, T., Kim, W., and Nishimori, M.: Modeling the Global Sowing and
Harvesting Windows of Major Crops Around the Year 2000, J. Adv. Model. Earth
Syst., 11, 99–112, https://doi.org/10.1029/2018MS001477, 2019.
Jägermeyr, J., Müller, C., Ruane, A. C., Elliott, J., Balkovic, J.,
Castillo, O., Faye, B., Foster, I., Folberth, C., Franke, J. A., Fuchs, K.,
Guarin, J. R., Heinke, J., Hoogenboom, G., Iizumi, T., Jain, A. K., Kelly,
D., Khabarov, N., Lange, S., Lin, T.-S., Liu, W., Mialyk, O., Minoli, S.,
Moyer, E. J., Okada, M., Phillips, M., Porter, C., Rabin, S. S., Scheer, C.,
Schneider, J. M., Schyns, J. F., Skalsky, R., Smerald, A., Stella, T.,
Stephens, H., Webber, H., Zabel, F., and Rosenzweig, C.: Climate impacts on
global agriculture emerge earlier in new generation of climate and crop
models, Nat. Food, 2, 873–885, https://doi.org/10.1038/s43016-021-00400-y (data available at: https://doi.org/10.5281/zenodo.5062513),
2021.
Lange, S.: EartH2Observe, WFDEI and ERA-Interim data Merged and
Bias-corrected for ISIMIP (EWEMBI), GFZ Data Services [data], https://doi.org/10.5880/PIK.2016.004,
2016.
Leff, B., Ramankutty, N., and Foley, J. A.: Geographic distribution of major
crops across the world, Glob. Biogeochem. Cycles, 18, GB1009,
https://doi.org/10.1029/2003GB002108, 2004.
Li, L., Friedl, M. A., Xin, Q., Gray, J., Pan, Y., and Frolking, S.: Mapping
Crop Cycles in China Using MODIS-EVI Time Series, Remote Sens., 6,
2473–2493, https://doi.org/10.3390/rs6032473, 2014.
Lin, J., Zhang, J., Gu, Z., Chen, J., and Lyu, H.: A new approach of
assessing soil erosion using the remotely sensed leaf area index and its
application in the hilly area, Yegetos, Int. J. Plant Res., 27, 1–12, 2014.
Lokupitiya, E., Denning, S., Paustian, K., Baker, I., Schaefer, K., Verma, S., Meyers, T., Bernacchi, C. J., Suyker, A., and Fischer, M.: Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands, Biogeosciences, 6, 969–986, https://doi.org/10.5194/bg-6-969-2009, 2009.
Lotsch, A., Friedl, M. A., Anderson, B. T., and Tucker, C. J.: Coupled
vegetation-precipitation variability observed from satellite and climate
records, Geophys. Res. Lett., 30, 1774, https://doi.org/10.1029/2003GL017506,
2003.
Lu, C. and Tian, H.: Global nitrogen and phosphorus fertilizer use for agriculture production in the past half century: shifted hot spots and nutrient imbalance, Earth Syst. Sci. Data, 9, 181–192, https://doi.org/10.5194/essd-9-181-2017 (data available at: https://doi.org/10.1594/PANGAEA.863323), 2017.
M. El-Marsafawy, S., Swelam, A., and Ghanem, A.: Evolution of Crop Water
Productivity in the Nile Delta over Three Decades (1985–2015), Water, 10,
1168, https://doi.org/10.3390/w10091168, 2018.
Ma, T., Duan, Z., Li, R., and Song, X.: Enhancing SWAT with remotely sensed
LAI for improved modelling of ecohydrological process in subtropics, J.
Hydrol., 570, 802–815, https://doi.org/10.1016/j.jhydrol.2019.01.024, 2019.
Makowski, D., Nesme, T., Papy, F., and Doré, T.: Global agronomy, a new
field of research. A review, Agron. Sustain. Dev., 34, 293–307,
https://doi.org/10.1007/s13593-013-0179-0, 2014.
Metzner, J. R. and Barnes, B. H.: Decision table languages and systems, Academic Press, ISBN 978-1483205366, 2014.
Molnár, D. K. and Julien, P. Y.: Estimation of upland erosion using GIS,
Comput. Geosci., 24, 183–192,
https://doi.org/10.1016/S0098-3004(97)00100-3, 1998.
Monteith, J. L.: Radiation and crops, Exp. Agric., 1, 241–251, 1965.
Msigwa, A., Komakech, H. C., Verbeiren, B., Salvadore, E., Hessels, T.,
Weerasinghe, I., and van Griensven, A.: Accounting for Seasonal Land Use
Dynamics to Improve Estimation of Agricultural Irrigation Water Withdrawals,
Water, 11, 2471, https://doi.org/10.3390/w11122471, 2019.
Mueller, B., Seneviratne, S. I., Jimenez, C., Corti, T., Hirschi, M.,
Balsamo, G., Ciais, P., Dirmeyer, P., Fisher, J. B., Guo, Z., Jung, M.,
Maignan, F., McCabe, M. F., Reichle, R., Reichstein, M., Rodell, M.,
Sheffield, J., Teuling, A. J., Wang, K., Wood, E. F., and Zhang, Y.:
Evaluation of global observations-based evapotranspiration datasets and IPCC
AR4 simulations, Geophys. Res. Lett., 38, 3–10,
https://doi.org/10.1029/2010GL046230, 2011.
Muthoni, F. K., Odongo, V. O., Ochieng, J., Mugalavai, E. M., Mourice, S.
K., Hoesche-Zeledon, I., Mwila, M., and Bekunda, M.: Long-term
spatial-temporal trends and variability of rainfall over Eastern and
Southern Africa, Theor. Appl. Climatol., 137, 1869–1882,
https://doi.org/10.1007/s00704-018-2712-1, 2019.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Williams, J. R., and King, K.
W.: SWAT theoretical documentation, Soil Water Res. Lab. Grassl., 494,
234–235, 2005.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., and Williams, J. R.: Soil and
water assessment tool theoretical documentation version 2009, Texas Water
Resources Institute, 2011.
Ngetich, K. F., Mucheru-Muna, M., Mugwe, J. N., Shisanya, C. A., Diels, J.,
and Mugendi, D. N.: Length of growing season, rainfall temporal
distribution, onset and cessation dates in the Kenyan highlands, Agric. For.
Meteorol., 188, 24–32, https://doi.org/10.1016/j.agrformet.2013.12.011,
2014.
Nile Basin Initiative: Land use/cover in the Nile Basin – Nile Basin Water
Resources Atlas, available at: https://atlas.nilebasin.org/treatise/land-usecover-in-the-nile-basin/ (last access: 8 January 2021), 2016.
Nkwasa, A., Chawanda, C. J., Msigwa, A., Komakech, H. C., Verbeiren, B., and
van Griensven, A.: How Can We Represent Seasonal Land Use Dynamics in SWAT
and SWAT+ Models for African Cultivated Catchments?, Water, 12, 1541,
https://doi.org/10.3390/w12061541, 2020.
Nkwasa, A.: Agricultural land use and crop management implementation in large-scale SWAT+ model applications, Zenodo [code], https://doi.org/10.5281/zenodo.5797553, 2021.
O'Neal, M. R., Nearing, M. A., Vining, R. C., Southworth, J., and Pfeifer,
R. A.: Climate change impacts on soil erosion in Midwest United States with
changes in crop management, Catena, 61, 165–184, 2005.
Onyutha, C. and Willems, P.: Spatial and temporal variability of rainfall in the Nile Basin, Hydrol. Earth Syst. Sci., 19, 2227–2246, https://doi.org/10.5194/hess-19-2227-2015, 2015.
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, Glob. Biogeochem.
Cycles, 24, GB1011, https://doi.org/10.1029/2008GB003435, 2010.
Potter, P., Ramankutty, N., Bennett, E. M., and Donner, S. D.:
Characterizing the spatial patterns of global fertilizer application and
manure production, Earth Interact., 14, 1–22, 2010.
Qi, J., Zhang, X., Yang, Q., Srinivasan, R., Arnold, J. G., Li, J.,
Waldholf, S. T., and Cole, J.: SWAT ungauged: Water quality modeling in the
Upper Mississippi River Basin, J. Hydrol., 584, 124601,
https://doi.org/10.1016/j.jhydrol.2020.124601, 2020.
Rajib, A., Kim, I. L., Golden, H. E., Lane, C. R., Kumar, S. V., Yu, Z., and
Jeyalakshmi, S.: Watershed Modeling with Remotely Sensed Big Data: MODIS
Leaf Area Index Improves Hydrology and Water Quality Predictions, Remote
Sens., 12, 2148, https://doi.org/10.3390/rs12132148, 2020.
Raymond, P. A., Oh, N.-H., Turner, R. E., and Broussard, W.:
Anthropogenically enhanced fluxes of water and carbon from the Mississippi
River, Nature, 451, 449–452, https://doi.org/10.1038/nature06505, 2008.
Rounsevell, M. D. A., Annetts, J. E., Audsley, E., Mayr, T., and Reginster,
I.: Modelling the spatial distribution of agricultural land use at the
regional scale, Agric. Ecosyst. Environ., 95, 465–479,
https://doi.org/10.1016/S0167-8809(02)00217-7, 2003.
Schuol, J. and Abbaspour, K. C.: Calibration and uncertainty issues of a
hydrological model (SWAT) applied to West Africa, Adv. Geosci., 9, 137–143,
2006.
Schuol, J., Abbaspour, K. C., Yang, H., Srinivasan, R., and Zehnder, A. J.
B.: Modeling blue and green water availability in Africa, Water Resour.
Res., 44, 1–18, https://doi.org/10.1029/2007WR006609, 2008.
Siad, S. M., Iacobellis, V., Zdruli, P., Gioia, A., Stavi, I., and
Hoogenboom, G.: A review of coupled hydrologic and crop growth models,
Agric. Water Manag., 224, 105746,
https://doi.org/10.1016/j.agwat.2019.105746, 2019.
Siebert, S., Henrich, V., Frenken, K., and Burke, J.: Global map of
irrigation areas version 5, Rheinische Friedrich-Wilhelms-Univ. Bonn Ger.
Agric. Organ. U. N. Rome Italy, 2, 1299–1327, available at: https://www.fao.org/aquastat/en/geospatial-information/global-maps-irrigated-areas/latest-version/ (last access: 16 February 2021), 2013.
Sietz, D., Conradt, T., Krysanova, V., Hattermann, F. F., and Wechsung, F.:
The Crop Generator: Implementing crop rotations to effectively advance
eco-hydrological modelling, Agric. Syst., 193, 103183,
https://doi.org/10.1016/j.agsy.2021.103183, 2021.
Sood, A. and Smakhtin, V.: Global hydrological models: a review, Hydrol.
Sci. J., 60, 549–565, https://doi.org/10.1080/02626667.2014.950580, 2015.
Souza, V. F. C. de, Bertol, I., and Wolschick, N. H.: Effects of soil
management practices on water erosion under natural rainfall conditions on a
Humic Dystrudept, Rev. Bras. Ciênc. Solo, 41, 1–14, https://doi.org/10.1590/18069657rbcs20160443, 2017.
Srinivasan, R., Zhang, X., and Arnold, J.: SWAT ungauged: hydrological
budget and crop yield predictions in the Upper Mississippi River Basin,
Trans. ASABE, 53, 1533–1546, 2010.
Srivastava, A., Kumari, N., and Maza, M.: Hydrological Response to
Agricultural Land Use Heterogeneity Using Variable Infiltration Capacity
Model, Water Resour. Manag., 34, 3779–3794,
https://doi.org/10.1007/s11269-020-02630-4, 2020.
Sugita, M., Matsuno, A., El-Kilani, R. M. M., Abdel-Fattah, A., and Mahmoud,
M. A.: Crop evapotranspiration in the Nile Delta under different irrigation
methods, Hydrol. Sci. J., 62, 1618–1635,
https://doi.org/10.1080/02626667.2017.1341631, 2017.
Sundborg, A. and White, W. R.: Sedimentation problems in river basins,
France, ISBN 9789231020148, 1982.
Swain, A.: Challenges for water sharing in the Nile basin: changing
geo-politics and changing climate, Hydrol. Sci. J., 56, 687–702,
https://doi.org/10.1080/02626667.2011.577037, 2011.
Tamene, L. and Le, Q. B.: Estimating soil erosion in sub-Saharan Africa
based on landscape similarity mapping and using the revised universal soil
loss equation (RUSLE), Nutr. Cycl. Agroecosystems, 102, 17–31,
https://doi.org/10.1007/s10705-015-9674-9, 2015.
Twine, T. E., Kucharik, C. J., and Foley, J. A.: Effects of Land Cover
Change on the Energy and Water Balance of the Mississippi River Basin, J.
Hydrometeorol., 5, 640–655,
https://doi.org/10.1175/1525-7541(2004)005<0640:EOLCCO>2.0.CO;2, 2004.
van Griensven, A., Ndomba, P., Yalew, S., and Kilonzo, F.: Critical review of SWAT applications in the upper Nile basin countries, Hydrol. Earth Syst. Sci., 16, 3371–3381, https://doi.org/10.5194/hess-16-3371-2012, 2012.
Viña, A., Gitelson, A. A., Nguy-Robertson, A. L., and Peng, Y.:
Comparison of different vegetation indices for the remote assessment of
green leaf area index of crops, Remote Sens. Environ., 115, 3468–3478,
https://doi.org/10.1016/j.rse.2011.08.010, 2011.
Waha, K., Müller, C., Bondeau, A., Dietrich, J. P., Kurukulasuriya, P.,
Heinke, J., and Lotze-Campen, H.: Adaptation to climate change through the
choice of cropping system and sowing date in sub-Saharan Africa, Glob.
Environ. Change, 23, 130–143,
https://doi.org/10.1016/j.gloenvcha.2012.11.001, 2013.
Waha, K., Dietrich, J. P., Portmann, F. T., Siebert, S., Thornton, P. K.,
Bondeau, A., and Herrero, M.: Multiple cropping systems of the world and the
potential for increasing cropping intensity, Glob. Environ. Change, 64,
102131, https://doi.org/10.1016/j.gloenvcha.2020.102131, 2020.
Wang, L., Good, S. P., and Caylor, K. K.: Global synthesis of vegetation
control on evapotranspiration partitioning, Geophys. Res. Lett., 41,
6753–6757, https://doi.org/10.1002/2014GL061439, 2014.
Williams, J. R. and Berndt, H. D.: Sediment yield prediction based on
watershed hydrology, Trans. ASAE, 20, 1100–1104, 1977.
Williams, J. R. and Singh, V.: The EPIC Model, Computer models of watershed
hydrology, Water Resour. Publ. Highl. Ranch Colo., 909–1000, 1995.
Xiong, J., Thenkabail, P. S., Gumma, M. K., Teluguntla, P., Poehnelt, J.,
Congalton, R. G., Yadav, K., and Thau, D.: Automated cropland mapping of
continental Africa using Google Earth Engine cloud computing, ISPRS J.
Photogramm. Remote Sens., 126, 225–244,
https://doi.org/10.1016/j.isprsjprs.2017.01.019, 2017.
Yin, X. and Struik, P. C.: C3 and C4 photosynthesis models: An overview from
the perspective of crop modelling, NJAS – Wagening. J. Life Sci., 57,
27–38, https://doi.org/10.1016/j.njas.2009.07.001, 2009.
Zhang, X., Friedl, M. A., Schaaf, C. B., Strahler, A. H., and Liu, Z.:
Monitoring the response of vegetation phenology to precipitation in Africa
by coupling MODIS and TRMM instruments, J. Geophys. Res.-Atmos., 110, D12103,
https://doi.org/10.1029/2004JD005263, 2005.
Zhang, Y., Wu, Z., Singh, V. P., He, H., He, J., Yin, H., and Zhang, Y.:
Coupled hydrology-crop growth model incorporating an improved
evapotranspiration module, Agric. Water Manag., 246, 106691,
https://doi.org/10.1016/j.agwat.2020.106691, 2021.
Zhao, W., Fu, B., and Qiu, Y.: An Upscaling Method for Cover-Management
Factor and Its Application in the Loess Plateau of China, Int. J. Environ.
Res. Public. Health, 10, 4752–4766, https://doi.org/10.3390/ijerph10104752,
2013.
Short summary
We present an approach on how to incorporate crop phenology in a regional hydrological model using decision tables and global datasets of rainfed and irrigated cropland with the associated cropping calendar and management practices. Results indicate improved temporal patterns of leaf area index (LAI) and evapotranspiration (ET) simulations in comparison with remote sensing data. In addition, the improvement of the cropping season also helps to improve soil erosion estimates in cultivated areas.
We present an approach on how to incorporate crop phenology in a regional hydrological model...
