Articles | Volume 20, issue 1
https://doi.org/10.5194/hess-20-529-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-529-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Feb 2016
Research article |
| 01 Feb 2016
Integrated water system simulation by considering hydrological and biogeochemical processes: model development, with parameter sensitivity and autocalibration
Y. Y. Zhang
CORRESPONDING AUTHOR
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Q. X. Shao
CORRESPONDING AUTHOR
CSIRO Digital Productivity Flagship, Leeuwin Centre, 65 Brockway Road, Floreat Park, WA 6014, Australia
College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
H. T. Xing
CSIRO Agriculture Flagship, GPO BOX 1666, Canberra, ACT 2601, Australia
J. Xia
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
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EGUsphere, https://doi.org/10.5194/egusphere-2024-3476, https://doi.org/10.5194/egusphere-2024-3476, 2024
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The classic logistic function characterizes the stationary relationship between drought loss and intensity. This paper incorporates the time into the three parameters of logistic function and derives three nonstationary intensity loss functions. The functions are tested through a case study of drought-affected population by province in mainland China during the period from 2006 to 2023. Overall, the nonstationary intensity loss functions are shown to be a useful tool for drought management.
Yongyong Zhang, Yongqiang Zhang, Xiaoyan Zhai, Jun Xia, Qiuhong Tang, Wei Wang, Jian Wu, Xiaoyu Niu, and Bing Han
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-126, https://doi.org/10.5194/hess-2024-126, 2024
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It is challenging to investigate flood variabilities and their formation mechanisms from massive event samples. This study explores spatiotemporal variabilities of 1446 flood events using hierarchical and partitional clustering methods. Control mechanisms of meteorological and physio-geographical factors are explored for individual flood event classes using constrained rank analysis. It provides insights into comprehensive changes of flood events, and aids in flood prediction and control.
Tongtiegang Zhao, Zecong Chen, and Yongyong Zhang
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The classic logistic function characterizes the stationary relationship between drought loss and intensity. This paper incorporates the time into the three parameters of logistic function and derives three nonstationary intensity loss functions. The functions are tested through a case study of drought-affected population by province in mainland China during the period from 2006 to 2023. Overall, the nonstationary intensity loss functions are shown to be a useful tool for drought management.
Yongyong Zhang, Yongqiang Zhang, Xiaoyan Zhai, Jun Xia, Qiuhong Tang, Wei Wang, Jian Wu, Xiaoyu Niu, and Bing Han
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-126, https://doi.org/10.5194/hess-2024-126, 2024
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It is challenging to investigate flood variabilities and their formation mechanisms from massive event samples. This study explores spatiotemporal variabilities of 1446 flood events using hierarchical and partitional clustering methods. Control mechanisms of meteorological and physio-geographical factors are explored for individual flood event classes using constrained rank analysis. It provides insights into comprehensive changes of flood events, and aids in flood prediction and control.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
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Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Song Wang, Carlos Sierra, Yiqi Luo, Jinsong Wang, Weinan Chen, Yahai Zhang, Aizhong Ye, and Shuli Niu
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-33, https://doi.org/10.5194/bg-2023-33, 2023
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Nitrogen is important for plant growth and carbon uptake, which is uaually limited in nature and can constrain carbon storage and impact efforts to combat climate change. We developed a new method of combining data and models to determine if and how much an ecosystem is nitrogen limited. This new method can help determine if and to what extent an ecosystem is nitrogen-limited, providing insight into nutrient limitations on a global scale and guiding ecosystem management decisions.
Feng Ma, Lifeng Luo, Aizhong Ye, and Qingyun Duan
Hydrol. Earth Syst. Sci., 22, 5697–5709, https://doi.org/10.5194/hess-22-5697-2018, https://doi.org/10.5194/hess-22-5697-2018, 2018
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Predicting meteorological droughts more than 2 months in advance became difficult due to low predictability, leading to weak skill for hydrological droughts in wet seasons. Hydrological drought forecasts showed skills up to 3–6 lead months due to the memory of initial hydrologic conditions in dry seasons. Human activities have increased hydrological predictability during wet seasons in the MHRB. This fills gaps in understanding drought and predictability predictions in endorheic and arid basins.
Xing Yuan, Feng Ma, Linying Wang, Ziyan Zheng, Zhuguo Ma, Aizhong Ye, and Shaoming Peng
Hydrol. Earth Syst. Sci., 20, 2437–2451, https://doi.org/10.5194/hess-20-2437-2016, https://doi.org/10.5194/hess-20-2437-2016, 2016
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An experimental seasonal hydrological forecasting system is established over the Yellow River basin to provide adaptive support in a changing environment. The system consists of downscaled NMME climate prediction, hydrological models calibrated against naturalized streamflow along the mainstream, and a post-processor to account for the human interventions implicitly. As the first paper of a two-part series, this paper investigates the hydrological predictability by using reverse ESP simulations.
W. Gong, Q. Duan, J. Li, C. Wang, Z. Di, Y. Dai, A. Ye, and C. Miao
Hydrol. Earth Syst. Sci., 19, 2409–2425, https://doi.org/10.5194/hess-19-2409-2015, https://doi.org/10.5194/hess-19-2409-2015, 2015
Y. Y. Zhang, Q. X. Shao, A. Z. Ye, and H. T. Xing
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-9219-2014, https://doi.org/10.5194/hessd-11-9219-2014, 2014
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Y. Mao, A. Ye, J. Xu, F. Ma, X. Deng, C. Miao, W. Gong, and Z. Di
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-7441-2014, https://doi.org/10.5194/hessd-11-7441-2014, 2014
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J. Li, Q. Y. Duan, W. Gong, A. Ye, Y. Dai, C. Miao, Z. Di, C. Tong, and Y. Sun
Hydrol. Earth Syst. Sci., 17, 3279–3293, https://doi.org/10.5194/hess-17-3279-2013, https://doi.org/10.5194/hess-17-3279-2013, 2013
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Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
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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
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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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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.
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.
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.
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.
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.
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.
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.
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.
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. Discuss., https://doi.org/10.5194/hess-2024-292, https://doi.org/10.5194/hess-2024-292, 2024
Revised manuscript accepted for HESS
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We developed the first high-resolution, integrated surface water-groundwater hydrologic model of the entire continental China using ParFlow. The model shows good performance 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.
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.
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. Discuss., https://doi.org/10.5194/hess-2024-279, https://doi.org/10.5194/hess-2024-279, 2024
Revised manuscript accepted for HESS
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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.
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
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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.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
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We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
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Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-221, https://doi.org/10.5194/hess-2024-221, 2024
Revised manuscript accepted for HESS
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Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what it truly reflects 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 time scales for accurate drought characterization and monitoring.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
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An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2133, https://doi.org/10.5194/egusphere-2024-2133, 2024
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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 hydrolgical models. The continental LSTM model, which includes data from diverse climate zones, is particularly effective for understanding climate impacts on water resources.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
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The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
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By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
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Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
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Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2024-1438, https://doi.org/10.5194/egusphere-2024-1438, 2024
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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 conducted simulation experiments using data with various temporal resolutions across multiple catchments, and found that higher resolution data does 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.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
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Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
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Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Cited articles
Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and Rasmussen, J.:
An Introduction to the European System: Systeme Hydrologique Europeen (SHE),
J. Hydrol., 87, 61–77, 1986.
Abrahamsen, P. and Hansen, S. D.: an open soil-crop-atmosphere system
model, Environ. Model. Softw., 15, 313–330, 2000.
Arheimer, B. and Brandt, M.: Modelling nitrogen transport and retention in
the catchments of southern Sweden, Ambio, 27, 471–480, 1998.
Arheimer, B. and Brandt, M.: Watershed modelling of non-point nitrogen
pollution from arable land to the Swedish coast in 1985 and 1994, Ecol.
Engin.,
14, 389–404, 2000.
Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.:
Large-area hydrologic modeling and assessment: Part I. Model development,
J. Am. Water Resour. Assoc., 34, 73–89, 1998.
Beven, K. J.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36,
2006.
Beven, K. J. and Kirkby, M. J.: A physically based variable contributing area
model of basin hydrology, Hydrol. Sci. Bull., 24, 43–69, 1979.
Bicknell, B. R., Imhoff, J. C., Kittle, J. L., Donigian, A. S., and
Johanson, R. C.: Hydrologic Simulation Program – FORTRAN (HSPF): User's
Manual for Release 10, Report No. EPA/600/R–93/174, US EPA
Environmental Research Lab, Athens, Ga, 1993.
Borah, D. K. and Bera, M.: Watershed-scale hydrologic and nonpoint-source
pollution models: Review of application, Trans. ASAE, 47, 789–803, 2004.
Bouraoui, F. and Dillaha, T. A.: ANSWERS – 2000: Runoff and sediment transport
model, J. Environ. Eng., 122, 493–502, 1996.
Brown, L. C. and Barnwell, T. O.: The enhanced stream water quality models
QUAL2E and QUAL2E-UNCAS: documentation and user manual, Tufts University and
Env. Res. Laboratory, US EPA, Athens, Georgia, 1987.
Burt, T. P. and Pinay, G.: Linking hydrology and biogeochemistry in complex
landscapes, Prog. Phys. Geog., 29, 297–316, 2005.
China's national standard (CNS): Current land use condition classification (GB/T21010–2007), General
administration of quality supervision, inspection and quarantine of China
and Standardization administration of China, Beijing, China, 2007.
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T.: A fast and elitist
multiobjective genetic algorithm: NSGA–II, IEEE T. Evolut. Comput., 6, 182–197, 2002.
Deng, J., Zhu, B., Zhou, Z. X., Zheng, X. H., Li, C. S., Wang, T., and Tang,
J. L.: Modeling nitrogen loadings from agricultural soils in southwest China
with modified DNDC, J. Geophys. Res., 116, G02020,
https://doi.org/10.1029/2010JG001609, 2011.
Di Toro, D. M., Fitzpatrick, J. J., and Thomann, R. V.: Water quality analysis
simulation program (WASP) and model verification program
(MVP)-Documentation, Hydroscience, Inc., Westwood, NY, for US EPA, Duluth,
MN, Contract No. 68–01–3872, 1983.
Duan, Q., Sorooshian, S., and Gupta, V. K.: Optimal use of the SCE-UA global
optimization method for calibrating watershed models, J. Hydrol., 158, 265–284,
1994.
Efstratiadis, A. and Koutsoyiannis, D.: One decade of multi-objective
calibration approaches in hydrological modelling: a review, Hydrol. Sci. J., 55, 58–78,
2010.
Euser, T., Winsemius, H. C., Hrachowitz, M., Fenicia, F., Uhlenbrook, S.,
and Savenije, H. H. G.: A framework to assess the realism of model structures
using hydrological signatures, Hydrol. Earth Syst. Sci., 17, 1893–1912, https://doi.org/10.5194/hess-17-1893-2013, 2013.
Fovet, O., Ruiz, L., Hrachowitz, M., Faucheux, M., and Gascuel-Odoux, C.:
Hydrological hysteresis and its value for assessing process consistency in
catchment conceptual models, Hydrol. Earth Syst. Sci., 19, 105–123, https://doi.org/10.5194/hess-19-105-2015, 2015.
Gassman, P. W., Reyes, M. R., Green, C. H., and Arnold, A. G.: The soil and
water assessment tool: historical development, applications, and future
research directions, T. ASABE, 50, 1211–1250, 2007.
Goldberg, D. E.: Genetic algorithms in search, optimization, and machine
learning, Reading Menlo Park: Addison-Wesley, Massachusetts, USA, 1989.
Hamrick, J. M.: A three-dimensional environmental fluid dynamics computer
code: theoretical and computational aspects, Special Report, The College of
William and Mary, Virginia Institute of Marine Science, Virginia, USA, 317,
1992.
Hargreaves, G. H. and Samani, Z. A.: Estimating potential
evapotranspiration, J. Irrigat. Drain. Div., 108, 225–230, 1982.
Henan Statistical Yearbook in 2003, 2004 and 2005: China Statistics Press,
Beijing, 2003, 2004, 2005.
Her, Y. and Chaubey, I.: Impact of the numbers of observations and
calibration parameters on equifinality, model performance, and output and
parameter uncertainty, Hydrol. Process., 29, 4220–4237, 2015.
Horst, W. J., Kamh, M., Jibrin, J. M., and Chude, V. O.: Agronomic measures for
increasing P availability to crops, Plant. Soil., 237, 211–223, 2001.
Hrachowitz, M., Fovet, O., Ruiz, L., Euser, T., Gharari, S., Nijzink, R.,
Freer, J., Savenije, H. H. G., and GascuelOdoux, C.: Process consistency in
models: The importance of system signatures, expert knowledge, and process
complexity, Water Resour. Res., 50, 7445–7469, 2014.
Johnes, P. J.: Evaluation and management of the impact of land use change on
the nitrogen and phosphorus load delivered to surface waters: the export
coefficient modelling approach, J. Hydrol., 183, 323–349, 1996.
Johnsson, H., Bergstrom, L., Jansson, P. E., and Paustian, K.: Simulated
nitrogen dynamics and losses in a layered agricultural soil, Agr. Ecosyst. Environ., 18,
333–356, 1987.
Kennedy, J.: Particle swarm optimization, Encyclopedia of Machine Learning,
Springer USA, 760–766, 2010.
Kindler, J.: Integrated water resources management: the meanders, Water Int.,
25, 312–319, 2000.
King, K. W., Arnold, J. G., and Bingner, R. L.: Comparison of Green-Ampt and
curve number methods on Goodwin Creek watershed using SWAT, T. ASABE, 42,
919–925, 1999.
Kirchner, J. W.: Getting the right answers for the right reasons: Linking
measurements, analyses, and models to advance the science of hydrology,
Water Resour. Res., 42, W03S04, https://doi.org/10.1029/2005WR004362, 2006.
Krysanova, V., Mueller-Wohlfeil, D. I., and Becker, A.: Development and test
of a spatially distributed hydrological/water quality model for mesoscale
watersheds, Ecol. Model., 106, 261–289, 1998.
Li, C., Frolking, S., and Frolking, T. A.: A model of nitrous oxide evolution
from soil driven by rainfall events: 1. Model structure and sensitivity, J. Geophys. Res., 97, 9759–9776, 1992.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A Simple
hydrologically based model of land surface water and energy fluxes for GSMs,
J. Geophys. Res., 99, 14415–14428, 1994.
Lindström, G., Pers, C. P., Rosberg, R., Strömqvist, J., and Arheimer,
B.: Development and test of the HYPE (Hydrological Predictions for the
Environment) model – A water quality model for different spatial scales,
Hydrol. Res., 41, 295–319, 2010.
Ma, F., Ye, A., Gong, W., Mao, Y., Miao, C., and Di, Z.: An estimate of human
and natural contributions to flood changes of the Huai River, Global Planet Change, 119,
39–50, 2014.
Mantovan, P. and Todini, E.: Hydrological forecasting uncertainty
assessment: Incoherence of the GLUE methodology, J. Hydrol., 330, 368–381, 2006.
Mantovan, P., Todini, E., and Martina, M. L. V.: Reply to comment by Keith
Beven, Paul Smith, and Jim Freer on “Hydrological forecasting uncertainty
assessment: Incoherence of the GLUE methodology”, J. Hydrol., 338, 319–324, 2007.
McDonnell, J. J., Sivapalan, M., Vache, K., Dunn, S., Grant, G., Haggerty,
R., Hinz, C., Hooper, R., Kirchner, J., Roderick, M. L., Selker, J., and
Weiler, M.: Moving beyond heterogeneity and process complexity: A new vision
for watershed hydrology, Water Resour. Res., 43, W07301, https://doi.org/10.1029/2006WR005467, 2007.
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Binger, R. L., Harmel, R.
D., and Veith, T.: Model evaluation guidelines for systematic quantification
of accuracy in watershed simulations, T. ASABE, 50, 885–900, 2007.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models. Part I – A discussion of principles, J. Hydrol., 27, 282–290, 1970.
Neitsch, S., Arnold, J., Kiniry, J., and Williams, J. R.: SWAT2009
Theoretical Documentation, Texas Water Resources Institute, Temple, Texas,
2011.
Onstad, C. A. and Foster, G. R.: Erosion modeling on a watershed, T. ASAE,
18, 288–292, 1975.
Paola, C., Foufoula-Georgiou, E., Dietrich, W. E., Hondzo, M., Mohrig, D.,
Parker, G., Power, M. E., Rodriguez-Iturbe, I., Voller, V., and Wilcock, P.:
Toward a unified science of the Earth's surface: opportunities for synthesis
among hydrology, geomorphology, geochemistry, and ecology, Water Resour. Res., 42,
W03S10, https://doi.org/10.1029/2005WR004336,
2006.
Pohlert, T., Breuer, L., Huisman, J. A., and Frede, H.-G.: Integration of a
detailed biogeochemical model into SWAT for improved nitrogen
predictions-model development, sensitivity and uncertainty analysis, Ecol.
Model.,
203, 215–228, 2006.
Pokhrel, P., Gupta, H. V., and Wagener, T.: A spatial regularization approach
to parameter estimation for a distributed watershed model, Water Resour. Res., 44,
W12419, https://doi.org/10.1029/2007WR006615,
2008.
Pushpalatha, R., Perrin, C., Le Moine, N., and Andréassian, V.: A review
of efficiency criteria suitable for evaluating low-?ow simulations,
J. Hydrol., 420–421, 171–182, 2012.
Rallison, R. E. and Miller, N.: Past, present and future SCS runoff
procedure, in: Rainfall runoff
relationship, edited by: Singh, V. P., Water Resources Publication, Littleton, CO, 353–364, 1981.
Ritchie, J. T.: A model for predicting evaporation from a row crop with
incomplete cover, Water Resour. Res., 8, 1205–1213, 1972.
Ritter, A. and Muñoz-Carpena, R.: Performance evaluation of hydrological
models: Statistical significance for reducing subjectivity in
goodness-of-fit assessments, J. Hydrol., 480, 33–45, 2013.
Sharpley, A. N. and Williams, J. R.: EPIC-erosion/productivity impact
calculator: 1. Model documentation. Technical Bulletin-United States
Department of Agriculture, Agric. Res. Service, Washington D.C., USA, 1990.
Shi, P., Chen, C., Srinivasan, R., Zhang, X., Cai, T., Fang, X., Qu, S.,
Chen, X., and Li, Q.: Evaluating the SWAT model for hydrological modeling in
the Xixian watershed and a comparison with the XAJ model, Water Resour.
Manag., 25, 2595–2612, 2011.
Singh, V. P. and Woolhiser, D. A.: Mathematical modeling of watershed
hydrology, J. Hydrol. Eng., 7, 270–292, 2002.
Sivapalan, M. and Kalma, J. D.: Scale problems in hydrology: contributions
of the Robertson Workshop, Hydrol. Process., 9, 243–250, 1995.
Strömqvist, J., Arheimer, B., Dahné, J., Donnelly, C., and
Lindström, G.: Water and nutrient predictions in ungauged basins: set-up
and evaluation of a model at the national scale, Hydrol. Sci. J., 57,
229–247, 2012.
Tattari, S., Bärlund, I., Rekolainen, S., Posch, M., Siimes, K.,
Tuhkanen, H. R., and Yli-Halla, M.: Modeling sediment yield and phosphorus
transport in Finnish clayey soils, T. ASABE, 44, 297–307, 2001.
Tonkin, M. J. and Doherty, J.: A hybrid regularized inversion methodology
for highly parameterized environmental models, Water Resour. Res., 41, W10412,
https://doi.org/10.1029/2005WR003995, 2005.
van Griensven, A., Meixner, T., Grunwald, S., Bishop, T., Diluzio, M., and
Srinivasan, R.: A global sensitivity analysis tool for the parameters of
multi-variable catchment models, J. Hydrol., 324, 10–23, 2006.
Vinogradov, Y. B., Semenova, O. M., and Vinogradova, T. A.: An approach to
the scaling problem in hydrological modelling: the deterministic modelling
hydrological system, Hydrol. Process., 25, 1055–1073, 2011.
Wang, G. S., Xia, J., Tan, G., and Lu, A. F.: A research on distributed time
variant gain model: A case study on Chao River basin, Prog. Geogr., 21,
573–582, 2002 (in Chinese).
Wang, G., Xia, J., and Chen, J.: Quantification of effects of climate
variations and human activities on runoff by a monthly water balance model: A
case study of the Chaobai River basin in northern China, Water Resour. Res.,
45, W00A11, https://doi.org/10.1029/2007WR006768, 2009.
Wang, J. Q., Ma, W. Q., Jiang, R. F., and Zhang, F. S.: Analysis about amount and
ratio of basal fertilizer and topdressing fertilizer on rice, wheat, maize
in China, Chin. J. Soil Sci., 39, 329–333, 2008 (in Chinese).
Wang, X.: Summary of Huaihe River Basin and Shandong Peninsula Integrated
Water Resources Plan, China Water Resour., 23, 112–114, 2011.
Williams, J. R., Jones, C. A., and Dyke, P. T.: Modeling approach to
determining the relationship between erosion and soil productivity, Trans. ASAE,
27,
129–144, 1984.
Williams, J. R., Jones, C. A., Kiniry, J. R., and Spanel, D. A.: The EPIC
crop growth model, Trans. ASAE, 32, 497–511, 1989.
Xia, J.: Identification of a constrained nonlinear hydrological system
described by Volterra Functional Series, Water Resour. Res., 27, 2415–2420, 1991.
Xia, J., Wang, G. S., Tan, G., Ye, A. Z., and Huang, G. H.: Development of
distributed time-variant gain model for nonlinear hydrological systems,
Sci. China: Earth Sci., 48, 713–723, 2005.
Xing, G. X. and Zhu, Z. L.: An assessment of N loss from agricultural
fields to the environment in China, Nutr. Cycl. Agroecosys., 57, 67–73, 2000.
Zhai, X. Y., Zhang, Y. Y., Wang, X. L., Xia, J., and Liang, T.: Non-point
source pollution modeling using Soil and Water Assessment Tool and its
parameter sensitivity analysis in Xin'anjiang Catchment, China, Hydrol.
Process., 28, 1627–1640, 2014.
Zhang, Y. Y., Xia, J., Liang, T., and Shao, Q. X.: Impact of water projects
on River Flow Regimes and Water Quality in Huai River Basin, Water Resour.
Manag., 24, 889–908, 2010.
Zhang, Y. Y., Xia, J., Shao, Q. X., and Zhai, X. Y.: Water quantity and
quality simulation by improved SWAT in highly regulated Huai River Basin of
China, Stoch. Env. Res. Risk A., 27, 11–27, 2013.
Zhu, Z. L.: Loss of fertilizer N from plants-soil system and the strategies
and techniques for its reduction, Soil Environ. Sci., 9, 1–6, 2000 (in Chinese).
Short summary
We developed an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality and ecology, and considering the interference of human activities. The parameter sensitivity and autocalibration modules were also developed to improve the simulation efficiency. The proposed model was applied in the Shaying River catchment, which is a highly regulated and heavily polluted region in China.
We developed an integrated water system model by coupling multiple water-related processes in...
