Articles | Volume 24, issue 3
https://doi.org/10.5194/hess-24-1347-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-1347-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Mar 2020
Research article |
| 23 Mar 2020
| 23 Mar 2020
Dynamics of hydrological-model parameters: mechanisms, problems and solutions
Tian Lan
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Kairong Lin
CORRESPONDING AUTHOR
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Guangdong Engineering Technology Research Center of Water Security
Regulation and Control for Southern China, Guangzhou, 510275, China
School of Civil Engineering, Sun Yat-sen University, Guangzhou,
510275, China
Chong-Yu Xu
Department of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0316 Oslo, Norway
Xuezhi Tan
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Guangdong Engineering Technology Research Center of Water Security
Regulation and Control for Southern China, Guangzhou, 510275, China
School of Civil Engineering, Sun Yat-sen University, Guangzhou,
510275, China
Xiaohong Chen
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Guangdong Engineering Technology Research Center of Water Security
Regulation and Control for Southern China, Guangzhou, 510275, China
School of Civil Engineering, Sun Yat-sen University, Guangzhou,
510275, China
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Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-100, https://doi.org/10.5194/hess-2017-100, 2017
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Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-619, https://doi.org/10.5194/hess-2016-619, 2016
Revised manuscript not accepted
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J. E. Reynolds, S. Halldin, C. Y. Xu, J. Seibert, and A. Kauffeldt
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-7437-2015, https://doi.org/10.5194/hessd-12-7437-2015, 2015
Revised manuscript not accepted
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A. Kauffeldt, S. Halldin, A. Rodhe, C.-Y. Xu, and I. K. Westerberg
Hydrol. Earth Syst. Sci., 17, 2845–2857, https://doi.org/10.5194/hess-17-2845-2013, https://doi.org/10.5194/hess-17-2845-2013, 2013
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Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Achieving water budget closure through physical hydrological processes modelling: insights from a large-sample study
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Heavy-tailed flood peak distributions: What is the effect of the spatial variability of rainfall and runoff generation?
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
State updating in the Xin'anjiang Model: Joint assimilating streamflow and multi-source soil moisture data via Asynchronous Ensemble Kalman Filter with enhanced Error Models
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
A diversity centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
Elevational control of isotopic composition and application in understanding hydrologic processes in the mid Merced River catchment, Sierra Nevada, California, USA
Lack of robustness of hydrological models: A large-sample diagnosis and an attempt to identify the hydrological and climatic drivers
Exploring the Potential Processes Controls for Changes of Precipitation-Runoff Relationships in Non-stationary Environments
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Broadleaf afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
CH-RUN: A data-driven spatially contiguous runoff monitoring product for Switzerland
Simulating the Tone River Eastward Diversion Project in Japan Carried Out Four Centuries Ago
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
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.
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.
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.
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. Discuss., https://doi.org/10.5194/hess-2024-272, https://doi.org/10.5194/hess-2024-272, 2024
Preprint under review for HESS
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Our study projects how climate change will affect drying of river segments and stream networks in Europe, using advanced modeling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent, intense and start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists in evaluating the ecological health of river ecosystem.
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.
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.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-230, https://doi.org/10.5194/hess-2024-230, 2024
Revised manuscript accepted for HESS
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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 Datasets Correction Framework grounded in Physical Hydrological Processes Modelling to enhance water budget closure, called 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.
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.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-181, https://doi.org/10.5194/hess-2024-181, 2024
Revised manuscript accepted for HESS
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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 compared to large catchments, and that spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show an effect. The results can improve estimations of occurrence probabilities of extreme floods.
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.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-211, https://doi.org/10.5194/hess-2024-211, 2024
Revised manuscript accepted for HESS
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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 better prepare for and respond to floods.
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.
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.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
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Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
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Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-169, https://doi.org/10.5194/hess-2024-169, 2024
Revised manuscript accepted for HESS
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Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine-learning models are increasingly being applied for flood forecasting. Such models are typically trained to large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets, that maximise the spatiotemproal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
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We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
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In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-80, https://doi.org/10.5194/hess-2024-80, 2024
Revised manuscript accepted for HESS
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This work aims at investigating how hydrological models can be transferred to a period in which climatic conditions are different to the ones of the period in which it was set up. The RAT method, built to detect dependencies between model error and climatic drivers, was applied to 3 different hydrological models on 352 catchments in Denmark, France and Sweden. Potential issues are detected for a significant number of catchments for the 3 models even though these catchments differ for each model.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-118, https://doi.org/10.5194/hess-2024-118, 2024
Revised manuscript accepted for HESS
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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 controls for 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.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-993, https://doi.org/10.5194/egusphere-2024-993, 2024
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This study uses deep learning to predict spatially contiguous water runoff in Switzerland from 1962–2023. It outperforms traditional models, requiring less data and computational power. Key findings include increased dry years and summer water scarcity. This method offers significant advancements in water monitoring.
Joško Trošelj and Naota Hanasaki
EGUsphere, https://doi.org/10.5194/egusphere-2024-595, https://doi.org/10.5194/egusphere-2024-595, 2024
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This study presents the first distributed hydrological simulation which confirms the claims raised by historians that the Eastward Diversion Project of the Tone River in Japan was conducted four centuries ago to increase low flows and subsequent travelling possibilities surrounding the Capitol Edo (Tokyo) using inland navigation. We reconstructed six historical river maps and indirectly validated the historical simulations with reachable ancient river ports via increased low-flow water levels.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
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Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
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We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Cited articles
Aldrich, J.: R. A. Fisher and the making of maximum likelihood 1912–1922,
Statist. Sci., 12, 162–176, https://doi.org/10.1214/ss/1030037906, 1997.
Arora, S. and Singh, S.: The firefly optimization algorithm: convergence
analysis and parameter selection, Int. J. Comput. Appl., 69, 48–52, https://doi.org/10.5120/11826-7528, 2013.
Arsenault, R., Poulin, A., Côté, P., and Brissette, F.: Comparison of Stochastic Optimization Algorithms in Hydrological Model Calibration, J. Hydrol. Eng., 19, 1374–1384, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000938, 2014.
Azad, S. K. J. S. and Optimization, M.: Monitored convergence curve: a new
framework for metaheuristic structural optimization algorithms, Struct. Multidiscip. O., 60, 481–499, https://doi.org/10.1007/s00158-019-02219-5, 2019.
Bárdossy, A.: Calibration of hydrological model parameters for ungauged
catchments, Hydrol. Earth Syst. Sci., 11, 703–710, https://doi.org/10.5194/hess-11-703-2007, 2007.
Bárdossy, A. and Singh, S. K.: Robust estimation of hydrological model
parameters, Hydrol. Earth Syst. Sci., 12, 1273–1283,
https://doi.org/10.5194/hess-12-1273-2008, 2008.
Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, https://doi.org/10.1002/hyp.3360060305, 1992.
Brigode, P., Oudin, L., and Perrin, C.: Hydrological model parameter instability: A source of additional uncertainty in estimating the hydrological impacts of climate change?, J. Hydrol., 476, 410–425,
https://doi.org/10.1016/j.jhydrol.2012.11.012, 2013.
Chen, Y., Chen, X. W., Xu, C. Y., Zhang, M. F., Liu, M. B., and Gao, L.:
Toward improved calibration of SWAT using season-based multi-objective
optimization: A case study in the Jinjiang basin in southeastern China, Water Resour. Manage,, 32, 1193–1207, https://doi.org/10.1007/s11269-017-1862-8, 2017.
Cheng, L., Yaeger, M., Viglione, A., Coopersmith, E., Ye, S., and Sivapalan,
M.: Exploring the physical controls of regional patterns of flow duration
curves – Part 1: Insights from statistical analyses, Hydrol. Earth Syst. Sci., 16, 4435–4446, https://doi.org/10.5194/hess-16-4435-2012, 2012.
Choi, H. T. and Beven, K.: Multi-period and multi-criteria model conditioning to reduce prediction uncertainty in an application of TOPMODEL within the GLUE framework, J. Hydrol., 332, 316–336, https://doi.org/10.1016/j.jhydrol.2006.07.012, 2007.
Cibin, R., Sudheer, K. P., and Chaubey, I.: Sensitivity and identifiability of stream flow generation parameters of the SWAT model, Hydrol. Process., 24,
1133–1148, https://doi.org/10.1002/hyp.7568, 2010.
CMDC: One Hour of Precipotation and Hour Temperature datasets during 1980–1990 on China Meteorological Data Service Center (CMDC), available at: https://data.cma.cn/en/?r=data/online&t=6 (last access: 20 March 2020), 2019.
Cooper, V. A., Nguyen, V. T. V., and Nicell, J. A.: Evaluation of global
optimization methods for conceptual rainfall-runoff model calibration, Water
Sci. Technol., 36, 53–60, https://doi.org/10.1016/S0273-1223(97)00461-7, 1997.
Coopersmith, E., Yaeger, M. A., Ye, S., Cheng, L., and Sivapalan, M.: Exploring the physical controls of regional patterns of flow duration curves
– Part 3: A catchment classification system based on regime curve indicators, Hydrol. Earth Syst. Sci., 16, 4467–4482, https://doi.org/10.5194/hess-16-4467-2012, 2012.
Coron, L., Andreassian, V., Perrin, C., Bourqui, M., and Hendrickx, F.: On
the lack of robustness of hydrologic models regarding water balance simulation: a diagnostic approach applied to three models of increasing
complexity on 20 mountainous catchments, Hydrol. Earth Syst. Sci., 18, 727–746, https://doi.org/10.5194/hess-18-727-2014, 2014.
Dakhlaoui, H., Ruelland, D., Tramblay, Y., and Bargaoui, Z.: Evaluating the
robustness of conceptual rainfall-runoff models under climate variability in
northern Tunisia, J. Hydrol., 550, 201–217, https://doi.org/10.1016/j.jhydrol.2017.04.032, 2017.
Delorit, J., Ortuya, E. C. G., and Block, P.: Evaluation of model-based seasonal streamflow and water allocation forecasts for the Elqui Valley,
Chile, Hydrol. Earth Syst. Sci., 21, 4711–4725, https://doi.org/10.5194/hess-21-4711-2017, 2017.
Deng, C., Liu, P., Guo, S. L., Li, Z. J., and Wang, D. B.: Identification of
hydrological model parameter variation using ensemble Kalman filter, Hydrol.
Earth Syst. Sci., 20, 4949–4961, https://doi.org/10.5194/hess-20-4949-2016, 2016.
Deng, C., Liu, P., Wang, D. B., and Wang, W. G.: Temporal variation and scaling of parameters for a monthly hydrologic model, J. Hydrol., 558, 290–300, https://doi.org/10.1016/j.jhydrol.2018.01.049, 2018.
Derrac, J., García, S., Hui, S., Suganthan, P. N., and Herrera, F.:
Analyzing convergence performance of evolutionary algorithms: A statistical
approach, Inform. Sci., 289, 41–58, https://doi.org/10.1016/j.ins.2014.06.009, 2014.
de Vos, N. J., Rientjes, T. H. M., and Gupta, H. V.: Diagnostic evaluation of conceptual rainfall-runoff models using temporal clustering, Hydrol. Process., 24, 2840–2850, https://doi.org/10.1002/hyp.7698, 2010.
Duan, Q., Sorooshian, S., and Gupta, V.: Effective and efficient global
optimization for conceptual rainfall-runoff models, Water Resour. Res., 28, 1015–1031, https://doi.org/10.1029/91WR02985, 1992.
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.
Duan, Q. Y., Gupta, V. K., and Sorooshian, S.: Shuffled Complex Evolution
Approach for Effective and Efficient Global Minimization, J. Optimiz. Theor. Appl., 76, 501–521, https://doi.org/10.1007/Bf00939380, 1993.
Fang, J. Y., Song, Y. C., Liu, H. Y., and Piao, S. L.: Vegetation-climate
relationship and its application in the division of vegetation zone in China, Acta Bot. Sin., 44, 1105–1122, 2002.
Fenicia, F., Kavetski, D., Savenije, H. H. G., Clark, M. P., Schoups, G., Pfister, L., and Freer, J.: Catchment properties, function, and conceptual model representation: is there a correspondence?, Hydrol. Process., 28, 2451–2467, https://doi.org/10.1002/hyp.9726, 2014.
Fenicia, F., Kavetski, D., Reichert, P., and Albert, C.: Signature-Domain
Calibration of Hydrological Models Using Approximate Bayesian Computation:
Empirical Analysis of Fundamental Properties, Water Resour. Res., 54,
3958–3987, https://doi.org/10.1002/2017wr021616, 2018.
Forrest, T. J. A. S.: Fitness Distance Correlation as a Measure of Problem
Difficulty for Genetic Algorithms, in: Proceedings of the Sixth International
Conference on Genetic Algorithms, 15–19 July 1995,
University of Pittsburgh, Pittsburgh, PA 15260, United States, 184–192, 1995.
Fowler, K., Coxon, G., Freer, J., Peel, M., Wagener, T., Western, A., Woods, R., and Zhang, L.: Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement, Water Resour. Res., 54, 9812–9832, https://doi.org/10.1029/2018wr023989, 2018.
Freer, J., Beven, K., and Peters, N.: Multivariate seasonal period model
rejection within the generalised likelihood uncertainty estimation procedure, in: Calibration of watershed models, 69–87, https://agupubs.onlinelibrary.wiley.com/doi/10.1029/WS006p0069 (last access: 11 March 2020), 2003.
Gharari, S., Hrachowitz, M., Fenicia, F., and Savenije, H. H. G.: An approach to identify time consistent model parameters: sub-period calibration, Hydrol. Earth Syst. Sci., 17, 149–161, https://doi.org/10.5194/hess-17-149-2013, 2013.
Gibbs, M. S., Maier, H. R., and Dandy, G. C.: Applying fitness landscape
measures to water distribution optimization problems, in: Hydroinformatics,
World Scientific Publishing Company, Singapore, 795–802, 2004.
Golmohammadi, G., Rudra, R., Dickinson, T., Goel, P., and Veliz, M.: Predicting the temporal variation of flow contributing areas using SWAT, J. Hydrol., 547, 375–386, https://doi.org/10.1016/j.jhydrol.2017.02.008, 2017.
Gomez, J.: Stochastic global optimization algorithms: A systematic formal
approach, Inform. Sci., 472, 53–76, https://doi.org/10.1016/j.ins.2018.09.021, 2019.
Guntner, A., Uhlenbrook, S., Seibert, J., and Leibundgut, C.: Multi-criterial validation of TOPMODEL in a mountainous catchment, Hydrol. Process., 13, 1603–1620, https://doi.org/10.1002/(sici)1099-1085(19990815)13:11<1603::aid-hyp830>3.3.co;2-b, 1999.
Guo, D., Johnson, F., and Marshall, L.: Assessing the Potential Robustness of Conceptual Rainfall-Runoff Models Under a Changing Climate, Water Resour. Res., 54, 5030–5049, https://doi.org/10.1029/2018WR022636, 2018.
Gupta, H. V., Sorooshian, S., and Yapo, P. O.: Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information, Water Resour. Res., 34, 751–763, https://doi.org/10.1029/97WR03495, 1998.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Guse, B., Pfannerstill, M., Strauch, M., Reusser, D. E., Ludtke, S., Volk, M., Gupta, H., and Fohrer, N.: On characterizing the temporal dominance
patterns of model parameters and processes, Hydrol. Process., 30, 2255–2270,
https://doi.org/10.1002/hyp.10764, 2016.
Hanne, T. J. J. O. H.: Global Multiobjective Optimization Using Evolutionary
Algorithms, J. Heuristics, 6, 347–360, https://doi.org/10.1023/a:1009630531634, 2000.
Harik, G., Cantú-Paz, E., Goldberg, D. E., and Miller, B. L.: The
Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations,
7, 231-253, 10.1162/evco.1999.7.3.231, 1999.
Herman, J. D., Reed, P. M., and Wagener, T.: Time-varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior, Water Resour. Res., 49, 1400–1414, https://doi.org/10.1002/wrcr.20124, 2013.
Hintze, J. L. and Nelson, R. D.: Violin plots: a box plot-density trace
synergism, Am. Statist., 52, 181–184, https://doi.org/10.2307/2685478, 1998.
Höge, M., Wöhling, T., and Nowak, W.: A primer for model selection:
The decisive role of model complexity, Water Resour. Res., 54, 1688–1715, 2018.
Huang, G. H.: Model identifiability, Wiley StatsRef: Statistics Reference
Online, available at: https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118445112.stat06411.pub2
(last access: 2016), 2005.
Hublart, P., Ruelland, D., De Cortázar-Atauri, L. G., Gascoin, S., Lhermitte, S., and Ibacache, A.: Reliability of lumped hydrological modeling
in a semi-arid mountainous catchment facing water-use changes, Hydrol. Earth
Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, 2016.
Kim, D. and Kaluarachchi, J.: Predicting streamflows in snowmelt-driven watersheds using the flow duration curve method, Hydrol. Earth Syst. Sci., 18, 1679–1693, https://doi.org/10.5194/hess-18-1679-2014, 2014.
Kim, K. B. and Han, D.: Exploration of sub-annual calibration schemes of
hydrological models, Hydrol. Res., 48, 1014–1031, https://doi.org/10.2166/nh.2016.296,
2017.
Kim, K. B., Kwon, H.-H., and Han, D.: Hydrological modelling under climate
change considering nonstationarity and seasonal effects, Hydrol. Res., 47, nh2015103, https://doi.org/10.2166/nh.2015.103, 2015.
Kiptala, J. K., Mul, M. L., Mohamed, Y. A., and van der Zaag, P.: Modelling
stream flow and quantifying blue water using a modified STREAM model for a
heterogeneous, highly utilized and data-scarce river basin in Africa, Hydrol.
Earth Syst. Sci., 18, 2287–2303, https://doi.org/10.5194/hess-18-2287-2014, 2014.
Klemeš, V.: Operational testing of hydrological simulation models, Hydrolog. Sci. J., 31, 13–24, 1986.
Klotz, D., Herrnegger, M., and Schulz, K.: Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models, Water Resour. Res., 53, 9402–9423, https://doi.org/10.1002/2017wr021253, 2017.
Laloy, E. and Vrugt, J. A.: High-dimensional posterior exploration of hydrologic models using multiple-try DREAM(ZS) and high-performance computing, Water Resour. Res., 48, W01526, https://doi.org/10.1029/2011wr010608, 2012.
Lan, T., Lin, K. R., Liu, Z. Y., He, Y. H., Xu, C. Y., Zhang, H. B., and
Chen, X. H.: A Clustering Preprocessing Framework for the Subannual Calibration of a Hydrological Model Considering Climate-Land Surface
Variations, Water Resour. Res., 54, 10034–10052, https://doi.org/10.1029/2018wr023160, 2018.
Lin, K., Zhang, Q., and Chen, X.: An evaluation of impacts of DEM resolution and parameter correlation on TOPMODEL modeling uncertainty, J. Hydrol., 394, 370–383, https://doi.org/10.1016/j.jhydrol.2010.09.012, 2010.
Liu, Z. Y., Zhou, P., Chen, X. Z., and Guan, Y. H.: A multivariate conditional model for streamflow prediction and spatial precipitation refinement, J. Geophys. Res.-Atmos., 120, 10116–110129, https://doi.org/10.1002/2015JD02378, 2015.
Liu, Z. Y., Cheng, L. Y., Hao, Z. C., Li, J. J., Thorstensen, A., and Gao, H. K.: A framework for exploring joint effects of conditional factors on compound floods, Water Resour. Res., 54, 2681–2696, https://doi.org/10.1002/2017WR021662, 2018.
Luo, J. M., Wang, E. L., Shen, S. H., Zheng, H. X., and Zhang, Y. Q.: Effects of conditional parameterization on performance of rainfall-runoff model regarding hydrologic non-stationarity, Hydrol. Process., 26, 3953–3961,
https://doi.org/10.1002/hyp.8420, 2012.
Madsen, H.: Automatic calibration of a conceptual rainfall–runoff model
using multiple objectives, J. Hydrol., 235, 276–288,
https://doi.org/10.1016/S0022-1694(00)00279-1, 2000.
Maier, H. R., Kapelan, Z., Kasprzyk, J., Kollat, J., Matott, L. S., Cunha, M. C., Dandy, G. C., Gibbs, M. S., Keedwell, E., Marchi, A., Ostfeld, A., Savic, D., Solomatine, D. P., Vrugt, J. A., Zecchin, A. C., Minsker, B. S., Barbour, E. J., Kuczera, G., Pasha, F., Castelletti, A., Giuliani, M., and Reed, P. M.: Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions, Environ. Modell. Softw., 62, 271–299, 2014.
Me, W., Abell, J. M., and Hamilton, D. P.: Effects of hydrologic conditions on SWAT model performance and parameter sensitivity for a small, mixed land
use catchment in New Zealand, Hydrol. Earth Syst. Sci., 19, 4127–4147,
https://doi.org/10.5194/hess-19-4127-2015, 2015.
Merz, R., Parajka, J., and Bloschl, G.: Time stability of catchment model
parameters: Implications for climate impact analyses, Water Resour. Res., 47, W02531, https://doi.org/10.1029/2010wr009505, 2011.
Michalewicz, Z. and Schoenauer, M.: Evolutionary Algorithms for Constrained
Parameter Optimization Problems, Evol. Comput., 4, 1–32, https://doi.org/10.1162/evco.1996.4.1.1, 1996.
Moore, R. J.: The probability-distributed principle and runoff production at
point and basin scales, Hydrol. Sci. J., 30, 273–297,
https://doi.org/10.1080/02626668509490989, 1985.
Motavita, D. F., Chow, R., Guthke, A., and Nowak, W.: The comprehensive differential split-sample test: A stress-test for hydrological model robustness under climate variability, J. Hydrol., 573, 501–515,
https://doi.org/10.1016/j.jhydrol.2019.03.054, 2019.
NASA: Global digital elevation model (GDEM) with a cell size of 30×30 m on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), available at:
https://asterweb.jpl.nasa.gov/gdem.asp (last access: 20 March 2020), 2019.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models part I – A discussion of principles, J. Hydrol., 10, 282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Nijzink, R. C., Samaniego, L., Mai, J., Kumar, R., Thober, S., Zink, M.,
Schäfer, D., Savenije, H. H. G., and Hrachowitz, M.: The importance of
topography-controlled sub-grid process heterogeneity and semi-quantitative
prior constraints in distributed hydrological models, Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, 2016.
Omran, M. G. H. and Mahdavi, M.: Global-best harmony search, Appl. Math. Comput., 198, 643–656, https://doi.org/10.1016/j.amc.2007.09.004, 2008.
Osuch, M., Wawrzyniak, T., and Nawrot, A.: Diagnosis of the hydrology of a small Arctic permafrost catchment using HBV conceptual rainfall-runoff model,
Hydrol. Res., 50, 459–478, 2019.
Ouyang, Y., Xu, D., Leininger, T. D., and Zhang, N.: A system dynamic model to estimate hydrological processes and water use in a eucalypt plantation, Ecol. Eng., 86, 290–299, https://doi.org/10.1016/j.ecoleng.2015.11.008, 2016.
Pande, S. and Moayeri, M.: Hydrological Interpretation of a Statistical
Measure of Basin Complexity, Water Resour. Res., 54, 7403–7416,
https://doi.org/10.1029/2018WR022675, 2018.
Pathiraja, S., Marshall, L., Sharma, A., and Moradkhani, H.: Hydrologic modeling in dynamic catchments: A data assimilation approach, Water Resour. Res., 52, 3350–3372, https://doi.org/10.1002/2015wr017192, 2016.
Pathiraja, S., Anghileri, D., Burlando, P., Sharma, A., Marshall, L., and
Moradkhani, H.: Time-varying parameter models for catchments with land use
change: the importance of model structure, Hydrol. Earth Syst. Sci., 22,
2903–2919, https://doi.org/10.5194/hess-22-2903-2018, 2018.
Pfannerstill, M., Guse, B., and Fohrer, N.: Smart low flow signature metrics
for an improved overall performance evaluation of hydrological models, J. Hydrol., 510, 447–458, https://doi.org/10.1016/j.jhydrol.2013.12.044, 2014.
Pfannerstill, M., Guse, B., Reusser, D., and Fohrer, N.: Process verification of a hydrological model using a temporal parameter sensitivity analysis, Hydrol. Earth Syst. Sci., 19, 4365–4376, https://doi.org/10.5194/hess-19-4365-2015, 2015.
Piel, F. B., Patil, A. P., Howes, R. E., Nyangiri, O. A., Gething, P. W.,
Williams, T. N., Weatherall, D. J., and Hay, S. I.: Global distribution of
the sickle cell gene and geographical confirmation of the malaria hypothesis, Nat. Commun., 1, 104, https://doi.org/10.1038/ncomms1104, 2010.
Piotrowski, A. P., Napiorkowski, M. J., Napiorkowski, J. J., and Rowinski, P. M.: Swarm Intelligence and Evolutionary Algorithms: Performance versus speed, Inform. Sci., 384, 34–85, https://doi.org/10.1016/j.ins.2016.12.028, 2017.
Pool, S., Viviroli, D., and Seibert, J.: Prediction of hydrographs and
flow-duration curves in almost ungauged catchments: Which runoff measurements are most informative for model calibration?, J. Hydrol., 554, 613–622, https://doi.org/10.1016/j.jhydrol.2017.09.037, 2017.
Pugliese, A., Castellarin, A., and Brath, A.: Geostatistical prediction of
flow–duration curves in an index-flow framework, Hydrol. Earth Syst. Sci., 18, 3801–3816, https://doi.org/10.5194/hess-18-3801-2014, 2014.
Rahnamay Naeini, M., Yang, T., Sadegh, M., AghaKouchak, A., Hsu, K.-L., Sorooshian, S., Duan, Q., and Lei, X.: Shuffled Complex-Self Adaptive Hybrid
EvoLution (SC-SAHEL) optimization framework, Environ. Model. Softw., 104,
215–235, https://doi.org/10.1016/j.envsoft.2018.03.019, 2018.
Sarhadi, A., Burn, D. H., Concepción Ausín, M., and Wiper, M. P.:
Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula, Water Resour. Res., 52, 2327–2349, https://doi.org/10.1002/2015wr018525, 2016.
Sarrazin, F., Pianosi, F., and Wagener, T.: Global Sensitivity Analysis of
environmental models: Convergence and validation, Environ. Model. Softw., 79,
135–152, https://doi.org/10.1016/j.envsoft.2016.02.005, 2016.
Sivakumar, B.: Dominant processes concept in hydrology: moving forward, Hydrol. Process., 18, 2349–2353, https://doi.org/10.1002/hyp.5606, 2004.
Sorooshian, S., Duan, Q., and Gupta, V. K.: Calibration of rainfall-runoff
models: Application of global optimization to the Sacramento Soil Moisture
Accounting Model, Water Resour. Res., 29, 1185–1194, https://doi.org/10.1029/92wr02617, 1993.
Storn, R. and Price, K.: Differential Evolution – A Simple and Efficient
Heuristic for global Optimization over Continuous Spaces, J. Global Optimiz., 11, 341–359, https://doi.org/10.1023/a:1008202821328, 1997.
Sun, J., Wu, X., Palade, V., Fang, W., Lai, C.-H., and Xu, W.: Convergence
analysis and improvements of quantum-behaved particle swarm optimization,
Inform. Sci., 193, 81–103, https://doi.org/10.1016/j.ins.2012.01.005, 2012.
Todorovic, A. and Plavsic, J.: The role of conceptual hydrologic model calibration in climate change impact on water resources assessment, J. Water Clim. Change, 7, 16–28, https://doi.org/10.2166/wcc.2015.086, 2015.
Tongal, H. and Booij, M. J.: Simulation and forecasting of streamflows using machine learning models coupled with base flow separation, J. Hydrol., 564, 266–282, https://doi.org/10.1016/j.jhydrol.2018.07.004, 2018.
Turner, S. W. D., Bennett, J. C., Robertson, D. E., and Galelli, S.: Complex
relationship between seasonal streamflow forecast skill and value in reservoir operations, Hydrol. Earth Syst. Sci., 21, 4841–4859,
https://doi.org/10.5194/hess-21-4841-2017, 2017.
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,
https://doi.org/10.1016/j.jhydrol.2005.09.008, 2006.
Vormoor, K., Heistermann, M., Bronstert, A., and Lawrence, D.: Hydrological
model parameter (in)stability – “crash testing” the HBV model under contrasting flood seasonality conditions, Hydrolog. Sci. J., 63, 991–1007, https://doi.org/10.1080/02626667.2018.1466056, 2018.
Vrugt, J. A. and Beven, K. J.: Embracing equifinality with efficiency: Limits of Acceptability sampling using the DREAM (LOA) algorithm, J. Hydrol., 559, 954–971, https://doi.org/10.1016/j.jhydrol.2018.02.026, 2018.
Vrugt, J. A., Bouten, W., Gupta, H. V., and Sorooshian, S.: Toward improved
identifiability of hydrologic model parameters: The information content of
experimental data, Water Resour. Res., 38, 48-41–48-13, https://doi.org/10.1029/2001WR001118, 2002.
Vrugt, J. A., Diks, C. G. H., Gupta, H. V., Bouten, W., and Verstraten, J. M.: Improved treatment of uncertainty in hydrologic modeling: Combining the
strengths of global optimization and data assimilation, Water Resour. Res., 41, W01017, https://doi.org/10.1029/2004wr003059, 2005.
Wagener, T. and Kollat, J.: Numerical and visual evaluation of hydrological and environmental models using the Monte Carlo analysis toolbox, Environ.
Model. Softw., 22, 1021–1033, https://doi.org/10.1016/j.envsoft.2006.06.017, 2007.
Wagener, T., Boyle, D. P., Lees, M. J., Wheater, H. S., Gupta, H. V., and
Sorooshian, S.: A framework for development and application of hydrological
models, Hydrol. Earth Syst. Sci., 5, 13–26, https://doi.org/10.5194/hess-5-13-2001, 2001.
Wagener, T., McIntyre, N., Lees, M. J., Wheater, H. S., and Gupta, H. V.:
Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic
identifiability analysis, Hydrol. Process., 17, 455–476, https://doi.org/10.1002/hyp.1135, 2003.
Wang, S., Huang, G. H., Baetz, B. W., and Ancell, B. C.: Towards robust
quantification and reduction of uncertainty in hydrologic predictions:
Integration of particle Markov chain Monte Carlo and factorial polynomial chaos expansion, J. Hydrol., 548, 484–497, https://doi.org/10.1016/j.jhydrol.2017.03.027, 2017a.
Wang, S., Huang, G. H., Baetz, B. W., Cai, X. M., Ancell, B. C., and Fan, Y. R.: Examining dynamic interactions among experimental factors influencing
hydrologic data assimilation with the ensemble Kalman filter, J. Hydrol., 554, 743–757, https://doi.org/10.1016/j.jhydrol.2017.09.052, 2017b.
Wang, S., Ancell, B., Huang, G., and Baetz, B.: Improving Robustness of
Hydrologic Ensemble Predictions Through Probabilistic Pre-and Post-Processing in Sequential Data Assimilation, Water Resour. Res., 54, 2129–2151, 2018.
Weinberger, E. J. B. C.: Correlated and uncorrelated fitness landscapes and
how to tell the difference, Biol. Cyber., 63, 325–336, https://doi.org/10.1007/bf00202749, 1990.
Weise, T.: Global optimization algorithms-theory and application, Self-Published, second edition, available at: http://www.it-weise.de/projects/book.pdf (last access: 20 March 2020), 2009.
Westra, S., Thyer, M., Leonard, M., Kavetski, D., and Lambert, M.: A strategy for diagnosing and interpreting hydrological model nonstationarity, Water Resour. Res., 50, 5090–5113, 2014.
Wi, S., Yang, Y. C. E., Steinschneider, S., Khalil, A., and Brown, C. M.:
Calibration approaches for distributed hydrologic models in poorly gaged
basins: implication for streamflow projections under climate change, Hydrol.
Earth Syst. Sci., 19, 857–876, https://doi.org/10.5194/hess-19-857-2015, 2015.
Xiong, B., Xiong, L., Chen, J., Xu, C.-Y., and Li, L.: Multiple causes of
nonstationarity in the Weihe annual low-flow series, Hydrol. Earth Syst. Sci., 22, 1525–1542, https://doi.org/10.5194/hess-22-1525-2018, 2018.
Xiong, M., Liu, P., Cheng, L., Deng, C., Gui, Z., Zhang, X., and Liu, Y.:
Identifying time-varying hydrological model parameters to improve simulation
efficiency by the ensemble Kalman filter: A joint assimilation of streamflow
and actual evapotranspiration, J. Hydrol., 568, 758–768,
https://doi.org/10.1016/j.jhydrol.2018.11.038, 2019.
Yadav, M., Wagener, T., and Gupta, H.: Regionalization of constraints on
expected watershed response behavior for improved predictions in ungauged basins, Adv. Water Resour., 30, 1756–1774, https://doi.org/10.1016/j.advwatres.2007.01.005, 2007.
Yiu-Wing, L. and Yuping, W.: An orthogonal genetic algorithm with quantization for global numerical optimization, IEEE T. Evol. Comput., 5,
41–53, https://doi.org/10.1109/4235.910464, 2001.
Zecchin, A. C., Simpson, A. R., Maier, H. R., Marchi, A., and Nixon, J. B.:
Improved understanding of the searching behavior of ant colony optimization
algorithms applied to the water distribution design problem, Water Resour. Res., 48, W09505,
https://doi.org/10.1029/2011wr011652, 2012.
Zhang, D. J., Chen, X. W., Yao, H. X., and Lin, B. Q.: Improved calibration
scheme of SWAT by separating wet and dry seasons, Ecol. Model., 301, 54–61,
https://doi.org/10.1016/j.ecolmodel.2015.01.018, 2015.
Zhang, H., Huang, G. H., Wang, D. L., and Zhang, X. D.: Multi-period
calibration of a semi-distributed hydrological model based on hydroclimatic
clustering, Adv. Water Resour., 34, 1292–1303, https://doi.org/10.1016/j.advwatres.2011.06.005, 2011.
Zhang, X., Srinivasan, R., Zhao, K., and Liew, M. V.: Evaluation of global
optimization algorithms for parameter calibration of a computationally
intensive hydrologic model, Hydrol. Process., 23, 430–441,
https://doi.org/10.1002/hyp.7152, 2009.
Zhang, Y., Hao, Z., Xu, C.-Y., and Lai, X.: Response of melt water and rainfall runoff to climate change and their roles in controlling streamflow changes of the two upstream basins over the Tibetan Plateau, Hydrol. Res., nh2019075, https://doi.org/10.2166/nh.2019.075, 2019.
Zhao, B., Dai, H., Han, D., and Rong, G.: The sub-annual calibration of hydrological models considering climatic intra-annual variations, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-396, 2017.
Zheng, F., Zecchin, A. C., Newman, J. P., Maier, H. R., and Dandy, G. C.: An
Adaptive Convergence-Trajectory Controlled Ant Colony Optimization Algorithm
With Application to Water Distribution System Design Problems, IEEE T. Evol.
Comput., 21, 773–791, https://doi.org/10.1109/TEVC.2017.2682899, 2017.
