Articles | Volume 20, issue 6
https://doi.org/10.5194/hess-20-2467-2016
© 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-20-2467-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Jun 2016
Research article |
| 23 Jun 2016
Rainfall erosivity in catchments contaminated with fallout from the Fukushima Daiichi nuclear power plant accident
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Unité Mixte de Recherche 8212 (CEA-CNRS-UVSQ/IPSL), Université Paris-Saclay, Gif-sur-Yvette, France
Caroline Chartin
Georges Lemaître Centre for Earth and Climate Research, Earth and Life Institute, Université catholique de Louvain, Louvain, Belgium
Olivier Evrard
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Unité Mixte de Recherche 8212 (CEA-CNRS-UVSQ/IPSL), Université Paris-Saclay, Gif-sur-Yvette, France
Yuichi Onda
Graduate School of Life and Environmental Sciences, Center for Research in Isotopes and Environmental Dynamics (CRIED), University of Tsukuba, Tsukuba, Japan
Laurent Garcia-Sanchez
Laboratoire de Biogéochimie, Biodisponibilité et Transferts de Radionucléides, IRSN/PRP-ENV/SERIS/L2BT, Cadarache, France
Olivier Cerdan
Bureau de Recherches Géologiques et Minières, Orléans, France
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Gerald Dicen, Floriane Guillevic, Surya Gupta, Pierre-Alexis Chaboche, Katrin Meusburger, Pierre Sabatier, Olivier Evrard, and Christine Alewell
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-509, https://doi.org/10.5194/essd-2024-509, 2024
Preprint under review for ESSD
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Fallout radionuclides such as 137Cs and 239+240Pu are considered as critical tools in various environmental research. Here, we compiled reference soil data on these fallout radionuclides from the literature to build a comprehensive database. Using this database, we determined the distribution and sources of 137Cs and 239+240Pu. We also demonstrated how the database can be used to identify the environmental factors that influence their distribution using a machine-learning algorithm.
Thomas Chalaux-Clergue, Rémi Bizeul, Pedro V. G. Batista, Núria Martínez-Carreras, J. Patrick Laceby, and Olivier Evrard
SOIL, 10, 109–138, https://doi.org/10.5194/soil-10-109-2024, https://doi.org/10.5194/soil-10-109-2024, 2024
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Sediment source fingerprinting is a relevant tool to support soil conservation and watershed management in the context of accelerated soil erosion. To quantify sediment source contribution, it requires the selection of relevant tracers. We compared the three-step method and the consensus method and found very contrasted trends. The divergences between virtual mixtures and sample prediction ranges highlight that virtual mixture statistics are not directly transferable to actual samples.
Anthony Foucher, Sergio Morera, Michael Sanchez, Jhon Orrillo, and Olivier Evrard
Hydrol. Earth Syst. Sci., 27, 3191–3204, https://doi.org/10.5194/hess-27-3191-2023, https://doi.org/10.5194/hess-27-3191-2023, 2023
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The current research investigated, as a representative study case, the sediment accumulated in the Poechos Reservoir (located on the west coast of northern Peru) for retrospectively reconstructing the impact on sediment dynamics (1978–2019) of extreme phases of the El Niño–Southern Oscillation, land cover changes after humid periods and agricultural expansion along the riverine system.
Olivier Evrard, Thomas Chalaux-Clergue, Pierre-Alexis Chaboche, Yoshifumi Wakiyama, and Yves Thiry
SOIL, 9, 479–497, https://doi.org/10.5194/soil-9-479-2023, https://doi.org/10.5194/soil-9-479-2023, 2023
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Twelve years after the nuclear accident that occurred in Fukushima in March 2011, radioactive contamination remains a major concern in north-eastern Japan. The Japanese authorities completed an unprecedented decontamination programme. The central objective was to not expose local inhabitants to excessive radioactive doses. At the onset of the full reopening of the Difficult-to-Return Zone in 2023, the current review provides an update of a previous synthesis published in 2019.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
Laurie Boithias, Olivier Ribolzi, Emma Rochelle-Newall, Chanthanousone Thammahacksa, Paty Nakhle, Bounsamay Soulileuth, Anne Pando-Bahuon, Keooudone Latsachack, Norbert Silvera, Phabvilay Sounyafong, Khampaseuth Xayyathip, Rosalie Zimmermann, Sayaphet Rattanavong, Priscia Oliva, Thomas Pommier, Olivier Evrard, Sylvain Huon, Jean Causse, Thierry Henry-des-Tureaux, Oloth Sengtaheuanghoung, Nivong Sipaseuth, and Alain Pierret
Earth Syst. Sci. Data, 14, 2883–2894, https://doi.org/10.5194/essd-14-2883-2022, https://doi.org/10.5194/essd-14-2883-2022, 2022
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Fecal pathogens in surface waters may threaten human health, especially in developing countries. The Escherichia coli (E. coli) database is organized in three datasets and includes 1602 records from 31 sampling stations located within the Mekong River basin in Lao PDR. Data have been used to identify the drivers of E. coli dissemination across tropical catchments, including during floods. Data may be further used to interpret new variables or to map the health risk posed by fecal pathogens.
Edouard Patault, Valentin Landemaine, Jérôme Ledun, Arnaud Soulignac, Matthieu Fournier, Jean-François Ouvry, Olivier Cerdan, and Benoit Laignel
Hydrol. Earth Syst. Sci., 25, 6223–6238, https://doi.org/10.5194/hess-25-6223-2021, https://doi.org/10.5194/hess-25-6223-2021, 2021
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The goal of this study was to assess the sediment discharge variability at a water treatment plant (Normandy, France) according to multiple realistic land use scenarios. We developed a new cascade modelling approach and simulations suggested that coupling eco-engineering and best farming practices can significantly reduce the sediment discharge (up to 80 %).
Virginie Sellier, Oldrich Navratil, John Patrick Laceby, Cédric Legout, Anthony Foucher, Michel Allenbach, Irène Lefèvre, and Olivier Evrard
SOIL, 7, 743–766, https://doi.org/10.5194/soil-7-743-2021, https://doi.org/10.5194/soil-7-743-2021, 2021
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Open-cast mining increases soil erosion and transfer of sediment in river systems. Providing a methodology to better understand the sediment dynamic of these catchments is essential to manage this pollution. In this study, different tracers such as elemental geochemistry or colour properties were tested to trace and quantify the mining source contributions to the sediment inputs in the Thio River catchment, one of the first areas exploited for nickel mining in New Caledonia (i.e. since 1880).
Anthony Foucher, Pierre-Alexis Chaboche, Pierre Sabatier, and Olivier Evrard
Earth Syst. Sci. Data, 13, 4951–4966, https://doi.org/10.5194/essd-13-4951-2021, https://doi.org/10.5194/essd-13-4951-2021, 2021
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Sediment archives provide a powerful and unique tool for reconstructing the trajectory and the resilience of terrestrial and aquatic ecosystems facing major environmental changes. Establishing an age depth–model is the first prerequisite of any paleo-investigation. This study synthesizes the distribution of two radionuclides classically used to this aim, providing a worldwide reference to help the scientific community reach a consensus for dating recent sedimentary archives.
Olivier Evrard, Caroline Chartin, J. Patrick Laceby, Yuichi Onda, Yoshifumi Wakiyama, Atsushi Nakao, Olivier Cerdan, Hugo Lepage, Hugo Jaegler, Rosalie Vandromme, Irène Lefèvre, and Philippe Bonté
Earth Syst. Sci. Data, 13, 2555–2560, https://doi.org/10.5194/essd-13-2555-2021, https://doi.org/10.5194/essd-13-2555-2021, 2021
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This dataset provides an original compilation of radioactive dose rates and artificial radionuclide activities in sediment deposited after floods in the rivers draining the main radioactive pollution plume in Fukushuma, Japan, between November
2011 and November 2020. In total, 782 sediment samples collected from 27 to 71 locations during 16 fieldwork campaigns were analysed. This provides a unique post-accidental dataset to better understand the environmental fate of radionuclides.
André-Marie Dendievel, Brice Mourier, Alexandra Coynel, Olivier Evrard, Pierre Labadie, Sophie Ayrault, Maxime Debret, Florence Koltalo, Yoann Copard, Quentin Faivre, Thomas Gardes, Sophia Vauclin, Hélène Budzinski, Cécile Grosbois, Thierry Winiarski, and Marc Desmet
Earth Syst. Sci. Data, 12, 1153–1170, https://doi.org/10.5194/essd-12-1153-2020, https://doi.org/10.5194/essd-12-1153-2020, 2020
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Polychlorinated biphenyl indicators (ΣPCBi) from sediment cores, bed and flood deposits, suspended particulate matter, and dredged sediments along the major French rivers (1945–2018) are compared with socio-hydrological drivers. ΣPCBi increased from 1945 to the 1990s due to urban and industrial emissions. It gradually decreased with the implementation of regulations. Specific ΣPCBi fluxes reveal the amount of PCB-polluted sediment transported by French rivers to European seas over 40 years.
Olivier Evrard, J. Patrick Laceby, and Atsushi Nakao
SOIL, 5, 333–350, https://doi.org/10.5194/soil-5-333-2019, https://doi.org/10.5194/soil-5-333-2019, 2019
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The Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident in March 2011 resulted in the contamination of Japanese landscapes with radioactive fallout. The objective of this review is to provide an overview of the decontamination strategies and their potential effectiveness in Japan. Overall, we believe it is important to synthesise the remediation lessons learnt following the FDNPP nuclear accident, which could be fundamental if radioactive fallout occurred somewhere on Earth in the future.
Wenchao Ma, Jun Asanuma, Jianqing Xu, and Yuichi Onda
Earth Syst. Sci. Data, 10, 2295–2309, https://doi.org/10.5194/essd-10-2295-2018, https://doi.org/10.5194/essd-10-2295-2018, 2018
E. Gourdin, S. Huon, O. Evrard, O. Ribolzi, T. Bariac, O. Sengtaheuanghoung, and S. Ayrault
Biogeosciences, 12, 1073–1089, https://doi.org/10.5194/bg-12-1073-2015, https://doi.org/10.5194/bg-12-1073-2015, 2015
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The origin and dynamics of particulate organic matter were studied in a 11.6km² catchment (northern Laos) during the first erosive flood of the 2012 rainy season. Upstream suspended sediments mainly originated from cultivated soils labelled by their C3 vegetation cover. In contrast, channel banks with C4 vegetation supplied significant quantities of sediment to the river downstream. Swamps located along the main stream acted as sediment filters and controlled the composition of suspended POM.
M. S. Kim, Y. Onda, and J. K. Kim
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-3-227-2015, https://doi.org/10.5194/nhessd-3-227-2015, 2015
Revised manuscript not accepted
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The accuracy of shallow landslide prediction based on SHALSTAB model varying the input soil data was examined. Soil parameters calculated from a stochastic hydro-geomorphological model were applied to the SHALSTAB model. Results showed that the use of soil properties reflecting soil thickness can improve the accuracy of shallow landslide prediction.
H. Lepage, O. Evrard, Y. Onda, I. Lefèvre, J. P. Laceby, and S. Ayrault
SOIL Discuss., https://doi.org/10.5194/soild-1-401-2014, https://doi.org/10.5194/soild-1-401-2014, 2014
Revised manuscript not accepted
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
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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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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.
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.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-131, https://doi.org/10.5194/hess-2024-131, 2024
Revised manuscript accepted for HESS
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ET is computed from vegetation (plant transpiration) and soil (soil evaporation). In Western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented with the leaf-area-index (LAI). In this study, we evaluate the importance of LAI for the ET calculation. We take a close look at the LAI-ET interaction and show the relevance to consider both, LAI and ET. Our work contributes to the understanding of the processes of the terrestrial water cycle.
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.
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.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
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This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
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To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-57, https://doi.org/10.5194/hess-2024-57, 2024
Revised manuscript accepted for HESS
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. In this work we investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analysis indicate that adding two vegetation is enough to improve the representation of evaporation, and the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
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Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
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Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
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Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Cited articles
Akaike, H.: A new look at the statistical model identification, Automatic Control, IEEE Transactions on, 19, 716–723, 1974.
Barry, R. G. and Chorley, R. J.: Atmosphere, weather and climate, Routledge, 536 pp., 2009.
Belyaev, V. R., Golosov, V. N., Ivanova, N. N., Markelov, M. V., and Tishkina, E. V.: Human-accelerated soil redistribution within an intensively cultivated dry valley catchment in southern European Russia, IAHS-P, 291, 11–20, 2005.
Capolongo, D., Diodato, N., Mannaerts, C. M., Piccarreta, M., and Strobl, R. O.: Analyzing temporal changes in climate erosivity using a simplified rainfall erosivity model in Basilicata (southern Italy), J. Hydrol., 356, 119–130, https://doi.org/10.1016/j.jhydrol.2008.04.002, 2008.
Chartin, C., Evrard, O., Onda, Y., Patin, J., Lefèvre, I., Ottlé, C., Ayrault, S., Lepage, H., and Bonté, P.: Tracking the early dispersion of contaminated sediment along rivers draining the Fukushima radioactive pollution plume, Anthropocene, 1, 23–34, 2013.
Chartin, C., Evrard, O., Onda, Y., Laceby, P., Cerdan, O., Lepage, H., Ottlé, C., Lefèvre, I., and Bonté, P.: The impact of typhoons on sediment connectivity: Lessons learnt from contaminated coastal catchments of Fukushima Prefecture (Japan), Earth Surf. Process. Landf., in revision, 2016.
Chino, M., Nakayama, H., Nagai, H., Terada, H., Katata, G., and Yamazawa, H.: Preliminary estimation of release amounts of 131I and 137Cs accidentally discharged from the Fukushima Daiichi nuclear power plant into the atmosphere, J. Nucl. Sci. Technol., 48, 1129–1134, 2011.
Daly, C.: Variable influence of terrain on precipitation patterns: Delineation and use of effective terrain height in PRISM, World Wide Web document, http://www.ocs.orst.edu/prism/effter.pdf (last access: 15 April 2016), 2002.
Daly, C., Gibson, W. P., Taylor, G. H., Johnson, G. L., and Pasteris, P.: A knowledge-based approach to the statistical mapping of climate, Clim. Res., 22, 99–113, 2002.
de Brogniez, D., Ballabio, C., Stevens, A., Jones, R., Montanarella, L., and van Wesemael, B.: A map of the topsoil organic carbon content of Europe generated by a generalized additive model, Europ. J. Soil Sci., 66, 121–134, 2015.
Duan, W., He, B., Takara, K., Luo, P., Hu, M., Alias, N. E., and Nover, D.: Changes of precipitation amounts and extremes over Japan between 1901 and 2012 and their connection to climate indices, Clim. Dynam., 45, 2273–2292, 2015.
Eltaif, N. I., Gharaibeh, M. A., Al-Zaitawi, F., and Alhamad, M. N.: Approximation of Rainfall Erosivity Factors in North Jordan, Pedosphere, 20, 711–717, https://doi.org/10.1016/S1002-0160(10)60061-6, 2010.
ESRI: ArcGIS Desktop: Release 10, Redlands, Environmental Systems Research Institute, CA, 2011.
Evrard, O., Chartin, C., Onda, Y., Patin, J., Lepage, H., Lefèvre, I., Ayrault, S., Ottlé, C., and Bonté, P.: Evolution of radioactive dose rates in fresh sediment deposits along coastal rivers draining Fukushima contamination plume, Scientific reports, 3, 3079, https://doi.org/10.1038/srep03079, 2013.
Evrard, O., Chartin, C., Onda, Y., Lepage, H., Cerdan, O., Lefevre, I., and Ayrault, S.: Renewed soil erosion and remobilisation of radioactive sediment in Fukushima coastal rivers after the 2013 typhoons, Sci. Rep., 4, 4574, https://doi.org/10.1038/srep04574, 2014.
Evrard, O., Laceby, J. P., Lepage, H., Onda, Y., Cerdan, O., and Ayrault, S.: Radiocesium transfer from hillslopes to the Pacific Ocean after the Fukushima Nuclear Power Plant accident: A review, J. Environ. Radioactiv., 148, 92–110, https://doi.org/10.1016/j.jenvrad.2015.06.018, 2015.
García-Oliva, F., Maass, J. M., and Galicia, L.: Rainstorm Analysis and Rainfall Erosivity of a Seasonal Tropical Region with a Strong Cyclonic Influence on the Pacific Coast of Mexico, J. Appl. Meteorol., 34, 2491–2498, https://doi.org/10.1175/1520-0450(1995)034<2491:RAAREO>2.0.CO;2, 1995.
Hastie, T. and Tibshirani, R.: Generalized additive models, Statistical science, 297–310, 1986.
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., and Jarvis, A.: Very high resolution interpolated climate surfaces for global land areas, Int. J. Climatol., 25, 1965–1978, 2005.
Jarvis, A., Reuter, H. I., Nelson, A., and Guevara, E.: Hole-filled SRTM for the globe Version 4, available from the CGIAR-CSI SRTM 90m Database http://srtm.csi.cgiar.org (last access: 15 April 2016), 2008.
JMA (Japanese Meteorological Agency) RSMC Tokyo – Typhoon Center: http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/RSMC_HP.htm, last access: 12 February 2016.
Karki, K. B. and Shibano, H.: Soil loss in a forested watershed underlain by deeply weathered granite: comparison of observations to predictions of a GIS-based USLE, Bulletin of the Tokyo University Forests, 2006.
Karydas, C. G., Tzoraki, O., and Panagos, P.: A New Spatiotemporal Risk Index for Heavy Metals: Application in Cyprus, Water, 7, 4323–4342, 2015.
Kato, H., Onda, Y., and Teramage, M.: Depth distribution of 137Cs, 134Cs, and 131I in soil profile after Fukushima Dai-ichi Nuclear Power Plant Accident, J. Environ. Radioactiv., 111, 59–64, https://doi.org/10.1016/j.jenvrad.2011.10.003, 2012.
Kim, S., Nakakita, E., Tachikawa, Y., and Takara, K.: Precipitation changes in Japan under the A1B climate change scenario, Ann. J. Hydr. Eng., 54, 127–132, 2010.
Kinnell, P. I. A.: Event soil loss, runoff and the Universal Soil Loss Equation family of models: A review, J. Hydrol., 385, 384–397, https://doi.org/10.1016/j.jhydrol.2010.01.024, 2010.
Kitamura, A., Yamaguchi, M., Kurikami, H., Yui, M., and Onishi, Y.: Predicting sediment and cesium-137 discharge from catchments in eastern Fukushima, Anthropocene, 5, 22–31, https://doi.org/10.1016/j.ancene.2014.07.001, 2014.
Larionov, G.: Erosion and deflation of soils, Moscow University Press, Moscow, Russia, 200 pp., 1993.
Lee, J.-H. and Heo, J.-H.: Evaluation of estimation methods for rainfall erosivity based on annual precipitation in Korea, J. Hydrol., 409, 30–48, https://doi.org/10.1016/j.jhydrol.2011.07.031, 2011.
Lu, H. and Yu, B.: Spatial and seasonal distribution of rainfall erosivity in Australia, Soil Research, 40, 887-901, 2002.
Ma, X., He, Y., Xu, J., van Noordwijk, M., and Lu, X.: Spatial and temporal variation in rainfall erosivity in a Himalayan watershed, CATENA, 121, 248–259, https://doi.org/10.1016/j.catena.2014.05.017, 2014.
McFarlane, D., Westcott, T., and Davies, J.: Rainfall erosivity in Western Australia, Hydrology and Water Resources Symposium 1986: River Basin Management, Preprints of Papers, 350, 1986.
Mello, C. R., Viola, M. R., Beskow, S., and Norton, L. D.: Multivariate models for annual rainfall erosivity in Brazil, Geoderma, 202–203, 88–102, https://doi.org/10.1016/j.geoderma.2013.03.009, 2013.
Meusburger, K., Steel, A., Panagos, P., Montanarella, L., and Alewell, C.: Spatial and temporal variability of rainfall erosivity factor for Switzerland, Hydrol. Earth Syst. Sci., 16, 167–177, https://doi.org/10.5194/hess-16-167-2012, 2012.
Moore, T.: Rainfall erosivity in East Africa, Phys. Geogr., 147–156, 1979.
Mouri, G., Golosov, V., Shiiba, M., and Hori, T.: Assessment of the caesium-137 flux adsorbed to suspended sediment in a reservoir in the contaminated Fukushima region in Japan, Environ. Pollut., 187, 31–41, https://doi.org/10.1016/j.envpol.2013.12.018, 2014.
Nagao, S., Kanamori, M., Ochiai, S., Tomihara, S., Fukushi, K., and Yamamoto, M.: Export of 134Cs and 137Cs in the Fukushima river systems at heavy rains by Typhoon Roke in September 2011, Biogeosciences, 10, 6215–6223, https://doi.org/10.5194/bg-10-6215-2013, 2013.
Nazarok, P., Kruglov, O., Menshov, O., Kutsenko, M., and Sukhorada, A.: Mapping soil erosion using magnetic susceptibility. A case study in Ukraine, Solid Earth Discuss., 6, 831–848, https://doi.org/10.5194/sed-6-831-2014, 2014.
Oliveira, P. T. S., Wendland, E., and Nearing, M. A.: Rainfall erosivity in Brazil: A review, CATENA, 100, 139–147, https://doi.org/10.1016/j.catena.2012.08.006, 2013.
Onishi, Y., Kurikami, H., and Yokuda, S.: Simulation of Sediment and Cesium Transport in the Ukedo River and the Ogi Dam Reservoir during a Rainfall Event using the TODAM Code, Pacific Northwest National Laboratory (PNNL), Richland, WA, 124 pp., 2014.
Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., Tadić, M. P., Michaelides, S., Hrabaliková, M., and Olsen, P.: Rainfall erosivity in Europe, Sci. Total Environ., 511, 801–814, 2015.
Peel, M. C., Finlayson, B. L., and McMahon, T. A.: Updated world map of the Köppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633–1644, https://doi.org/10.5194/hess-11-1633-2007, 2007.
Poggio, L., Gimona, A., and Brewer, M. J.: Regional scale mapping of soil properties and their uncertainty with a large number of satellite-derived covariates, Geoderma, 209, 1–14, 2013.
Renard, K. G. and Freimund, J. R.: Using monthly precipitation data to estimate the R factor in the revised USLE, J. Hydrol., 157, 287–306, https://doi.org/10.1016/0022-1694(94)90110-4, 1994.
Renard, K. G., Foster, G. R., Weesies, G. A., and Porter, J. P.: RUSLE: Revised universal soil loss equation, J. Soil Water Conserv., 46, 30–33, 1991.
Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D., and Yoder, D.: Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE), Agriculture Handbook Washington, 403 pp., 1997.
Rosa, D. D. L., Crompvoets, J., Mayol, F., and Moreno, J. A.: Land vulnerability evaluation and climate change impacts in Andalucia, Agrophys. J., 10, 225–238, 1996.
Saito, K. and Onda, Y.: Outline of the national mapping projects implemented after the Fukushima accident, J. Environ. Radioactiv., 139, 240–249, 2015.
Saito, K., Tanihata, I., Fujiwara, M., Saito, T., Shimoura, S., Otsuka, T., Onda, Y., Hoshi, M., Ikeuchi, Y., and Takahashi, F.: Detailed deposition density maps constructed by large-scale soil sampling for gamma-ray emitting radioactive nuclides from the Fukushima Dai-ichi Nuclear Power Plant accident, J. Environ. Radioactiv., 139, 308–319, 2015.
Sawhiney, B.: Selective sorption and fixation of cations by clay minerals: a review, Clays Clay Miner, 20, 93–100, 1972.
Shamshad, A., Azhari, M. N., Isa, M. H., Hussin, W. M. A. W., and Parida, B. P.: Development of an appropriate procedure for estimation of RUSLE EI30 index and preparation of erosivity maps for Pulau Penang in Peninsular Malaysia, CATENA, 72, 423–432, https://doi.org/10.1016/j.catena.2007.08.002, 2008.
Shiono, T., Ogawa, S., Miyamoto, T., and Kameyama, K.: Expected impacts of climate change on rainfall erosivity of farmlands in Japan, Ecol. Eng., 61, 678–689, 2013.
Svetlitchnyi, A.: Soil Erosion Induced Degradation of Agrolandscapes in Ukraine: Modeling, Computation and Prediction in Conditions of the Climate Changes, in: Regional Aspects of Climate-Terrestrial-Hydrologic Interactions in Non-boreal Eastern Europe, edited by: Groisman, P., and Ivanov, S., NATO Science for Peace and Security Series C: Environmental Security, Springer Netherlands, 191–199, 2009.
Takeuchi, B. K. and Ishidaira, H.: The examination of sediment production estimation by the USLE method in mountainous basins of Japan, Hydr. Eng., 45, 85–90, 2001.
Tamura, T.: Consequences of activity release: selective sorption reactions of cesium with soil minerals, Nucl. Safety 5, 262–268, 1964.
Thakur, P., Ballard, S., and Nelson, R.: An overview of Fukushima radionuclides measured in the northern hemisphere, Sci. Total Environ., 458–460, 577–613, https://doi.org/10.1016/j.scitotenv.2013.03.105, 2013.
Tran, T. A., Mitani, Y., Ikemi, H., and Matsuki, H.: Human Impacts on Erosion and Deposition in Onga River Basin, Kyushu, Japan, Memoirs of the Faculty of Engineering, Kyushu University, 71, 47–65, 2011.
USDA: Rainfall Intensity Summarization Tool (RIST), United States Department of Agriculture (USDA), Agriculture Research Service, National Sedimentation Laboratory, Oxford, Mississippi, Version 3.88, 2013.
Wang, X. L., Chen, H., Wu, Y., Feng, Y., and Pu, Q.: New Techniques for the Detection and Adjustment of Shifts in Daily Precipitation Data Series, J. Appl. Meteorol. Climatol., 49, 2416–2436, https://doi.org/10.1175/2010JAMC2376.1, 2010.
Wikipedia Pacific typhoon climatology: https://en.wikipedia.org/wiki/Pacific_typhoon_climatology, last access: 13 February 2016.
Wilkinson, S. N., Prosser, I. P., Rustomji, P., and Read, A. M.: Modelling and testing spatially distributed sediment budgets to relate erosion processes to sediment yields, Environ. Model. Softw., 24, 489–501, 2009.
Wischmeier, W. H. and Smith, D. D.: Rainfall energy and its relationship to soil loss, T. Am. Geophys. Union, 39, 285–291, https://doi.org/10.1029/TR039i002p00285, 1958.
Wischmeier, W. H. and Smith, D. D.: Predicting rainfall erosion losses-A guide to conservation planning, Predicting rainfall erosion losses – A guide to conservation planning, 58 pp., 1978.
Wood, S. N.: mgcv: GAMs and generalized ridge regression for r, R news, 1, 2–25, 2001.
Yamaguchi, M., Kitamura, A., Oda, Y., and Onishi, Y.: Predicting the long-term 137Cs distribution in Fukushima after the Fukushima Dai-ichi nuclear power plant accident: a parameter sensitivity analysis, J. Environ. Radioactiv., 135, 135–146, https://doi.org/10.1016/j.jenvrad.2014.04.011, 2014.
Yamashiki, Y., Onda, Y., Smith, H. G., Blake, W. H., Wakahara, T., Igarashi, Y., Matsuura, Y., and Yoshimura, K.: Initial flux of sediment-associated radiocesium to the ocean from the largest river impacted by Fukushima Daiichi Nuclear Power Plant, Sci. Reports, 4, https://doi.org/10.1038/srep03714, 2014.
Yoshimura, K., Onda, Y., and Kato, H.: Evaluation of radiocaesium wash-off by soil erosion from various land uses using USLE plots, J. Environ. Radioactiv., 139, 362–369, https://doi.org/10.1016/j.jenvrad.2014.07.019, 2015.
Yu, B., Hashim, G., and Eusof, Z.: Estimating the R factor with limited rainfall data: a case study from peninsular Malaysia, Journal of Soil and Water Conservation, 56, 101–105, 2001.
Zar, J. H.: Biostatistical Analysis, 5th Edition ed., Prentice Hall, New Jersey, 960 pp., 2010.
Short summary
Characterizing rainfall erosivity in the Fukushima fallout-impacted region is important for predicting radiocesium behavior. The majority of rainfall (60 %) and rainfall erosivity (86 %) occurs between June and October. Tropical cyclones contribute 22 % of the precipitation though 44 % of the rainfall erosivity. Understanding the rainfall regime and the influence of tropical cyclones is important managing radiocesium transfers in contaminated catchments in the Fukushima prefecture.
Characterizing rainfall erosivity in the Fukushima fallout-impacted region is important for...
