Articles | Volume 25, issue 6
https://doi.org/10.5194/hess-25-2979-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-2979-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jun 2021
Research article |
| 03 Jun 2021
| 03 Jun 2021
Performance of automated methods for flash flood inundation mapping: a comparison of a digital terrain model (DTM) filling and two hydrodynamic methods
GERS-LEE, Univ. Gustave Eiffel, IFSTTAR, F-44344 Bouguenais, France
Olivier Payrastre
CORRESPONDING AUTHOR
GERS-LEE, Univ. Gustave Eiffel, IFSTTAR, F-44344 Bouguenais, France
François Bourgin
GERS-LEE, Univ. Gustave Eiffel, IFSTTAR, F-44344 Bouguenais, France
Université Paris-Saclay, INRAE, UR HYCAR, 92160 Antony, France
Eric Gaume
GERS-LEE, Univ. Gustave Eiffel, IFSTTAR, F-44344 Bouguenais, France
Philippe Davy
Géosciences Rennes, Université Rennes 1, CNRS, UMR 6118, 35042 Rennes, France
Dimitri Lague
Géosciences Rennes, Université Rennes 1, CNRS, UMR 6118, 35042 Rennes, France
Lea Poinsignon
Cerema Méditerranée, 13290 Aix-en-Provence, France
Frederic Pons
Cerema Méditerranée, 13290 Aix-en-Provence, France
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Taha-Abderrahman El Ouahabi, François Bourgin, Charles Perrin, and Vazken Andréassian
EGUsphere, https://doi.org/10.5194/egusphere-2025-3586, https://doi.org/10.5194/egusphere-2025-3586, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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To improve hydrological uncertainty estimation, recent studies have explored machine learning (ML)-based post-processing approaches. Among these, quantile random forests (QRF) are increasingly used for their balance between interpretability and performance. We develop a hydrologically informed QRF trained in a multi-site setting. Our results show that the regional QRF approach is beneficial, particularly in catchments where local information is insufficient.
Juliette Godet, Pierre Nicolle, Nabil Hocini, Eric Gaume, Philippe Davy, Frederic Pons, Pierre Javelle, Pierre-André Garambois, Dimitri Lague, and Olivier Payrastre
Earth Syst. Sci. Data, 17, 2963–2983, https://doi.org/10.5194/essd-17-2963-2025, https://doi.org/10.5194/essd-17-2963-2025, 2025
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This paper describes a dataset that includes input, output, and validation data for the simulation of flash flood hazards and three specific flash flood events in the French Mediterranean region. This dataset is particularly valuable as flood mapping methods often lack sufficient benchmark data. Additionally, we demonstrate how the hydraulic method we used, named Floodos, produces highly satisfactory results.
Marion Fournereau, Laure Guerit, Philippe Steer, Jean-Jacques Kermarrec, Paul Leroy, Christophe Lanos, Hélène Hivert, Claire Astrié, and Dimitri Lague
EGUsphere, https://doi.org/10.5194/egusphere-2025-1541, https://doi.org/10.5194/egusphere-2025-1541, 2025
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River bedrock erosion can occur by polishing and by the removal of entire blocks. We observe that when there is no to little fractures most erosion occurs by polishing whereas with more fractures, blocks can be removed at once leading to different patterns of erosion and riverbed morphology. Fractures affect barely mean erosion rate but change the location and occurrence of block removal. Our results highlight how river bedrock properties influence erosion processes and thus landscape evolution.
Marine Le Minor, Dimitri Lague, Jamie Howarth, and Philippe Davy
EGUsphere, https://doi.org/10.5194/egusphere-2025-1271, https://doi.org/10.5194/egusphere-2025-1271, 2025
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In natural rivers, flow variability and sediment heterogeneity affect how sediment grains are transported. A unique law that predicts the total amount of sediment transportable by a river for a wide range of sediment mixtures and flow conditions exist but unclear trends remain. Two improvements of this law, a standardized onset of sediment transport and a common reference transport height across all sizes, appear to be critical to have a functional multi grain-size total sediment load.
Juliette Godet, Eric Gaume, Pierre Javelle, Thomas Dias, Pierre Nicolle, and Olivier Payrastre
Abstr. Int. Cartogr. Assoc., 9, 16, https://doi.org/10.5194/ica-abs-9-16-2025, https://doi.org/10.5194/ica-abs-9-16-2025, 2025
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
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The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Jean-Emmanuel Paturel, Bérenger Kouacou, Franck Lohou, Frédéric Pons, Kouakou Dje, Naky Coulibaly, Harouna Karambiri, Valérie Borrell, Andrew Ogilvie, and Eric Servat
Proc. IAHS, 385, 219–224, https://doi.org/10.5194/piahs-385-219-2024, https://doi.org/10.5194/piahs-385-219-2024, 2024
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In 2011, the XVI World Meteorological Congress urged Members to make every effort to prevent the deterioration of climate-relevant data and to make these data available to support climate change analyses and relevant climate services. In response to the WMO call, we used the NUNIEAU software which allows the digitization of different types of paper documents by automatic recognition. This software has been used on rainfall pluviograms in Burkina Faso and Côte d'Ivoire.
Juliette Godet, Eric Gaume, Pierre Javelle, Pierre Nicolle, and Olivier Payrastre
Hydrol. Earth Syst. Sci., 28, 1403–1413, https://doi.org/10.5194/hess-28-1403-2024, https://doi.org/10.5194/hess-28-1403-2024, 2024
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This work was performed in order to precisely address a point that is often neglected by hydrologists: the allocation of points located on a river network to grid cells, which is often a mandatory step for hydrological modelling.
Juliette Godet, Olivier Payrastre, Pierre Javelle, and François Bouttier
Nat. Hazards Earth Syst. Sci., 23, 3355–3377, https://doi.org/10.5194/nhess-23-3355-2023, https://doi.org/10.5194/nhess-23-3355-2023, 2023
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This article results from a master's research project which was part of a natural hazards programme developed by the French Ministry of Ecological Transition. The objective of this work was to investigate a possible way to improve the operational flash flood warning service by adding rainfall forecasts upstream of the forecasting chain. The results showed that the tested forecast product, which is new and experimental, has a real added value compared to other classical forecast products.
Maryse Charpentier-Noyer, Daniela Peredo, Axelle Fleury, Hugo Marchal, François Bouttier, Eric Gaume, Pierre Nicolle, Olivier Payrastre, and Maria-Helena Ramos
Nat. Hazards Earth Syst. Sci., 23, 2001–2029, https://doi.org/10.5194/nhess-23-2001-2023, https://doi.org/10.5194/nhess-23-2001-2023, 2023
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This paper proposes a methodological framework designed for event-based evaluation in the context of an intense flash-flood event. The evaluation adopts the point of view of end users, with a focus on the anticipation of exceedances of discharge thresholds. With a study of rainfall forecasts, a discharge evaluation and a detailed look at the forecast hydrographs, the evaluation framework should help in drawing robust conclusions about the usefulness of new rainfall ensemble forecasts.
Thomas Hermans, Pascal Goderniaux, Damien Jougnot, Jan H. Fleckenstein, Philip Brunner, Frédéric Nguyen, Niklas Linde, Johan Alexander Huisman, Olivier Bour, Jorge Lopez Alvis, Richard Hoffmann, Andrea Palacios, Anne-Karin Cooke, Álvaro Pardo-Álvarez, Lara Blazevic, Behzad Pouladi, Peleg Haruzi, Alejandro Fernandez Visentini, Guilherme E. H. Nogueira, Joel Tirado-Conde, Majken C. Looms, Meruyert Kenshilikova, Philippe Davy, and Tanguy Le Borgne
Hydrol. Earth Syst. Sci., 27, 255–287, https://doi.org/10.5194/hess-27-255-2023, https://doi.org/10.5194/hess-27-255-2023, 2023
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Although invisible, groundwater plays an essential role for society as a source of drinking water or for ecosystems but is also facing important challenges in terms of contamination. Characterizing groundwater reservoirs with their spatial heterogeneity and their temporal evolution is therefore crucial for their sustainable management. In this paper, we review some important challenges and recent innovations in imaging and modeling the 4D nature of the hydrogeological systems.
Philippe Steer, Laure Guerit, Dimitri Lague, Alain Crave, and Aurélie Gourdon
Earth Surf. Dynam., 10, 1211–1232, https://doi.org/10.5194/esurf-10-1211-2022, https://doi.org/10.5194/esurf-10-1211-2022, 2022
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The morphology and size of sediments influence erosion efficiency, sediment transport and the quality of aquatic ecosystem. In turn, the spatial evolution of sediment size provides information on the past dynamics of erosion and sediment transport. We have developed a new software which semi-automatically identifies and measures sediments based on 3D point clouds. This software is fast and efficient, offering a new avenue to measure the geometrical properties of large numbers of sediment grains.
Clément Desormeaux, Vincent Godard, Dimitri Lague, Guillaume Duclaux, Jules Fleury, Lucilla Benedetti, Olivier Bellier, and the ASTER Team
Earth Surf. Dynam., 10, 473–492, https://doi.org/10.5194/esurf-10-473-2022, https://doi.org/10.5194/esurf-10-473-2022, 2022
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Landscape evolution is highly dependent on climatic parameters, and the occurrence of intense precipitation events is considered to be an important driver of river incision. We compare the rate of erosion with the variability of river discharge in a mountainous landscape of SE France where high-magnitude floods regularly occur. Our study highlights the importance of the hypotheses made regarding the threshold that river discharge needs to exceed in order to effectively cut down into the bedrock.
M. Letard, A. Collin, D. Lague, T. Corpetti, Y. Pastol, and A. Ekelund
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 463–470, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-463-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-463-2022, 2022
Christoph Lécuyer, François Atrops, François Fourel, Jean-Pierre Flandrois, Gilles Pinay, and Philippe Davy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-132, https://doi.org/10.5194/hess-2022-132, 2022
Manuscript not accepted for further review
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Located in the French Southern Alps, the Cerveyrette valley constitutes a watershed of about 100 km2. Cyclicality in the stable isotope compositions of the river waters recorded over two years allowed us to estimate a time lag of three to four months between precipitations and their sampling at the discharge point of the watershed. We thus show that the transfer time from mountain-accumulated snow toward the low-altitude areas is a sensitive variable responding to the current climate warming.
Léopold de Lavaissière, Stéphane Bonnet, Anne Guyez, and Philippe Davy
Earth Surf. Dynam., 10, 229–246, https://doi.org/10.5194/esurf-10-229-2022, https://doi.org/10.5194/esurf-10-229-2022, 2022
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Rivers are known to record changes in tectonic or climatic variation through long adjustment of their longitudinal profile slope. Here we describe such adjustments in experimental landscapes and show that they may result from the sole effect of intrinsic geomorphic processes. We propose a new model of river evolution that links long profile adjustment to cycles of river widening and narrowing. This result emphasizes the need to better understand control of lateral erosion on river width.
Thomas G. Bernard, Dimitri Lague, and Philippe Steer
Earth Surf. Dynam., 9, 1013–1044, https://doi.org/10.5194/esurf-9-1013-2021, https://doi.org/10.5194/esurf-9-1013-2021, 2021
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Both landslide mapping and volume estimation accuracies are crucial to quantify landscape evolution and manage such a natural hazard. We developed a method to robustly detect landslides and measure their volume from repeat 3D point cloud lidar data. This method detects more landslides than classical 2D inventories and resolves known issues of indirect volume measurement. Our results also suggest that the number of small landslides classically detected from 2D imagery is underestimated.
Benjamin Campforts, Charles M. Shobe, Philippe Steer, Matthias Vanmaercke, Dimitri Lague, and Jean Braun
Geosci. Model Dev., 13, 3863–3886, https://doi.org/10.5194/gmd-13-3863-2020, https://doi.org/10.5194/gmd-13-3863-2020, 2020
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Landslides shape the Earth’s surface and are a dominant source of terrestrial sediment. Rivers, then, act as conveyor belts evacuating landslide-produced sediment. Understanding the interaction among rivers and landslides is important to predict the Earth’s surface response to past and future environmental changes and for mitigating natural hazards. We develop HyLands, a new numerical model that provides a toolbox to explore how landslides and rivers interact over several timescales.
O. Perrin, S. Christophe, F. Jacquinod, and O. Payrastre
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 795–801, https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-795-2020, https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-795-2020, 2020
Lionel Berthet, François Bourgin, Charles Perrin, Julie Viatgé, Renaud Marty, and Olivier Piotte
Hydrol. Earth Syst. Sci., 24, 2017–2041, https://doi.org/10.5194/hess-24-2017-2020, https://doi.org/10.5194/hess-24-2017-2020, 2020
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An increasing number of flood forecasting services assess and communicate the uncertainty associated with their forecasts. We present a crash-testing framework that evaluates the quality of hydrological forecasts in an extrapolation context. Overall, the results highlight the challenge of uncertainty quantification when forecasting high flows. They show a significant drop in reliability when forecasting high flows and considerable variability among catchments and across lead times.
Etienne Lavoine, Philippe Davy, Caroline Darcel, and Romain Le Goc
Adv. Geosci., 49, 77–83, https://doi.org/10.5194/adgeo-49-77-2019, https://doi.org/10.5194/adgeo-49-77-2019, 2019
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In this study, we are interested in quantifying natural fracture density variability, at any scale. We develop and numerically validate analytical solutions considering stochastic Discrete Fracture Networks, with application to networks following power-law fracture size distributions. Particularly, we show that for this kind of networks, the scaling of three-dimensional fracture density variability clearly depends on the power-law exponent, but not on the orientation distribution.
Philippe Steer, Thomas Croissant, Edwin Baynes, and Dimitri Lague
Earth Surf. Dynam., 7, 681–706, https://doi.org/10.5194/esurf-7-681-2019, https://doi.org/10.5194/esurf-7-681-2019, 2019
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We use a statistical earthquake generator to investigate the influence of fault activity on river profile development and on the formation of co-seismic knickpoints. We find that the magnitude distribution of knickpoints resulting from a purely seismic fault is homogeneous. Shallow aseismic slip favours knickpoints generated by large-magnitude earthquakes nucleating at depth. Accounting for fault burial by alluvial cover can modulate the topographic expression of earthquakes and fault activity.
William Amponsah, Pierre-Alain Ayral, Brice Boudevillain, Christophe Bouvier, Isabelle Braud, Pascal Brunet, Guy Delrieu, Jean-François Didon-Lescot, Eric Gaume, Laurent Lebouc, Lorenzo Marchi, Francesco Marra, Efrat Morin, Guillaume Nord, Olivier Payrastre, Davide Zoccatelli, and Marco Borga
Earth Syst. Sci. Data, 10, 1783–1794, https://doi.org/10.5194/essd-10-1783-2018, https://doi.org/10.5194/essd-10-1783-2018, 2018
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The EuroMedeFF database comprises 49 events that occurred in France, Israel, Germany, Slovenia, Romania, and Italy. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the verification of flash flood hydrological models and for hydro-meteorological forecast systems. It provides, moreover, a sample of rainfall and flood discharge extremes in different climates.
Guillaume Le Bihan, Olivier Payrastre, Eric Gaume, David Moncoulon, and Frédéric Pons
Hydrol. Earth Syst. Sci., 21, 5911–5928, https://doi.org/10.5194/hess-21-5911-2017, https://doi.org/10.5194/hess-21-5911-2017, 2017
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This paper illustrates how an integrated flash flood monitoring (or forecasting) system may be designed to directly provide information on possibly flooded areas and associated impacts on a very detailed river network and over large territories. The approach is extensively tested in the regions of Alès and Draguignan, located in south-eastern France. Validation results are presented in terms of accuracy of the estimated flood extents and related impacts (based on insurance claim data).
F. Bourgin, V. Andréassian, C. Perrin, and L. Oudin
Hydrol. Earth Syst. Sci., 19, 2535–2546, https://doi.org/10.5194/hess-19-2535-2015, https://doi.org/10.5194/hess-19-2535-2015, 2015
A. Armandine Les Landes, L. Aquilina, P. Davy, V. Vergnaud-Ayraud, and C. Le Carlier
Hydrol. Earth Syst. Sci., 19, 1413–1426, https://doi.org/10.5194/hess-19-1413-2015, https://doi.org/10.5194/hess-19-1413-2015, 2015
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The crystalline rock aquifers of the Armorican Massif present clear evidence of a marine origin of the saline component in the fluids on the regional scale. High chloride concentrations are attributed to three past marine transgressions. The relationship between chloride concentration and transgression age provides constraints for the timescales of fluid circulation. This time frame is useful information for developing conceptual models of the paleo-functioning of Armorican aquifers.
A. Boisson, D. Roubinet, L. Aquilina, O. Bour, and P. Davy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-9829-2014, https://doi.org/10.5194/hessd-11-9829-2014, 2014
Revised manuscript not accepted
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
A distributed hybrid physics–AI framework for learning corrections of internal hydrological fluxes and enhancing high-resolution regionalized flood modeling
Adaptation of root zone storage capacity to climate change and its effects on future streamflow in Alpine catchments: towards non-stationary model parameters
Finding process-behavioural parameterisations of a hydrological model using a multi-step process-based calibration and evaluation scheme
Merits and limits of SWAT-GL: application in contrasting glaciated catchments
Hydrological regime index for non-perennial rivers
Assessing the adequacy of traditional hydrological models for climate change impact studies: a case for long short-term memory (LSTM) neural networks
Assessing the value of high-resolution data and parameter transferability across temporal scales in hydrological modeling: a case study in northern China
Technical note: How many models do we need to simulate hydrologic processes across large geographical domains?
CONCN: a high-resolution, integrated surface water–groundwater ParFlow modeling platform of continental China
Evaluating the effects of topography and land use change on hydrological signatures: a comparative study of two adjacent watersheds
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Long short-term memory networks for enhancing real-time flood forecasts: a case study for an underperforming hydrologic model
Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China
Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable
Scale dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Extended-range forecasting of stream water temperature with deep-learning models
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
Enhanced Baseflow Separation in Rural Catchments: Event-Specific Calibration of Recursive Digital Filters with Tracer-Derived Data
Projections of streamflow intermittence under climate change in European drying river networks
Economic valuation of subsurface water contributions to watershed ecosystem services using a fully integrated groundwater–surface-water model
Catchment Attributes and MEteorology for Large-Sample SPATially distributed analysis (CAMELS-SPAT): Streamflow observations, forcing data and geospatial data for hydrologic studies across North America
Analyzing the generalization capabilities of a hybrid hydrological model for extrapolation to extreme events
CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland
Runoff component quantification and future streamflow projection in a large mountainous basin based on a multidata-constrained cryospheric–hydrological model
Exploring the potential processes controlling changes in precipitation–runoff relationships in non-stationary environments
Spatially Resolved Rainfall Streamflow Modeling in Central Europe
A diversity-centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Simulating the Tone River eastward diversion project in Japan carried out 4 centuries ago
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study
Heavy-tailed flood peak distributions: what is the effect of the spatial variability of rainfall and runoff generation?
Combining uncertainty quantification and entropy-inspired concepts into a single objective function for rainfall-runoff model calibration
State updating of the Xin'anjiang model: joint assimilating streamflow and multi-source soil moisture data via the asynchronous ensemble Kalman filter with enhanced error models
Improving the hydrological consistency of a process-based solute-transport model by simultaneous calibration of streamflow and stream concentrations
Understanding the relationship between streamflow forecast skill and value across the western US
Leveraging soil diversity to mitigate hydrological extremes with nature-based solutions in productive catchments
Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments
The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa
Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model
Spatio-temporal patterns and trends of streamflow in water-scarce Mediterranean basins
A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments
Seasonal variation in land cover estimates reveals sensitivities and opportunities for environmental models
Soil moisture and precipitation intensity control the transit time distribution of quick flow in a flashy headwater catchment
Estimating response times, flow velocities, and roughness coefficients of Canadian Prairie basins
Learning landscape features from streamflow with autoencoders
The influence of lateral flow on land surface fluxes in southeast Australia varies with model resolution
Constraining pesticide degradation in conceptual distributed catchment models with compound-specific isotope analysis (CSIA)
On the use of streamflow transformations for hydrological model calibration
Unveiling the Impact of Potential Evapotranspiration Method Selection on Trends in Hydrological Cycle Components Across Europe
Simulation-based inference for parameter estimation of complex watershed simulators
Ngo Nghi Truyen Huynh, Pierre-André Garambois, Benjamin Renard, François Colleoni, Jérôme Monnier, and Hélène Roux
Hydrol. Earth Syst. Sci., 29, 3589–3613, https://doi.org/10.5194/hess-29-3589-2025, https://doi.org/10.5194/hess-29-3589-2025, 2025
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Understanding and modeling flash-flood-prone areas remains challenging due to limited data and scale-relevant hydrological theory. While machine learning shows promise, its integration with process-based models is difficult. We present an approach incorporating machine learning into a high-resolution hydrological model to correct internal fluxes and transfer parameters between watersheds. Results show improved accuracy, advancing the development of learnable and interpretable process-based models.
Magali Ponds, Sarah Hanus, Harry Zekollari, Marie-Claire ten Veldhuis, Gerrit Schoups, Roland Kaitna, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 3545–3568, https://doi.org/10.5194/hess-29-3545-2025, https://doi.org/10.5194/hess-29-3545-2025, 2025
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This research examines how future climate changes impact root zone storage, a key hydrological model parameter. Root zone storage – the soil water accessible to plants – adapts to climate but is often kept constant in models. We estimated climate-adapted storage in six Austrian Alps catchments. While storage increased, streamflow projections showed minimal change, which suggests that dynamic root zone representation is less critical in humid regions but warrants further study in arid areas.
Moritz M. Heuer, Hadysa Mohajerani, and Markus C. Casper
Hydrol. Earth Syst. Sci., 29, 3503–3525, https://doi.org/10.5194/hess-29-3503-2025, https://doi.org/10.5194/hess-29-3503-2025, 2025
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This study presents a process-behavioural calibration approach for water balance models. The different calibration steps aim at calibrating different hydrological processes: evapotranspiration, the runoff partitioning into surface runoff, interflow, and groundwater recharge, as well as the groundwater behaviour. This allows for selection of a model parameterisation that correctly predicts the discharge at the catchment outlet and simultaneously correctly depicts the underlying hydrological processes.
Timo Schaffhauser, Florentin Hofmeister, Gabriele Chiogna, Fabian Merk, Ye Tuo, Julian Machnitzke, Lucas Alcamo, Jingshui Huang, and Markus Disse
Hydrol. Earth Syst. Sci., 29, 3227–3256, https://doi.org/10.5194/hess-29-3227-2025, https://doi.org/10.5194/hess-29-3227-2025, 2025
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The glacier-expanded SWAT (Soil Water Assessment Tool) version, SWAT-GL, was tested in four different catchments, highlighting the capabilities of the glacier routine. It was evaluated based on the representation of glacier mass balance, snow cover and glacier hypsometry. The glacier changes over a long timescale could be adequately represented, leading to promising potential future applications in glaciated and high mountain environments and significantly outperforming standard SWAT models.
Pablo Fernando Dornes and Rocío Noelia Comas
Hydrol. Earth Syst. Sci., 29, 2901–2923, https://doi.org/10.5194/hess-29-2901-2025, https://doi.org/10.5194/hess-29-2901-2025, 2025
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The Desaguadero–Salado–Chadiluevú–Curacó (DSCC) River is a semiarid river which is heavily dammed at its tributaries which collect the snowmelt runoff. This runoff feeds mostly gravitational irrigation systems of very low efficiency. As a result, the DSCC River does not have natural runoff. The proposed hydrological regime index (HRI) is able to discriminate and quantify regime alterations under permanent and non-permanent flow conditions and with low- and high-impoundment conditions.
Jean-Luc Martel, François Brissette, Richard Arsenault, Richard Turcotte, Mariana Castañeda-Gonzalez, William Armstrong, Edouard Mailhot, Jasmine Pelletier-Dumont, Gabriel Rondeau-Genesse, and Louis-Philippe Caron
Hydrol. Earth Syst. Sci., 29, 2811–2836, https://doi.org/10.5194/hess-29-2811-2025, https://doi.org/10.5194/hess-29-2811-2025, 2025
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This study compares long short-term memory (LSTM) neural networks with traditional hydrological models to predict future streamflow under climate change. Using data from 148 catchments, it finds that LSTM models, which learn from extensive data sequences, perform differently and often better than traditional hydrological models. The continental LSTM model, which includes data from diverse climate zones, is particularly effective for understanding climate impacts on water resources.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 2633–2654, https://doi.org/10.5194/hess-29-2633-2025, https://doi.org/10.5194/hess-29-2633-2025, 2025
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We assessed the value of high-resolution data and parameter transferability across temporal scales based on seven catchments in northern China. We found that higher-resolution data do not always improve model performance, questioning the need for such data. Model parameters are transferable across different data resolutions but not across computational time steps. It is recommended to utilize a smaller computational time step when building hydrological models even without high-resolution data.
Wouter J. M. Knoben, Ashwin Raman, Gaby J. Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, Katie van Werkhoven, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 29, 2361–2375, https://doi.org/10.5194/hess-29-2361-2025, https://doi.org/10.5194/hess-29-2361-2025, 2025
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Hydrologic models are needed to provide simulations of water availability, floods, and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models and thus cannot easily be used to select an appropriate model for a specific place.
Chen Yang, Zitong Jia, Wenjie Xu, Zhongwang Wei, Xiaolang Zhang, Yiguang Zou, Jeffrey McDonnell, Laura Condon, Yongjiu Dai, and Reed Maxwell
Hydrol. Earth Syst. Sci., 29, 2201–2218, https://doi.org/10.5194/hess-29-2201-2025, https://doi.org/10.5194/hess-29-2201-2025, 2025
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We developed the first high-resolution, integrated surface water–groundwater hydrologic model of the entirety of continental China using ParFlow. The model shows good performance in terms of streamflow and water table depth when compared to global data products and observations. It is essential for water resources management and decision-making in China within a consistent framework in the changing world. It also has significant implications for similar modeling in other places in the world.
Haifan Liu, Haochen Yan, and Mingfu Guan
Hydrol. Earth Syst. Sci., 29, 2109–2132, https://doi.org/10.5194/hess-29-2109-2025, https://doi.org/10.5194/hess-29-2109-2025, 2025
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Land changes and landscape features critically impact water systems. Studying two watersheds in China’s Greater Bay Area, we found slope strongly influences water processes in mountainous areas. However, this relationship is weak in the lower regions of steeper watersheds. Urbanization leads to an increase in annual surface runoff, while flatter watersheds exhibit a buffering capacity against this effect. However, this buffering capacity diminishes with increasing annual rainfall intensity.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci., 29, 1981–2002, https://doi.org/10.5194/hess-29-1981-2025, https://doi.org/10.5194/hess-29-1981-2025, 2025
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Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite the fact that they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what they truly reflect in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and timescales for accurate drought characterization and monitoring.
Sebastian Gegenleithner, Manuel Pirker, Clemens Dorfmann, Roman Kern, and Josef Schneider
Hydrol. Earth Syst. Sci., 29, 1939–1962, https://doi.org/10.5194/hess-29-1939-2025, https://doi.org/10.5194/hess-29-1939-2025, 2025
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Accurate early-warning systems are crucial for reducing the damage caused by flooding events. In this study, we explored the potential of long short-term memory networks for enhancing the forecast accuracy of hydrologic models employed in operational flood forecasting. The presented approach elevated the investigated hydrologic model’s forecast accuracy for further ahead predictions and at flood event runoff.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025, https://doi.org/10.5194/hess-29-1919-2025, 2025
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Common intuition holds that higher input data resolution leads to better results. To assess the benefits of high-resolution data, we conduct simulation experiments using data with various temporal resolutions across multiple catchments and find that higher-resolution data do not always improve model performance, challenging the necessity of pursuing such data. In catchments with small areas or significant flow variability, high-resolution data is more valuable.
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025, https://doi.org/10.5194/hess-29-1703-2025, 2025
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The quantification of precipitation into evaporation and runoff is vital for water resources management. The Budyko framework, based on aridity and evaporative indices of a catchment, can be an ideal tool for that. However, recent research highlights deviations of catchments from the expected evaporative index, casting doubt on its reliability. This study quantifies deviations of 2387 catchments, finding them minor and predictable. Integrating these into predictions upholds the framework's efficacy.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025, https://doi.org/10.5194/hess-29-1725-2025, 2025
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In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until we observe overparameterization.
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025, https://doi.org/10.5194/hess-29-1685-2025, 2025
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We generate operational forecasts of daily maximum stream water temperature for 32 consecutive days at 54 stations in Switzerland with our best-performing data-driven model. The average forecast error is 0.38 °C for 1 d ahead and increases to 0.90 °C for 32 d ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1749–1758, https://doi.org/10.5194/hess-29-1749-2025, https://doi.org/10.5194/hess-29-1749-2025, 2025
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Long short-term memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modelling. However, most studies focus on predictions at a daily scale, limiting the benefits of sub-daily (e.g. hourly) predictions in applications like flood forecasting. In this study, we introduce a new architecture, multi-frequency LSTM (MF-LSTM), designed to use inputs of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
Fernanda Helfer, Felipe Bernardi, Claudia Alessandra Peixoto de Barros, Daniel Gustavo Allasia, Jean Paolo Gomes Minella, Rutinéia Tassi, and Néverton Scariot
EGUsphere, https://doi.org/10.5194/egusphere-2025-244, https://doi.org/10.5194/egusphere-2025-244, 2025
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We explored how water flows in small rural streams to improve tools for better managing water resources. Using a new method, we adjusted existing models to consider the size of rainfall events, showing that water movement patterns change depending on the rain’s intensity. This approach makes predictions more accurate and helps scientists and managers understand water availability and protect ecosystems.
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci., 29, 1615–1636, https://doi.org/10.5194/hess-29-1615-2025, https://doi.org/10.5194/hess-29-1615-2025, 2025
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Our study projects how climate change will affect the drying of river segments and stream networks in Europe, using advanced modelling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent and intense and will start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists for evaluating the ecological health of river ecosystem.
Tariq Aziz, Steven K. Frey, David R. Lapen, Susan Preston, Hazen A. J. Russell, Omar Khader, Andre R. Erler, and Edward A. Sudicky
Hydrol. Earth Syst. Sci., 29, 1549–1568, https://doi.org/10.5194/hess-29-1549-2025, https://doi.org/10.5194/hess-29-1549-2025, 2025
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This study determines the value of subsurface water for ecosystem services' supply in an agricultural watershed in Ontario, Canada. Using a fully integrated water model and an economic valuation approach, the research highlights subsurface water's critical role in maintaining watershed ecosystem services. The study informs on the sustainable use of subsurface water and introduces a new method for managing watershed ecosystem services.
Wouter J. M. Knoben, Kasra Keshavarz, Laura Torres-Rojas, Cyril Thébault, Nathaniel W. Chaney, Alain Pietroniro, and Martyn P. Clark
EGUsphere, https://doi.org/10.5194/egusphere-2025-893, https://doi.org/10.5194/egusphere-2025-893, 2025
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Many existing data sets for hydrologic analysis tend treat catchments as single, spatially homogeneous units, focus on daily data and typically do not support more complex models. This paper introduces a data set that goes beyond this setup by: (1) providing data at higher spatial and temporal resolution, (2) specifically considering the data requirements of all common hydrologic model types, (3) using statistical summaries of the data aimed at quantifying spatial and temporal heterogeneity.
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1277–1294, https://doi.org/10.5194/hess-29-1277-2025, https://doi.org/10.5194/hess-29-1277-2025, 2025
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Data-driven techniques have shown the potential to outperform process-based models in rainfall–runoff simulations. Hybrid models, combining both approaches, aim to enhance accuracy and maintain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions, we test their generalization capabilities for extreme hydrological events.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
Hydrol. Earth Syst. Sci., 29, 1061–1082, https://doi.org/10.5194/hess-29-1061-2025, https://doi.org/10.5194/hess-29-1061-2025, 2025
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This study reconstructs daily runoff in Switzerland (1962–2023) using a deep-learning model, providing a spatially contiguous dataset on a medium-sized catchment grid. The model outperforms traditional hydrological methods, revealing shifts in Swiss water resources, including more frequent dry years and declining summer runoff. The reconstruction is publicly available.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1033–1060, https://doi.org/10.5194/hess-29-1033-2025, https://doi.org/10.5194/hess-29-1033-2025, 2025
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Owing to differences in the existing published results, we conducted a detailed analysis of the runoff components and future trends in the Yarlung Tsangpo River basin and found that the contributions of snowmelt and glacier melt runoff to streamflow (both ~5 %) are limited and much lower than previous results. The streamflow in this area will continuously increase in the future, but the overestimated contribution of glacier melt could lead to an underestimation of this increasing trend.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025, https://doi.org/10.5194/hess-29-903-2025, 2025
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This study develops an integrated framework based on the novel Driving index for changes in Precipitation–Runoff Relationships (DPRR) to explore the controlling changes in precipitation–runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation–runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Marc Aurel Vischer, Noelia Otero, and Jackie Ma
EGUsphere, https://doi.org/10.5194/egusphere-2024-3649, https://doi.org/10.5194/egusphere-2024-3649, 2025
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We use a neural network to predict the amount of water flowing into rivers. Our focus is on large river catchment areas in central Europe with pronounced human activity. Our model scales efficiently to large amounts of data and is thus able to processes the input without prior aggregation, capturing fine spatial detail and improving prediction in large catchments. Our model’s internal states can be adapted to allow capturing human activity more explicitly in the future.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025, https://doi.org/10.5194/hess-29-785-2025, 2025
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Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine learning (ML) models are increasingly being applied for flood forecasting. Such models are typically trained on large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets that maximise the spatio-temporal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025, https://doi.org/10.5194/hess-29-753-2025, 2025
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This study presents the first distributed hydrological simulation which confirms claims raised by historians that the eastward diversion project of the Tone River in Japan was conducted 4 centuries ago to increase low flows and subsequent travelling possibilities surrounding the capital, Edo (Tokyo), using inland navigation. We showed that great steps forward can be made for improving quality of life with small human engineering waterworks and small interventions in the regime of natural flows.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025, https://doi.org/10.5194/hess-29-683-2025, 2025
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This work investigates how hydrological models are transferred to a period in which climate conditions are different to the ones of the period in which they were set up. The robustness assessment test built to detect dependencies between model error and climatic drivers was applied to three hydrological models in 352 catchments in Denmark, France and Sweden. Potential issues are seen in a significant number of catchments for the models, even though the catchments differ for each model.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025, https://doi.org/10.5194/hess-29-627-2025, 2025
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Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 29, 447–463, https://doi.org/10.5194/hess-29-447-2025, https://doi.org/10.5194/hess-29-447-2025, 2025
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Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small catchments compared to large catchments, and spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show effects. The results can improve estimations of probabilities of extreme floods.
Alonso Pizarro, Demetris Koutsoyiannis, and Alberto Montanari
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-389, https://doi.org/10.5194/hess-2024-389, 2025
Revised manuscript accepted for HESS
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We introduce RUMI, a new metric to improve rainfall-runoff simulations. RUMI better captures the link between observed and simulated stream flows by considering uncertainty at a core computation step. Tested on 99 catchments and with the GR4J model, it outperforms traditional metrics by providing more reliable and consistent results. RUMI paves the way for more accurate hydrological predictions.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht H. Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci., 29, 335–360, https://doi.org/10.5194/hess-29-335-2025, https://doi.org/10.5194/hess-29-335-2025, 2025
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Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping to better prepare for and respond to floods.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
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To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their physical realism, which is measured by the ability of the model to reproduce observed system dynamics. Using a model to represent the dynamics of water and nitrate and dissolved organic carbon concentrations in an agricultural catchment, we showed that using solute-concentration data for calibration is useful to improve the hydrological consistency of the model.
Parthkumar A. Modi, Jared C. Carbone, Keith S. Jennings, Hannah Kamen, Joseph R. Kasprzyk, Bill Szafranski, Cameron W. Wobus, and Ben Livneh
EGUsphere, https://doi.org/10.5194/egusphere-2024-4046, https://doi.org/10.5194/egusphere-2024-4046, 2025
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This study shows that in unmanaged snow-dominated basins, high forecast accuracy doesn’t always lead to high economic value, especially during extreme conditions like droughts. It highlights how irregular errors in modern forecasting systems weaken the connection between accuracy and value. These findings call for forecast evaluations to focus not only on accuracy but also on economic impacts, providing valuable guidance for better water resource management under uncertainty.
Benjamin Guillaume, Adrien Michez, and Aurore Degré
EGUsphere, https://doi.org/10.5194/egusphere-2024-3978, https://doi.org/10.5194/egusphere-2024-3978, 2025
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Nature-based solutions (NbS) can mitigate floods and agricultural droughts by enhancing soil health and restoring hydrological cycles. This study highlights that leveraging soil diversity is key to optimizing NbS performance.
Haley A. Canham, Belize Lane, Colin B. Phillips, and Brendan P. Murphy
Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025, https://doi.org/10.5194/hess-29-27-2025, 2025
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The influence of watershed disturbances has proved challenging to disentangle from natural streamflow variability. This study evaluates the influence of time-varying hydrologic controls on rainfall–runoff in undisturbed and wildfire-disturbed watersheds using a novel time-series event separation method. Across watersheds, water year type and season influenced rainfall–runoff patterns. Accounting for these controls enabled clearer isolation of wildfire effects.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci., 28, 5511–5539, https://doi.org/10.5194/hess-28-5511-2024, https://doi.org/10.5194/hess-28-5511-2024, 2024
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Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
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This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Laia Estrada, Xavier Garcia, Joan Saló-Grau, Rafael Marcé, Antoni Munné, and Vicenç Acuña
Hydrol. Earth Syst. Sci., 28, 5353–5373, https://doi.org/10.5194/hess-28-5353-2024, https://doi.org/10.5194/hess-28-5353-2024, 2024
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Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological model, integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, https://doi.org/10.5194/hess-28-5331-2024, 2024
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Daniel T. Myers, David Jones, Diana Oviedo-Vargas, John Paul Schmit, Darren L. Ficklin, and Xuesong Zhang
Hydrol. Earth Syst. Sci., 28, 5295–5310, https://doi.org/10.5194/hess-28-5295-2024, https://doi.org/10.5194/hess-28-5295-2024, 2024
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We studied how streamflow and water quality models respond to land cover data collected by satellites during the growing season versus the non-growing season. The land cover data showed more trees during the growing season and more built areas during the non-growing season. We next found that the use of non-growing season data resulted in a higher modeled nutrient export to streams. Knowledge of these sensitivities would be particularly important when models inform water resource management.
Hatice Türk, Christine Stumpp, Markus Hrachowitz, Karsten Schulz, Peter Strauss, Günter Blöschl, and Michael Stockinger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-359, https://doi.org/10.5194/hess-2024-359, 2024
Revised manuscript accepted for HESS
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Using advances in transit time estimation and tracer data, we tested if fast-flow transit times are controlled solely by soil moisture or are also controlled by precipitation intensity. We used soil moisture-dependent and precipitation intensity-conditional transfer functions. We showed that significant portion of event water bypasses the soil matrix through fast flow paths (overland flow, tile drains, preferential flow paths) in dry soil conditions for both low and high-intensity precipitation.
Kevin R. Shook, Paul H. Whitfield, Christopher Spence, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 28, 5173–5192, https://doi.org/10.5194/hess-28-5173-2024, https://doi.org/10.5194/hess-28-5173-2024, 2024
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Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Anjana Devanand, Jason Evans, Andy Pitman, Sujan Pal, David Gochis, and Kevin Sampson
EGUsphere, https://doi.org/10.5194/egusphere-2024-3148, https://doi.org/10.5194/egusphere-2024-3148, 2024
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Including lateral flow increases evapotranspiration near major river channels in high-resolution land surface simulations in southeast Australia, consistent with observations. The 1-km resolution model shows a widespread pattern of dry ridges that does not exist at coarser resolutions. Our results have implications for improved simulations of droughts and future water availability.
Sylvain Payraudeau, Pablo Alvarez-Zaldivar, Paul van Dijk, and Gwenaël Imfeld
EGUsphere, https://doi.org/10.5194/egusphere-2024-2840, https://doi.org/10.5194/egusphere-2024-2840, 2024
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Our study focuses on the rising concern of pesticides damaging aquatic ecosystems, which puts drinking water, the environment, and human health at risk. We provided more accurate estimates of how pesticides break down and spread in small water systems, helping to improve pesticide management practices. By using unique chemical markers in our analysis, we enhanced the accuracy of our predictions, offering important insights for better protection of water sources and natural ecosystems.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
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We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Vishal Thakur, Yannis Markonis, Rohini Kumar, Johanna Ruth Thomson, Mijael Rodrigo Vargas Godoy, Martin Hanel, and Oldrich Rakovec
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-341, https://doi.org/10.5194/hess-2024-341, 2024
Revised manuscript accepted for HESS
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Understanding the changes in water movement in earth is crucial for everyone. To quantify this water movement there are several techniques. We examined how different methods of estimating evaporation impact predictions of various types of water movement across Europe. We found that, while these methods generally agree on whether changes are increasing or decreasing, they differ in magnitude. This means selecting the right evaporation method is crucial for accurate predictions of water movement.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Cited articles
Afshari, S., Tavakoly, A. A., Rajib, M. A., Zheng, X., Follum, M. L., Omranian, E., and Fekete, B. M.:
Comparison of new generation low-complexity flood inundation mapping tools with a hydrodynamic model,
J. Hydrol.,
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Alfieri, L., Salamon, P., Bianchi, A., Neal, J., Bates, P., and Feyen, L.:
Advances in pan-European flood hazard mapping,
Hydrol. Process.,
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Ali, A. M., Baldassarre, G. D., and Solomatine, D. P.:
Testing different cross-section spacing in 1D hydraulic modelling: a case study on Johor River, Malaysia,
Hydrolog. Sci. J.,
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Aubert, Y., Arnaud, P., Ribstein, P., and Fine, J.-A.:
The SHYREG flow method – application to 1605 basins in metropolitan France,
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Bates, P. D., Horritt, M. S., and Fewtrell, T. J.:
A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling,
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Brêda, J. P. L. F., Paiva, R. C. D., Bravo, J. M., Passaia, O. A., and Moreira, D. M.:
Assimilation of Satellite Altimetry Data for Effective River Bathymetry,
Water Resour. Res.,
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Brunner, G. W.:
HEC – RAS River Analysis System Hydraulic Reference Manual version 5.0, software CPD-69,
US Army Corps of Engineers Hydrologic Engineering Center (HEC), 609 Second Street, Davis, CA 95616-4687,
available at: https://www.hec.usace.army.mil/software/hec-ras/documentation/HEC-RAS 5.0 Reference Manual.pdf (last access: 28 May 2021), 2016. a
Brunner, G. W., Sanchez, A., Molls, T., Ford, D., and Parr, D. A.:
HEC-RAS verification and validation tests, resreport RD-52, US Army Corps of Engineers, Insitute for Water Resources, Hydrologic Engineering Center, 609 Second Street, Davis, CA 95616-4687,
available at: https://www.hec.usace.army.mil/software/hec-ras/documentation/RD-52_HEC-RAS Verification and Validation.pdf (last access: 28 May 2021), 2018. a
Caumont, O., Mandement, M., Bouttier, F., Eeckman, J., Lebeaupin Brossier, C., Lovat, A., Nuissier, O., and Laurantin, O.: The heavy precipitation event of 14–15 October 2018 in the Aude catchment: a meteorological study based on operational numerical weather prediction systems and standard and personal observations, Nat. Hazards Earth Syst. Sci., 21, 1135–1157, https://doi.org/10.5194/nhess-21-1135-2021, 2021. a, b
Cea, L. and Bladé, E.:
A simple and efficient unstructured finite volume scheme for solving the shallow water equations in overland flow applications,
Water Resour. Res.,
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Champeaux, J.-L., Dupuy, P., Laurantin, O., Soulan, I., Tabary, P., and Soubeyroux, J.-M.:
Rainfall measurements and quantitative precipitation estimations at Météo-France: inventory and prospects,
Houille Blanche, 95, 28–34, https://doi.org/10.1051/lhb/2009052, 2009. a
Choi, C. C. and Mantilla, R.:
Development and Analysis of GIS Tools for the Automatic Implementation of 1D Hydraulic Models Coupled with Distributed Hydrological Models,
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Davy, P., Croissant, T., and Lague, D.:
A precipiton method to calculate river hydrodynamics, with applications to flood prediction, landscape evolution models, and braiding instabilities,
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Dottori, F., Baldassarre, G. D., and Todini, E.:
Detailed data is welcome, but with a pinch of salt: Accuracy, precision, and uncertainty in flood inundation modeling,
Water Resour. Res.,
49, 6079–6085, https://doi.org/10.1002/wrcr.20406, 2013. a
Dottori, F., Salamon, P., Bianchi, A., Alfieri, L., Hirpa, F. A., and Feyen, L.:
Development and evaluation of a framework for global flood hazard mapping,
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Dottori, F., Kalas, M., Salamon, P., Bianchi, A., Alfieri, L., and Feyen, L.: An operational procedure for rapid flood risk assessment in Europe, Nat. Hazards Earth Syst. Sci., 17, 1111–1126, https://doi.org/10.5194/nhess-17-1111-2017, 2017. a, b
Ducrocq, V., Boudevillain, B., Bouvier, C., Braud, I., Fourri, N., Lebeaupin-Brossier, C., Javelle, P., Nuissier, O., Payrastre, O., Roux, H., Ruin, I., and Vincendon, B.:
HyMeX – Advances in understanding and forecasting of heavy precipitation and flash floods in the Mediterranean,
Houille Blanche, 105, 5–12, https://doi.org/10.1051/lhb/2019048, 2019. a
Fleischmann, A., Paiva, R., and Collischonn, W.:
Can regional to continental river hydrodynamic models be locally relevant? A cross-scale comparison,
Journal of Hydrology X,
3, 100027, https://doi.org/10.1016/j.hydroa.2019.100027, 2019. a
Follum, M. L., Tavakoly, A. A., Niemann, J. D., and Snow, A. D.:
AutoRAPID: A Model for Prompt Streamflow Estimation and Flood Inundation Mapping over Regional to Continental Extents,
J. Am. Water Resour. As.,
53, 280–299, https://doi.org/10.1111/1752-1688.12476, 2017. a
Follum, M. L., Vera, R., Tavakoly, A. A., and Gutenson, J. L.: Improved accuracy and efficiency of flood inundation mapping of low-, medium-, and high-flow events using the AutoRoute model, Nat. Hazards Earth Syst. Sci., 20, 625–641, https://doi.org/10.5194/nhess-20-625-2020, 2020. a
García-Feal, O., González-Cao, J., Gómez-Gesteira, M., Cea, L., Domínguez, M. J., and Formella, A.:
An Accelerated Tool for Flood Modelling Based on Iber,
Water,
10, 10, https://doi.org/10.3390/w10101459, 2018. a
Garousi-Nejad, I., Tarboton, D. G., Aboutalebi, M., and Torres-Rua, A. F.:
Terrain Analysis Enhancements to the Height Above Nearest Drainage Flood Inundation Mapping Method,
Water Resour. Res.,
55, 7983–8009, https://doi.org/10.1029/2019wr024837, 2019. a
Gleason, C. J. and Smith, L. C.:
Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry,
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111, 4788–4791, https://doi.org/10.1073/pnas.1317606111, 2014. a
Goutal, N., Lacombe, J.-M., Zaoui, F., and El-Kadi-Abderrezzak, K.:
MASCARET: a 1-D open-source software for flow hydrodynamic and water quality in open channel networks,
in: River Flow 2012,
edited by: Munoz, R. M., CRC Press, London, https://doi.org/10.1201/b13250, pp. 1169–1174, 2012. a
Grimaldi, S., Li, Y., Walker, J. P., and Pauwels, V. R. N.:
Effective Representation of River Geometry in Hydraulic Flood Forecast Models,
Water Resour. Res.,
54, 1031–1057, https://doi.org/10.1002/2017wr021765, 2018. a
Hocini, N. and Payrastre, O.:
Comparison of three automated flood inundation mapping methods in a context of flash floods, SEDOO OMP, Toulouse, https://doi.org/10.6096/mistrals-hymex.1598, 2020. a, b
Johnson, J. M., Munasinghe, D., Eyelade, D., and Cohen, S.: An integrated evaluation of the National Water Model (NWM)–Height Above Nearest Drainage (HAND) flood mapping methodology, Nat. Hazards Earth Syst. Sci., 19, 2405–2420, https://doi.org/10.5194/nhess-19-2405-2019, 2019. a, b
Kirstetter, G., Delestre, O., Lagrée, P.-Y., Popinet, S., and Josserand, C.: B-flood 1.0: an open-source Saint-Venant model for flash flood simulation using adaptive refinement, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2021-15, in review, 2021. a
Lague, D. and Feldmann, B.:
Topo-bathymetric airborne LiDAR for fluvial-geomorphology analysis,
in: Remote Sensing of Geomorphology,
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Lamichhane, N. and Sharma, S.:
Effect of input data in hydraulic modeling for flood warning systems,
Hydrolog. Sci. J.,
63, 938–956, https://doi.org/10.1080/02626667.2018.1464166, 2018. a, b
Le Bihan, G., Payrastre, O., Gaume, E., Moncoulon, D., and Pons, F.: The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data, Hydrol. Earth Syst. Sci., 21, 5911–5928, https://doi.org/10.5194/hess-21-5911-2017, 2017. a, b, c
Leedal, D., Neal, J., Beven, K., Young, P., and Bates, P.:
Visualization approaches for communicating real-time flood forecasting level and inundation information,
J. Flood Risk Manag.,
3, 140–150, https://doi.org/10.1111/j.1753-318x.2010.01063.x, 2010. a
Liu, Y. Y., Maidment, D. R., Tarboton, D. G., Zheng, X., and Wang, S.:
A CyberGIS Integration and Computation Framework for High-Resolution Continental-Scale Flood Inundation Mapping,
J. Am. Water Resour. As., 54, 770–784, https://doi.org/10.1111/1752-1688.12660, 2018. a, b
Lumbroso, D. and Gaume, E.:
Reducing the uncertainty in indirect estimates of extreme flash flood discharges,
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414, 16–30, https://doi.org/10.1016/j.jhydrol.2011.08.048, 2012. a
Merz, B., Kuhlicke, C., Kunz, M., Pittore, M., Babeyko, A., Bresch, D. N., Domeisen, D. I. V., Feser, F., Koszalka, I., Kreibich, H., Pantillon, F., Parolai, S., Pinto, J. G., Punge, H. J., Rivalta, E., Schröter, K., Strehlow, K., Weisse, R., and Wurpts, A.:
Impact Forecasting to Support Emergency Management of Natural Hazards,
Rev. Geophys.,
58, 4, https://doi.org/10.1029/2020rg000704, 2020. a
Morsy, M. M., Goodall, J. L., O'Neil, G. L., Sadler, J. M., Voce, D., Hassan, G., and Huxley, C.:
A cloud-based flood warning system for forecasting impacts to transportation infrastructure systems,
Environ. Modell. Softw.,
107, 231–244, https://doi.org/10.1016/j.envsoft.2018.05.007, 2018. a, b
Naulin, J. P., Payrastre, O., and Gaume, E.:
Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France,
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486, 8–99, https://doi.org/10.1016/j.jhydrol.2013.01.044, 2013. a
Neal, J., Dunne, T., Sampson, C., Smith, A., and Bates, P.:
Optimisation of the two-dimensional hydraulic model LISFOOD-FP for CPU architecture,
Environ. Modell. Softw.,
107, 148–157, https://doi.org/10.1016/j.envsoft.2018.05.011, 2018. a
Neal, J. C., Odoni, N. A., Trigg, M. A., Freer, J. E., Garcia-Pintado, J., Mason, D. C., Wood, M., and Bates, P. D.:
Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models,
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529, 169–183, https://doi.org/10.1016/j.jhydrol.2015.07.026, 2015. a
Nguyen, P., Thorstensen, A., Sorooshian, S., Hsu, K., AghaKouchak, A., Sanders, B., Koren, V., Cui, Z., and Smith, M.:
A high resolution coupled hydrologic–hydraulic model (HiResFlood-UCI) for flash flood modeling,
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541, 401–420, https://doi.org/10.1016/j.jhydrol.2015.10.047, 2016. a
Nobre, A. D., Cuartas, L. A., Hodnett, M., Rennó, C. D., Rodrigues, G., Silveira, A., Waterloo, M., and Saleska, S.:
Height Above the Nearest Drainage – a hydrologically relevant new terrain model,
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404, 13–29, https://doi.org/10.1016/j.jhydrol.2011.03.051, 2011. a, b
Nobre, A. D., Cuartas, L. A., Momo, M. R., Severo, D. L., Pinheiro, A., and Nobre, C. A.:
HAND contour: a new proxy predictor of inundation extent,
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Pappenberger, F., Dutra, E., Wetterhall, F., and Cloke, H. L.: Deriving global flood hazard maps of fluvial floods through a physical model cascade, Hydrol. Earth Syst. Sci., 16, 4143–4156, https://doi.org/10.5194/hess-16-4143-2012, 2012. a
Payrastre, O., Gaume, E., Javelle, P., Janet, B., Fourrnigue, P., Lefort, P., Martin, A., Boudevillain, B., Brunet, P., Delrieu, G., Marchi, L., Aubert, Y., Dautrey, E., Durand, L., Lang, M., Boissier, L., Douvinet, J., Martin, C., and evenements Hy, E. E. P.:
Hydrological analysis of the catastrophic flash flood of 15th June 2010 in the area of Draguignan (Var, France),
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Pons, F., Laroche, C., Fourmigue, P., and Alquier, M.:
Flood hazard maps for extreme event scenario: the study of Nartuby river,
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Rebolho, C., Andréassian, V., and Le Moine, N.: Inundation mapping based on reach-scale effective geometry, Hydrol. Earth Syst. Sci., 22, 5967–5985, https://doi.org/10.5194/hess-22-5967-2018, 2018. a, b
Rennó, C. D., Nobre, A. D., Cuartas, L. A., Soares, J. V., Hodnett, M. G., Tomasella, J., and Waterloo, M. J.:
HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia,
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Ritter, J., Berenguer, M., Corral, C., Park, S., and Sempere-Torres, D.:
ReAFFIRM: Real-time Assessment of Flash Flood Impacts – a Regional high-resolution Method,
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Sampson, C. C., Smith, A. M., Bates, P. D., Neal, J. C., Alfieri, L., and Freer, J. E.:
A high-resolution global flood hazard model,
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PRIMo: Parallel raster inundation model,
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Savage, J. T. S., Bates, P., Freer, J., Neal, J., and Aronica, G.:
When does spatial resolution become spurious in probabilistic flood inundation predictions?,
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Schumann, G. J.-P. and Bates, P. D.:
The Need for a High-Accuracy, Open-Access Global DEM,
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Schumann, G. J.-P., Stampoulis, D., Smith, A. M., Sampson, C. C., Andreadis, K. M., Neal, J. C., and Bates, P. D.:
Rethinking flood hazard at the global scale,
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Speckhann, G. A., Borges Chaffe, P. L., Fabris Goerl, R., de Abreu, J. J., and Altamirano Flores, J. A.:
Flood hazard mapping in Southern Brazil: a combination of flow frequency analysis and the HAND model,
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Teng, J., Jakeman, A., Vaze, J., Croke, B., Dutta, D., and Kim, S.:
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Wing, O. E., Sampson, C. C., Bates, P. D., Quinn, N., Smith, A. M., and Neal, J. C.:
A flood inundation forecast of Hurricane Harvey using a continental-scale 2D hydrodynamic model,
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Wing, O. E. J., Bates, P. D., Sampson, C. C., Smith, A. M., Johnson, K. A., and Erickson, T. A.:
Validation of a 30 m resolution flood hazard model of the conterminous United States,
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Xia, X., Liang, Q., Ming, X., and Hou, J.:
An efficient and stable hydrodynamic model with novel source term discretization schemes for overland flow and flood simulations,
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Zheng, X., Tarboton, D. G., Maidment, D. R., Liu, Y. Y., and Passalacqua, P.:
River Channel Geometry and Rating Curve Estimation Using Height above the Nearest Drainage,
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Short summary
Efficient flood mapping methods are needed for large-scale, comprehensive identification of flash flood inundation hazards caused by small upstream rivers. An evaluation of three automated mapping approaches of increasing complexity, i.e., a digital terrain model (DTM) filling and two 1D–2D hydrodynamic approaches, is presented based on three major flash floods in southeastern France. The results illustrate some limits of the DTM filling method and the value of using a 2D hydrodynamic approach.
Efficient flood mapping methods are needed for large-scale, comprehensive identification of...
