Articles | Volume 27, issue 23
https://doi.org/10.5194/hess-27-4227-2023
© Author(s) 2023. 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-27-4227-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Nov 2023
Research article |
| 30 Nov 2023
| 30 Nov 2023
Rapid spatio-temporal flood modelling via hydraulics-based graph neural networks
Roberto Bentivoglio
CORRESPONDING AUTHOR
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Elvin Isufi
Department of Intelligent Systems, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, the Netherlands
Sebastiaan Nicolas Jonkman
Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Riccardo Taormina
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
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Roberto Bentivoglio, Elvin Isufi, Sebastian Nicolaas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci., 26, 4345–4378, https://doi.org/10.5194/hess-26-4345-2022, https://doi.org/10.5194/hess-26-4345-2022, 2022
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Deep learning methods have been increasingly used in flood management to improve traditional techniques. While promising results have been obtained, our review shows significant challenges in building deep learning models that can (i) generalize across multiple scenarios, (ii) account for complex interactions, and (iii) perform probabilistic predictions. We argue that these shortcomings could be addressed by transferring recent fundamental advancements in deep learning to flood mapping.
Roberto Bentivoglio, Elvin Isufi, Sebastian Nicolaas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-614, https://doi.org/10.5194/hess-2021-614, 2021
Manuscript not accepted for further review
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Deep Learning methods have been increasingly used in flood mapping as an alternative to traditional modeling techniques. While promising results have been obtained, our review shows significant challenges in building Deep Learning models that can generalize across multiple scenarios, account for complex interactions, and provide probabilistic predictions. We argue that these shortcomings could be addressed by transferring recent fundamental advancements in Deep Learning.
Nienke Tessa Tempel, Laurene Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
EGUsphere, https://doi.org/10.5194/egusphere-2024-115, https://doi.org/10.5194/egusphere-2024-115, 2024
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This study explores the impact of climatic variability on root zone water storage capacities 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.
Hanqing Xu, Elisa Ragno, Sebastiaan N. Jonkman, Jun Wang, Jeremy D. Bricker, Zhan Tian, and Laixiang Sun
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-261, https://doi.org/10.5194/hess-2023-261, 2023
Preprint under review for HESS
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A coupled statistical-hydrodynamic model framework is used to quantitatively assess the sensitivity of the compound flood hazard to the relative timing between peak surge and rainfall. The results indicate that the timing difference between storm surges and rainfall plays a crucial role in flood inundation depth and extension. The most severe inundation occurs when rainfall precedes the storm surge peak of 2 hours.
Roberto Bentivoglio, Elvin Isufi, Sebastian Nicolaas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci., 26, 4345–4378, https://doi.org/10.5194/hess-26-4345-2022, https://doi.org/10.5194/hess-26-4345-2022, 2022
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Deep learning methods have been increasingly used in flood management to improve traditional techniques. While promising results have been obtained, our review shows significant challenges in building deep learning models that can (i) generalize across multiple scenarios, (ii) account for complex interactions, and (iii) perform probabilistic predictions. We argue that these shortcomings could be addressed by transferring recent fundamental advancements in deep learning to flood mapping.
Julius Schlumberger, Christian Ferrarin, Sebastiaan N. Jonkman, Manuel Andres Diaz Loaiza, Alessandro Antonini, and Sandra Fatorić
Nat. Hazards Earth Syst. Sci., 22, 2381–2400, https://doi.org/10.5194/nhess-22-2381-2022, https://doi.org/10.5194/nhess-22-2381-2022, 2022
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Flooding has serious impacts on the old town of Venice. This paper presents a framework combining a flood model with a flood-impact model to support improving protection against future floods in Venice despite the recently built MOSE barrier. Applying the framework to seven plausible flood scenarios, it was found that individual protection has a significant damage-mediating effect if the MOSE barrier does not operate as anticipated. Contingency planning thus remains important in Venice.
Manuel Andres Diaz Loaiza, Jeremy D. Bricker, Remi Meynadier, Trang Minh Duong, Rosh Ranasinghe, and Sebastiaan N. Jonkman
Nat. Hazards Earth Syst. Sci., 22, 345–360, https://doi.org/10.5194/nhess-22-345-2022, https://doi.org/10.5194/nhess-22-345-2022, 2022
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Extratropical cyclones are one of the major causes of coastal floods in Europe and the world. Understanding the development process and the flooding of storm Xynthia, together with the damages that occurred during the storm, can help to forecast future losses due to other similar storms. In the present paper, an analysis of shallow water variables (flood depth, velocity, etc.) or coastal variables (significant wave height, energy flux, etc.) is done in order to develop damage curves.
Christopher H. Lashley, Sebastiaan N. Jonkman, Jentsje van der Meer, Jeremy D. Bricker, and Vincent Vuik
Nat. Hazards Earth Syst. Sci., 22, 1–22, https://doi.org/10.5194/nhess-22-1-2022, https://doi.org/10.5194/nhess-22-1-2022, 2022
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Many coastlines around the world have shallow foreshores (e.g. salt marshes and mudflats) that reduce storm waves and the risk of coastal flooding. However, most of the studies that tried to quantify this effect have excluded the influence of very long waves, which often dominate in shallow water. Our newly developed framework addresses this oversight and suggests that safety along these coastlines may be overestimated, since these very long waves are largely neglected in flood risk assessments.
Roberto Bentivoglio, Elvin Isufi, Sebastian Nicolaas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-614, https://doi.org/10.5194/hess-2021-614, 2021
Manuscript not accepted for further review
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Deep Learning methods have been increasingly used in flood mapping as an alternative to traditional modeling techniques. While promising results have been obtained, our review shows significant challenges in building Deep Learning models that can generalize across multiple scenarios, account for complex interactions, and provide probabilistic predictions. We argue that these shortcomings could be addressed by transferring recent fundamental advancements in Deep Learning.
Erik C. van Berchum, Mathijs van Ledden, Jos S. Timmermans, Jan H. Kwakkel, and Sebastiaan N. Jonkman
Nat. Hazards Earth Syst. Sci., 20, 2633–2646, https://doi.org/10.5194/nhess-20-2633-2020, https://doi.org/10.5194/nhess-20-2633-2020, 2020
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Flood risk management is especially complicated in coastal cities. The complexity of multiple flood hazards in a rapidly changing urban environment leads to a situation with many different potential measures and future scenarios. This research demonstrates a new model capable of quickly simulating flood impact and comparing many different strategies. This is applied to the city of Beira, where it was able to provide new insights into the local flood risk and potential strategies.
Sebastiaan N. Jonkman, Maartje Godfroy, Antonia Sebastian, and Bas Kolen
Nat. Hazards Earth Syst. Sci., 18, 1073–1078, https://doi.org/10.5194/nhess-18-1073-2018, https://doi.org/10.5194/nhess-18-1073-2018, 2018
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An analysis was made of the loss of life directly caused by Hurricane Harvey. Information was collected for 70 fatalities that occurred directly due to the event. Most of the fatalities occurred in the greater Houston area, which was most severely affected by extreme rainfall and heavy flooding. The majority of fatalities in this area were recovered outside the designated 100- and 500-year flood zones. Most fatalities occurred due to drowning (81 %), particularly in and around vehicles.
Dominik Paprotny, Michalis I. Vousdoukas, Oswaldo Morales-Nápoles, Sebastiaan N. Jonkman, and Luc Feyen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-132, https://doi.org/10.5194/hess-2018-132, 2018
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Dominik Paprotny, Oswaldo Morales-Nápoles, and Sebastiaan N. Jonkman
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Dominik Paprotny, Oswaldo Morales-Nápoles, and Sebastiaan N. Jonkman
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Nat. Hazards Earth Syst. Sci., 15, 59–73, https://doi.org/10.5194/nhess-15-59-2015, https://doi.org/10.5194/nhess-15-59-2015, 2015
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Related subject area
Subject: Hillslope hydrology | Techniques and Approaches: Modelling approaches
Understanding hydrologic controls of sloping soil response to precipitation through machine learning analysis applied to synthetic data
Elucidating the role of soil hydraulic properties on aspect-dependent landslide initiation
Recession discharge from compartmentalized bedrock hillslopes
Frozen soil hydrological modeling for a mountainous catchment northeast of the Qinghai–Tibet Plateau
On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes
Spatiotemporal changes in flow hydraulic characteristics and soil loss during gully headcut erosion under controlled conditions
Estimation of rainfall erosivity based on WRF-derived raindrop size distributions
Physically based model for gully simulation: application to the Brazilian semiarid region
Assessing the perturbations of the hydrogeological regime in sloping fens due to roads
A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates
Hybridizing Bayesian and variational data assimilation for high-resolution hydrologic forecasting
Multi-source data assimilation for physically based hydrological modeling of an experimental hillslope
A new method, with application, for analysis of the impacts on flood risk of widely distributed enhanced hillslope storage
Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem
Reconstructing long-term gully dynamics in Mediterranean agricultural areas
Evaluating performance of simplified physically based models for shallow landslide susceptibility
Multiresponse modeling of variably saturated flow and isotope tracer transport for a hillslope experiment at the Landscape Evolution Observatory
Determinants of modelling choices for 1-D free-surface flow and morphodynamics in hydrology and hydraulics: a review
Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale
Quantification of the influence of preferential flow on slope stability using a numerical modelling approach
Hydrological hysteresis and its value for assessing process consistency in catchment conceptual models
Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach
Stable water isotope tracing through hydrological models for disentangling runoff generation processes at the hillslope scale
Analysis of landslide triggering conditions in the Sarno area using a physically based model
The influence of grid resolution on the prediction of natural and road-related shallow landslides
Incipient subsurface heterogeneity and its effect on overland flow generation – insight from a modeling study of the first experiment at the Biosphere 2 Landscape Evolution Observatory
Coupled prediction of flood response and debris flow initiation during warm- and cold-season events in the Southern Appalachians, USA
Predicting subsurface stormflow response of a forested hillslope – the role of connected flow paths
Interplay of riparian forest and groundwater in the hillslope hydrology of Sudanian West Africa (northern Benin)
A model-based assessment of the potential use of compound-specific stable isotope analysis in river monitoring of diffuse pesticide pollution
A paradigm shift in stormflow predictions for active tectonic regions with large-magnitude storms: generalisation of catchment observations by hydraulic sensitivity analysis and insight into soil-layer evolution
Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems
Statistical analysis and modelling of surface runoff from arable fields in central Europe
Hydrological modelling of a slope covered with shallow pyroclastic deposits from field monitoring data
Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico
Characterization of groundwater dynamics in landslides in varved clays
A critical assessment of simple recharge models: application to the UK Chalk
The effect of spatial throughfall patterns on soil moisture patterns at the hillslope scale
Snow accumulation/melting model (SAMM) for integrated use in regional scale landslide early warning systems
Suspended sediment concentration–discharge relationships in the (sub-) humid Ethiopian highlands
A model of hydrological and mechanical feedbacks of preferential fissure flow in a slow-moving landslide
Scale effect on overland flow connectivity at the plot scale
Physical models for classroom teaching in hydrology
Coupling the modified SCS-CN and RUSLE models to simulate hydrological effects of restoring vegetation in the Loess Plateau of China
Effects of peatland drainage management on peak flows
A conceptual model of the hydrological influence of fissures on landslide activity
A structure generator for modelling the initial sediment distribution of an artificial hydrologic catchment
A novel explicit approach to model bromide and pesticide transport in connected soil structures
Quantifying spatial and temporal discharge dynamics of an event in a first order stream, using distributed temperature sensing
Effect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model
Daniel Camilo Roman Quintero, Pasquale Marino, Giovanni Francesco Santonastaso, and Roberto Greco
Hydrol. Earth Syst. Sci., 27, 4151–4172, https://doi.org/10.5194/hess-27-4151-2023, https://doi.org/10.5194/hess-27-4151-2023, 2023
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This study shows a methodological approach using machine learning techniques to disentangle the relationships among the variables in a synthetic dataset to identify suitable variables that control the hydrologic response of the slopes. It has been found that not only is the rainfall responsible for the water accumulation in the slope; the ground conditions (soil water content and aquifer water level) also indicate the activation of natural slope drainage mechanisms.
Yanglin Guo and Chao Ma
Hydrol. Earth Syst. Sci., 27, 1667–1682, https://doi.org/10.5194/hess-27-1667-2023, https://doi.org/10.5194/hess-27-1667-2023, 2023
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In a localized area with the same vegetation, an overwhelming propensity of shallow landslides on the south-facing slope over the north-facing slope could not be attributed to plant roots. We provide new evidence from the pore water pressure of failing mass, unsaturated hydraulic conductivity, water storage, and drainage and the hillslope stability fluctuation to prove that the infinite slope model may be suitable for elucidating the aspect-dependent landslide distribution in the study area.
Clément Roques, David E. Rupp, Jean-Raynald de Dreuzy, Laurent Longuevergne, Elizabeth R. Jachens, Gordon Grant, Luc Aquilina, and John S. Selker
Hydrol. Earth Syst. Sci., 26, 4391–4405, https://doi.org/10.5194/hess-26-4391-2022, https://doi.org/10.5194/hess-26-4391-2022, 2022
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Streamflow dynamics are directly dependent on contributions from groundwater, with hillslope heterogeneity being a major driver in controlling both spatial and temporal variabilities in recession discharge behaviors. By analysing new model results, this paper identifies the major structural features of aquifers driving streamflow dynamics. It provides important guidance to inform catchment-to-regional-scale models, with key geological knowledge influencing groundwater–surface water interactions.
Hongkai Gao, Chuntan Han, Rensheng Chen, Zijing Feng, Kang Wang, Fabrizio Fenicia, and Hubert Savenije
Hydrol. Earth Syst. Sci., 26, 4187–4208, https://doi.org/10.5194/hess-26-4187-2022, https://doi.org/10.5194/hess-26-4187-2022, 2022
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Frozen soil hydrology is one of the 23 unsolved problems in hydrology (UPH). In this study, we developed a novel conceptual frozen soil hydrological model, FLEX-Topo-FS. The model successfully reproduced the soil freeze–thaw process, and its impacts on hydrologic connectivity, runoff generation, and groundwater. We believe this study is a breakthrough for the 23 UPH, giving us new insights on frozen soil hydrology, with broad implications for predicting cold region hydrology in future.
Fadji Z. Maina, Haruko M. Wainwright, Peter James Dennedy-Frank, and Erica R. Siirila-Woodburn
Hydrol. Earth Syst. Sci., 26, 3805–3823, https://doi.org/10.5194/hess-26-3805-2022, https://doi.org/10.5194/hess-26-3805-2022, 2022
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We propose a hillslope clustering approach based on the seasonal changes in groundwater levels and test its performance by comparing it to several common clustering approaches (aridity index, topographic wetness index, elevation, land cover, and machine-learning clustering). The proposed approach is robust as it reasonably categorizes hillslopes with similar elevation, land cover, hydroclimate, land surface processes, and subsurface hydrodynamics, hence a similar hydrologic function.
Mingming Guo, Zhuoxin Chen, Wenlong Wang, Tianchao Wang, Qianhua Shi, Hongliang Kang, Man Zhao, and Lanqian Feng
Hydrol. Earth Syst. Sci., 25, 4473–4494, https://doi.org/10.5194/hess-25-4473-2021, https://doi.org/10.5194/hess-25-4473-2021, 2021
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Gully headcut erosion is always a difficult issue in soil erosion, which hinders the revelation of gully erosion mechanisms and the establishment of a gully erosion model. This study clarified the spatiotemporal changes in flow properties, energy consumption, and soil loss, confirming that gully head consumed the most of flow energy (78 %) and can contribute 89 % of total soil loss. Critical energy consumption initiating soil erosion of the upstream area, gully head, and gully bed is confirmed.
Qiang Dai, Jingxuan Zhu, Shuliang Zhang, Shaonan Zhu, Dawei Han, and Guonian Lv
Hydrol. Earth Syst. Sci., 24, 5407–5422, https://doi.org/10.5194/hess-24-5407-2020, https://doi.org/10.5194/hess-24-5407-2020, 2020
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Rainfall is a driving force that accounts for a large proportion of soil loss around the world. Most previous studies used a fixed rainfall–energy relationship to estimate rainfall energy, ignoring the spatial and temporal changes of raindrop microphysical processes. This study proposes a novel method for large-scale and long-term rainfall energy and rainfall erosivity investigations based on rainfall microphysical parameterization schemes in the Weather Research and Forecasting (WRF) model.
Pedro Henrique Lima Alencar, José Carlos de Araújo, and Adunias dos Santos Teixeira
Hydrol. Earth Syst. Sci., 24, 4239–4255, https://doi.org/10.5194/hess-24-4239-2020, https://doi.org/10.5194/hess-24-4239-2020, 2020
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Soil erosion by water has been emphasized as a key problem to be faced in the 21st century. Thus, it is critical to understand land degradation and to answer fundamental questions regarding how and why such processes occur. Here, we present a model for gully erosion (channels carved by rainwater) based on existing equations, and we identify some major variables that influence the initiation and evolution of this process. The successful model can help in planning soil conservation practices.
Fabien Cochand, Daniel Käser, Philippe Grosvernier, Daniel Hunkeler, and Philip Brunner
Hydrol. Earth Syst. Sci., 24, 213–226, https://doi.org/10.5194/hess-24-213-2020, https://doi.org/10.5194/hess-24-213-2020, 2020
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Roads in sloping fens constitute a hydraulic barrier for surface and subsurface flow. This can lead to the drying out of downslope areas of the fen as well as gully erosion. By combining fieldwork and numerical models, this study presents an assessment of the hydrogeological impact of three road structures especially designed to limit their impact. The study shows that the impact of roads on the hydrological regime in fens can be significantly reduced by using appropriate engineering measures.
Rubianca Benavidez, Bethanna Jackson, Deborah Maxwell, and Kevin Norton
Hydrol. Earth Syst. Sci., 22, 6059–6086, https://doi.org/10.5194/hess-22-6059-2018, https://doi.org/10.5194/hess-22-6059-2018, 2018
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Soil erosion is a global problem and models identify vulnerable areas for management. One such model is the Revised Universal Soil Loss Equation. We review its different sub-factors and compile studies and equations that modified it for local conditions. The limitations of RUSLE include its data requirements and exclusion of gullying and landslides. Future directions include accounting for these erosion types. This paper serves as a reference for others working with RUSLE and related approaches.
Felipe Hernández and Xu Liang
Hydrol. Earth Syst. Sci., 22, 5759–5779, https://doi.org/10.5194/hess-22-5759-2018, https://doi.org/10.5194/hess-22-5759-2018, 2018
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Predicting floods requires first knowing the amount of water in the valleys, which is complicated because we cannot know for sure how much water there is in the soil. We created a unique system that combines the best methods to estimate these conditions accurately based on the observed water flow in the rivers and on detailed simulations of the valleys. Comparisons with popular methods show that our system can produce realistic predictions efficiently, even for very detailed river networks.
Anna Botto, Enrica Belluco, and Matteo Camporese
Hydrol. Earth Syst. Sci., 22, 4251–4266, https://doi.org/10.5194/hess-22-4251-2018, https://doi.org/10.5194/hess-22-4251-2018, 2018
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We present a multivariate application of the ensemble Kalman filter (EnKF) in hydrological modeling of a real-world hillslope test case with dominant unsaturated dynamics and strong nonlinearities. Overall, the EnKF is able to correctly update system state and soil parameters. However, multivariate data assimilation may lead to significant tradeoffs between model predictions of different variables, if the observation data are not high quality or representative.
Peter Metcalfe, Keith Beven, Barry Hankin, and Rob Lamb
Hydrol. Earth Syst. Sci., 22, 2589–2605, https://doi.org/10.5194/hess-22-2589-2018, https://doi.org/10.5194/hess-22-2589-2018, 2018
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Flooding is a significant hazard and extreme events in recent years have focused attention on effective means of reducing its risk. An approach known as natural flood management (NFM) seeks to increase flood resilience by a range of measures that work with natural processes. The paper develops a modelling approach to assess one type NFM of intervention – distributed additional hillslope storage features – and demonstrates that more strategic placement is required than has hitherto been applied.
Abraham Endalamaw, W. Robert Bolton, Jessica M. Young-Robertson, Don Morton, Larry Hinzman, and Bart Nijssen
Hydrol. Earth Syst. Sci., 21, 4663–4680, https://doi.org/10.5194/hess-21-4663-2017, https://doi.org/10.5194/hess-21-4663-2017, 2017
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This study applies plot-scale and hill-slope knowledge to a process-based mesoscale model to improve the skill of distributed hydrological models to simulate the spatially and basin-integrated hydrological processes of complex ecosystems in the sub-arctic boreal forest. We developed a sub-grid parameterization method to parameterize the surface heterogeneity of interior Alaskan discontinuous permafrost watersheds.
Antonio Hayas, Tom Vanwalleghem, Ana Laguna, Adolfo Peña, and Juan V. Giráldez
Hydrol. Earth Syst. Sci., 21, 235–249, https://doi.org/10.5194/hess-21-235-2017, https://doi.org/10.5194/hess-21-235-2017, 2017
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Gully erosion is one of the most important erosion processes. In this study, we provide new data on gully dynamics over long timescales with an unprecedented temporal resolution. We apply a new Monte Carlo based method for calculating gully volumes based on orthophotos and, especially, for constraining uncertainties of these estimations. Our results show that gully erosion rates are highly variable from year to year and significantly higher than other erosion processes.
Giuseppe Formetta, Giovanna Capparelli, and Pasquale Versace
Hydrol. Earth Syst. Sci., 20, 4585–4603, https://doi.org/10.5194/hess-20-4585-2016, https://doi.org/10.5194/hess-20-4585-2016, 2016
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This paper focuses on performance evaluation of simplified, physically based landslide susceptibility models. It presents a new methodology to systemically and objectively calibrate, verify, and compare different models and models performances indicators in order to individuate and select the models whose behavior is more reliable for a certain case study. The procedure was implemented in a package for landslide susceptibility analysis and integrated the open-source hydrological model NewAge.
Carlotta Scudeler, Luke Pangle, Damiano Pasetto, Guo-Yue Niu, Till Volkmann, Claudio Paniconi, Mario Putti, and Peter Troch
Hydrol. Earth Syst. Sci., 20, 4061–4078, https://doi.org/10.5194/hess-20-4061-2016, https://doi.org/10.5194/hess-20-4061-2016, 2016
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Very few studies have applied a physically based hydrological model with integrated and distributed multivariate observation data of both flow and transport phenomena. In this study we address this challenge for a hillslope-scale unsaturated zone isotope tracer experiment. The results show how model complexity evolves as the number and detail of simulated responses increases. Possible gaps in process representation for simulating solute transport phenomena in very dry soils are discussed.
Bruno Cheviron and Roger Moussa
Hydrol. Earth Syst. Sci., 20, 3799–3830, https://doi.org/10.5194/hess-20-3799-2016, https://doi.org/10.5194/hess-20-3799-2016, 2016
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This review paper investigates the determinants of modelling choices for numerous applications of 1-D free-surface flow and morphodynamics in hydrology and hydraulics. Each case study has a signature composed of given contexts (spatiotemporal scales, flow typology, and phenomenology) and chosen concepts (refinement and subscales of the flow model). This review proposes a normative procedure possibly enriched by the community for a larger, comprehensive and updated image of modelling strategies.
F. Todisco, L. Brocca, L. F. Termite, and W. Wagner
Hydrol. Earth Syst. Sci., 19, 3845–3856, https://doi.org/10.5194/hess-19-3845-2015, https://doi.org/10.5194/hess-19-3845-2015, 2015
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We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.
W. Shao, T. A. Bogaard, M. Bakker, and R. Greco
Hydrol. Earth Syst. Sci., 19, 2197–2212, https://doi.org/10.5194/hess-19-2197-2015, https://doi.org/10.5194/hess-19-2197-2015, 2015
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The effect of preferential flow on the stability of landslides is studied through numerical simulation of two types of rainfall events on a hypothetical hillslope. A model is developed that consists of two parts. The first part is a model for combined saturated/unsaturated subsurface flow and is used to compute the spatial and temporal water pressure response to rainfall. Preferential flow is simulated with a dual-permeability continuum model consisting of a matrix/preferential flow domain.
O. Fovet, L. Ruiz, M. Hrachowitz, M. Faucheux, and C. Gascuel-Odoux
Hydrol. Earth Syst. Sci., 19, 105–123, https://doi.org/10.5194/hess-19-105-2015, https://doi.org/10.5194/hess-19-105-2015, 2015
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We studied the annual hysteretic patterns observed between stream flow and water storage in the saturated and unsaturated zones of a hillslope and a riparian zone. We described these signatures using a hysteresis index and then used this to assess conceptual hydrological models. This led us to identify four hydrological periods and a clearly distinct behaviour between riparian and hillslope groundwaters and to provide new information about the model performances.
D. J. Peres and A. Cancelliere
Hydrol. Earth Syst. Sci., 18, 4913–4931, https://doi.org/10.5194/hess-18-4913-2014, https://doi.org/10.5194/hess-18-4913-2014, 2014
Short summary
Short summary
A Monte Carlo approach, combining rainfall-stochastic models and hydrological and slope stability physically based models, is used to derive rainfall thresholds of landslide triggering. The uncertainty in threshold assessment related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall) is analyzed and measured via ROC-based indexes, with a specific focus dedicated to the widely used power-law rainfall intensity-duration (I-D) thresholds.
D. Windhorst, P. Kraft, E. Timbe, H.-G. Frede, and L. Breuer
Hydrol. Earth Syst. Sci., 18, 4113–4127, https://doi.org/10.5194/hess-18-4113-2014, https://doi.org/10.5194/hess-18-4113-2014, 2014
G. Capparelli and P. Versace
Hydrol. Earth Syst. Sci., 18, 3225–3237, https://doi.org/10.5194/hess-18-3225-2014, https://doi.org/10.5194/hess-18-3225-2014, 2014
D. Penna, M. Borga, G. T. Aronica, G. Brigandì, and P. Tarolli
Hydrol. Earth Syst. Sci., 18, 2127–2139, https://doi.org/10.5194/hess-18-2127-2014, https://doi.org/10.5194/hess-18-2127-2014, 2014
G.-Y. Niu, D. Pasetto, C. Scudeler, C. Paniconi, M. Putti, P. A. Troch, S. B. DeLong, K. Dontsova, L. Pangle, D. D. Breshears, J. Chorover, T. E. Huxman, J. Pelletier, S. R. Saleska, and X. Zeng
Hydrol. Earth Syst. Sci., 18, 1873–1883, https://doi.org/10.5194/hess-18-1873-2014, https://doi.org/10.5194/hess-18-1873-2014, 2014
J. Tao and A. P. Barros
Hydrol. Earth Syst. Sci., 18, 367–388, https://doi.org/10.5194/hess-18-367-2014, https://doi.org/10.5194/hess-18-367-2014, 2014
J. Wienhöfer and E. Zehe
Hydrol. Earth Syst. Sci., 18, 121–138, https://doi.org/10.5194/hess-18-121-2014, https://doi.org/10.5194/hess-18-121-2014, 2014
A. Richard, S. Galle, M. Descloitres, J.-M. Cohard, J.-P. Vandervaere, L. Séguis, and C. Peugeot
Hydrol. Earth Syst. Sci., 17, 5079–5096, https://doi.org/10.5194/hess-17-5079-2013, https://doi.org/10.5194/hess-17-5079-2013, 2013
S. R. Lutz, H. J. van Meerveld, M. J. Waterloo, H. P. Broers, and B. M. van Breukelen
Hydrol. Earth Syst. Sci., 17, 4505–4524, https://doi.org/10.5194/hess-17-4505-2013, https://doi.org/10.5194/hess-17-4505-2013, 2013
Makoto Tani
Hydrol. Earth Syst. Sci., 17, 4453–4470, https://doi.org/10.5194/hess-17-4453-2013, https://doi.org/10.5194/hess-17-4453-2013, 2013
M. N. Papa, V. Medina, F. Ciervo, and A. Bateman
Hydrol. Earth Syst. Sci., 17, 4095–4107, https://doi.org/10.5194/hess-17-4095-2013, https://doi.org/10.5194/hess-17-4095-2013, 2013
P. Fiener, K. Auerswald, F. Winter, and M. Disse
Hydrol. Earth Syst. Sci., 17, 4121–4132, https://doi.org/10.5194/hess-17-4121-2013, https://doi.org/10.5194/hess-17-4121-2013, 2013
R. Greco, L. Comegna, E. Damiano, A. Guida, L. Olivares, and L. Picarelli
Hydrol. Earth Syst. Sci., 17, 4001–4013, https://doi.org/10.5194/hess-17-4001-2013, https://doi.org/10.5194/hess-17-4001-2013, 2013
C. Lepore, E. Arnone, L. V. Noto, G. Sivandran, and R. L. Bras
Hydrol. Earth Syst. Sci., 17, 3371–3387, https://doi.org/10.5194/hess-17-3371-2013, https://doi.org/10.5194/hess-17-3371-2013, 2013
J. E. van der Spek, T. A. Bogaard, and M. Bakker
Hydrol. Earth Syst. Sci., 17, 2171–2183, https://doi.org/10.5194/hess-17-2171-2013, https://doi.org/10.5194/hess-17-2171-2013, 2013
A. M. Ireson and A. P. Butler
Hydrol. Earth Syst. Sci., 17, 2083–2096, https://doi.org/10.5194/hess-17-2083-2013, https://doi.org/10.5194/hess-17-2083-2013, 2013
A. M. J. Coenders-Gerrits, L. Hopp, H. H. G. Savenije, and L. Pfister
Hydrol. Earth Syst. Sci., 17, 1749–1763, https://doi.org/10.5194/hess-17-1749-2013, https://doi.org/10.5194/hess-17-1749-2013, 2013
G. Martelloni, S. Segoni, D. Lagomarsino, R. Fanti, and F. Catani
Hydrol. Earth Syst. Sci., 17, 1229–1240, https://doi.org/10.5194/hess-17-1229-2013, https://doi.org/10.5194/hess-17-1229-2013, 2013
C. D. Guzman, S. A. Tilahun, A. D. Zegeye, and T. S. Steenhuis
Hydrol. Earth Syst. Sci., 17, 1067–1077, https://doi.org/10.5194/hess-17-1067-2013, https://doi.org/10.5194/hess-17-1067-2013, 2013
D. M. Krzeminska, T. A. Bogaard, J.-P. Malet, and L. P. H. van Beek
Hydrol. Earth Syst. Sci., 17, 947–959, https://doi.org/10.5194/hess-17-947-2013, https://doi.org/10.5194/hess-17-947-2013, 2013
A. Peñuela, M. Javaux, and C. L. Bielders
Hydrol. Earth Syst. Sci., 17, 87–101, https://doi.org/10.5194/hess-17-87-2013, https://doi.org/10.5194/hess-17-87-2013, 2013
A. Rodhe
Hydrol. Earth Syst. Sci., 16, 3075–3082, https://doi.org/10.5194/hess-16-3075-2012, https://doi.org/10.5194/hess-16-3075-2012, 2012
G. Y. Gao, B. J. Fu, Y. H. Lü, Y. Liu, S. Wang, and J. Zhou
Hydrol. Earth Syst. Sci., 16, 2347–2364, https://doi.org/10.5194/hess-16-2347-2012, https://doi.org/10.5194/hess-16-2347-2012, 2012
C. E. Ballard, N. McIntyre, and H. S. Wheater
Hydrol. Earth Syst. Sci., 16, 2299–2310, https://doi.org/10.5194/hess-16-2299-2012, https://doi.org/10.5194/hess-16-2299-2012, 2012
D. M. Krzeminska, T. A. Bogaard, Th. W. J. van Asch, and L. P. H. van Beek
Hydrol. Earth Syst. Sci., 16, 1561–1576, https://doi.org/10.5194/hess-16-1561-2012, https://doi.org/10.5194/hess-16-1561-2012, 2012
T. Maurer, A. Schneider, and H. H. Gerke
Hydrol. Earth Syst. Sci., 15, 3617–3638, https://doi.org/10.5194/hess-15-3617-2011, https://doi.org/10.5194/hess-15-3617-2011, 2011
J. Klaus and E. Zehe
Hydrol. Earth Syst. Sci., 15, 2127–2144, https://doi.org/10.5194/hess-15-2127-2011, https://doi.org/10.5194/hess-15-2127-2011, 2011
M. C. Westhoff, T. A. Bogaard, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 15, 1945–1957, https://doi.org/10.5194/hess-15-1945-2011, https://doi.org/10.5194/hess-15-1945-2011, 2011
J. Minet, E. Laloy, S. Lambot, and M. Vanclooster
Hydrol. Earth Syst. Sci., 15, 1323–1338, https://doi.org/10.5194/hess-15-1323-2011, https://doi.org/10.5194/hess-15-1323-2011, 2011
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Short summary
To overcome the computational cost of numerical models, we propose a deep-learning approach inspired by hydraulic models that can simulate the spatio-temporal evolution of floods. We show that the model can rapidly predict dike breach floods over different topographies and breach locations, with limited use of ground-truth data.
To overcome the computational cost of numerical models, we propose a deep-learning approach...
