Articles | Volume 26, issue 7
https://doi.org/10.5194/hess-26-1907-2022
© Author(s) 2022. 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-26-1907-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Apr 2022
Research article |
| 14 Apr 2022
| 14 Apr 2022
Exploring the possible role of satellite-based rainfall data in estimating inter- and intra-annual global rainfall erosivity
University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia
Pasquale Borrelli
Department of Earth and Environmental Sciences, University of Pavia, Pavia, Italy
Department of Biological Environment, Kangwon National University,
Chuncheon 24341, Republic of Korea
Panos Panagos
European Commission, Joint Research Centre (JRC), Ispra, Italy
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Francis Matthews, Pasquale Borrelli, Panos Panagos, and Nejc Bezak
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-402, https://doi.org/10.5194/hess-2024-402, 2025
Preprint under review for HESS
Short summary
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Rainfall erosivity is the main driver of water-induced soil erosion. A ground radar-based data was used to prepare a rainfall erosivity map of Europe. This study shows that the radar-based data products are a valuable solution for estimating large-scale rainfall erosivity, especially in regions with limited station-based precipitation data. A rainfall erosivity ensemble was derived to give first insights into a future avenue for updatable pan-European rainfall erosivity predictions.
Nejc Bezak, Panos Panagos, Leonidas Liakos, and Matjaž Mikoš
Nat. Hazards Earth Syst. Sci., 23, 3885–3893, https://doi.org/10.5194/nhess-23-3885-2023, https://doi.org/10.5194/nhess-23-3885-2023, 2023
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Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
Short summary
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Ross Pidoto, Nejc Bezak, Hannes Müller-Thomy, Bora Shehu, Ana Claudia Callau-Beyer, Katarina Zabret, and Uwe Haberlandt
Earth Surf. Dynam., 10, 851–863, https://doi.org/10.5194/esurf-10-851-2022, https://doi.org/10.5194/esurf-10-851-2022, 2022
Short summary
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Erosion is a threat for soils with rainfall as the driving force. The annual rainfall erosivity factor quantifies rainfall impact by analysing high-resolution rainfall time series (~ 5 min). Due to a lack of measuring stations, alternatives for its estimation are analysed in this study. The best results are obtained for regionalisation of the erosivity factor itself. However, the identified minimum of 60-year time series length suggests using rainfall generators as in this study as well.
Theano Iliopoulou, Cristina Aguilar, Berit Arheimer, María Bermúdez, Nejc Bezak, Andrea Ficchì, Demetris Koutsoyiannis, Juraj Parajka, María José Polo, Guillaume Thirel, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 73–91, https://doi.org/10.5194/hess-23-73-2019, https://doi.org/10.5194/hess-23-73-2019, 2019
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We investigate the seasonal memory properties of a large sample of European rivers in terms of high and low flows. We compute seasonal correlations between peak and low flows and average flows in the previous seasons and explore the links with various physiographic and hydro-climatic catchment descriptors. Our findings suggest that there is a traceable physical basis for river memory which in turn can be employed to reduce uncertainty and improve probabilistic predictions of floods and droughts.
Francis Matthews, Pasquale Borrelli, Panos Panagos, and Nejc Bezak
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-402, https://doi.org/10.5194/hess-2024-402, 2025
Preprint under review for HESS
Short summary
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Rainfall erosivity is the main driver of water-induced soil erosion. A ground radar-based data was used to prepare a rainfall erosivity map of Europe. This study shows that the radar-based data products are a valuable solution for estimating large-scale rainfall erosivity, especially in regions with limited station-based precipitation data. A rainfall erosivity ensemble was derived to give first insights into a future avenue for updatable pan-European rainfall erosivity predictions.
Nejc Bezak, Panos Panagos, Leonidas Liakos, and Matjaž Mikoš
Nat. Hazards Earth Syst. Sci., 23, 3885–3893, https://doi.org/10.5194/nhess-23-3885-2023, https://doi.org/10.5194/nhess-23-3885-2023, 2023
Short summary
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Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
Francis Matthews, Panos Panagos, Arthur Fendrich, and Gert Verstraeten
EGUsphere, https://doi.org/10.5194/egusphere-2023-2693, https://doi.org/10.5194/egusphere-2023-2693, 2023
Preprint withdrawn
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We assess if a simplistic model can simulate the timing of soil erosion and sediment transport (delivery) in several small agricultural catchments in North-West Europe. The findings show that the loss of soil in fields and the delivery of sediment to streams are related in complex (non-linear) ways through time which impact our knowledge of soil redistribution. Furthermore, we show how adaptations of simplistic models can be used to reveal the missing processes which require future developments.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
Short summary
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
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Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Ross Pidoto, Nejc Bezak, Hannes Müller-Thomy, Bora Shehu, Ana Claudia Callau-Beyer, Katarina Zabret, and Uwe Haberlandt
Earth Surf. Dynam., 10, 851–863, https://doi.org/10.5194/esurf-10-851-2022, https://doi.org/10.5194/esurf-10-851-2022, 2022
Short summary
Short summary
Erosion is a threat for soils with rainfall as the driving force. The annual rainfall erosivity factor quantifies rainfall impact by analysing high-resolution rainfall time series (~ 5 min). Due to a lack of measuring stations, alternatives for its estimation are analysed in this study. The best results are obtained for regionalisation of the erosivity factor itself. However, the identified minimum of 60-year time series length suggests using rainfall generators as in this study as well.
Jeppe Aagaard Kristensen, Thomas Balstrøm, Robert J. A. Jones, Arwyn Jones, Luca Montanarella, Panos Panagos, and Henrik Breuning-Madsen
SOIL, 5, 289–301, https://doi.org/10.5194/soil-5-289-2019, https://doi.org/10.5194/soil-5-289-2019, 2019
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In a world of increasing pressure on our environment, large-scale knowledge about our soil resources is in high demand. We show how five decades of collaboration between EU member states resulted in a full-coverage soil profile analytical database for Europe (SPADE), with soil data provided by soil experts from each country. We show how the dataset can be applied to estimate soil organic carbon in Europe and suggest further improvement to this critical support tool in continental-scale policies.
Theano Iliopoulou, Cristina Aguilar, Berit Arheimer, María Bermúdez, Nejc Bezak, Andrea Ficchì, Demetris Koutsoyiannis, Juraj Parajka, María José Polo, Guillaume Thirel, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 73–91, https://doi.org/10.5194/hess-23-73-2019, https://doi.org/10.5194/hess-23-73-2019, 2019
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We investigate the seasonal memory properties of a large sample of European rivers in terms of high and low flows. We compute seasonal correlations between peak and low flows and average flows in the previous seasons and explore the links with various physiographic and hydro-climatic catchment descriptors. Our findings suggest that there is a traceable physical basis for river memory which in turn can be employed to reduce uncertainty and improve probabilistic predictions of floods and droughts.
Simon Schmidt, Christine Alewell, Panos Panagos, and Katrin Meusburger
Hydrol. Earth Syst. Sci., 20, 4359–4373, https://doi.org/10.5194/hess-20-4359-2016, https://doi.org/10.5194/hess-20-4359-2016, 2016
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We present novel research on the seasonal dynamics of the impact of rainfall (R-factor) on the mobilization of topsoil as soil erosion by water for Switzerland. A modeling approach was chosen that enables the dynamical mapping of the R-factor. Based on the maps and modeling results, we could investigate the spatial and temporal distribution of that factor, which is high for Switzerland. With these results, agronomists can introduce selective erosion control measures.
C. Bosco, D. de Rigo, O. Dewitte, J. Poesen, and P. Panagos
Nat. Hazards Earth Syst. Sci., 15, 225–245, https://doi.org/10.5194/nhess-15-225-2015, https://doi.org/10.5194/nhess-15-225-2015, 2015
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A new pan-European map of soil erosion is presented following a novel extension of the RUSLE model (e-RUSLE) designed for data-poor regional assessment and for identifying areas in Europe where to concentrate efforts for preventing soil degradation. e-RUSLE exploits the array-based semantics of a multiplicity of factors (semantic array programming). A climatic ensemble of an array of erosivity equations is considered along with a new factor for better considering soil stoniness within the model.
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
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Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
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Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
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Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
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Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
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Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
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This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
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Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
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Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
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We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
EGUsphere, https://doi.org/10.5194/egusphere-2024-1969, https://doi.org/10.5194/egusphere-2024-1969, 2024
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In this study, we present a detailed characterisation of flash drought in United Kingdom over the period 1969–2021.The spatiotemporal distribution of flash droughts is highly variable, with important regional and seasonal contrasts. In the UK, flash drought occurrence responds primarily to precipitation variability, although the atmospheric evaporative demand (AED) is important as a secondary driver. The atmospheric and oceanic conditions during flash droughts development were also analyzed.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-132, https://doi.org/10.5194/hess-2024-132, 2024
Revised manuscript accepted for HESS
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Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and The Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Mohammad Ali Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1256, https://doi.org/10.5194/egusphere-2024-1256, 2024
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This study investigates how key hydrological processes enhance soil water retention and release in land surface models, crucial for accurate weather and climate forecasting. Experiments show that soil hydraulics effectively sustain soil moisture. Additionally, allowing surface water ponding and improving soil permeability through macropores both enhance soil moisture persistency in the models.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-78, https://doi.org/10.5194/hess-2024-78, 2024
Revised manuscript accepted for HESS
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Observations from a study site network in eastern Canada showed a temperature interval the overlapping probabilities for rain, snow or a mix of both. Models using random forest algorithms were developed to classify the precipitation phase using meteorological data to evaluate operational applications. They showed significantly improved phase classification compared to benchmarks, but misclassification led to costlier errors. However, accurate prediction of mixed phase remains a challenge.
Lorenzo Silvestri, Miriam Saraceni, Giulia Passadore, and Paolina Bongioannini Cerlini
EGUsphere, https://doi.org/10.5194/egusphere-2024-889, https://doi.org/10.5194/egusphere-2024-889, 2024
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This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in certain areas of the Central Mediterranean. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance and, in general, dry events are better captured than wet events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
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Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
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Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Cited articles
Aghakouchak, A., Mehran, A., Norouzi, H., and Behrangi, A.: Systematic and
random error components in satellite precipitation data sets, Geophys. Res.
Lett., 39, L09406, https://doi.org/10.1029/2012GL051592, 2012.
An, Y., Zhao, W., Li, C., and Liu, Y.: Evaluation of Six Satellite and
Reanalysis Precipitation Products Using Gauge Observations over the Yellow
River Basin, China, Atmosphere, 11, 1–20, https://doi.org/10.3390/atmos11111223,
2020.
Angulo-Martínez, M. and Beguería, S.: Trends in rainfall erosivity in NE Spain at annual, seasonal and daily scales, 1955–2006, Hydrol. Earth Syst. Sci., 16, 3551–3559, https://doi.org/10.5194/hess-16-3551-2012, 2012.
Ballabio, C., Borrelli, P., Spinoni, J., Meusburger, K., Michaelides, S.,
Beguería, S., Klik, A., Petan, S., Janeček, M., Olsen, P., Aalto,
J., Lakatos, M., Rymszewicz, A., Dumitrescu, A., Tadić, M. P., Diodato,
N., Kostalova, J., Rousseva, S., Banasik, K., Alewell, C., and Panagos, P.:
Mapping monthly rainfall erosivity in Europe, Sci. Total Environ., 579,
1298–1315, https://doi.org/10.1016/J.SCITOTENV.2016.11.123, 2017.
Beck, H. E., Pan, M., Roy, T., Weedon, G. P., Pappenberger, F., van Dijk, A. I. J. M., Huffman, G. J., Adler, R. F., and Wood, E. F.: Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS, Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, 2019a.
Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. G., Van Dijk,
A. I. J. M., McVicar, T. R., and Adler, R. F.: MSWep v2 Global 3-hourly
0.1∘ precipitation: Methodology and quantitative assessment, B.
Am. Meteorol. Soc., 100, 473–500, https://doi.org/10.1175/BAMS-D-17-0138.1, 2019b.
Beck, H. E., Wood, E. F., McVicar, T. R., Zambrano-Bigiarini, M.,
Alvarez-Garreton, C., Baez-Villanueva, O. M., Sheffield, J., and Karger, D.
N.: Bias correction of global high-resolution precipitation climatologies
using streamflow observations from 9372 catchments, J. Climate, 33,
1299–1315, https://doi.org/10.1175/JCLI-D-19-0332.1, 2020.
Bezak, N., Ballabio, C., Mikoš, M., Petan, S., Borrelli, P., and Panagos,
P.: Reconstruction of past rainfall erosivity and trend detection based on
the REDES database and reanalysis rainfall, J. Hydrol., 590, 125372,
https://doi.org/10.1016/j.jhydrol.2020.125372, 2020.
Bezak, N., Borrelli, P., and Panagos, P.: A first assessment of rainfall
erosivity synchrony scale at pan-European scale, Catena, 198, 105060,
https://doi.org/10.1016/j.catena.2020.105060, 2021.
Borrelli, P., Robinson, D. A., Fleischer, L. R., Lugato, E., Ballabio, C.,
Alewell, C., Meusburger, K., Modugno, S., Schütt, B., Ferro, V.,
Montanarella, L., and Panagos, P.: An assessment of the global impact of 21st
century land use change on soil erosion, Nat. Commun., 8, 2013, https://doi.org/10.1038/s41467-017-02142-7, 2017.
Borrelli, P., Robinson, D. A., Panagos, P., Lugato, E., Yang, J. E.,
Alewell, C., Wuepper, D., Montanarella, L., and Ballabio, C.: Land use and
climate change impacts on global soil erosion by water (2015–2070), P.
Natl. Acad. Sci. USA, 117, 21994–22001,
https://doi.org/10.1073/pnas.2001403117, 2020.
Brown, L. C. and Foster, G.: Storm erosivity using idealised intensity
distribution, T. ASAE, 30, 379–386, https://doi.org/10.13031/2013.31957, 1987.
Burn, D. H. and Hag Elnur, M. A.: Detection of hydrologic trends and
variability, J. Hydrol., 255, 107–122,
https://doi.org/10.1016/S0022-1694(01)00514-5, 2002.
Carollo, F. G., Ferro, V., and Serio, M. A.: Reliability of rainfall kinetic
power–intensity relationships, Hydrol. Process., 31, 1293–1300,
https://doi.org/10.1002/hyp.11099, 2017.
Chen, H., Chandrasekar, V., Cifelli, R., and Xie, P.: A Machine Learning
System for Precipitation Estimation Using Satellite and Ground Radar Network
Observations, IEEE Trans. Geosci. Remote Sens., 58, 982–994,
https://doi.org/10.1109/TGRS.2019.2942280, 2020.
Chen, Y., Xu, M., Wang, Z., Gao, P., and Lai, C.: Applicability of two
satellite-based precipitation products for assessing rainfall erosivity in
China, Sci. Total Environ., 757, 143975, https://doi.org/10.1016/j.scitotenv.2020.143975, 2021.
Cui, Y., Pan, C., Liu, C., Luo, M., and Guo, Y.: Spatiotemporal variation and
tendency analysis on rainfall erosivity in the Loess Plateau of China,
Hydrol. Res., 51, 1048–1062, https://doi.org/10.2166/nh.2020.030, 2020.
Dabney, S. M., Yoder, D. C., and Vieira, D. A. N.: The application of the
Revised Universal Soil Loss Equation, Version 2, to evaluate the impacts of
alternative climate change scenarios on runoff and sediment yield, J. Soil
Water Conserv., 67, 343–353, https://doi.org/10.2489/jswc.67.5.343, 2012.
Diodato, N., Borrelli, P., Panagos, P., Bellocchi, G., and Bertolin, C.:
Communicating Hydrological Hazard-Prone Areas in Italy With Geospatial
Probability Maps, Front. Environ. Sci., 7, 193, https://doi.org/10.3389/fenvs.2019.00193,
2019.
Dis, M. O., Anagnostou, E., and Mei, Y.: Using high-resolution satellite
precipitation for flood frequency analysis: case study over the Connecticut
River Basin, J. Flood Risk Manag., 11, S514–S526, https://doi.org/10.1111/jfr3.12250,
2018.
Dodson, R. and Marks, D.: Daily air temperature interpolated at high spatial
resolution over a large mountainous region, Clim. Res., 8, 61–73,
https://doi.org/10.3354/cr008001, 1997.
dos Santos Silva, D. S., Blanco, C. J. C., dos Santos Junior, C. S., and
Martins, W. L. D.: Modeling of the spatial and temporal dynamics of
erosivity in the Amazon, Model. Earth Syst. Environ., 6, 513–523,
https://doi.org/10.1007/s40808-019-00697-6, 2020.
ERA5: ERA5, https://doi.org/10.24381/cds.f17050d7, 2021.
Ganasri, B. P. and Ramesh, H.: Assessment of soil erosion by RUSLE model
using remote sensing and GIS – A case study of Nethravathi Basin, Geosci.
Front., 7, 953–961, https://doi.org/10.1016/j.gsf.2015.10.007, 2016.
Gebregiorgis, A. S. and Hossain, F.: How well can we estimate error variance
of satellite precipitation data around the world?, Atmos. Res., 154, 39–59,
https://doi.org/10.1016/j.atmosres.2014.11.005, 2015.
Ghajarnia, N., Daneshkar Arasteh, P., Liaghat, M., and Araghinejad, S.: Error
analysis on PERSIANN precipitation estimations: Case study of Urmia Lake
Basin, Iran, J. Hydrol. Eng., 23, 05018006-1, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001643,
2018.
Gini, C.: On the measurement of concentration and variability of characters,
Metron, 63, 3–38, 1914.
Habib, E., Haile, A. T., Tian, Y., and Joyce, R. J.: Evaluation of the
high-resolution CMORPH satellite rainfall product using dense rain gauge
observations and radar-based estimates, J. Hydrometeorol., 13,
1784–1798, https://doi.org/10.1175/JHM-D-12-017.1, 2012.
Haile, A. T., Yan, F., and Habib, E.: Accuracy of the CMORPH
satellite-rainfall product over Lake Tana Basin in Eastern Africa, Atmos.
Res., 163, 177–187, https://doi.org/10.1016/j.atmosres.2014.11.011, 2015.
Hamed, K. H.: Trend detection in hydrologic data: The Mann-Kendall trend
test under the scaling hypothesis, J. Hydrol., 349, 350–363,
https://doi.org/10.1016/j.jhydrol.2007.11.009, 2008.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.bd0915c6, 2018.
Islam, M. A., Yu, B., and Cartwright, N.: Assessment and comparison of five
satellite precipitation products in Australia, J. Hydrol., 590, 125474, https://doi.org/10.1016/j.jhydrol.2020.125474, 2020.
Jiang, Q., Li, W., Wen, J., Qiu, C., Sun, W., Fang, Q., Xu, M., and Tan, J.:
Accuracy evaluation of two high-resolution satellite-based rainfall
products: TRMM 3B42V7 and CMORPH in Shanghai, Water (Switzerland), 10, 40, https://doi.org/10.3390/w10010040, 2018.
Jiang, Q., Li, W., Wen, J., Fan, Z., Chen, Y., Scaioni, M., and Wang, J.:
Evaluation of satellite-based products for extreme rainfall estimations in
the eastern coastal areas of China, J. Integr. Environ. Sci., 16,
191–207, https://doi.org/10.1080/1943815X.2019.1707233, 2019.
Kidd, C., Bauer, P., Turk, J., Huffman, G. J., Joyce, R., Hsu, K.-L., and
Braithwaite, D.: Intercomparison of high-resolution precipitation products
over Northwest Europe, J. Hydrometeorol., 13, 67–83,
https://doi.org/10.1175/JHM-D-11-042.1, 2012.
Kim, J., Han, H., Kim, B., Chen, H., and Lee, J.-H.: Use of a
high-resolution-satellite-based precipitation product in mapping
continental-scale rainfall erosivity: A case study of the United States,
Catena, 193, 104602, https://doi.org/10.1016/j.catena.2020.104602, 2020.
Kim, J. P., Jung, I., Park, K. W., Yoon, S. K., and Lee, D.: Hydrological
utility and uncertainty of multi-satellite precipitation products in the
mountainous region of South Korea, Remote Sens., 8, 608, https://doi.org/10.3390/rs8070608, 2016.
Kinnell, P. I. A.: Event soil loss, runoff and the Universal Soil Loss
Equation family of models: A review, J. Hydrol., 385, 384–397,
https://doi.org/10.1016/j.jhydrol.2010.01.024, 2010.
Kinnell, P. I. A.: CLIGEN as a weather generator for RUSLE2, Catena, 172,
877–880, https://doi.org/10.1016/j.catena.2018.09.016, 2019.
Lehner, B. and Grill, G.: Global river hydrography and network routing:
Baseline data and new approaches to study the world's large river systems,
Hydrol. Process., 27, 2171–2186, https://doi.org/10.1002/hyp.9740, 2013.
Li, X., Li, Z., and Lin, Y.: Suitability of trmm products with different
temporal resolution (3-hourly, daily, and monthly) for rainfall erosivity
estimation, Remote Sens., 12, 1–21, https://doi.org/10.3390/rs12233924, 2020.
Liu, Y., Zhao, W., Liu, Y., and Pereira, P.: Global rainfall erosivity
changes between 1980 and 2017 based on an erosivity model using daily
precipitation data, Catena, 194, 104768, https://doi.org/10.1016/j.catena.2020.104768, 2020.
Lorenz, M. O.: Methods of measuring the concentration of wealth, Publ. Am.
Stat. Assoc., 9, 209–219, https://doi.org/10.2307/2276207, 1905.
Masaki, Y., Hanasaki, N., Takahashi, K., and Hijioka, Y.: Global-scale
analysis on future changes in flow regimes using Gini and Lorenz asymmetry
coefficients, Water Resour. Res., 50, 4054–4078,
https://doi.org/10.1002/2013WR014266, 2014.
McLeod, A. I.: Kendall rank correlation and Mann-Kendall trend test, 12, http://www.stats.uwo.ca/faculty/aim (last access: 10 January 2022), 2011.
Mineo, C., Ridolfi, E., Moccia, B., Russo, F., and Napolitano, F.: Assessment
of rainfall kinetic-energy-intensity relationships, Water,
11, 1994, https://doi.org/10.3390/w11101994, 2019.
Nearing, M. A., Unkrich, C. L., Goodrich, D. C., Nichols, M. H., and Keefer,
T. O.: Temporal and elevation trends in rainfall erosivity on a 149 km2
watershed in a semi-arid region of the American Southwest, Int. Soil Water
Conserv. Res., 3, 77–85, https://doi.org/10.1016/j.iswcr.2015.06.008, 2015.
Nearing, M. A., Yin, S.-Q., Borrelli, P., and Polyakov, V. O.: Rainfall
erosivity: An historical review, Catena, 157, 357–362,
https://doi.org/10.1016/j.catena.2017.06.004, 2017.
Nel, W., Reynhardt, D. A., and Sumner, P. D.: Effect of altitude on erosive
characteristics of concurrent rainfall events in the northern kwazulu-natal
drakensberg, Water, 36, 509–512, 2010.
NOAA: CMORPH dataset, https://www.ncei.noaa.gov/data/cmorph-high-resolution-global-precipitation-estimates/access/, last access 28 March 2022.
Palharini, R. S. A., Vila, D. A., Rodrigues, D. T., Quispe, D. P.,
Palharini, R. C., de Siqueira, R. A., and de Sousa Afonso, J. M.: Assessment
of the extreme precipitation by satellite estimates over South America,
Remote Sens., 12, 2085, https://doi.org/10.3390/rs12132085, 2020.
Panagos, P., Van Liedekerke, M., Jones, A., and Montanarella, L.: European
Soil Data Centre: Response to European policy support and public data
requirements, Land Use Policy, 29, 329–338,
https://doi.org/10.1016/j.landusepol.2011.07.003, 2012 (data available at: https://esdac.jrc.ec.europa.eu/resource-type/datasets, last access: 10 January 2022).
Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva,
S., Tadić, M. P., Michaelides, S., Hrabalíková, M., Olsen, P.,
Beguería, S., and Alewell, C.: Rainfall erosivity in Europe, Sci. Total
Environ., 511, 801–814, https://doi.org/10.1016/j.scitotenv.2015.01.008, 2015.
Panagos, P., Borrelli, P., Spinoni, J., Ballabio, C., Meusburger, K.,
Beguería, S., Klik, A., Michaelides, S., Petan, S.,
Hrabalíková, M., Banasik, K., and Alewell, C.: Monthly rainfall
erosivity: Conversion factors for different time resolutions and regional
assessments, Water, 8, 119, https://doi.org/10.3390/w8040119, 2016a.
Panagos, P., Ballabio, C., Borrelli, P., and Meusburger, K.: Spatio-temporal
analysis of rainfall erosivity and erosivity density in Greece, Catena, 137,
161–172, https://doi.org/10.1016/j.catena.2015.09.015, 2016b.
Panagos, P., Borrelli, P., Meusburger, K., Yu, B., Klik, A., Jae Lim, K.,
Yang, J. E., Ni, J., Miao, C., Chattopadhyay, N., Sadeghi, S. H., Hazbavi,
Z., Zabihi, M., Larionov, G. A., Krasnov, S. F., Gorobets, A. V, Levi, Y.,
Erpul, G., Birkel, C., Hoyos, N., Naipal, V., Oliveira, P. T. S., Bonilla,
C. A., Meddi, M., Nel, W., Al Dashti, H., Boni, M., Diodato, N., Van Oost,
K., Nearing, M., and Ballabio, C.: Global rainfall erosivity assessment based
on high-temporal resolution rainfall records, Sci. Rep., 7, 4175,
https://doi.org/10.1038/s41598-017-04282-8, 2017.
Peel, M. C., Finlayson, B. L., and McMahon, T. A.: Updated world map of the Köppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633–1644, https://doi.org/10.5194/hess-11-1633-2007, 2007.
Petan, S., Rusjan, S., Vidmar, A., and Mikoš, M.: The rainfall kinetic
energy-intensity relationship for rainfall erosivity estimation in the
mediterranean part of Slovenia, J. Hydrol., 391, 314–321,
https://doi.org/10.1016/j.jhydrol.2010.07.031, 2010.
Petek, M., Mikoš, M., and Bezak, N.: Rainfall erosivity in Slovenia:
Sensitivity estimation and trend detection, Environ. Res., 167, 528–535,
https://doi.org/10.1016/j.envres.2018.08.020, 2018.
Prakash, S.: Performance assessment of CHIRPS, MSWEP, SM2RAIN-CCI, and TMPA
precipitation products across India, J. Hydrol., 571, 50–59,
https://doi.org/10.1016/j.jhydrol.2019.01.036, 2019.
Prakash, S., Mitra, A. K., AghaKouchak, A., and Pai, D. S.: Error
characterization of TRMM Multisatellite Precipitation Analysis (TMPA-3B42)
products over India for different seasons, J. Hydrol., 529, 1302–1312,
https://doi.org/10.1016/j.jhydrol.2015.08.062, 2015.
Rahmawati, N. and Lubczynski, M. W.: Validation of satellite daily rainfall
estimates in complex terrain of Bali Island, Indonesia, Theor. Appl.
Climatol., 134, 513–532, https://doi.org/10.1007/s00704-017-2290-7, 2018.
Reder, A. and Rianna, G.: Exploring ERA5 reanalysis potentialities for
supporting landslide investigations: a test case from Campania Region
(Southern Italy), Landslides, 1909–1924, https://doi.org/10.1007/s10346-020-01610-4, 2021.
Renard, K. G. and Freimund, J. R.: Using monthly precipitation data to
estimate the R-factor in the revised USLE, J. Hydrol., 157, 287–306,
https://doi.org/10.1016/0022-1694(94)90110-4, 1994.
Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., and Yoder, D.
C.: Predicting Soil Erosion byWater: A Guide to Conservation Planning with
the Revised Universal Soil Loss Equation (RUSLE) (Agricultural Handbook
703), US Department of Agriculture, ISBN 0-16-048938-5, 1997.
Rodrigues da Silva, V. D. P., Belo Filho, A. F., Rodrigues Almeida, R. S.,
de Holanda, R. M., and da Cunha Campos, J. H. B.: Shannon information entropy
for assessing space-time variability of rainfall and streamflow in semiarid
region, Sci. Total Environ., 544, 330–338,
https://doi.org/10.1016/j.scitotenv.2015.11.082, 2016.
SAGA GIS: http://www.saga-gis.org/ (last access: 10 January 2022), 2021.
Sanchez-Moreno, J. F., Mannaerts, C. M., and Jetten, V.: Rainfall erosivity
mapping for Santiago Island, Cape Verde, Geoderma, 217–218, 74–82,
https://doi.org/10.1016/j.geoderma.2013.10.026, 2014.
Seo, B.-C., Krajewski, W. F., Quintero, F., ElSaadani, M., Goska, R., Cunha,
L. K., Dolan, B., Wolff, D. B., Smith, J. A., Rutledge, S. A., Rutledge, S.
A., and Petersen, W. A.: Comprehensive evaluation of the IFloodS Radar
rainfall products for hydrologic applications, J. Hydrometeorol., 19,
1793–1813, https://doi.org/10.1175/JHM-D-18-0080.1, 2018.
Skok, G., Žagar, N., Honzak, L., Žabkar, R., Rakovec, J., and Ceglar,
A.: Precipitation intercomparison of a set of satellite- and
raingauge-derived datasets, ERA Interim reanalysis, and a single WRF
regional climate simulation over Europe and the North Atlantic, Theor. Appl.
Climatol., 123, 217–232, https://doi.org/10.1007/s00704-014-1350-5, 2016.
Stampoulis, D. and Anagnostou, E.: Evaluation of global satellite rainfall
products over Continental Europe, J. Hydrometeorol., 13, 588–603,
https://doi.org/10.1175/JHM-D-11-086.1, 2012.
Stampoulis, D., Anagnostou, E. N., and Nikolopoulos, E. I.: Assessment of
high-resolution satellite-based rainfall estimates over the mediterranean
during heavy precipitation events, J. Hydrometeorol., 14, 1500–1514,
https://doi.org/10.1175/JHM-D-12-0167.1, 2013.
Sun, R., Yuan, H., and Yang, Y.: Using multiple satellite-gauge merged
precipitation products ensemble for hydrologic uncertainty analysis over the
Huaihe River basin, J. Hydrol., 566, 406–420,
https://doi.org/10.1016/j.jhydrol.2018.09.024, 2018.
Sunilkumar, K., Narayana Rao, T., Saikranthi, K., and Purnachandra Rao, M.:
Comprehensive evaluation of multisatellite precipitation estimates over
India using gridded rainfall data, J. Geophys. Res., 120, 8987–9005,
https://doi.org/10.1002/2015JD023437, 2015.
Sutanto, S. J., Vitolo, C., Di Napoli, C., D'Andrea, M., and Van Lanen, H. A.
J.: Heatwaves, droughts, and fires: Exploring compound and cascading dry
hazards at the pan-European scale, Environ. Int., 134, 105276, https://doi.org/10.1016/j.envint.2019.105276, 2020.
Tang, G., Clark, M. P., Papalexiou, S. M., Ma, Z., and Hong, Y.: Have
satellite precipitation products improved over last two decades? A
comprehensive comparison of GPM IMERG with nine satellite and reanalysis
datasets, Remote Sens. Environ., 240, 111697, https://doi.org/10.1016/j.rse.2020.111697, 2020.
Teng, H., Ma, Z., Chappell, A., Shi, Z., Liang, Z., and Yu, W.: Improving
rainfall erosivity estimates using merged TRMM and gauge data, Remote Sens.,
9, 1134, https://doi.org/10.3390/rs9111134, 2017.
Tian, Y., Peters-Lidard, C. D., Eylander, J. B., Joyce, R. J., Huffman, G.
J., Adler, R. F., Hsu, K., Turk, F. J., Garcia, M., and Zeng, J.: Component
analysis of errors in satellite-based precipitation estimates, J. Geophys.
Res.-Atmos., 114, D24101, https://doi.org/10.1029/2009JD011949, 2009.
Verstraeten, G., Poesen, J., Demarée, G., and Salles, C.: Long-term (105
years) variability in rain erosivity as derived from 10 min rainfall depth
data for Ukkel (Brussels, Belgium): Implications for assessing soil erosion
rates, J. Geophys. Res.-Atmos., 111, D22109, https://doi.org/10.1029/2006JD007169, 2006.
Wang, M., Yin, S., Yue, T., Yu, B., and Wang, W.: Rainfall erosivity estimation using gridded daily precipitation datasets, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2020-633, 2020.
Wei, G., Lü, H., Crow, W. T., Zhu, Y., Wang, J., and Su, J.:
Comprehensive evaluation of GPM-IMERG, CMORPH, and TMPA precipitation
products with gauged rainfall over mainland China, Adv. Meteorol., 2018, 3024190, https://doi.org/10.1155/2018/3024190, 2018.
Xie, P., Joyce, R., Wu, S., Yoo, S.-H., Yarosh, Y., Sun, F., and Lin, R.:
Reprocessed, bias-corrected CMORPH global high-resolution precipitation
estimates from 1998, J. Hydrometeorol., 18, 1617–1641,
https://doi.org/10.1175/JHM-D-16-0168.1, 2017.
Xie, P., Joyce, R., Yoo, S., Yarosh, S. H., Sun, Y., and Lin, F.: NOAA
Climate Data Record (CDR) of CPC Morphing Technique (CMORPH) High Resolution
Global Precipitation Estimates, Version 1, https://doi.org/10.25921/w9va-q159, 2021.
Yin, S., Nearing, M. A., Borrelli, P., and Xue, X.: Rainfall erosivity: An
overview of methodologies and applications, Vadose Zone J., 16, 1–16, https://doi.org/10.2136/vzj2017.06.0131, 2017.
Yu, B. and Rosewell, C. J.: Rainfall erosivity estimation using daily
rainfall amounts for South Australia, Aust. J. Soil Res., 34, 721–733,
https://doi.org/10.1071/SR9960721, 1996.
Short summary
Rainfall erosivity is one of the main factors in soil erosion. A satellite-based global map of rainfall erosivity was constructed using data with a 30 min time interval. It was shown that the satellite-based precipitation products are an interesting option for estimating rainfall erosivity, especially in regions with limited ground data. However, ground-based high-frequency precipitation measurements are (still) essential for accurate estimates of rainfall erosivity.
Rainfall erosivity is one of the main factors in soil erosion. A satellite-based global map of...
