Articles | Volume 26, issue 24
https://doi.org/10.5194/hess-26-6339-2022
© 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-26-6339-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Dec 2022
Research article |
| 16 Dec 2022
| 16 Dec 2022
River flooding mechanisms and their changes in Europe revealed by explainable machine learning
Department of Computational Hydrosystems, Helmholtz Centre for
Environmental Research, 04318 Leipzig, Germany
Emanuele Bevacqua
Department of Computational Hydrosystems, Helmholtz Centre for
Environmental Research, 04318 Leipzig, Germany
Jakob Zscheischler
Department of Computational Hydrosystems, Helmholtz Centre for
Environmental Research, 04318 Leipzig, Germany
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Lily-belle Sweet, Christoph Müller, Jonas Jägermeyr, and Jakob Zscheischler
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Lou Brett, Christopher J. White, Daniela I. V. Domeisen, Bart van den Hurk, Philip Ward, and Jakob Zscheischler
Nat. Hazards Earth Syst. Sci., 25, 2591–2611, https://doi.org/10.5194/nhess-25-2591-2025, https://doi.org/10.5194/nhess-25-2591-2025, 2025
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Compound events, where multiple weather or climate hazards occur together, pose significant risks to both society and the environment. These events, like simultaneous wind and rain, can have more severe impacts than single hazards. Our review of compound event research from 2012–2022 reveals a rise in studies, especially on events that occur concurrently, hot and dry events, and compounding flooding. The review also highlights opportunities for research in the coming years.
Bastien François, Khalil Teber, Lou Brett, Richard Leeding, Luis Gimeno-Sotelo, Daniela I. V. Domeisen, Laura Suarez-Gutierrez, and Emanuele Bevacqua
Earth Syst. Dynam., 16, 1029–1051, https://doi.org/10.5194/esd-16-1029-2025, https://doi.org/10.5194/esd-16-1029-2025, 2025
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Spatially compounding wind and precipitation (CWP) extremes can lead to severe impacts on society. We find that concurrent climate variability modes favor the occurrence of such wintertime spatially compounding events in the Northern Hemisphere and can even amplify the number of regions and population exposed. Our analysis highlights the importance of considering the interplay between variability modes to improve risk management of such spatially compounding events.
Daniel Klotz, Peter Miersch, Thiago V. M. do Nascimento, Fabrizio Fenicia, Martin Gauch, and Jakob Zscheischler
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-450, https://doi.org/10.5194/essd-2024-450, 2025
Revised manuscript under review for ESSD
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Data availability is central to hydrological science. It is the basis for advancing our understanding of hydrological processes, building prediction models, and anticipatory water management. We present a data-driven daily runoff reconstruction product for natural streamflow. We name it EARLS: European aggregated reconstruction for large-sample studies. The reconstructions represent daily simulations of natural streamflow across Europe and cover the period from 1953 to 2020.
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.
Daniel Klotz, Martin Gauch, Frederik Kratzert, Grey Nearing, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3665–3673, https://doi.org/10.5194/hess-28-3665-2024, https://doi.org/10.5194/hess-28-3665-2024, 2024
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The evaluation of model performance is essential for hydrological modeling. Using performance criteria requires a deep understanding of their properties. We focus on a counterintuitive aspect of the Nash–Sutcliffe efficiency (NSE) and show that if we divide the data into multiple parts, the overall performance can be higher than all the evaluations of the subsets. Although this follows from the definition of the NSE, the resulting behavior can have unintended consequences in practice.
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024, https://doi.org/10.5194/nhess-24-2689-2024, 2024
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Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
Derrick Muheki, Axel A. J. Deijns, Emanuele Bevacqua, Gabriele Messori, Jakob Zscheischler, and Wim Thiery
Earth Syst. Dynam., 15, 429–466, https://doi.org/10.5194/esd-15-429-2024, https://doi.org/10.5194/esd-15-429-2024, 2024
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Colin Manning, Martin Widmann, Douglas Maraun, Anne F. Van Loon, and Emanuele Bevacqua
Weather Clim. Dynam., 4, 309–329, https://doi.org/10.5194/wcd-4-309-2023, https://doi.org/10.5194/wcd-4-309-2023, 2023
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Climate models differ in their representation of dry spells and high temperatures, linked to errors in the simulation of persistent large-scale anticyclones. Models that simulate more persistent anticyclones simulate longer and hotter dry spells, and vice versa. This information is important to consider when assessing the likelihood of such events in current and future climate simulations so that we can assess the plausibility of their future projections.
Natacha Le Grix, Jakob Zscheischler, Keith B. Rodgers, Ryohei Yamaguchi, and Thomas L. Frölicher
Biogeosciences, 19, 5807–5835, https://doi.org/10.5194/bg-19-5807-2022, https://doi.org/10.5194/bg-19-5807-2022, 2022
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Compound events threaten marine ecosystems. Here, we investigate the potentially harmful combination of marine heatwaves with low phytoplankton productivity. Using satellite-based observations, we show that these compound events are frequent in the low latitudes. We then investigate the drivers of these compound events using Earth system models. The models share similar drivers in the low latitudes but disagree in the high latitudes due to divergent factors limiting phytoplankton production.
Alexandre Tuel, Bettina Schaefli, Jakob Zscheischler, and Olivia Martius
Hydrol. Earth Syst. Sci., 26, 2649–2669, https://doi.org/10.5194/hess-26-2649-2022, https://doi.org/10.5194/hess-26-2649-2022, 2022
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Elisabeth Tschumi, Sebastian Lienert, Karin van der Wiel, Fortunat Joos, and Jakob Zscheischler
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Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele
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Jun Li, Zhaoli Wang, Xushu Wu, Jakob Zscheischler, Shenglian Guo, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 1587–1601, https://doi.org/10.5194/hess-25-1587-2021, https://doi.org/10.5194/hess-25-1587-2021, 2021
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We introduce a daily-scale index, termed the standardized compound drought and heat index (SCDHI), to measure the key features of compound dry-hot conditions. SCDHI can not only monitor the long-term compound dry-hot events, but can also capture such events at sub-monthly scale and reflect the related vegetation activity impacts. The index can provide a new tool to quantify sub-monthly characteristics of compound dry-hot events, which are vital for releasing early and timely warning.
Natacha Le Grix, Jakob Zscheischler, Charlotte Laufkötter, Cecile S. Rousseaux, and Thomas L. Frölicher
Biogeosciences, 18, 2119–2137, https://doi.org/10.5194/bg-18-2119-2021, https://doi.org/10.5194/bg-18-2119-2021, 2021
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Marine ecosystems could suffer severe damage from the co-occurrence of a marine heat wave with extremely low chlorophyll concentration. Here, we provide a first assessment of compound marine heat wave and
low-chlorophyll events in the global ocean from 1998 to 2018. We reveal hotspots of these compound events in the equatorial Pacific and in the Arabian Sea and show that they mostly occur in summer at high latitudes and their frequency is modulated by large-scale modes of climate variability.
Johannes Vogel, Pauline Rivoire, Cristina Deidda, Leila Rahimi, Christoph A. Sauter, Elisabeth Tschumi, Karin van der Wiel, Tianyi Zhang, and Jakob Zscheischler
Earth Syst. Dynam., 12, 151–172, https://doi.org/10.5194/esd-12-151-2021, https://doi.org/10.5194/esd-12-151-2021, 2021
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We present a statistical approach for automatically identifying multiple drivers of extreme impacts based on LASSO regression. We apply the approach to simulated crop failure in the Northern Hemisphere and identify which meteorological variables including climate extreme indices and which seasons are relevant to predict crop failure. The presented approach can help unravel compounding drivers in high-impact events and could be applied to other impacts such as wildfires or flooding.
Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16, https://doi.org/10.5194/esd-12-1-2021, https://doi.org/10.5194/esd-12-1-2021, 2021
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Compound extremes such as heavy precipitation and extreme winds can lead to large damage. To date it is unclear how well climate models represent such compound extremes. Here we present a new measure to assess differences in the dependence structure of bivariate extremes. This measure is applied to assess differences in the dependence of compound precipitation and wind extremes between three model simulations and one reanalysis dataset in a domain in central Europe.
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Short summary
Using a novel explainable machine learning approach, we investigated the contributions of precipitation, temperature, and day length to different peak discharges, thereby uncovering three primary flooding mechanisms widespread in European catchments. The results indicate that flooding mechanisms have changed in numerous catchments over the past 70 years. The study highlights the potential of artificial intelligence in revealing complex changes in extreme events related to climate change.
Using a novel explainable machine learning approach, we investigated the contributions of...
