Articles | Volume 26, issue 3
https://doi.org/10.5194/nhess-26-1417-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-1417-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Mar 2026
Research article |
| 19 Mar 2026
| 19 Mar 2026
Climate and impact attribution of compound flooding induced by tropical cyclone Idai in Mozambique
Doris M. Vertegaal
CORRESPONDING AUTHOR
Deltares, Delft, the Netherlands
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Bart J. J. M. van den Hurk
Deltares, Delft, the Netherlands
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Anaïs Couasnon
Deltares, Delft, the Netherlands
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Natalia Aleksandrova
Deltares, Delft, the Netherlands
Tycho Bovenschen
Deltares, Delft, the Netherlands
Fernaldi Gradiyanto
Deltares, Delft, the Netherlands
Tim W. B. Leijnse
Deltares, Delft, the Netherlands
Henrique M. D. Goulart
Deltares, Delft, the Netherlands
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Sanne Muis
Deltares, Delft, the Netherlands
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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This study explains why the impacts of Tropical Cyclone Idai in Mozambique in 2019 were so severe. By combining hydrolgical modelling with insights from interviews, we found that land-use changes, including deforestation and unplanned urban growth, worsened flooding alongside climate change. The results show that understanding disasters requires considering local socio-economic drivers, helping reveal overlooked drivers of risk and supporting better planning to reduce future impacts.
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Giorgia Di Capua, Dim Coumou, Bart van den Hurk, Antje Weisheimer, Andrew G. Turner, and Reik V. Donner
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Dirk Eilander, Anaïs Couasnon, Frederiek C. Sperna Weiland, Willem Ligtvoet, Arno Bouwman, Hessel C. Winsemius, and Philip J. Ward
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This study presents a framework for assessing compound flood risk using hydrodynamic, impact, and statistical modeling. A pilot in Mozambique shows the importance of accounting for compound events in risk assessments. We also show how the framework can be used to assess the effectiveness of different risk reduction measures. As the framework is based on global datasets and is largely automated, it can easily be applied in other areas for first-order assessments of compound flood risk.
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Nat. Hazards Earth Syst. Sci., 23, 1921–1946, https://doi.org/10.5194/nhess-23-1921-2023, https://doi.org/10.5194/nhess-23-1921-2023, 2023
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Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, https://doi.org/10.5194/nhess-23-823-2023, 2023
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In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Mariana C. A. Clare, Tim W. B. Leijnse, Robert T. McCall, Ferdinand L. M. Diermanse, Colin J. Cotter, and Matthew D. Piggott
Nat. Hazards Earth Syst. Sci., 22, 2491–2515, https://doi.org/10.5194/nhess-22-2491-2022, https://doi.org/10.5194/nhess-22-2491-2022, 2022
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Assessing uncertainty is computationally expensive because it requires multiple runs of expensive models. We take the novel approach of assessing uncertainty from coastal flooding using a multilevel multifidelity (MLMF) method which combines the efficiency of less accurate models with the accuracy of more expensive models at different resolutions. This significantly reduces the computational cost but maintains accuracy, making previously unfeasible real-world studies possible.
Tim Willem Bart Leijnse, Alessio Giardino, Kees Nederhoff, and Sofia Caires
Nat. Hazards Earth Syst. Sci., 22, 1863–1891, https://doi.org/10.5194/nhess-22-1863-2022, https://doi.org/10.5194/nhess-22-1863-2022, 2022
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Deriving reliable estimates of design conditions resulting from tropical cyclones is a challenge of high relevance to coastal engineering. Here, having few historical observations is overcome by using the Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE) to create thousands of synthetic realizations, representative of 1000 years of tropical cyclone activity for the Bay of Bengal. The use of synthetic tracks is shown to provide more reliable wind speed, storm surge and wave estimates.
Ruud T. W. L. Hurkmans, Bart van den Hurk, Maurice J. Schmeits, Fredrik Wetterhall, and Ilias G. Pechlivanidis
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-604, https://doi.org/10.5194/hess-2021-604, 2022
Manuscript not accepted for further review
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Seasonal forecasts can help in safely and efficiently managing a fresh water reservoir in the Netherlands. We compare hydrological forecast systems of the river Rhine, the lakes most important source and analyze forecast skill for over 1993–2016 and for specific extreme years. On average, forecast skill is high in spring due to Alpine snow and smaller in summer. Dry summers appear to be more predictable, skill increases with event extremity. In those cases, seasonal forecasts are valuable tools.
Martin Wegmann, Yvan Orsolini, Antje Weisheimer, Bart van den Hurk, and Gerrit Lohmann
Weather Clim. Dynam., 2, 1245–1261, https://doi.org/10.5194/wcd-2-1245-2021, https://doi.org/10.5194/wcd-2-1245-2021, 2021
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Northern Hemisphere winter weather is influenced by the strength of westerly winds 30 km above the surface, the so-called polar vortex. Eurasian autumn snow cover is thought to modulate the polar vortex. So far, however, the modeled influence of snow on the polar vortex did not fit the observed influence. By analyzing a model experiment for the time span of 110 years, we could show that the causality of this impact is indeed sound and snow cover can weaken the polar vortex.
Henrique M. D. Goulart, Karin van der Wiel, Christian Folberth, Juraj Balkovic, and Bart van den Hurk
Earth Syst. Dynam., 12, 1503–1527, https://doi.org/10.5194/esd-12-1503-2021, https://doi.org/10.5194/esd-12-1503-2021, 2021
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Agriculture is sensitive to weather conditions and to climate change. We identify the weather conditions linked to soybean failures and explore changes related to climate change. Additionally, we build future versions of a historical extreme season under future climate scenarios. Results show that soybean failures are likely to increase with climate change. Future events with similar physical conditions to the extreme season are not expected to increase, but events with similar impacts are.
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Short summary
This study highlights the need to disentangle climate change effects on flood drivers using storyline attribution. Whether information is presented as change in one or multiple drivers, or as change in hazard or impact, determines the attribution statement. For compound flooding from tropical cyclone Idai, that hit Mozambique in 2019, we attribute 1–19 % of the flood hazard and 8–35 % of the damage to climate change. The attribution framework can be applied to other events worldwide.
This study highlights the need to disentangle climate change effects on flood drivers using...
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