Articles | Volume 16, issue 6
https://doi.org/10.5194/esd-16-2295-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-16-2295-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
22 Dec 2025
Research article | Highlight paper |
| 22 Dec 2025
| 22 Dec 2025
Bridging science and practice on multi-hazard risk drivers: stakeholder insights from five pilot studies in Europe
Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Marleen de Ruiter
Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Wiebke Jäger
Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Veronica Casartelli
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Venice, Italy
Roxana Ciurean
British Geological Survey, Keyworth NG12 5GG, United Kingdom
Noemi Padrón-Fumero
Universidad de La Laguna, La Laguna, Spain
Anne Sophie Daloz
Center for International Climate Research, Oslo, Norway
David Geurts
Deltares, Delft, the Netherlands
Stefania Gottardo
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Venice, Italy
Stefan Hochrainer-Stigler
IIASA – International Institute for Applied Systems Analysis, Laxenburg, Austria
Abel López Diez
Universidad de La Laguna, La Laguna, Spain
Jaime Díaz Pacheco
Universidad de La Laguna, La Laguna, Spain
Pedro Dorta Antequera
Universidad de La Laguna, La Laguna, Spain
Tamara Febles Arévalo
Universidad de La Laguna, La Laguna, Spain
Sara García González
Universidad de La Laguna, La Laguna, Spain
Raúl Hernández-Martín
Universidad de La Laguna, La Laguna, Spain
Carmen Alvarez-Albelo
Universidad de La Laguna, La Laguna, Spain
Juan José Diaz-Hernandez
Universidad de La Laguna, La Laguna, Spain
Center for International Climate Research, Oslo, Norway
Letizia Monteleone
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Venice, Italy
Karina Reiter
IIASA – International Institute for Applied Systems Analysis, Laxenburg, Austria
Tristian Stolte
Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Robert Šakić Trogrlić
IIASA – International Institute for Applied Systems Analysis, Laxenburg, Austria
Silvia Torresan
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Venice, Italy
Sharon Tatman
Deltares, Delft, the Netherlands
David Romero Manrique de Lara
Universidad de La Laguna, La Laguna, Spain
Yeray Hernández González
Universidad de La Laguna, La Laguna, Spain
Philip J. Ward
Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Deltares, Delft, the Netherlands
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Nicole van Maanen, Joël J.-F. G. De Plaen, Timothy Tiggeloven, Maria Luisa Colmenares, Philip J. Ward, Paolo Scussolini, and Elco Koks
Nat. Hazards Earth Syst. Sci., 25, 2075–2080, https://doi.org/10.5194/nhess-25-2075-2025, https://doi.org/10.5194/nhess-25-2075-2025, 2025
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Sophie Kaashoek, Žiga Malek, Nadia Bloemendaal, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 25, 1963–1974, https://doi.org/10.5194/nhess-25-1963-2025, https://doi.org/10.5194/nhess-25-1963-2025, 2025
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Ekta Aggarwal, Marleen C. de Ruiter, Kartikeya S. Sangwan, Rajiv Sinha, Sophie Buijs, Ranjay Shrestha, Sanjeev Gupta, and Alexander C. Whittaker
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Nivedita Sairam and Marleen de Ruiter
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Davide Mauro Ferrario, Marcello Sanò, Margherita Maraschini, Andrea Critto, and Silvia Torresan
EGUsphere, https://doi.org/10.5194/egusphere-2025-670, https://doi.org/10.5194/egusphere-2025-670, 2025
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This review explores how Machine Learning (ML) can advance multi-hazard and multi-risk going through four main themes: data processing, hazard prediction, risk assessment, and future climate scenarios. It shows how ML is widely used for Earth observations and climate data processing, with Deep Learning applied for hazard prediction and ensemble ML methods for risks, and how future research moving towards analysis of multi-hazard interactions, dynamic vulnerability and early warning systems.
Joshua Green, Ivan D. Haigh, Niall Quinn, Jeff Neal, Thomas Wahl, Melissa Wood, Dirk Eilander, Marleen de Ruiter, Philip Ward, and Paula Camus
Nat. Hazards Earth Syst. Sci., 25, 747–816, https://doi.org/10.5194/nhess-25-747-2025, https://doi.org/10.5194/nhess-25-747-2025, 2025
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Compound flooding, involving the combination or successive occurrence of two or more flood drivers, can amplify flood impacts in coastal/estuarine regions. This paper reviews the practices, trends, methodologies, applications, and findings of coastal compound flooding literature at regional to global scales. We explore the types of compound flood events, their mechanistic processes, and the range of terminology. Lastly, this review highlights knowledge gaps and implications for future practices.
Franziska Hellmuth, Tim Carlsen, Anne Sophie Daloz, Robert Oscar David, Haochi Che, and Trude Storelvmo
Atmos. Chem. Phys., 25, 1353–1383, https://doi.org/10.5194/acp-25-1353-2025, https://doi.org/10.5194/acp-25-1353-2025, 2025
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Harriet E. Thompson, Joel C. Gill, Robert Šakić Trogrlić, Faith E. Taylor, and Bruce D. Malamud
Nat. Hazards Earth Syst. Sci., 25, 353–381, https://doi.org/10.5194/nhess-25-353-2025, https://doi.org/10.5194/nhess-25-353-2025, 2025
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We present a methodology to compile single hazards and multi-hazard interrelationships in data-scarce urban settings, which we apply to the Kathmandu Valley, Nepal. Using blended sources, we collate evidence of 21 single natural hazard types and 83 multi-hazard interrelationships that could impact the Kathmandu Valley. We supplement these exemplars with multi-hazard scenarios developed by practitioner stakeholders, emphasising the need for inclusive disaster preparedness and response approaches.
Sadhana Nirandjan, Elco E. Koks, Mengqi Ye, Raghav Pant, Kees C. H. Van Ginkel, Jeroen C. J. H. Aerts, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 24, 4341–4368, https://doi.org/10.5194/nhess-24-4341-2024, https://doi.org/10.5194/nhess-24-4341-2024, 2024
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Critical infrastructures (CIs) are exposed to natural hazards, which may result in significant damage and burden society. Vulnerability is a key determinant for reducing these risks, yet crucial information is scattered in the literature. Our study reviews over 1510 fragility and vulnerability curves for CI assets, creating a unique publicly available physical vulnerability database that can be directly used for hazard risk assessments, including floods, earthquakes, windstorms, and landslides.
Benjamin Poschlod and Anne Sophie Daloz
The Cryosphere, 18, 1959–1981, https://doi.org/10.5194/tc-18-1959-2024, https://doi.org/10.5194/tc-18-1959-2024, 2024
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Information about snow depth is important within climate research but also many other sectors, such as tourism, mobility, civil engineering, and ecology. Climate models often feature a spatial resolution which is too coarse to investigate snow depth. Here, we analyse high-resolution simulations and identify added value compared to a coarser-resolution state-of-the-art product. Also, daily snow depth extremes are well reproduced by two models.
Eric Mortensen, Timothy Tiggeloven, Toon Haer, Bas van Bemmel, Dewi Le Bars, Sanne Muis, Dirk Eilander, Frederiek Sperna Weiland, Arno Bouwman, Willem Ligtvoet, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 24, 1381–1400, https://doi.org/10.5194/nhess-24-1381-2024, https://doi.org/10.5194/nhess-24-1381-2024, 2024
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Current levels of coastal flood risk are projected to increase in coming decades due to various reasons, e.g. sea-level rise, land subsidence, and coastal urbanization: action is needed to minimize this future risk. We evaluate dykes and coastal levees, foreshore vegetation, zoning restrictions, and dry-proofing on a global scale to estimate what levels of risk reductions are possible. We demonstrate that there are several potential adaptation pathways forward for certain areas of the world.
Georg C. Pflug, Viktoria Kittler, and Stefan Hochrainer-Stigler
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-194, https://doi.org/10.5194/nhess-2023-194, 2024
Preprint withdrawn
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Multi-hazard events can be devastating and there are indications that in such situations the exposed risk-bearers are affected more severely compared to single-hazard events. We present some statistical modeling approaches to determine possible interrelationships of hazards and tested them for the specific case of the countries within the Danube Region. We especially focused on the question whether certain hazards are more likely to occur due to preceding hazardous events.
Clemens Schwingshackl, Anne Sophie Daloz, Carley Iles, Kristin Aunan, and Jana Sillmann
Nat. Hazards Earth Syst. Sci., 24, 331–354, https://doi.org/10.5194/nhess-24-331-2024, https://doi.org/10.5194/nhess-24-331-2024, 2024
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Ambient heat in European cities will substantially increase under global warming, as projected by three heat metrics calculated from high-resolution climate model simulations. While the heat metrics consistently project high levels of ambient heat for several cities, in other cities the projected heat levels vary considerably across the three heat metrics. Using complementary heat metrics for projections of ambient heat is thus important for assessments of future risks from heat stress.
Dirk Eilander, Anaïs Couasnon, Frederiek C. Sperna Weiland, Willem Ligtvoet, Arno Bouwman, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 2251–2272, https://doi.org/10.5194/nhess-23-2251-2023, https://doi.org/10.5194/nhess-23-2251-2023, 2023
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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.
Job C. M. Dullaart, Sanne Muis, Hans de Moel, Philip J. Ward, Dirk Eilander, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 23, 1847–1862, https://doi.org/10.5194/nhess-23-1847-2023, https://doi.org/10.5194/nhess-23-1847-2023, 2023
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Coastal flooding is driven by storm surges and high tides and can be devastating. To gain an understanding of the threat posed by coastal flooding and to identify areas that are especially at risk, now and in the future, it is crucial to accurately model coastal inundation and assess the coastal flood hazard. Here, we present a global dataset with hydrographs that represent the typical evolution of an extreme sea level. These can be used to model coastal inundation more accurately.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
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.
Paolo Scussolini, Job Dullaart, Sanne Muis, Alessio Rovere, Pepijn Bakker, Dim Coumou, Hans Renssen, Philip J. Ward, and Jeroen C. J. H. Aerts
Clim. Past, 19, 141–157, https://doi.org/10.5194/cp-19-141-2023, https://doi.org/10.5194/cp-19-141-2023, 2023
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We reconstruct sea level extremes due to storm surges in a past warmer climate. We employ a novel combination of paleoclimate modeling and global ocean hydrodynamic modeling. We find that during the Last Interglacial, about 127 000 years ago, seasonal sea level extremes were indeed significantly different – higher or lower – on long stretches of the global coast. These changes are associated with different patterns of atmospheric storminess linked with meridional shifts in wind bands.
Robert Šakić Trogrlić, Amy Donovan, and Bruce D. Malamud
Nat. Hazards Earth Syst. Sci., 22, 2771–2790, https://doi.org/10.5194/nhess-22-2771-2022, https://doi.org/10.5194/nhess-22-2771-2022, 2022
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Here we present survey responses of 350 natural hazard community members to key challenges in natural hazards research and step changes to achieve the Sustainable Development Goals. Challenges identified range from technical (e.g. model development, early warning) to governance (e.g. co-production with community members). Step changes needed are equally broad; however, the majority of answers showed a need for wider stakeholder engagement, increased risk management and interdisciplinary work.
Anne Sophie Daloz, Clemens Schwingshackl, Priscilla Mooney, Susanna Strada, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Michal Belda, Tomas Halenka, Marcus Breil, Rita M. Cardoso, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 2403–2419, https://doi.org/10.5194/tc-16-2403-2022, https://doi.org/10.5194/tc-16-2403-2022, 2022
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Snow plays a major role in the regulation of the Earth's surface temperature. Together with climate change, rising temperatures are already altering snow in many ways. In this context, it is crucial to better understand the ability of climate models to represent snow and snow processes. This work focuses on Europe and shows that the melting season in spring still represents a challenge for climate models and that more work is needed to accurately simulate snow–atmosphere interactions.
Weihua Zhu, Kai Liu, Ming Wang, Philip J. Ward, and Elco E. Koks
Nat. Hazards Earth Syst. Sci., 22, 1519–1540, https://doi.org/10.5194/nhess-22-1519-2022, https://doi.org/10.5194/nhess-22-1519-2022, 2022
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We present a simulation framework to analyse the system vulnerability and risk of the Chinese railway system to floods. To do so, we develop a method for generating flood events at both the national and river basin scale. Results show flood system vulnerability and risk of the railway system are spatially heterogeneous. The event-based approach shows how we can identify critical hotspots, taking the first steps in developing climate-resilient infrastructure.
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
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The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Priscilla A. Mooney, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Natalie de Noblet-Ducoudré, Marcus Breil, Rita M. Cardoso, Anne Sophie Daloz, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 1383–1397, https://doi.org/10.5194/tc-16-1383-2022, https://doi.org/10.5194/tc-16-1383-2022, 2022
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We use multiple regional climate models to show that afforestation in sub-polar and alpine regions reduces the radiative impact of snow albedo on the atmosphere, reduces snow cover, and delays the start of the snowmelt season. This is important for local communities that are highly reliant on snowpack for water resources and winter tourism. However, models disagree on the amount of change particularly when snow is melting. This shows that more research is needed on snow–vegetation interactions.
Stefano Terzi, Janez Sušnik, Stefan Schneiderbauer, Silvia Torresan, and Andrea Critto
Nat. Hazards Earth Syst. Sci., 21, 3519–3537, https://doi.org/10.5194/nhess-21-3519-2021, https://doi.org/10.5194/nhess-21-3519-2021, 2021
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This study combines outputs from multiple models with statistical assessments of past and future water availability and demand for the Santa Giustina reservoir (Autonomous Province of Trento, Italy). Considering future climate change scenarios, results show high reductions for stored volume and turbined water, with increasing frequency, duration and severity. These results call for the need to adapt to reductions in water availability and effects on the Santa Giustina reservoir management.
Lucas Wouters, Anaïs Couasnon, Marleen C. de Ruiter, Marc J. C. van den Homberg, Aklilu Teklesadik, and Hans de Moel
Nat. Hazards Earth Syst. Sci., 21, 3199–3218, https://doi.org/10.5194/nhess-21-3199-2021, https://doi.org/10.5194/nhess-21-3199-2021, 2021
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This research introduces a novel approach to estimate flood damage in Malawi by applying a machine learning model to UAV imagery. We think that the development of such a model is an essential step to enable the swift allocation of resources for recovery by humanitarian decision-makers. By comparing this method (EUR 10 140) to a conventional land-use-based approach (EUR 15 782) for a specific flood event, recommendations are made for future assessments.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, https://doi.org/10.5194/hess-25-5287-2021, 2021
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Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
Marleen Carolijn de Ruiter, Anaïs Couasnon, and Philip James Ward
Geosci. Commun., 4, 383–397, https://doi.org/10.5194/gc-4-383-2021, https://doi.org/10.5194/gc-4-383-2021, 2021
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Many countries can get hit by different hazards, such as earthquakes and floods. Generally, measures and policies are aimed at decreasing the potential damages of one particular hazard type despite their potential of having unwanted effects on other hazard types. We designed a serious game that helps professionals to improve their understanding of these potential negative effects of measures and policies that reduce the impacts of disasters across many different hazard types.
Claudia Canedo-Rosso, Stefan Hochrainer-Stigler, Georg Pflug, Bruno Condori, and Ronny Berndtsson
Nat. Hazards Earth Syst. Sci., 21, 995–1010, https://doi.org/10.5194/nhess-21-995-2021, https://doi.org/10.5194/nhess-21-995-2021, 2021
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Drought is a major natural hazard that causes large losses for farmers. This study evaluated drought severity based on a drought classification scheme using NDVI and LST, which was related to the ENSO anomalies. In addition, the spatial distribution of NDVI was associated with precipitation and air temperature at the local level. Our findings show that drought severity increases during El Niño years, and as a consequence the socio-economic drought risk of farmers will likely increase.
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This paper offers the first cross-regional synthesis of stakeholder perspectives on multi-hazard risk drivers across Europe, providing empirically grounded insights into how hazard interactions, vulnerability dynamics and disaster risk reduction measures evolve over time. By integrating qualitative methods with multi-risk governance analysis, it promotes context-sensitive and actionable disaster risk knowledge. Its findings are highly relevant to the geosciences community working on risk modeling and hazard interactions and are also of great interest for practitioners, policymakers and media focusing on disaster risk governance, climate adaptation, and societal resilience.
This paper offers the first cross-regional synthesis of stakeholder perspectives on multi-hazard...
Short summary
Disaster risk management faces growing challenges from multiple, changing hazards. Interviews with stakeholders in five European regions reveal that climate change, urban growth, and socio-economic shifts increase vulnerability and exposure. Measures to reduce one risk can worsen others, highlighting the need for better coordination. The study calls for flexible, context-specific strategies that connect scientific risk assessments with real-world decision-making.
Disaster risk management faces growing challenges from multiple, changing hazards. Interviews...
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