https://nhess.copernicus.org/articles/ Combined list of the recent articles of the journal Natural Hazards and Earth System Sciences and the recent discussion forum Natural Hazards and Earth System Sciences Discussions en https://doi.org/10.5194/nhess-26-2637-2026 https://doi.org/10.5194/nhess-26-2637-2026 <b>Quantifying the current and future likelihood of the 2022 extreme wildfire weather conditions in France with anthropogenic climate change</b><br> Shengling Zhu, Renaud Barbero, François Pimont, and Benjamin Renard<br> Nat. Hazards Earth Syst. Sci., 26, 2637–2652, https://doi.org/10.5194/nhess-26-2637-2026, 2026<br> In 2022, southwestern France saw exceptional wildfires, burning an area about 14 times the regional average. Using fire records, weather data, and climate simulations with and without human influence, we show that human-caused climate change made the weather conditions linked to the 3 largest wildfires about 2 to 10 times more likely; such conditions could become roughly 10 to 100 times more probable by 2100 under moderate emissions, highlighting a growing need for prevention. Fri, 05 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2609-2026 https://doi.org/10.5194/nhess-26-2609-2026 <b>Wikimpacts 1.0: a new global climate impact database based on automated information extraction from Wikipedia</b><br> Ni Li, Wim Thiery, Shorouq Zahra, Mariana Madruga de Brito, Koffi Worou, Murathan Kurfalı, Seppe Lampe, Paul Muñoz, Clare Flynn, Camila Trigoso, Joakim Nivre, Jakob Zscheischler, and Gabriele Messori<br> Nat. Hazards Earth Syst. Sci., 26, 2609–2636, https://doi.org/10.5194/nhess-26-2609-2026, 2026<br> Climate extremes threaten society and ecosystems, making impact understanding critical. Wikimpacts 1.0 provides an automated pipeline processing Wikipedia texts with underexploited information on climate impacts, yielding comprehensive socio-economic impact data for 2726 climate events from 1034–2024. It offers broader storm-related impacts and finer spatial resolution than established databases, showcasing natural language processing's potential to advance climate impact data. Thu, 04 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2579-2026 https://doi.org/10.5194/nhess-26-2579-2026 <b>Monitoring the displacement of large alpine rock slope instabilities with L-band SAR interferometric techniques</b><br> Tazio Strozzi, Nina Jones, Federico Agliardi, Alessandro De Pedrini, Othmar Frey, Philipp Bernhard, Rafael Caduff, Christian Ambrosi, and Andrea Manconi<br> Nat. Hazards Earth Syst. Sci., 26, 2579–2607, https://doi.org/10.5194/nhess-26-2579-2026, 2026<br> The latest satellite technology with longer wavelength radar improves our ability to detect and monitor large alpine rock slope instabilities. This approach works better than current satellite systems in forested areas and on fast-moving slopes, giving experts more reliable data to understand these major hazards. Our results from three locations in Italy and Switzerland also provide important recommendations for the preparation of future satellite radar missions. Thu, 04 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2551-2026 https://doi.org/10.5194/nhess-26-2551-2026 <b>Brief communication: Vent opening at Campi Flegrei – clues from dyke propagation patterns</b><br> Jacopo Selva and Nello Mangone<br> Nat. Hazards Earth Syst. Sci., 26, 2551–2560, https://doi.org/10.5194/nhess-26-2551-2026, 2026<br> Forecasting the potential position of future eruptions is fundamental for managing volcanic hazards. Here, we develop a new approach to identify the most likely positions for future eruptions based on the propagation path of the magma that fed past eruptions. Its application to Campi Flegrei shows probability peaks at 2 and 4 km from the caldera center and in the direction of existing topographic peaks. High probability areas correlate well with caldera’s structure and recent major seismicity. Wed, 03 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2525-2026 https://doi.org/10.5194/nhess-26-2525-2026 <b>Multi-level assessment of flood risk perception and flood behaviour</b><br> Rocío Coloma, Vicente Saenger, Felipe Link, and Oscar Link<br> Nat. Hazards Earth Syst. Sci., 26, 2525–2550, https://doi.org/10.5194/nhess-26-2525-2026, 2026<br> Based on a survey of 1007 residents in four different localities of Chile exposed to river floods, this study builds and applies a framework for assessment of flood risk perception and flood behaviour at the individual, household, neighbourhood and municipality levels. Obtained results suggest that risk communication and risk management strategies should be adapted to focus on the needs of specific neighbourhoods exposed to floods. Wed, 03 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2505-2026 https://doi.org/10.5194/nhess-26-2505-2026 <b>Spatiotemporal assessment of landslide risk over large areas: a case study of the Valencian Community (1950–2021)</b><br> Isidro Cantarino Martí, Miguel Ángel Carrión Carmona, Eric Gielen, and José-Sergio Palencia-Jiménez<br> Nat. Hazards Earth Syst. Sci., 26, 2505–2523, https://doi.org/10.5194/nhess-26-2505-2026, 2026<br> This study assesses landslide risk across the Valencian Community over time using a regional-scale approach. It shows how urban expansion into unsuitable areas has increased exposure. By combining different indicators, we identify where risk is higher and how it evolves. The results support land-use planning and help decision-makers reduce potential impacts. Wed, 03 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2561-2026 https://doi.org/10.5194/nhess-26-2561-2026 <b>Capturing the complete landslide–debris-rich flood continuum for accurate inventory, susceptibility and exposure mapping – lessons from Cyclone Idai</b><br> Antoine Dille, Olivier Dewitte, Jente Broeckx, Koen Verbist, Andile Sindiso Dube, Jean Poesen, and Matthias Vanmaercke<br> Nat. Hazards Earth Syst. Sci., 26, 2561–2577, https://doi.org/10.5194/nhess-26-2561-2026, 2026<br> In mountain regions, intense rainfall can trigger thousands of landslides within hours. Yet, while most efforts focus on where landslides start, the worst impacts often occur far downstream because slope material can mix with large runoffs. Studying Cyclone Idai’s impacts in eastern Zimbabwe, we found that landslide sources explain only one-fifth of total population exposure, highlighting the need to consider the full landslide–flood continuum to better protect people and plan safer landscapes. Wed, 03 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2487-2026 https://doi.org/10.5194/nhess-26-2487-2026 <b>Morphological response of vegetated and urbanized barrier islands to Hurricane Ian</b><br> Hassan Ilyas, Ap van Dongeren, Dano Roelvink, Ellen Quataert, and Christopher Daly<br> Nat. Hazards Earth Syst. Sci., 26, 2487–2504, https://doi.org/10.5194/nhess-26-2487-2026, 2026<br> This research investigates how natural and urbanized barrier islands along Florida’s coast responded to Hurricane Ian. It shows how vegetation and the built environment influence sediment transport during extreme storms and highlights the importance of incorporating land use and land cover data into models to predict coastal response and evaluate how vegetation can enhance resilience to future climatic events. Wed, 03 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2437-2026 https://doi.org/10.5194/nhess-26-2437-2026 <b>A single framework for assessing flash flood and landslide susceptibility: an application to the Mediterranean Liguria region, Italy</b><br> Alessia Riveros, Chamidu Gunaratne, Mario Martinelli, and Frederiek Christianne Sperna Weiland<br> Nat. Hazards Earth Syst. Sci., 26, 2437–2459, https://doi.org/10.5194/nhess-26-2437-2026, 2026<br> Flash floods and landslides have caused severe economic damages and loss of life, especially in mountainous regions e.g. Liguria. We created susceptibility maps to both hazards based on past recorded events and open-data such as slopes and altitude. We found a similar high predisposition to both hazards along the coast. Outside the coastal area, river valleys and urban areas (or upper river courses) exhibited high susceptibility only to flash floods (or landslides). Mon, 01 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2461-2026 https://doi.org/10.5194/nhess-26-2461-2026 <b>Predicting the risk of individual tree fall along powerlines in Norway with a mechanistic wind risk model and machine learning</b><br> Morgane Merlin, Barry Gardiner, and Svein Solberg<br> Nat. Hazards Earth Syst. Sci., 26, 2461–2485, https://doi.org/10.5194/nhess-26-2461-2026, 2026<br> Tree falls along power lines cause safety, cost, and environmental issues. Drones can map individual trees to improve risk management. We applied the ForestGALES wind-risk model to individual trees along power lines in southern Norway. It performed moderately alone but combining it with machine learning greatly improved accuracy, offering managers precise guidance for safer vegetation management. Mon, 01 Jun 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2415-2026 https://doi.org/10.5194/nhess-26-2415-2026 <b>The TSUSY Database: a global database of historical tsunami events and a tsunami-occurrence criterion based on historical earthquakes</b><br> David Galán Pérez, Iñigo Aniel-Quiroga, Albert Gallego, Ignacio Aguirre-Ayerbe, Mauricio González, Omar Quetzalcóatl, Jose A. Álvarez-Gómez, and Luis Pedraz<br> Nat. Hazards Earth Syst. Sci., 26, 2415–2436, https://doi.org/10.5194/nhess-26-2415-2026, 2026<br> Tsunamis can have devastating consequences, yet it remains challenging to identify which earthquakes generate them. This study presents a criterion for identifying tsunamigenic events based on numerical simulations, as well as a global database of tsunami simulations based on historical earthquakes. By comparing the results with historical records, this approach can improve tsunami identification and support tsunami warnings worldwide. Fri, 29 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2387-2026 https://doi.org/10.5194/nhess-26-2387-2026 <b>Evaluating the effects of preprocessing, method selection, and hyperparameter tuning on SAR-based flood mapping and water depth estimation</b><br> Jean-Paul Travert, Cédric Goeury, Sébastien Boyaval, Vito Bacchi, and Fabrice Zaoui<br> Nat. Hazards Earth Syst. Sci., 26, 2387–2413, https://doi.org/10.5194/nhess-26-2387-2026, 2026<br> This study presents the impact of various processing methods on flood maps and water depth estimates derived from Synthetic Aperture Radar (SAR) satellite data. The results suggest that the choice of methods and parameters at each processing step has a strong influence on the outputs. This study emphasizes the importance of evaluating the entire processing pipeline to quantify the uncertainties which may hinder the capability to calibrate or validate hydrodynamic models. Wed, 27 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2367-2026 https://doi.org/10.5194/nhess-26-2367-2026 <b>Constructing physical-based rainfall landslides prediction model: insights from rainfall threshold curves database of slope units</b><br> Kai Wang, Linmao Xie, Shuailong Xie, Shaojie Zhang, Yongyang Jiang, Ji Zhang, Lin Zhu, Zhiliu Wang, and Fuzhou Qi<br> Nat. Hazards Earth Syst. Sci., 26, 2367–2385, https://doi.org/10.5194/nhess-26-2367-2026, 2026<br> This manuscript integrates physical methods, rainfall threshold warning methods, and slope units to develop a rapid forecasting model for rainfall landslides at a regional scale. The application results indicate that the model runs in less than 12 min, with missing alarm and false alarm rates of 11.8 % and 21.1 %, respectively. This study is expected to provide insights for the rapid forecasting of rainfall landslides in the impoverished mountainous regions of developing countries. Tue, 26 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2353-2026 https://doi.org/10.5194/nhess-26-2353-2026 <b>Enhancing hydrological hazard early warning: a 60 d streamflow forecasting framework integrating deep learning and process-based modeling</b><br> Zhijie Liu, Hanbo Yang, and Dawen Yang<br> Nat. Hazards Earth Syst. Sci., 26, 2353–2366, https://doi.org/10.5194/nhess-26-2353-2026, 2026<br> Reliable medium- and long-term streamflow forecasts are essential for hazard early warning. We develop a 60-day forecasting framework that corrects precipitation from numerical weather prediction models, utilizes a physical hydrologic model and mitigates systematic simulation errors. Applied to the Upper Yangtze River Basin, it yields practical 60-day forecasts with good accuracy, providing a robust tool for proactive decision making in hazard mitigation to ensure regional water security. Tue, 26 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2319-2026 https://doi.org/10.5194/nhess-26-2319-2026 <b>Culvert blockages in 2D-hydrodynamic flash flood modeling: quantifying the impact on flood dynamics and mitigation strategies</b><br> Leon Frederik De Vos, Karan Mahajan, Daniel Caviedes-Voullième, and Nils Rüther<br> Nat. Hazards Earth Syst. Sci., 26, 2319–2352, https://doi.org/10.5194/nhess-26-2319-2026, 2026<br> In this study, we assess the impact of culvert blockages on flash flood dynamics. Applying the 2D Shallow Water Equations, we model multiple flash flood and blockage scenarios within a steep catchment in central Germany. The results emphasize the need for accurate culvert representation in hydrodynamic models and demonstrate how scenario-based blockage modeling can support the identification of critical infrastructure and the development of targeted mitigation measures. Wed, 20 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2305-2026 https://doi.org/10.5194/nhess-26-2305-2026 <b>A workflow to identify and monitor slow-moving landslides through spaceborne optical feature tracking</b><br> Lorenzo Nava, Maximillian Van Wyk de Vries, and Louie Elliot Bell<br> Nat. Hazards Earth Syst. Sci., 26, 2305–2318, https://doi.org/10.5194/nhess-26-2305-2026, 2026<br> We introduce TerraTrack, an open-source tool for detecting and monitoring slow-moving landslides using Sentinel-2 data. It automates image acquisition, landslide identification, and time-series generation in an accessible and cloud-based workflow. TerraTrack supports early warning, complements interferometric synthetic aperture radar (InSAR), and offers a scalable solution for landslide hazard identification and monitoring. Tue, 19 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2291-2026 https://doi.org/10.5194/nhess-26-2291-2026 <b>Detection of atmospheric rivers affecting the western Mediterranean and producing extreme rainfall over northern-central Italy</b><br> Silvio Davolio, Isacco Sala, Alessandro Comunian, Daniele Mastrangelo, Mario Marcello Miglietta, Lucia Drago Pitura, and Federico Grazzini<br> Nat. Hazards Earth Syst. Sci., 26, 2291–2304, https://doi.org/10.5194/nhess-26-2291-2026, 2026<br> Atmospheric rivers, narrow and long corridors of intense horizontal moisture transport, may produce heavy precipitation where they are forced to rise over the orography. This has been recently shown to occur also in the Mediterranean basin, especially over the Alps and Apennines in Italy. The present study analyses the presence of atmospheric rivers in this area, in the period 1961–2024, and reveals a strong connection with extreme rainfall over northern-central Italy. Tue, 19 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2269-2026 https://doi.org/10.5194/nhess-26-2269-2026 <b>Projections of changes in extreme storm surges for European coasts using statistical downscaling</b><br> Maialen Irazoqui Apecechea, Angélique Melet, Melisa Menendez, Hector Lobeto, and Jonathan B. Valle-Rodriguez<br> Nat. Hazards Earth Syst. Sci., 26, 2269–2290, https://doi.org/10.5194/nhess-26-2269-2026, 2026<br> We applied a fast statistical model to estimate future extreme storm surges in Europe using data from 17 climate models – about twice as many as in past studies. Results show robust regional patterns – decreases in the Mediterranean and Moroccan coast, increases in the Irish Sea and Gulf of Finland – with high uncertainty in other areas. Out results increase our knowledge on future storm surge uncertainties, needed for informed coastal planning. Fri, 15 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2227-2026 https://doi.org/10.5194/nhess-26-2227-2026 <b>Seismo-acoustic and GNSS observations of a record-breaking Black Sea storm: repurposing geophysical sensors for environmental monitoring</b><br> Laura Petrescu, Bogdan Antonescu, Sorin Nistor, Iustin Floroiu, Dragoş Ene, Daniela Ghica, Constantin Ionescu, Andrei Anghel, and Mihai Datcu<br> Nat. Hazards Earth Syst. Sci., 26, 2227–2247, https://doi.org/10.5194/nhess-26-2227-2026, 2026<br> In August 2024, a powerful storm hit Romania’s Black Sea coast, breaking rainfall records. We used a mix of ground and satellite sensors to track the storm’s development and impacts. The data revealed clear signs of intense rainfall, lightning, and ground vibrations likely linked to storm activity. Our study shows that combining different types of sensors can improve how we monitor extreme storms and may help in building better early-warning systems in coastal areas. Wed, 13 May 2026 11:46:48 +0200 https://doi.org/10.5194/nhess-26-2249-2026 https://doi.org/10.5194/nhess-26-2249-2026 <b>Monitoring diffuse volcanic degassing with seismic ambient noise</b><br> Helena Seivane and Martin Schimmel<br> Nat. Hazards Earth Syst. Sci., 26, 2249–2268, https://doi.org/10.5194/nhess-26-2249-2026, 2026<br> Mantle-derived gases can seep to the surface before a volcanic eruption, but detecting them is difficult when emissions are weak. We used seismic noise from individual stations at Cumbre Vieja Volcano, La Palma, to monitor shallow gas accumulation being modulated by atmospheric cycles. We find clear links between pressure variations and gas release, with a marked increase months before the 2021 eruption, highlighting potential for early warning and hazard assessment. Wed, 13 May 2026 11:46:48 +0200