Natural Hazards and Earth System Sciences

Review article: Insuring the green economy against natural hazards – charting research frontiers in vulnerability assessment
Harikesan Baskaran, Ioanna Ioannou, Tiziana Rossetto, Jonas Cels, Mathis Joffrain, Nicolas Mortegoutte, Aurelie Fallon Saint-Lo, and Catalina Spataru
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-82,2024
Preprint under review for NHESS (discussion: open, 0 comments)
There is a global need for insuring green economy assets against natural hazard events. But their complexity and low exposure history, means the data required for vulnerability evaluation by the insurance industry is scarce. A systematic literature review is conducted in this study, to determine the suitability of current, published literature for this purpose. Knowledge gaps are charted, and a representative asset-hazard taxonomy is proposed, to guide future, quantitative research.

Multisectoral analysis of drought impacts and management responses to the 2008–2015 record drought in the Colorado Basin, Texas
Stephen B. Ferencz, Ning Sun, Sean W. D. Turner, Brian A. Smith, and Jennie S. Rice
Nat. Hazards Earth Syst. Sci., 24, 1871–1896, https://doi.org/10.5194/nhess-24-1871-2024, 2024
Drought has long posed an existential threat to society. Population growth, economic development, and the potential for more extreme and prolonged droughts due to climate change pose significant water security challenges. Better understanding the impacts and adaptive responses resulting from extreme drought can aid adaptive planning. The 2008–2015 record drought in the Colorado Basin, Texas, United States, is used as a case study to assess impacts and responses to severe drought.

Automating tephra fall building damage assessment using deep learning
Eleanor Tennant, Susanna F. Jenkins, Victoria Miller, Richard Robertson, Bihan Wen, Sang-Ho Yun, and Benoit Taisne
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-81,2024
Preprint under review for NHESS (discussion: open, 0 comments)
After a volcanic eruption, assessing building damage quickly is vital for response and recovery. Traditional post-event damage assessment methods such as ground surveys, are often time-consuming and resource-intensive, hindering rapid response and recovery efforts. To overcome this, we have developed an automated approach that uses UAV acquired optical images and deep learning to rapidly generate spatial building damage information.

A methodology to compile multi-hazard interrelationships in a data-scarce setting: an application to Kathmandu Valley, Nepal
Harriet E. Thompson, Joel C. Gill, Robert Šakić Trogrlić, Faith E. Taylor, and Bruce D. Malamud
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-101,2024
Preprint under review for NHESS (discussion: open, 0 comments)
We describe a methodology to systematically gather evidence of the breadth of single natural hazards and their multi-hazard interrelationships in data-scarce urban settings. We apply this methodology to Kathmandu Valley, Nepal, where we find evidence of 21 single hazard types, and 83 multi-hazard interrelationships. This evidence is supplemented with multi-hazard scenarios developed by practitioner stakeholders engaged in disaster risk reduction research and practice in Kathmandu Valley.

Insights into the development of a landslide early warning system prototype in an informal settlement: the case of Bello Oriente in Medellín, Colombia
Christian Werthmann, Marta Sapena, Marlene Kühnl, John Singer, Carolina Garcia, Tamara Breuninger, Moritz Gamperl, Bettina Menschik, Heike Schäfer, Sebastian Schröck, Lisa Seiler, Kurosch Thuro, and Hannes Taubenböck
Nat. Hazards Earth Syst. Sci., 24, 1843–1870, https://doi.org/10.5194/nhess-24-1843-2024, 2024
Early warning systems (EWSs) promise to decrease the vulnerability of self-constructed (informal) settlements. A living lab developed a partially functional prototype of an EWS for landslides in a Medellín neighborhood. The first findings indicate that technical aspects can be manageable, unlike social and political dynamics. A resilient EWS for informal settlements has to achieve sufficient social and technical redundancy to maintain basic functionality in a reduced-support scenario.

Simulating sea level extremes from synthetic low-pressure systems
Jani Särkkä, Jani Räihä, Mika Rantanen, and Matti Kämäräinen
Nat. Hazards Earth Syst. Sci., 24, 1835–1842, https://doi.org/10.5194/nhess-24-1835-2024, 2024
We study the relationship between tracks of low-pressure systems and related sea level extremes. We perform the studies by introducing a method to simulate sea levels using synthetic low-pressure systems. We test the method using sites located along the Baltic Sea coast. We find high extremes, where the sea level extreme reaches up to 3.5 m. In addition, we add the maximal value of the mean level of the Baltic Sea (1 m), leading to a sea level of 4.5 m.

Modelling seismic ground motion and its uncertainty in different tectonic contexts: challenges and application to the 2020 European Seismic Hazard Model (ESHM20)
Graeme Weatherill, Sreeram Reddy Kotha, Laurentiu Danciu, Susana Vilanova, and Fabrice Cotton
Nat. Hazards Earth Syst. Sci., 24, 1795–1834, https://doi.org/10.5194/nhess-24-1795-2024, 2024
The ground motion models (GMMs) selected for the 2020 European Seismic Hazard Model (ESHM20) and their uncertainties require adaptation to different tectonic environments. Using insights from new data, local experts and developments in the scientific literature, we further calibrate the ESHM20 GMM logic tree to capture previously unmodelled regional variation. We also propose a new scaled-backbone logic tree for application to Europe's subduction zones and the Vrancea deep seismic source.

Predicting the thickness of shallow landslides in Switzerland using machine learning
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-76,2024
Preprint under review for NHESS (discussion: open, 0 comments)
We developed a machine learning-based approach to predict the potential thickness of shallow landslides to generate improved inputs for slope stability models. We selected 21 explanatory variables including metrics on terrain, geomorphology, vegetation height, and lithology and used data from two Swiss field inventories to calibrate and test the models. The best performing machine learning model consistently reduced the mean average error by least 17 % compared to previously existing models.

AutoATES v2.0: Automated Avalanche Terrain Exposure Scale mapping
Håvard B. Toft, John Sykes, Andrew Schauer, Jordy Hendrikx, and Audun Hetland
Nat. Hazards Earth Syst. Sci., 24, 1779–1793, https://doi.org/10.5194/nhess-24-1779-2024, 2024
Manual Avalanche Terrain Exposure Scale (ATES) mapping is time-consuming and inefficient for large-scale applications. The updated algorithm for automated ATES mapping overcomes previous limitations by including forest density data, improving the avalanche runout estimations in low-angle runout zones, accounting for overhead exposure and open-source software. Results show that the latest version has significantly improved its performance.

Text mining uncovers the unique dynamics of socio-economic impacts of the 2018–2022 multi-year drought in Germany
Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, and Mariana Madruga de Brito
Nat. Hazards Earth Syst. Sci., 24, 1757–1777, https://doi.org/10.5194/nhess-24-1757-2024, 2024
We delved into the socio-economic impacts of the 2018–2022 drought in Germany. We derived a dataset covering the impacts of droughts in Germany between 2000 and 2022 on sectors such as agriculture and forestry based on newspaper articles. Notably, our study illustrated that the longer drought had a wider reach and more varied effects. We show that dealing with longer droughts requires different plans compared to shorter ones, and it is crucial to be ready for the challenges they bring.

The usefulness of Extended-Range Probabilistic Forecasts for Heat wave forecasts in Europe
Natalia Korhonen, Otto Hyvärinen, Virpi Kollanus, Timo Lanki, Juha Jokisalo, Risto Kosonen, David S. Richardson, and Kirsti Jylhä
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-75,2024
Preprint under review for NHESS (discussion: open, 0 comments)
The skill of hindcasts of the European Centre for Medium-Range Weather Forecasts in forecasting heat wave days (periods with the 5-day moving average temperature being above its local summer 90th percentile) over Europe 1 to 4 weeks ahead is examined. The heat wave days forecasts show potential in warning of heat risk in 1–2 weeks in advance, and enhanced accuracy in forecasting prolonged heat waves, in lead times of up to 3 weeks, when the heat wave had initiated prior to the forecast issuance.

Analysis of three-dimensional slope stability combined with rainfall and earthquake
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, 2024
With a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, a global analysis method that considers both seepage and seismic forces is proposed to determine the safety factor of slopes subjected to the combined effect of rainfall and earthquakes. By taking a slope in the Three Gorges Reservoir area as an example, the safety evolution of the slope combined with both rainfall and earthquake is also examined.