Natural Hazards and Earth System Sciences

Regional-scale landslide risk assessment in Central Asia
Francesco Caleca, Chiara Scaini, William Frodella, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 13–27, https://doi.org/10.5194/nhess-24-13-2024, 2024
Landslide risk analysis is a powerful tool because it allows us to identify where physical and economic losses could occur due to a landslide event. The purpose of our work was to provide the first regional-scale analysis of landslide risk for central Asia, and it represents an advanced step in the field of risk analysis for very large areas. Our findings show, per square kilometer, a total risk of about USD 3.9 billion and a mean risk of USD 0.6 million.

Floods in the Pyrenees: A global view through a regional database
María Carmen Llasat, Montserrat Llasat-Botija, Erika Pardo, Raül Marcos-Matamoros, and Marc Lemus-Canovas
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2023-206,2024
Preprint under review for NHESS (discussion: open, 0 comments)
Climate change is leading in the Pyrenees Massif to a change in socioeconomic increasing their sensitivity to natural risks such as floods. However, until now, no systematic study like this one had been carried out that would allow evaluating the frequency, distribution and main meteorological features of these events on a massif scale. In 35 years there have been 181 flood events that have produced 154 fatalities.

Volcanic risk ranking and regional mapping of the Central Volcanic Zone of the Andes
Maria-Paz Reyes-Hardy, Luigia Sara Di Maio, Lucia Dominguez, Corine Frischknecht, Sébastien Biass, Leticia Guimarães, Amiel Nieto-Torres, Manuela Elissondo, Gabriela Pedreros, Rigoberto Aguilar, Álvaro Amigo, Sebastián García, Pablo Forte, and Costanza Bonadonna
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2023-225,2024
Preprint under review for NHESS (discussion: open, 0 comments)
The Central Volcanic Zone of the Andes is shared by four countries and groups 59 volcanoes. We identified the ones with the most intense and frequent eruptions (e.g., El Misti and Ubinas), the cities with the highest density of elements at risk (e.g., Arequipa and Mequegua), and the volcanoes with the highest potential impact (e.g., Cerro Blanco and Yucamane). Our study contributes into the prioritization of risk reduction resources, which is crucial for surrounding communities.

Spatial identification of regions at risk to multi-hazards at pan European level: an implemented methodological approach
Tiberiu-Eugen Antofie, Stefano Luoni, Alois Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2023-220,2024
Preprint under review for NHESS (discussion: open, 0 comments)
This is the first study that uses spatial patterns (clusters/hot-spots) and meta-analysis in order to identify the regions at European level at risk to multi-hazards. The findings point out the socio-economic dimension as determinant factor for the risk potential to multi-hazard. The outcome provides valuable input for the Disaster Risk Management policy support and will assist national authorities on the implementation of a multi-hazard approach in the National Risk Assessments preparation.

Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, 2024
Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.

A downward counterfactual analysis of flash floods in Germany
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2023-224,2024
Preprint under review for NHESS (discussion: open, 1 comment)
To identify the flash flood potential in Germany, we shifted the most extreme rainfall events from the last 22 years systematically across Germany and simulated the consequent run off reaction. Our results show, that almost all areas in Germany have not seen the worst-case scenario of flood peaks within the last 22 years. With a slight spatial change of historical rainfall events, flood peaks by the factor 2 or more would be achieved for most areas. The results can aid disaster risk management.

On the potential of using smartphone sensors for wildfire hazard estimation
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2023-211,2024
Preprint under review for NHESS (discussion: open, 1 comment)
We have used the temperature and relative humidity sensors in smartphones to estimate the Vapor Pressure Deficit (VPD), and important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal show the potential for using smartphone data to both compliment the regular weather station network, while also providing high spatial resolution of the VPD index.

Intense rains in Israel associated with the 'Train effect'
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2023-215,2024
Preprint under review for NHESS (discussion: open, 0 comments)
'Train effect' is related to convective cells that pass over the same place. Trains produce heavy rainfall, sometimes floods, and reported in N. America during spring and summer. In Israel, 17 trains were identified by radar images, associated with Cyprus Lows, sharing the following features: Found at the cold sector south of the low center, at the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km, last 1–3 hours and yield 35 mm rainfall, up to 60 mm.