Articles | Volume 24, issue 1
https://doi.org/10.5194/nhess-24-13-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-24-13-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Jan 2024
Research article |
| 09 Jan 2024
| 09 Jan 2024
Regional-scale landslide risk assessment in Central Asia
Francesco Caleca
CORRESPONDING AUTHOR
Department of Earth Sciences, University of Florence, via G. la Pira 4, 50121 Florence, Italy
Chiara Scaini
National Institute of Oceanography and Applied Geophysics – OGS, Borgo Grotta Gigante, 34100 Sgonico (Trieste), Italy
William Frodella
Department of Earth Sciences, University of Florence, via G. la Pira 4, 50121 Florence, Italy
Veronica Tofani
Department of Earth Sciences, University of Florence, via G. la Pira 4, 50121 Florence, Italy
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Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
Short summary
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Central Asia regions are marked by active tectonics, high mountains with glaciers, and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
Ascanio Rosi, William Frodella, Nicola Nocentini, Francesco Caleca, Hans Balder Havenith, Alexander Strom, Mirzo Saidov, Gany Amirgalievich Bimurzaev, and Veronica Tofani
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This work was carried out within the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project and is focused on the first landslide susceptibility analysis at a regional scale for Central Asia. The most detailed available landslide inventories were implemented in a random forest model. The final aim was to provide a useful tool for reduction strategies to landslide scientists, practitioners, and administrators.
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
Short summary
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Central Asia regions are marked by active tectonics, high mountains with glaciers, and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
Chiara Scaini, Alberto Tamaro, Baurzhan Adilkhan, Satbek Sarzhanov, Vakhitkhan Ismailov, Ruslan Umaraliev, Mustafo Safarov, Vladimir Belikov, Japar Karayev, and Ettore Faga
Nat. Hazards Earth Syst. Sci., 24, 929–945, https://doi.org/10.5194/nhess-24-929-2024, https://doi.org/10.5194/nhess-24-929-2024, 2024
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Central Asia is highly exposed to multiple hazards, including earthquakes, floods and landslides, for which risk reduction strategies are currently under development. We provide a regional-scale database of assets at risk, including population and residential buildings, based on existing information and recent data collected for each Central Asian country. The population and number of buildings are also estimated for the year 2080 to support the definition of disaster risk reduction strategies.
Chiara Scaini, Alberto Tamaro, Baurzhan Adilkhan, Satbek Sarzhanov, Zukhritdin Ergashev, Ruslan Umaraliev, Mustafo Safarov, Vladimir Belikov, Japar Karayev, and Ettore Fagà
Nat. Hazards Earth Syst. Sci., 24, 355–373, https://doi.org/10.5194/nhess-24-355-2024, https://doi.org/10.5194/nhess-24-355-2024, 2024
Short summary
Short summary
Central Asia is prone to multiple hazards such as floods, landslides and earthquakes, which can affect a wide range of assets at risk. We develop the first regionally consistent database of assets at risk for non-residential buildings, transportation and croplands in Central Asia. The database combines global and regional data sources and country-based information and supports the development of regional-scale disaster risk reduction strategies for the Central Asia region.
Antonella Peresan, Chiara Scaini, Sergey Tyagunov, and Paola Ceresa
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-156, https://doi.org/10.5194/nhess-2023-156, 2023
Publication in NHESS not foreseen
Short summary
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The experience collected during a capacity building experience in Central Asia is illustrated, which consisted in the organization of a series of training workshops devoted to the different components of risk assessment, focused on earthquakes, floods and selected landslide scenarios. The activity consisted of five country-based workshops on exposure assessment in each of the Countries of Central Asia, plus three regional scale thematic workshops on hazard, vulnerability and risk modelling.
Ascanio Rosi, William Frodella, Nicola Nocentini, Francesco Caleca, Hans Balder Havenith, Alexander Strom, Mirzo Saidov, Gany Amirgalievich Bimurzaev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 23, 2229–2250, https://doi.org/10.5194/nhess-23-2229-2023, https://doi.org/10.5194/nhess-23-2229-2023, 2023
Short summary
Short summary
This work was carried out within the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project and is focused on the first landslide susceptibility analysis at a regional scale for Central Asia. The most detailed available landslide inventories were implemented in a random forest model. The final aim was to provide a useful tool for reduction strategies to landslide scientists, practitioners, and administrators.
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Short summary
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.
Landslide risk analysis is a powerful tool because it allows us to identify where physical and...
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