Articles | Volume 25, issue 1
https://doi.org/10.5194/nhess-25-403-2025
© Author(s) 2025. 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-25-403-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Large-scale flood risk assessment in data-scarce areas: an application to Central Asia
Risk Engineering + Development (RED), 27100 Pavia, Italy
Gianbattista Bussi
Risk Engineering + Development (RED), 27100 Pavia, Italy
Simona Denaro
Risk Engineering + Development (RED), 27100 Pavia, Italy
Gabriele Coccia
Risk Engineering + Development (RED), 27100 Pavia, Italy
Paolo Bazzurro
Risk Engineering + Development (RED), 27100 Pavia, Italy
Scuola Universitaria Superiore Pavia (IUSS), 27100 Pavia, Italy
Mario Martina
Risk Engineering + Development (RED), 27100 Pavia, Italy
Scuola Universitaria Superiore Pavia (IUSS), 27100 Pavia, Italy
Ettore Fagà
Risk Engineering + Development (RED), 27100 Pavia, Italy
Carlos Avelar
Evaluación de Riesgos Naturales (ERN), 01050 Mexico City, Mexico
Mario Ordaz
Evaluación de Riesgos Naturales (ERN), 01050 Mexico City, Mexico
Benjamin Huerta
Evaluación de Riesgos Naturales (ERN), 01050 Mexico City, Mexico
Osvaldo Garay
Evaluación de Riesgos Naturales (ERN), 01050 Mexico City, Mexico
Zhanar Raimbekova
Department of Geography and Environmental Sciences, Al-Farabi Kazakh National University, A15E3C7, Al-Farabi Ave., 71/19, Almaty, Kazakhstan
Kanatbek Abdrakhmatov
Institute of Seismology of the National Academy of the Sciences Kyrgyz Republic, 720060 Bishkek, Kyrgyz Republic
Sitora Mirzokhonova
Institute of Water Problems, Hydropower and Ecology of the National Academy of Science of Tajikistan, 734042 Dushanbe, Tajikistan
Tajik National University, 734042 Dushanbe, Tajikistan
Vakhitkhan Ismailov
Institute of Seismology of the Academy of Sciences of Uzbekistan, 700128 Tashkent, Uzbekistan
Vladimir Belikov
Independent consultant, 744000, Ashgabat, Turkmenistan
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Valerio Poggi, Stefano Parolai, Natalya Silacheva, Anatoly Ischuk, Kanatbek Abdrakhmatov, Zainalobudin Kobuliev, Vakhitkhan Ismailov, Roman Ibragimov, Japar Karaev, Paola Ceresa, Marco Santulin, and Paolo Bazzurro
Nat. Hazards Earth Syst. Sci., 25, 817–842, https://doi.org/10.5194/nhess-25-817-2025, https://doi.org/10.5194/nhess-25-817-2025, 2025
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A regionally consistent probabilistic risk assessment for multiple hazards and assets was developed under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) programme, supported by the European Union, the World Bank, and the Global Facility for Disaster Reduction and Recovery. This paper outlines the preparation of the source model and presents key results of the probabilistic earthquake hazard analysis for the Central Asian countries.
Mario A. Salgado-Gálvez, Mario Ordaz, Benjamín Huerta, Osvaldo Garay, Carlos Avelar, Ettore Fagà, Mohsen Kohrangi, Paola Ceresa, Georgios Triantafyllou, and Ulugbek T. Begaliev
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Central Asia is prone to earthquake losses, which can heavily impact different types of assets. This paper presents the details of a probabilistic earthquake risk model which made use of a regionally consistent approach to assess feasible earthquake losses in five countries. Results are presented in terms of commonly used risk metrics, which are aimed at facilitating a policy dialogue regarding different disaster risk management strategies, from risk mitigation to disaster risk financing.
Valerio Poggi, Stefano Parolai, Natalya Silacheva, Anatoly Ischuk, Kanatbek Abdrakhmatov, Zainalobudin Kobuliev, Vakhitkhan Ismailov, Roman Ibragimov, Japar Karaev, Paola Ceresa, and Paolo Bazzurro
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As part of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) programme, funded by the European Union in collaboration with the World Bank and GFDRR, a regionally consistent probabilistic multi-hazard and multi-asset risk assessment has been developed. This paper describes the preparation of the input datasets (earthquake catalogue and active-fault database) required for the implementation of the probabilistic seismic hazard model.
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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
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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.
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This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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When hot temperatures and drought occur together (compound events), they can cause harmful impacts on crops and society. Using six decades of climate data, we show that such compound events repeatedly occurred in three breadbaskets of the Northern Hemisphere. These events are linked to atmospheric circulation patterns that favor heat and dryness, which in turn interact to amplify the impact. Our study contributes to understand the drivers of these events to support climate impact assessment.
Naveen Ragu Ramalingam, Kendra Johnson, Marco Pagani, and Mario L. V. Martina
Nat. Hazards Earth Syst. Sci., 25, 1655–1679, https://doi.org/10.5194/nhess-25-1655-2025, https://doi.org/10.5194/nhess-25-1655-2025, 2025
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By combining limited tsunami simulations with machine learning, we developed a fast and efficient framework to predict tsunami impacts such as wave heights and inundation depths at different coastal sites. Testing our model with historical tsunami source scenarios helped assess its reliability and broad applicability. This work enables more efficient and comprehensive tsunami hazard modelling workflow, which is essential for tsunami risk evaluations and enhancing coastal disaster preparedness.
Valerio Poggi, Stefano Parolai, Natalya Silacheva, Anatoly Ischuk, Kanatbek Abdrakhmatov, Zainalobudin Kobuliev, Vakhitkhan Ismailov, Roman Ibragimov, Japar Karaev, Paola Ceresa, Marco Santulin, and Paolo Bazzurro
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A regionally consistent probabilistic risk assessment for multiple hazards and assets was developed under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) programme, supported by the European Union, the World Bank, and the Global Facility for Disaster Reduction and Recovery. This paper outlines the preparation of the source model and presents key results of the probabilistic earthquake hazard analysis for the Central Asian countries.
Mario A. Salgado-Gálvez, Mario Ordaz, Benjamín Huerta, Osvaldo Garay, Carlos Avelar, Ettore Fagà, Mohsen Kohrangi, Paola Ceresa, Georgios Triantafyllou, and Ulugbek T. Begaliev
Nat. Hazards Earth Syst. Sci., 24, 3851–3868, https://doi.org/10.5194/nhess-24-3851-2024, https://doi.org/10.5194/nhess-24-3851-2024, 2024
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Central Asia is prone to earthquake losses, which can heavily impact different types of assets. This paper presents the details of a probabilistic earthquake risk model which made use of a regionally consistent approach to assess feasible earthquake losses in five countries. Results are presented in terms of commonly used risk metrics, which are aimed at facilitating a policy dialogue regarding different disaster risk management strategies, from risk mitigation to disaster risk financing.
Athanasios N. Papadopoulos, Philippe Roth, Laurentiu Danciu, Paolo Bergamo, Francesco Panzera, Donat Fäh, Carlo Cauzzi, Blaise Duvernay, Alireza Khodaverdian, Pierino Lestuzzi, Ömer Odabaşi, Ettore Fagà, Paolo Bazzurro, Michèle Marti, Nadja Valenzuela, Irina Dallo, Nicolas Schmid, Philip Kästli, Florian Haslinger, and Stefan Wiemer
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Valerio Poggi, Stefano Parolai, Natalya Silacheva, Anatoly Ischuk, Kanatbek Abdrakhmatov, Zainalobudin Kobuliev, Vakhitkhan Ismailov, Roman Ibragimov, Japar Karaev, Paola Ceresa, and Paolo Bazzurro
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As part of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) programme, funded by the European Union in collaboration with the World Bank and GFDRR, a regionally consistent probabilistic multi-hazard and multi-asset risk assessment has been developed. This paper describes the preparation of the input datasets (earthquake catalogue and active-fault database) required for the implementation of the probabilistic seismic hazard model.
Chiara Scaini, Alberto Tamaro, Baurzhan Adilkhan, Satbek Sarzhanov, Vakhitkhan Ismailov, Ruslan Umaraliev, Mustafo Safarov, Vladimir Belikov, Japar Karayev, and Ettore Faga
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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
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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.
Emilio Berny, Carlos Avelar, Mario A. Salgado-Gálvez, and Mario Ordaz
Nat. Hazards Earth Syst. Sci., 24, 53–62, https://doi.org/10.5194/nhess-24-53-2024, https://doi.org/10.5194/nhess-24-53-2024, 2024
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This paper presents a methodology to estimate the total emergency costs based on modelled damages for earthquakes and floods, together with the demographic and building characteristics of the study area. The methodology has been applied in five countries in central Asia, the first time that these estimates are made available for the study area and are intended to be useful for regional and local stakeholders and decision makers.
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
Short summary
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.
Luigi Cesarini, Rui Figueiredo, Beatrice Monteleone, and Mario L. V. Martina
Nat. Hazards Earth Syst. Sci., 21, 2379–2405, https://doi.org/10.5194/nhess-21-2379-2021, https://doi.org/10.5194/nhess-21-2379-2021, 2021
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Weather index insurance is an innovative program used to manage the risk associated with natural disasters, providing instantaneous financial support to the insured party. This paper proposes a methodology that exploits the power of machine learning to identify extreme events for which a payout from the insurance could be delivered. The improvements achieved using these algorithms are an encouraging step forward in the promotion and implementation of this insurance instrument.
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Short summary
A fully probabilistic flood risk assessment was carried out for five Central Asian countries to support regional and national risk financing and insurance applications. The paper presents the first high-resolution regional-scale transboundary flood risk assessment study in the area aiming to provide tools for decision-making.
A fully probabilistic flood risk assessment was carried out for five Central Asian countries to...
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