Rising social and economic losses from natural hazards, particularly in mountain regions, driven by increasing exposure, climate change-driven extremes, and improved impact reporting, highlight the need for a multi-hazard approach in their study. Multi-hazard risk assessment requires clear methodologies (hazard, exposure, vulnerability), yet high-resolution frameworks remain underdeveloped. Their development demands extensive modeling to quantify hazards and derive necessary data, especially for hydrological risks (droughts and floods). This research advances multi-hazard risk assessment by establishing a methodology for quantifying key hazards, its risk assessment and demonstrating the potential of a hydrological digital twin (HDT) framework. The analyzed study area is the Trentino Alto-Adige region in Italy and the Adige River. A novel statistical framework is developed to characterize heat and cold waves using probabilistic methods that account for the absence of events in certain years. This enables risk quantification through integrating hazards with spatially and temporally explicit exposures and vulnerabilities. A significant increase in heatwave risk of the region is revealed while cold wave risk declines except for large cities. This emphasizes the need for targeted adaptation strategies. To support hydrological hazard quantification, a Hydrological Digital Twin (HDT) is developed for the Adige basin. It simulates the water cycle while incorporating anthropogenic influences (e.g. reservoirs, land-use changes, irrigation water uses). To confirm its accuracy, it has been extensively validated using multi-site observation data (for river discharge) and remote sensing products (for snow, actual evapotranspiration and soil water content). Projected climate scenarios applied to the HDT without irrigation indicate seasonal water shifts with rising winter discharge but summer reductions, a substantial decline in snow cover, and an increase in evapotranspiration. The Adige River remains snow-fed but there are potential consequences for agriculture, hydropower, and water management. By combining historical analysis, high-resolution modeling, and future climate projections, this research provides a framework for defining hazards and a relevant modelling effort to derive data necessary for a multi-hazard risk assessment. The findings enable the implementation of such an assessment to guide policymakers in climate adaptation and risk mitigation.
Assessing Natural Hazards and Climate Change in a Mountain Region with a Hydrological Digital Twin
Morlot, Martin Jean-luc Emile
2025
Abstract
Rising social and economic losses from natural hazards, particularly in mountain regions, driven by increasing exposure, climate change-driven extremes, and improved impact reporting, highlight the need for a multi-hazard approach in their study. Multi-hazard risk assessment requires clear methodologies (hazard, exposure, vulnerability), yet high-resolution frameworks remain underdeveloped. Their development demands extensive modeling to quantify hazards and derive necessary data, especially for hydrological risks (droughts and floods). This research advances multi-hazard risk assessment by establishing a methodology for quantifying key hazards, its risk assessment and demonstrating the potential of a hydrological digital twin (HDT) framework. The analyzed study area is the Trentino Alto-Adige region in Italy and the Adige River. A novel statistical framework is developed to characterize heat and cold waves using probabilistic methods that account for the absence of events in certain years. This enables risk quantification through integrating hazards with spatially and temporally explicit exposures and vulnerabilities. A significant increase in heatwave risk of the region is revealed while cold wave risk declines except for large cities. This emphasizes the need for targeted adaptation strategies. To support hydrological hazard quantification, a Hydrological Digital Twin (HDT) is developed for the Adige basin. It simulates the water cycle while incorporating anthropogenic influences (e.g. reservoirs, land-use changes, irrigation water uses). To confirm its accuracy, it has been extensively validated using multi-site observation data (for river discharge) and remote sensing products (for snow, actual evapotranspiration and soil water content). Projected climate scenarios applied to the HDT without irrigation indicate seasonal water shifts with rising winter discharge but summer reductions, a substantial decline in snow cover, and an increase in evapotranspiration. The Adige River remains snow-fed but there are potential consequences for agriculture, hydropower, and water management. By combining historical analysis, high-resolution modeling, and future climate projections, this research provides a framework for defining hazards and a relevant modelling effort to derive data necessary for a multi-hazard risk assessment. The findings enable the implementation of such an assessment to guide policymakers in climate adaptation and risk mitigation.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/209142
URN:NBN:IT:UNITN-209142