The change of the Earth's climate and the increasing human action (e.g., increasing impervious areas) are influencing the recurrence and magnitude of flooding events and consequently the exposure of urban and rural communities. Under these conditions, flood hazard analysis needs to account for this change through the adoption of nonstationary approaches. Such methods, showing how flood hazard evolves over time, are able to support a long-term plan of adaptation in hazard changing perspective, reducing expected annual damage in flood prone areas. On this basis, in this paper a reevaluation of flood hazard in the Benevento province of southern Italy, is presented, providing a reduced complexity methodological framework for near future flood hazard prediction under nonstationary conditions. The proposed procedure uses multiple nonstationary probability models and a LiDAR-derived high-resolution inundation model to provide present and future flood scenarios in the form of hazard maps. Such maps are derived using a spatialization routine of stage probability across the inundation model that is able to work at different scales. The analysis indicates that, overall, (i) flood hazard is going to decrease in the next 30 years over the Benevento province and (ii) many areas of the Calore river floodplain are going to be subject to higher return level events. Consequently, many areas would require new guidelines of use as the hazard level decreases. Limitations of the analysis are related to the choice of the probability model and the parameter estimation approach. A further limit is that, currently, this method is not able to account for the presence of mitigation measurements. However, result validation indicates a very high accuracy of the proposed procedure with a matching degree, with a recently observed 225-years flood, estimated in 98%. On this basis, the proposed framework can be considered a very important approach in flood hazard estimation able to predict near future evolution of flood hazard as modulated by the ongoing climate change.
Modelling prospective flood hazard in a changing climate, Benevento province, southern Italy
Guerriero L.;Ruzza G.;Guadagno F. M.;Revellino P.
2020-01-01
Abstract
The change of the Earth's climate and the increasing human action (e.g., increasing impervious areas) are influencing the recurrence and magnitude of flooding events and consequently the exposure of urban and rural communities. Under these conditions, flood hazard analysis needs to account for this change through the adoption of nonstationary approaches. Such methods, showing how flood hazard evolves over time, are able to support a long-term plan of adaptation in hazard changing perspective, reducing expected annual damage in flood prone areas. On this basis, in this paper a reevaluation of flood hazard in the Benevento province of southern Italy, is presented, providing a reduced complexity methodological framework for near future flood hazard prediction under nonstationary conditions. The proposed procedure uses multiple nonstationary probability models and a LiDAR-derived high-resolution inundation model to provide present and future flood scenarios in the form of hazard maps. Such maps are derived using a spatialization routine of stage probability across the inundation model that is able to work at different scales. The analysis indicates that, overall, (i) flood hazard is going to decrease in the next 30 years over the Benevento province and (ii) many areas of the Calore river floodplain are going to be subject to higher return level events. Consequently, many areas would require new guidelines of use as the hazard level decreases. Limitations of the analysis are related to the choice of the probability model and the parameter estimation approach. A further limit is that, currently, this method is not able to account for the presence of mitigation measurements. However, result validation indicates a very high accuracy of the proposed procedure with a matching degree, with a recently observed 225-years flood, estimated in 98%. On this basis, the proposed framework can be considered a very important approach in flood hazard estimation able to predict near future evolution of flood hazard as modulated by the ongoing climate change.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
