Risk analysis for local management from hydro-geomorphologic disaster databases

Abstract

• Hydro-geomorphological database allows historic reconstruction of losses and damages. • Different database criteria improve risk matrix evaluation and local hazard scopes. • Territorial forcers that shape disaster consequences have been changing overtime. • Cluster analysis and risk matrices conduced to risk profiles supporting management. This article describes the applications of a hydro-geomorphologic disaster database allowing a more appropriate local risk management. Two databases of loss and damage with different criteria, using Central Portugal occurrences, were constructed upon national and regional newspapers: one included all the disaster occurrences regardless of the level of loss and damage reported and the other only the major disasters for which casualties and other human losses were reported. Risk matrices, exploring likelihood and consequence, were analysed along with data regarding urban and demographic dynamics over time and risk profiles by municipality were obtained. The results show that the database which only included major disasters produced a risk matrix with lower levels of risk in comparison to the one produced from the more inclusive database. The most densely urbanised municipalities represent a greater number of disaster occurrences, but when considering only major losses, other peripheral municipalities emerge as high risk. Changes in territorial forcers are shaping the impact patterns in the region. Along with an increase in the housing density, an increase in disasters is observed, although the decrease of inhabitants. Impacts and territorial forcers cluster analysis and risk matrices’ results conduced to municipal risk profiles supporting management. Those profiles conduce to different frames of action from specific emergency planning, warning and alert, multi-hazard planning, or prevention measures involving land use planning or insurance and mutualisation solutions. Disaster databases that allow differentiating local patterns of impacts–and their respective contexts - contribute to define locally adequate risk management policies.