Abstract :
The growing concern of the possible impact of natural disasters and extreme events on the environment has recently created new demands for information from, and assessment by, environmental engineers and climatologists. Mediterranean river basins encompass a diverse range of valley and floodplain environments and are affected by many different processes, such as hydroclimate, land-use, catchment geology, and relief. The objective of this paper is to develop a methodology for exploratory rainstorms data analysis and uncertainty estimation in regional hydrogeomorphological frequency analysis (HFA). A general framework is proposed for designing spatial variability of rainstorms with assigned return periods (T) inducing multiple damaging hydrogeomorphological events in the Campania region, south Italy. To this end, the analysis of precipitation, involving means techniques of regional HFA and geostatistical theory integrated approaches, is a subject of great interest. However, the hydrogeomorphological consequences depend on complex interactions between extreme precipitation and torrential characteristics of the landscape. In Mediterranean environments, climatic fluctuations in hydrological regime, especially those exceeding rain thresholds for an acceptable range of flexibility, can be the main causes of relevant hydrogeomorphological impacts. An algorithm for the characterization of this impact termed with the acronym DRHI (Design Rainstorms Hazard Index) in this paper is presented first. Next, the continuous DRHI data are converted at each location using a binary variable indicator transform based on critical thresholds. In the third step, the expansion of DRHI-soft information from point to landscapes were assessed geostatistically using the records of 70 rain stations of the Department of Civil Protection established by Regional Monitoring Networks. In this way, threshold values for extreme hydrogeomorphological impacts were selected based on geographical distribution patterns of precipitation maxima with a duration of 3 h for a return period of 10, 20, and 50 years. Moreover, the map-based method provides the identification where future infill sampling should be focused in support of more precise characterization.
