A simple geospatial model climate–1 based for designing 2 erosive rainfall pattern (pp. 451-468)
Authors: (Nazzareno Diodato and Massimo Fagnano)
Abstract: In the Earth Climatic System (ECS), water can be viewed as both a resource and a land disturbing force. In particular, the rainstorms influence of weather increases with its amount and intensity, whilst the protective effect of the landscape equipment network counteract this influence. Accurate estimation of the climate aggressiveness by erosive rainfall events plays a major role for agricultural and urban areas management and, in turn, for indirectly affecting ECS protection‘s (e.g., deluges, flash-floods, soil erosion and sediment transport). Although several studies have focused on the climate aggressiveness spatial pattern in Geographic Information System (GIS) within different methodologies, only a few have recently studied how the RUSLE–erosivity factor is affected by both climate and its extremes annuality. This was mainly due to the scarcity of erosivity–data in individual months or years, especially in mountainous and developing countries, where hourly and sub-hourly pluviometrical data are not available for the erosivity calculus.
With the purpose to skip over these drawbacks, a parsimonious framework is firstly developed in this paper for designing spatial variability of long-term average rain-erosivity and its extremes annuality within assigned return period (T). This methodology was successively applied for a test-site placed in a mountainous agricultural basin of the Campania Region (Southern Italy). In the third step, the approach was set to extend the information from point to landscapes with stochastic geospatial tools in GIS, using mainly daily records of 62 rain-stations of the Department of Civil Protection established by Campania and Basilicata Regional Monitoring Networks. To such goal, Regression Ordinary Kriging (ROK) based–maps have been generated for depicting the erosive rainfall spatial variability on annual-basis across the Sele River Basin (SRB), and to delineate its current trend in the regional climate change context.