Geoadditive modeling for extreme rainfall data

Extreme value models and techniques are widely applied in environmental studies to define protection systems against the effects of extreme levels of environmental processes. Regarding the matter related to the climate change science, a certain importance is cover by the implication of changes in the hydrological cycle. Among all hydrologic processes, rainfall is a very important variable as it is a fundamental component of flood risk mitigation and drought assessment, as well as water resources availability and management. We implement a geoadditive mixed model for extremes with a temporal random effect assuming that the observations follow generalized extreme value distribution with spatially dependent location. The analyzed territory is the catchment area of Arno River in Tuscany in Central Italy.