Assessing nonstationary spatial patterns of extreme droughts from long-term high-resolution observational dataset on a semiarid basin (Spain)

In basins of South-eastern Spain; such as the semiarid Segura River Basin (SRB), a strong decrease in runoff from the end of the 1970s has been observed. However, in the SRB the decreasing trend is not only related with climate variability and change, also with intensive reforestation aimed at halting desertification and erosion, whichever the reason is, the default assumption of stationarity in water resources systems cannot be guaranteed. Therefore there is an important need for improvement in the ability of monitoring and predicting the impacts associated with the change of hydrologic regimes. It is thus necessary to apply non-stationary probabilistic models, which are able to reproduce probability density functions whose parameters vary with time. From a high-resolution daily gridded rainfall dataset of more than five decades (1950-2007), the spatial distribution of lengths of maximum dry spells for several thresholds are assessed, applying Generalized Additive Models for Location Scale and Shape (GAMLSS) models at the grid site. Results reveal an intensification of extreme drought events in some headbasins of the SRB important for water supply. The identification of spatial patterns of drought hazards at basin scale, associated with return periods; contribute to designing strategies of drought contingency preparedness and recovery operations, which are the leading edge of adaptation strategies.