Abstract
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.
Highlights
Global warming has caused changes in rainfall patterns, and changes in the frequency and magnitude of extreme water events [1,2,3]
(Generalized Additive Models in Location, Scale and Shape) modeling framework was used. These tools consist of semi-parametric regression models, allowing the relation of the parameters of a probability density function (PDF) as a function of an explicative variable through non-parametric smoothing techniques [26]
This study describes the variability and discontinuities detected in the spatial patterns of drought events in a semi-arid Mediterranean basin of Southeast Spain (Segura River Basin), by non-stationary modeling of time series
Summary
Global warming has caused changes in rainfall patterns, and changes in the frequency and magnitude of extreme water events [1,2,3]. The correlation of detected trends in rainfall time series or drought events was studied with macroclimate indexes such as the North Atlantic Oscillation (NAO) [13], even studying the impacts on water resources [14,15,16,17]. From these studies, the NAO is suggested as one of the main factors controlling the changes in the circulation patterns as well as the trends of rainfall in the Euro-Atlantic area. Knowledge of plausible trends of drought events at basin scale is needed in order to take appropriate measures both to conserve aquatic ecosystems and to minimize impacts on water uses
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