The impact of climate change scenarios on droughts and their propagation in an arid Mediterranean basin. A useful approach for planning adaptation strategies

Areas where there is a scarcity of water frequently experience significant drought periods, which may become exacerbated in the future due to climate change. In this paper we propose a novel and integrated method for a semi-distributed analysis of the impact on potential future meteorological, hydrological, agronomical and operational droughts within a basin. We analyse the propagation and correlation of the different types of droughts, and then this analysis can be used to plan sustainable adaptation strategies. The proposed method is based on sequential applications of different statistical techniques and mathematical models. We have applied several statistical downscaling techniques to generate consistent local future climate scenarios considering both basic and drought statistics. This allows us to analyse the sensitivity of the results to the applied technique and the spatial distribution. A chain of models has been used to propagate climate scenarios to analyse the hydrological, agricultural, and operational impact. We have applied a clustering analysis to historical data to identify homogeneous hydro-climate areas used to analyse the spatial distribution of the impact. The approach has been applied in the Segura basin (in south-eastern Spain). The simulations of the impact in the 3 generated ensemble scenarios on the whole Segura Basin system for the horizon 2071-2100 under the RCP8.5 emission scenario show a significant mean reduction (40.9-59.1%) of the available resources, an increase in pumping rates in aquifers (36.4-42.7%) and lower guarantees (96.3% in the historical period and 75.0-77.6% in the future scenarios) for demand supply. The spatial distribution of the impact is heterogeneous, with the hydro-climate areas near to the coast for agricultural and operational droughts being more affected. An analysis of correlation between the meteorological and operational droughts shows the maximum correlation for a time delay of around 4 months. This information could help to identify when measures to reduce the operational impact should start to be applied when a meteorological drought starts.