Assessing Spatial Variability and Trends of Droughts in Eastern Algeria Using SPI, RDI, PDSI, and MedPDSI—A Novel Drought Index Using the FAO56 Evapotranspiration Method

Drought is one of the most severe natural disasters worldwide, but with a particular emphasis in sub-humid and semi-arid climates. Several indices have been created to appropriately identify drought’s characteristics variability. The main objectives this study consisted analyzing behavior different applied northeast Algeria comparing them across long-term data set (1961–2014). SPI RDI at 9-month time scales were compared PDSI MedPDSI based on 123 rainfall stations gridded PET interpolated all locations. A principal component analysis (PCA) S-mode varimax rotation (RPC) was monthly values analyze spatiotemporal patterns droughts. Two components retained, which identified two sub-regions coherent differences related their distance from Mediterranean Sea UNEP aridity index. Trends RPC scores assessed using modified Mann–Kendall (MMK) test Sen’s slope estimator, showed fundamental difference between sub-regions. drought trends decreases frequency severity droughts northern sub-region, increases southern region, where climate mostly arid. Only few cases statistically significant, when for sub-region. spatial moderate, severe, extreme occurrences similar pair probability anomalies, Sc-PDSI water balance anomalies. interpretation variability droughts, mainly ones, supported by an semi-variograms. novel index well other advantages performing soil following FAO56 dual Kc method actual olive evapotranspiration instead PET, better explaining droughts; addition, detected significant both