Innovative assessment of meteorological drought in northern Algeria using the NIFT index

This study evaluates meteorological drought exposure and desertification vulnerability in northern Algeria using the NIFT (Number/Intensity/Frequency/Trend) index at four temporal scales (1-, 3-, 6-, and 12-month). The analysis uses PERSIANN-CDR precipitation data from January 1983 to December 2022 and applies Hierarchical Cluster Analysis (HCA) to classify regions with similar drought characteristics. Across the different time scales, the NIFT index identifies three major spatial clusters, revealing consistent geographical patterns of drought exposure. The Sahara and Chott Hodna basins show the highest levels of severe to extreme exposure, with drought intensity gradually decreasing toward the northeastern regions. In contrast, the western part of northern Algeria exhibits predominantly moderate to low drought exposure. Relationships between NIFT values and key grid characteristics-longitude, latitude, mean precipitation, and rainfall variability-demonstrate time-dependent behavior. At shorter time scales, longitude exerts greater influence on NIFT variability, whereas latitude plays a more dominant role at longer scales. Higher mean rainfall is generally associated with lower drought exposure, while greater rainfall variability tends to increase drought sensitivity, although the strength of these relationships varies across time scales. These results highlight the spatial complexity of drought patterns in northern Algeria and emphasize the need for region-specific drought management strategies. While the NIFT index provides a useful multi-dimensional assessment, its performance remains conditioned by the resolution and uncertainty of satellite-derived precipitation data. The findings contribute to improved understanding of drought dynamics and support ongoing efforts in climate adaptation and water resource planning.