Leveraging Landsat, TERRACLIMATE, and SRTM-DEM data to model spatial patterns of unexpected drought at the Sahel/Sahara interface

This study proposes a geospatial procedure that leverages Landsat 8/9, TERRACLIMATE, and SRTM-DEM data, to spatialize drought patterns and dynamics, from a confrontation–confirmation–completion perspective of a reference (empirical) and observed (records) warmest period. First, Landsat 8/9 bi-month median image is used to develop the Improved Land Surface General Drought Index – version 3 (LSGDI3) with the Euclidean function. Next, a multi-regression computation supports the downscaling-adjustment of climate (climatic drought) and topography (topographic drought) to the previous step output. Further, the Weighted Residuals Aggregation Polynomial (WRAP) model is proposed, to produce the Land Surface-Climate-Topography Combined Drought Model (LSCTDMComb). As overall finding, the dual data reference/observed alternative is highly efficient to model drought spatial patterns at a regional scale and reflecting the global warming dynamics. For the 2014–2023 studied decade, the average decade cross-receiver operating characteristic/area under curve (cross-ROC/AUC) results are satisfying up to 0.818, sign of a balanced and robust model. Further support is provided by lower values of the root mean square error (RMSE), mean absolute error (MAE), and relative absolute error (RAE) metrics, respectively [0.0368–0.246], [0.0031–0.0233], and [0.005–0.0393]. Whereas the coefficient of determination values obtained between reference and observed warmest bi-months are, R2: [0.64–0.96], regardless of the temporal difference. Spatially, all LSCTDMComb agree on increasing risk of drought hazards with the latitudes at the Sahel–Sahara interface. These trends are similar to the patterns depicted by compared popular models, despite some caveats raised, especially the resolution discrepancies.