Spatiotemporal Drought Assessment over Sahelian Countries from 1985 to 2015


  • Due to infrequent rainfall, high temperatures, and degraded land, the Sahel region often suffers from droughts. The Sahel region is considered as one of the world’s driest and extreme environmental conditions. In order to assess spatiotemporal vulnerability of potential drought impacts, we used remote sensing and ground station data to evaluate drought conditions in the Sahel region from 1985 to 2015. The standard precipitation index (SPI), standard precipitation evapotranspiration index (SPEI), vegetation condition index (VCI) anomaly, along with socioeconomic indicators were performed. In addition, Pearson correlation coefficient (PCC) was computed between drought indices and three main crops (sorghum, millet, and maize) in the region to estimate the effects. The analysis showed that temperature increased by 0.78°C from 1985 to 2015, which had a significant impact on crop yield for sorghum, maize, and millet with a statistical significance value of P > 0.05. In the decade spanning 1994 to 2005 alone, the temperature increased by 0.57°C, which resulted in extreme drought in Algeria, Sudan, Chad, Nigeria, and Mauritania. For the effect of drought on crop production, high significance was noted on the SPI and SPEI-3 timescale: sorghum with SPI-3 (r = 0.71) and SPEI-3 (r = 0.65), millet with SPI-3 (r = 0.61) and SPEI-3 (r = 0.72), and maize with SPI-3 (r = 0.81) and SPEI-3 (r = 0.65) during the study period. In the growing season, VCI anomaly had strong correlations with sorghum and millet (r = 0.67 and 0.75, respectively). A significant agreement was also noticed between the combined drought index (CDI) and vulnerability index (VI) in Burkina Faso (r = −0.676; P < 0.00), Mali (r = −0.768; P < 0.00), Mauritania (r = 0.843; P < 0.001), Niger (r = −0.625; P < 0.001), and Nigeria (r = −0.75; P < 0.005). The results show that the above indices are effective in assessing agricultural drought and its impact on crop production in the Sahel, and in identifying areas most affected by drought.
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