Spatiotemporal Analysis of Drought and Impact on Millet Production across North Darfur State using Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI)

Drought severely affects the agricultural sector. Its effects have in fact been aggravated by the global warming climate scenario. Although drought has to a large extent been studied globally, it is often overlooked on the local and regional scales. Therefore, accurate and timely characterizations of agricultural drought at the local and regional scales are essential for developing adaptation and mitigation strategies. This study analyzed the spatiotemporal trend of drought events and their impact on millet production in North Darfur State, Sudan from 1981 to 2020. The Standardized Precipitation Index (SPI) and the Reconnaissance Drought Index (RDI) for the three-month (June -August), six-month (June -November), and nine -month (June -February) timescales were used to assess the relevant drought events. The drought -yield relationships were assessed using the Pearson correlation coefficient (r). The results indicate that for detecting drought trends the RDI index is more sensitive to variabilities than the SPI index. The drought events affecting North Darfur over broad spatial extents occurred particularly over the years, 1989, 1990, 1992, 1999, and 2001; the most extreme of drought events being in 2003. The correlation coefficient analysis (r) between the SPI and RDI respectively and the standardized variable of crop yield (SVCY) for millet grain yield showed a strong agreement between the respective variables. The moderate to extreme reductions in millet crop yield occurring in 1992, 1999, 2001, and 2003 corresponded with the moderate to extreme drought indicated by the RDI. Severe crop losses were experienced in Kabkabiya and Umm Kadadda. This study contributes to a clearer understanding of drought impacts on the local scale and thus to insights into developing more effective and targeted management strategies and to enhancing crop resilience.