Assessment of Two Drought Indices to Quantify and Characterize Drought Incidents: A Case Study of the Northern Part of Burundi

Abstract

Droughts are natural catastrophes that cost the health and wealth of humans due to their harmful effects on the natural environment, ecology, hydrology, and agriculture in particular. Droughts are recurring incidents that last for prolonged periods of time in the northern part of Burundi. Despite the region being prone to drought and often suffering from dry conditions, drought has not been widely investigated. For the quantification and characterization of dryness conditions, this research utilized two drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI), at 2-, 6-, 24-, and 48-month timescales, where 2-, 6-, 24-, and 48-months correspond to agricultural and hydrological droughts, respectively. The two drought indices were compared, and the difference between SPEI and SPI was illustrated by quantifying and characterizing drought incidents. The findings revealed that different types of droughts threatened the northern part of Burundi during the periods of 1993–2000 and 2002–2009. Both indices illustrated that 2005, 2006, and 2007 were extremely dry years. The drought incidents detected by the SPEI index were classified into moderate and severe categories, characterized by long duration and greater magnitude. In contrast, the drought incidents detected by SPI were classified into the “extremely dry” category, characterized by limited duration and lower magnitude but with higher intensities. This research highlighted that SPEI differs from SPI in quantifying and characterizing droughts and highly suggests the use of both SPEI and SPI when assessing droughts. The outcome of this study will be useful in drought prevention and mitigation strategies across Burundi, specifically for agricultural purposes.

Application of Statistical Functions for Rainfall Distribution Modelling and Spi Calculation in Mediterranean Watershed

“…It is applicable to all climate regimes and exhibits good spatial consistency, enabling comparison across different areas subject to varying climatic conditions (Pieper et al, 2020). Due to these exceptional advantages, the index has been demonstrated to be effective in detecting various historical drought events in numerous regions worldwide (Ndayiragije et al, 2022).…”