Drought Characterization and Trend Detection Using the Reconnaissance Drought Index for Setsoto Municipality of the Free State Province of South Africa and the Impact on Maize Yield

• Published in: Water (Basel) Vol. 12; no. 11; p. 2993
• Main Authors: Abubakar, Hadisu B., Newete, Solomon W., Scholes, Mary C.
• Format: Journal Article
• Language: English
• Published: MDPI AG 01.11.2020
• Subjects: Analysis; China; drought; Droughts; Free State province; Rain and rainfall; rainfall; reconnaissance drought index (RDI); Setsoto municipality; South Africa; temperature; United Kingdom; South Africa; United Kingdom; China
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w12112993

The reconnaissance drought index (RDI) for the Setsoto municipality of the Free State province in South Africa was calculated for the period between 1985 and 2019 at 3 month (October–December), 6 month (October–March), and 12 month (October–September) intervals. Rainfall and minimum and maximum temperature data from four weather stations (Clocolan, Ficksburg, Marquard, and Senekal) were used for this study to characterize drought using “DrinC” software together with the Mann Kendall test with Sen’s slope to detect drought trends and the rate of change. Extreme, severe, and moderate droughts were recorded for all the stations, with RDIs ranging from −3.6 to −1.0 at different temporal scales. The years 1991, 1994, 2006, 2011, and 2015 were highlighted using the RDI 3, 6, and 12 month calculations. Results showed that the yield decreased either in the year of the drought or in the subsequent year, due to the exact timing of the low-rainfall events in the season and soil moisture storage. Yields were low, on average 2.5 tons ha−1 year−1, with high variability. Optimal growing conditions are essential in the early part of the season, October–December, for maximizing yield; if droughts are experienced at this time then the yield is more greatly impacted than if the droughts occur later in the season. Spatial analysis shows a large variability of drought patterns across the Municipality, over the years, with the 3 month RDI values giving a more detailed picture of this variability than the 6 and 12 month RDI values.