Using SPI and SPEI for baseline probabilities and seasonal drought prediction in two agricultural regions of the Western Cape, South Africa

Drought is one of the most hazardous natural disasters in terms number people directly affected. An important characteristic drought prolonged absence rainfall relative to long-term average. The intrinsic persistence conditions continuing from month next can be utilized for monitoring and early warning systems. This study sought better understand probabilities baselines two agriculturally regions Western Cape, South Africa – with a distinct season which receives year-round rainfall. indices, Standardised Precipitation Evapotranspiration Index (SPEI) (SPI), were assessed obtain predictive information establish set baseline drought. Two sets synthetic time-series data used (one where seasonality was retained removed), along observed monthly minimum maximum temperature. Based on inherent characteristics, autocorrelation probability density function future state various SPI start lead times. Optimal also established. validity methodology then examined by application recent Cape Town (2015–2018). Results showed potential this applied systems decision support tools province.