Assessing SPI and SPEI for drought forecasting through the power law process: A case study in South Sulawesi, Indonesia

Abstract

This study presents a method for assessing drought events by integrating Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) into the Power Law Process (PLP) model. The method begins with identifying drought events based on SPI and SPEI, followed by the Cramér–von Mises goodness-of-fit test to ensure the drought data meets PLP assumptions. Parameter estimation is performed using Maximum Likelihood Estimation (MLE) with a time-truncated approach, treating drought as a random process within a defined observation period. Model validation is conducted by comparing actual drought events with predictions from the cumulative PLP function, while event probabilities are determined using the Nonhomogeneous Poisson Process. Applied to 24 regencies/cities in South Sulawesi, the method showed that 14 regions fit the PLP based on SPI, and 13 regions based on SPEI. Predictions indicate that over the next 12 months, drought will occur for one month based on SPI and two months based on SPEI. This method contributes to the development of drought monitoring and early warning systems, supporting mitigation and adaptation strategies in South Sulawesi.

The main contributions of this study include:

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  The development of a novel methodological framework by integrating SPI and SPEI into the PLP for drought analysis
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  Practical applications in drought early warning systems and drought risk management in South Sulawesi