Estimation of Standardized Precipitation Evapotranspiration Index (SPEI) and drought modeling using ARIMA time series in Raichur, Karnataka, India

Abstract

Drought, characterized by a prolonged absence of precipitation leading to water scarcity, profoundly impacts various sectors like agriculture, the environment, and human life. Accurate estimation of evapotranspiration through the Penman-Monteith method enhances the study's reliability. Assessing drought severity is effectively achieved by integrating drought indices, such as SPEI, into a statistical modeling framework. Incorporating these indices as input variables in time series models enables the analysis of temporal and spatial patterns, forecasting future drought conditions, and understanding drought impacts on different systems. This study demonstrates the efficacy of the ARIMA model in analysing SPEI time-series data at various temporal scales (1-month, 3-month, and 6-month). Emphasizing the importance of seasonal and monthly plots provides insights into climate analysis. Monthly SPEI plots facilitate the assessment of long-term drought trends and their potential connection to climate change. The findings underscore the increasing relationship between timescales and reveal the superior performance of the ARIMA model with SPEI6, as evidenced by the highest R-squared value, lowest MSE value, and lowest AIC value. These results enhance understanding of climatic patterns in the Raichur district, offering valuable insights for decision-making and resource management in the region.