Drought Index Prediction Using Data Intelligent Analytic Models: A Review

This review chapter discusses drought index predictions with data intelligent methods. Due to massive climate change owing to temperature increments, water resources have faced a serious deficiency on the perspectives on management and planning. Recently, much attention has been witnessed on studying the global drought change scenarios. Drought is a natural hazard having a highly stochastic and nonlinear characteristic owing to the influence of several climatic variables. The necessity of understanding the actual relationship between those climate variables and droughts is important for early warning and impact mitigation. Considering the limitation of conventional statistical methods, data intelligent analytic models have been used in recent years for the modeling relationship of climate variables with drought index forecasting of droughts. Different types of intelligent analytic models are developed for the prediction of drought indices. A review of studies is provided to comprehend recent advances and existing challenges in forecasting drought indices, primarily with intelligent data analytic modeling approaches.