OneMap Drought Monitoring Analysis Based on Statistical Models

As the effects of droughts on agriculture and industrial water availability intensify with climate change, developing suitable drought prevention mitigation measures has become increasingly important. However, measuring conditions using different indices leads to disjointed management responses by ministries agencies. Additionally, based only one variable are insufficient accurately assess conditions. Therefore, creating adopting a OneMap index would be beneficial in assessment implementation appropriate measures. In this study, we used multivariate statistical modeling Bayesian principal component analysis develop that unifies existing conditions, including meteorological, agricultural, hydrological indices. After evaluating accuracy corrected self-organizing migrating algorithm optimization technique, it was found applicability its ability regenerate were excellent for ground satellite data. authors recommend implementing step-by-step action plans integrated generate forecasts warnings, thus promoting concerted effective local governments authorities.