Direct and indirect simulating and projecting hydrological drought using a supervised machine learning method.

There is a trend in using Artificial Intelligence methods as simulation tools in different aspects of hydrology, including river discharge simulations, drought predictions, and crop yield simulations. The motivation of this work was to assess two various concepts in applying these methods in simulations and projections of hydrological drought. In this study, Standardized Runoff Index (SRI) was simulated and projected using Artificial Neural Networks (ANNs).