Prediction of Impending Drought Scenarios Based on Surface and Subsurface Parameters in a Selected Region of Tropical Queensland, Australia

Droughts occur in all climatic regions around the world costing a large expense to global economies. Reasonably accurate prediction of drought events helps water managers proper planning for utilization limited resources and distribution available waters different sectors avoid catastrophic consequences. Therefore, means create simplistic approach forecasting conditions with easily accessible parameters is highly desirable. This study proposes evaluates newly developed models utilizing various hydrologic, meteorological, geohydrology along use Artificial Neural Network (ANN) forecast lead times. The present develops multitude predict indices such as Standard Precipitation Index lead-time up 6 months, Soil Moisture 3 months. Furthermore, capability approximating surface groundwater storage levels including Ross River Dam level have been relatively high accuracy results obtained from these were compared current values, revealing that ANN based can be used simple effective predictive model utilized aspects scenarios typical area like Townsville, North Queensland, Australia which had suffered severe recent almost six years (2014 early 2019).