Enhancing real-time flood forecasting and warning system by integrating ensemble techniques and hydrologic model simulations

ABSTRACT Flooding poses a severe threat to communities and infrastructure worldwide, which requires advanced flood forecasting warning systems. In this research paper, a real-time flood forecasting and warning system for the Dharoi Dam in the state of Gujarat, India is developed. This novel system combines ensemble techniques and hydrological modeling simulations to enhance flood prediction accuracy and provides a timely warning. The study focuses on critical gaps in the current flood forecasting capabilities, recognizes the need for improved flood management in the region, and builds upon the existing research conducted globally and in India. The real-time flood forecasting and warning system uses information from various sources such as rainfall, river flows, and water level observations. The system enhances the accuracy of flood forecasts with a 1–5-day lead time by utilizing ensemble techniques, which incorporate multiple models and their corresponding forecasts. The 2-day and 3-day lead times combined with postprocessing techniques yield excellent results, as evidenced by the reservoir inflow correlation value of 0.86 and the receiver operating characteristic-area under the curve (ROC-AUC) value of 0.93. This work aims to reduce the impact of floods in this region and can be used by decision-makers as a disaster management tool.