In this study, we used Long-Short Term Memory(LSTM) models for predicting the discharge for the basin. We use input parameters like precipitation, temperature, wind speed, and PET for predicting the discharge corresponding to these parameters.

The thresholding model predicts flood extents based on river gauge measurements. The model leverages historical inundation data and river height measurements to forecast flood-prone areas, aiding in early warning systems and resource allocation during flood events. The Hoshangabad station was chosen for this study due to the availability of relevant data. Additionally, a comprehensive dashboard has been created to visualise inundation maps for specific dates and to predict inundation maps using the threshold model based on input gauge measurements.