A new deep learning model called GNRRM was developed to improve rainfall-runoff predictions by using high-resolution precipitation data and spatial information. This model breaks down large watersheds into smaller parts to better capture the geography and flow direction, resulting in more accurate forecasts compared to traditional models. The study shows that incorporating detailed hydrological data in deep learning models can lead to better predictions for water runoff.