418 - The Rain-on-Grid Modeling Approach in Hydrological and Hydraulic Processes over a River Basin

The conventional large-scale hydrological models often struggle to capture intricate phenomena such as the backwater effect and complex interactions between floodplains and streams. To conquer these hurdles, the Rain on Grid (RoG) approach simplifies this process by employing 2D shallow water equations to convey excess rainfall into streams as overland flow by meticulously computing fluxes at the computational cell faces by treating rainfall as the source and infiltration as the sink within the continuity equation. The RoG models, therefore, avoid the need for sequentially running hydrological and hydraulic models for flood simulation. In this work, the study area encompasses the Adyar River basin in the Tamil Nadu state of India. The measured precipitation data and the Soil Conservation Service (SCS) curve number method estimate excess rainfall within each grid cell. The gridded curve numbers leverage the Food and Agriculture Organization (FAO) soil map and land use and land cover (LULC) information pertinent to the Adyar basin. Validation encompasses the comparison of the simulated hydrograph at the Chembarabakam reservoir inlet with observed data and flood depths against measurements at various monitoring stations within Chennai city in the basin during the 2015 flood event. Encouragingly, the results are notably accurate, suggesting that our model can replace the loosely coupled hydrological and hydraulic models. Furthermore, our analysis explores the consequences of different return periods of rainfall and adverse flood scenarios, reaffirming the RoG approach's efficacy in streamlining flood modelling for enhanced risk management.