Enhancing the streamflow prediction capability of the National Water Model for predicting future streamflow in a coastal Alabama watershed

The application of the National Water Model (NWM) to accurately predict streamflow requires a new approach where major coastal flooding could cause backwater flooding into a tributary and adjacent land areas. The existing NWM routing scheme is not able to address this backwater effect explicitly. A new fast, flexible, and modular routing algorithm known as t-route has been developed although the program has not been tested extensively to evaluate the improvement in the performance of the NWM. This study evaluates the performance of the NWM in predicting streamflow in the Mobile River watershed in Alabama using the t-route routing algorithm. The Mobile River watershed is one of the examples where downstream conditions would need to be incorporated into the stream flow and depth calculation. In such a case, the t-route is expected to improve the predictive capability of the NWM. However, climate change makes streamflow prediction more challenging. In this study, we also take the climate change projections (e.g., precipitation, temperature) from the Global Climate Models (GCMs) from the CMIP6 database and put them as input into the NWM to characterize the impacts of climate change on the streamflow in the Mobile River watershed. The representative GCMs and Shared Socioeconomic Pathways (SSPs) will be selected from a range of GCMs and SSPs. Based on these GCMs and SSPs, the climate variables will be downscaled to the local scale using a statistical downscaling technique and pre-processed to be used in the NWM. This study would enable us to predict the streamflow more precisely for the flood-prone Mobile River watershed during the historical, present, and future periods.