Evaluation of NCEP-GFS-based Rainfall forecasts over the Nagavali and Vamsadhara basins in India

Rainfall forecasting and its spatio-temporal variability is important for many hydrological applications. It critical to understand the uncertainty verify quality of rainfall forecasts provided by Numerical Weather Prediction (NWP) models. In present study, National Center Environmental (NCEP) Global Forecast System (GFS) model performance evaluated day-1 day-5 forecast with a threshold 1 mm/day in Nagavali Vamsadhara river basins, India. From results, predicted correlation coefficient >0.3 probability detection >0.6 day-3 forecasts. The bias prediction shifted from overestimation underestimation 30% as lead time increased. total mean error decomposed into hit, false, missed bias. main sources are hit false However, influenced Bias correction applied events intensity >12 mm/day. RMSE improved >18% both improvement ranged between 3% 9% other days. basin, BIAS ME 44% 65% forecast, whereas it 93%. Our findings useful early warning dissemination during flood events, resource mobilization protect communities, sustainable water resources planning management.