NEW DESIGN OF SUBMERGED ENTRY NOZZLE FOR

In the context of increasing flood events due to climate change, accurate flood forecasting becomes essential for disaster management and planning. This study aims to evaluate various hydrological models suitable for predicting flood occurrences. We conducted a comparative analysis of three widely used hydrological models: the Soil Conservation Service Curve Number (SCS-CN) model, the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model, and the HEC-HMS model. The methodology included applying these models to the same watershed over a period of significant rainfall events, collecting data from both historical records and real-time monitoring systems. The results demonstrated that while all models provided valuable insights into flood dynamics, the GSSHA model outperformed the others in terms of prediction accuracy and reliability during peak flow events. This study highlights the strengths and limitations of each model, informing stakeholders about the best practices for flood management and enhancing the preparedness of communities facing flood risks. The findings support the need for ongoing development and calibration of hydrological models to improve flood forecasting capabilities in the face of changing environmental conditions.