<p>Meteorological forecasting is an effective method for helping to reduce the human and financial risks during the occurrence of floods. Hydrological forecasting is often considered a component of flood warning systems, which can improve the accuracy of alerts and the lead time of existing forecasts, providing more time for property protection and evacuation of at-risk areas. In this study, the Regional Climate Model (RegCM) for dynamic/meteorological forecasting, combined with the Storm Water Management Model (SWMM) for hydrological analysis, was employed to forecast and simulate monthly floods in the urban basin of Sabzevar. To apply the RegCM meteorological model, six convection schemes, two boundary layer schemes and six schemes were implemented, and their best configuration was set. The hydrological model was analyzed for sensitivity using 11 basin parameters. Its calibration and validation were performed. Subsequently, precipitation from the output of meteorological model was used as input to the hydrological model. Evaluating the results of the integrated models showed that the coefficient of determination (R<sup>2</sup>) of the predicted monthly runoff is effective between 0.53 and 0.92. This shows the accuracy of RegCM and SWMM models in forecasting and simulating rainfall-runoff in the urban basin. The results also showed that this approach could be used by planners, programmers, and engineers in flood risk assessment and the design of flood control projects, both in Sabzevar and through the application of these models in other locations with similar climate condition Worldwide. This is because the runoff associated with different storms can be estimated one month prior to their occurrence, and forecast data is used to identify flood-prone areas. Additionally, by integrating such models, forecasted data from meteorological models can be used for the desired period instead of observational data, enabling the establishment of an accurate flood warning system for the entire urban basin.</p>

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Forecasting and Simulation of Urban Floods Based on the Integration of RegCM and Stormwater Management Models

  • Mokhtar Karami,
  • Rasoul Sarvestan,
  • Manfred Kleidorfer

摘要

Meteorological forecasting is an effective method for helping to reduce the human and financial risks during the occurrence of floods. Hydrological forecasting is often considered a component of flood warning systems, which can improve the accuracy of alerts and the lead time of existing forecasts, providing more time for property protection and evacuation of at-risk areas. In this study, the Regional Climate Model (RegCM) for dynamic/meteorological forecasting, combined with the Storm Water Management Model (SWMM) for hydrological analysis, was employed to forecast and simulate monthly floods in the urban basin of Sabzevar. To apply the RegCM meteorological model, six convection schemes, two boundary layer schemes and six schemes were implemented, and their best configuration was set. The hydrological model was analyzed for sensitivity using 11 basin parameters. Its calibration and validation were performed. Subsequently, precipitation from the output of meteorological model was used as input to the hydrological model. Evaluating the results of the integrated models showed that the coefficient of determination (R2) of the predicted monthly runoff is effective between 0.53 and 0.92. This shows the accuracy of RegCM and SWMM models in forecasting and simulating rainfall-runoff in the urban basin. The results also showed that this approach could be used by planners, programmers, and engineers in flood risk assessment and the design of flood control projects, both in Sabzevar and through the application of these models in other locations with similar climate condition Worldwide. This is because the runoff associated with different storms can be estimated one month prior to their occurrence, and forecast data is used to identify flood-prone areas. Additionally, by integrating such models, forecasted data from meteorological models can be used for the desired period instead of observational data, enabling the establishment of an accurate flood warning system for the entire urban basin.