Integration of Hydrologic Gray Model with Global Search Method for Real-Time Flood Forecasting

Abstract

This paper presents a hydrologic gray model integrated with a global search method to improve the accuracy of real-time flood forecasting for two watersheds. The model’s applicability is evaluated by comparing the runoff forecasts to the observed values. The model’s accuracy is compared with the accuracy of two base models that employ multiple regression equations and the model capability is verified in real situations. The model parameters are corrected by combining the gray system parameters. The fifth-order differential equation is adopted to represent the characteristics of the study watersheds. The statistical values between the observed values and the runoff forecasts in calibration and validation indicate that the simulations are in close agreement with the observations. The model provides more consistent and satisfactory runoff forecasts than the multiple regression models across all flow ranges; the accuracy of the runoff forecasts varies according to hydrograph stages and lead times. These results demonstrate that the proposed model is able to reasonably forecast runoff with 1–6 h of lead time for the two study watersheds.