A dual model coupled flood forecasting method and system

By employing a dual-model coupling and joint inversion correction method, the problem of low flood forecast accuracy in small and medium-sized watersheds in hilly areas is solved, achieving high-precision, automated, and real-time flood forecasting, which is applicable to high mountain and canyon areas.

CN122287408APending Publication Date: 2026-06-26CHINA RAILWAY CONSTR BRIDGE ENG BUREAU GRP CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA RAILWAY CONSTR BRIDGE ENG BUREAU GRP CO LTD
Filing Date
2026-06-01
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing technologies for flood forecasting in small and medium-sized watersheds in hilly areas suffer from problems such as low forecast accuracy, strong dependence on boundary conditions, difficulty in parameter calibration, and low degree of automation. In particular, it is difficult to achieve real-time high-precision forecasting in high mountain and canyon areas.

Method used

A dual-model coupling method is adopted, combining the API model and the hydraulic model. The average rainfall of the watershed is calculated by the Thiessen polygon method. The boundary conditions of the hydraulic model are generated by the coupling time step synchronization mechanism and the boundary condition spatial interpolation algorithm. The model parameters are updated in real time by joint inversion correction through the ensemble Kalman filter algorithm.

Benefits of technology

It significantly improved the accuracy of flood forecasting, reduced the relative and time errors of peak flow, enhanced the level of automation, expanded the application scope of the model in areas with scarce data, and achieved real-time correction capabilities.

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Abstract

This invention provides a dual-model coupled flood forecasting method and system, relating to hydrological forecasting, including: calculating the basin-wide average rainfall using the Thiessen polygon method based on real-time rainfall and meteorological grid forecast data; calculating Pa value, runoff generation, and confluence based on the basin-wide average rainfall using the API model to obtain the channel outlet cross-section flow and the first forecast water level; converting the channel outlet cross-section flow data calculated by the API model into the boundary conditions of the hydraulic model based on a "coupled time step synchronization mechanism" and a "boundary condition spatial interpolation algorithm"; establishing a hydraulic model of the channel to be forecasted, solving the hydraulic model based on the boundary conditions to obtain the second forecast water level; and after obtaining measured water level data, using an ensemble Kalman filter algorithm to jointly invert and correct the Pa value of the API model and the roughness n value of the hydraulic model to update the model parameters in real time. The dual-model coupling method improves the accuracy of flood water level forecasting.
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