JOURNAL ARTICLE

A Dynamic Bidirectional Coupled Hydrologic-Hydrodynamic Model for Flood Prediction

Abstract

Abstract. As one of the main natural disasters, flood disaster poses a great threat to township development and property security. Numerous hydrological models and hydrodynamic models have been developed and implemented for flood simulation, risk prediction and inundation assessment. In this study, a dynamic and bidirectional coupled hydrodynamic-hydrologic-hydrodynamic model (DBCM) is developed to predict and evaluate inundation impact in a catchment in mountain area. Based on characteristic theory, the proposed method is able to dynamically adapt and alternate the simulation domain of hydrologic model, and/or hydrodynamic model according to the local flow condition, and a key feature of the proposed model is the dynamic coupling splitting the hydrologic and hydrodynamic simulation domains. The proposed model shows good prediction accuracy and overcomes the shortage existing in previous unidirectional coupling model (UCM). Existing numerical examples and physical experiments were both used to validate the performance of DBCM. Compared to UCM, results from DBCM show good agreements with analytical and measured data which indicates that the proposed model effectively reproduces flood propagation process and accounts for surface flow interaction between non-inundation region and inundation region. Finally, DBCM is applied to predict the flood in the Longxi river basin, and the simulation results show the capability of DBCM in conducting flood event simulation in interested catchment which can support flood risk early warning and future management.

Keywords:
Flood myth Computer science Environmental science Flow (mathematics) Geography

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2
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0.25
FWCI (Field Weighted Citation Impact)
0
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0.61
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Citation History

Topics

Flood Risk Assessment and Management
Physical Sciences →  Environmental Science →  Global and Planetary Change
Hydrology and Watershed Management Studies
Physical Sciences →  Environmental Science →  Water Science and Technology
Hydrological Forecasting Using AI
Physical Sciences →  Environmental Science →  Environmental Engineering
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