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Water 2018, 10(1), 12; https://doi.org/10.3390/w10010012

A Novel Flood Forecasting Method Based on Initial State Variable Correction

1
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
2
Beijing IWHR Technology Co., Ltd., Beijing 100038, China
3
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
4
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
*
Authors to whom correspondence should be addressed.
Received: 24 November 2017 / Revised: 22 December 2017 / Accepted: 22 December 2017 / Published: 25 December 2017
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Abstract

The influence of initial state variables on flood forecasting accuracy by using conceptual hydrological models is analyzed in this paper and a novel flood forecasting method based on correction of initial state variables is proposed. The new method is abbreviated as ISVC (Initial State Variable Correction). The ISVC takes the residual between the measured and forecasted flows during the initial period of the flood event as the objective function, and it uses a particle swarm optimization algorithm to correct the initial state variables, which are then used to drive the flood forecasting model. The historical flood events of 11 watersheds in south China are forecasted and verified, and important issues concerning the ISVC application are then discussed. The study results show that the ISVC is effective and applicable in flood forecasting tasks. It can significantly improve the flood forecasting accuracy in most cases. View Full-Text
Keywords: flood forecasting; forecast accuracy; conceptual hydrological model; initial state variable; particle swarm optimization algorithm flood forecasting; forecast accuracy; conceptual hydrological model; initial state variable; particle swarm optimization algorithm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Li, K.; Kan, G.; Ding, L.; Dong, Q.; Liu, K.; Liang, L. A Novel Flood Forecasting Method Based on Initial State Variable Correction. Water 2018, 10, 12.

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