Ensemble Method for Reservoir Flood Season Segmentation
Publication: Journal of Water Resources Planning and Management
Volume 143, Issue 3
Abstract
The practical reservoir flood season segmentation is crucial to dynamically adjusting the flood-limiting water level in flood seasons. An ensemble method structure (EMS) was designed to screen out the most suitable method structure for segmenting flood season. The performance of the proposed EMS approach was evaluated in a case study in Chengbihe Reservoir, China. The results indicate that the method structures containing flood volume series sampled by using the peaks-over-threshold (POT) technique outperform the other method structures. To further explore the impacts of the flood volume index and the POT sampling technique on segmentations, the 1-, 3-, and 5-day flood volume series sampled by using the POT1, POT2, and POT3 techniques, respectively, were used to segment the flood season by using the method of directional statistics. The main findings are as follows: (1) the segmentation is most sensitive to the selected indices, sensitive to the sampling techniques, and least sensitive to the segmentation methods; and (2) the variance of the segmentations increases with the amount of flood data used in segmenting flood season. Thus, the segmentations of the flood season in the Chengbihe Reservoir can be obtained by averaging the dates obtained with the latter constructed method structures. The case study demonstrates that the proposed EMS approach can be an effective tool for flood season segmentation.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant Nos. 41323001, 51539003), National Science Funds for Creative Research Groups of China (Grant No. 51421006), the program of Dual Innovative Talents Plan and Innovative Research Team in Jiangsu Province, the Special Fund of State Key Laboratory of Hydrology—Water Resources and Hydraulic Engineering of China (Grant No. 20145027312), and the Fundamental Research Funds for the Central Universities of China.
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©2016 American Society of Civil Engineers.
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Received: Mar 5, 2015
Accepted: Sep 4, 2016
Published online: Nov 7, 2016
Published in print: Mar 1, 2017
Discussion open until: Apr 7, 2017
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