Water Science and Engineering 2017, 10(1) 70-77 DOI:   http://dx.doi.org/10.1016/j.wse.2017.03.005  ISSN: 1674-2370 CN: 32-1785/TV

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Monitoring model
Particle swarm optimization algorithm
Earth rock dam
Lagging effect
Seepage pressure
Mutation factor
Piezometric level
Yan Xiang
Shu-yan Fu
Kai Zhu
Hui Yuan
Zhi-yuan Fang
Article by Yan Xiang
Article by Shu-yan Fu
Article by Kai Zhu
Article by Hui Yuan
Article by Zhi-yuan Fang

Seepage safety monitoring model for an earth rock dam under influence of high-impact typhoons based on particle swarm optimization algorithm

Yan Xiang a,b,*, Shu-yan Fu c,d, Kai Zhu b, Hui Yuan a,b, Zhi-yuan Fang a,b

a Dam Safety Management Center of the Ministry of Water Resources, Nanjing Hydraulic Research Institute, Nanjing 210029, China
b State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China
c College of Mechanics and Materials, Hohai University, Nanjing 210098, China
d School of Water Resources and Hydraulic Engineering, Yunnan Agricultural University, Kunming 650000, China


Extreme hydrological events induced by typhoons in reservoir areas have presented severe challenges to the safe operation of hydraulic structures. Based on analysis of the seepage characteristics of an earth rock dam, a novel seepage safety monitoring model was constructed in this study. The nonlinear influence processes of the antecedent reservoir water level and rainfall were assumed to follow normal distributions. The particle swarm optimization (PSO) algorithm was used to optimize the model parameters so as to raise the fitting accuracy. In addition, a mutation factor was introduced to simulate the sudden increase in the piezometric level induced by short-duration heavy rainfall and the possible historical extreme reservoir water level during a typhoon. In order to verify the efficacy of this model, the earth rock dam of the Siminghu Reservoir was used as an example. The piezometric level at the SW1-2 measuring point during Typhoon Fitow in 2013 was fitted with the present model, and a corresponding theoretical expression was established. Comparison of fitting results of the piezometric level obtained from the present statistical model and traditional statistical model with monitored values during the typhoon shows that the present model has a higher fitting accuracy and can simulate the uprush feature of the seepage pressure during the typhoon perfectly.

Keywords Monitoring model   Particle swarm optimization algorithm   Earth rock dam   Lagging effect   Typhoon   Seepage pressure   Mutation factor   Piezometric level  
Received 2016-09-02 Revised 2016-12-29 Online: 2017-01-31 
DOI: http://dx.doi.org/10.1016/j.wse.2017.03.005

This work was supported by the National Natural Science Foundation of China (Grants No. 51179108 and 51679151), the Special Fund for the Public Welfare Industry of the Ministry of Water Resources of China (Grant No. 201501033), the National Key Research and Development Program (Grant No. 2016YFC0401603), and the Program Sponsored for Scientific Innovation Research of College Graduates in Jiangsu Province (Grant No. KYZZ15_0140).

Corresponding Authors: Yan Xiang
Email: yxiang@nhri.cn
About author:


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