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.

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).

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