Seepage Monitoring Models Study of Earth-Rock Dams Influenced by Rainstorms

Jianchun Qiu,Dongjian Zheng,Kai Zhu

doi:10.1155/2016/1656738

Abstract

For earth-rock dams influenced by rainstorms, seepage status monitoring is very important and provides the basis for the safe and effective operation of earth-rock dams. The most influential factors concerning the seepage of earth-rock dams are the reservoir water level, precipitation, temperature, and timeliness, and the influence of the reservoir water level and precipitation on the seepage of an earth-rock dam exhibits hysteretic effects. The reservoir water level of an earth-rock dam abruptly increases and may exceed the historically highest water level, therein causing new deformations of the earth-rock dam or even plastic deformation. Thus, the permeability coefficient for parts of an earth-rock dam changes, and we present the exceeded water level factor. Considering the complexity of the seepage monitoring of earth-rock dams, based on the hysteretic reservoir water level and precipitation, temperature, timeliness, and the exceeded water level factor, a statistical model based on an explicit function and an artificial wavelet neural network model based on an implicit function are established. Based on these two models, an integrated monitoring model based on maximum entropy theory is established. At the end of this paper, three monitoring models are used for the seepage monitoring of a measuring point of an earth-rock dam influenced by rainstorms, and the results show that the three monitoring models obtain satisfactory predication accuracy.

Highlights

Due to the characteristics of low cost, fine environmental adaptability, and lower construction difficulty, earth-rock dams have been widely used and rapidly developed in the world, which make up over 80 percent of all dams [1]
At the end of this paper, three monitoring models are used for the seepage monitoring of a measuring point of an earth-rock dam influenced by rainstorms, and the results show that the three monitoring models obtain satisfactory predication accuracy
The three seepage monitoring models are applied to analyze the seepage status of an earth-rock dam influenced by rainstorms

Summary

Introduction

Due to the characteristics of low cost, fine environmental adaptability, and lower construction difficulty, earth-rock dams have been widely used and rapidly developed in the world, which make up over 80 percent of all dams [1]. By studying the earth-rock dam seepage statistical model considering the hysteretic effect of precipitation and reservoir water level and the exceeded water level factor, combined with the temperature component and timeliness component, the earth-rock dam seepage statistical model is obtained as follows:. The obtained parameters are substituted into the artificial wavelet neural network and combined with the import of reservoir water level component, precipitation component, temperature component, timeliness component, and the exceeded water level factor; the seepage index series are exported. Through the consideration of the hysteretic effect of seepage and the exceeded water level factor, the statistical model reflects the seepage status of the earth-rock dam to a certain extent. The earth-rock dam seepage index X is a discrete random variable, and the following equation based on maximum entropy theory is given: max S (X) = −∑pi ln pi. Repeating Step (3), the predicated series of the T seepage monitoring values of the earth-rock dam is obtained

Case Study

The Application of Three Models in Monitoring the Seepage Status

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Findings

Conclusions