Abstract
Heavy rainfall and changes in the water levels of reservoirs directly affect the degree of landslide disasters in major hydropower project reservoir areas. Correlation analyses of rainfall- and water-level fluctuations with landslide displacement changes can provide a scientific basis for the prevention and early warning of landslide disasters in reservoir areas. Because of the shortcomings of the traditional correlation analysis based on linear assumptions, this study proposed the use of a pseudo-maximum-likelihood-estimation-mixed-Copula (MLE-M-Copula) method instead of linear assumptions. We used the Bazimen landslide in the Three Gorges Reservoir Area as a case study to carry out the correlation analysis of the rainfall, water-level fluctuations, and landslide displacement. First, we selected several appropriate influencing factors to construct four candidate Copula models and estimated the parameters using the pseudo-MLE method. After the goodness-of-fit test, we selected the M-Copula model as the optimal model and used this model to study correlations between the monthly displacement increment of the landslide and influencing factors. We then established the joint distribution functions of these correlations. We computed and analyzed the overall and tail correlations between the displacement increment and the influencing factors, and we constructed the conditional probability distribution of the monthly displacement increment for different given conditions. The results showed that the pseudo-MLE-M-Copula method effectively quantified the correlation between the rainfall, reservoir-level fluctuations, and landslide displacement changes, and we obtained the return periods and value at risk of the influencing factors of the Bazimen landslide under different rainfall conditions and reservoir-level changes. Furthermore, the tail correlations between the monthly displacement increment of the landslide and the rainfall- and reservoir-level changes were higher than the overall correlations.
Highlights
The Three Gorges Hydropower Station is currently the largest hydropower station in the world, and it is the largest project ever constructed in China
Conditional Probability Distribution and Return Period We further studied the joint distribution of the two random variables under different influencing factors (Zhang and Singh, 2007b)
Building the Correlation Model According to the field monitoring curves for the displacement of the Bazimen landslide and the reservoir’s water level and rainfall, we found that the reservoir’s water level, rainfall, and monthly landslide displacement increment exhibited different trends with time
Summary
The Three Gorges Hydropower Station is currently the largest hydropower station in the world, and it is the largest project ever constructed in China. The ecological environment of the reservoir has deteriorated as a result of landslides caused by heavy rainfall and reservoir water-level changes, which has become a major potential hazard affecting the long-term operational safety of major hydropower projects and the ecological environment of the reservoir (Varnes, 1996). Important topics in the field of hydrodynamic landslide disaster monitoring and early warning and prevention include: 1) the analysis of the reservoir’s hydrodynamic landslide deformation characteristics and the deformation-induced response, 2) the analysis of landslide influencing factors and deformation prediction, and 3) the establishment of a threshold extraction model. To reveal the disaster-causing mechanism of hydrodynamic landslides in reservoir areas, it is important to study the correlation between the influencing factors and the displacement, which holds great significance for the monitoring and early warning of reservoir disasters and the prevention and mitigation of geological disasters
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