A landslide susceptibility model based on a metaheuristic optimization algorithm (germinal center optimization (GCO)) and support vector classification (SVC) is proposed and applied to landslide susceptibility mapping in the Three Gorges Reservoir area in this paper. The proposed GCO-SVC model was constructed via the following steps: First, data on 11 influencing factors and 292 landslide polygons were collected to establish the spatial database. Then, after the influencing factors were subjected to multicollinearity analysis, the data were randomly divided into training and testing sets at a ratio of 7:3. Next, the SVC model with 5-fold cross-validation was optimized by hyperparameter space search using GCO to obtain the optimal hyperparameters, and then the best model was constructed based on the optimal hyperparameters and training set. Finally, the best model acquired by GCO-SVC was applied for landslide susceptibility mapping (LSM), and its performance was compared with that of 6 popular models. The proposed GCO-SVC model achieved better performance (0.9425) than the genetic algorithm support vector classification (GA-SVC; 0.9371), grid search optimized support vector classification (GRID-SVC; 0.9198), random forest (RF; 0.9085), artificial neural network (ANN; 0.9075), K-nearest neighbor (KNN; 0.8976), and decision tree (DT; 0.8914) models in terms of the area under the receiver operating characteristic curve (AUC), and the trends of the other metrics were consistent with that of the AUC. Therefore, the proposed GCO-SVC model has some advantages in LSM and may be worth promoting for wide use.

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Cyclic wetting and drying treatment is commonly used to accelerate the weakening process of reservoir rock. The weakening is reflected in strength variation and structure variation, while the latter receives less attention. Based on a series of cyclic wetting and drying tests, this study tentatively applied the uniaxial compressive test, computed tomography (CT) test and digital image correlation (DIC) test to investigate the weakening of slate in a reservoir area. Test results show that the weakening is mainly reflected in the reduction of compressive strength, followed by the decrease of ability to resist cracking and elastic deformation. The weakening seems more likely to be caused by structure variation rather than composition change. Two failure modes, e.g., splitting and splitting-tension, are concluded based on the crack paths: the splitting failure mode occurs in the highly weathered samples and the splitting-tension failure mode appears in the low-weathered samples. The transition zones of deformation are inside samples. The nephogram maps quantify the continuous deformation and correspond to the aforementioned structure variation process. This study offers comprehensive methods to the weakening investigation of slate in reservoir area and may provide qualitative reference in the stability evaluation of related slate rock slope.