Abstract. The existence of debris flows not only destroys the facilities but also seriously threatens human lives, especially in scenic areas. Therefore, the classification and susceptibility analysis of debris flow are particularly important. In this paper, 21 debris flow catchments located in Huangsongyu Township, Pinggu District, Beijing, China, were investigated. Besides field investigation, a geographic information system, a global positioning system and remote-sensing technology were applied to determine the characteristics of debris flows. This article introduced a clustering validity index to determine the clustering number, and the fuzzy C-means
algorithm and factor analysis method were combined to classify 21 debris
flow catchments in the study area. The results were divided into four types: debris flow closely related to scale–topography–human activity, topography–human activity–matter source, scale–matter source–geology and topography–scale–matter source–human activity. Nine major factors screened from the classification result
were selected for susceptibility analysis, using both the efficacy coefficient method and the combination weighting. Susceptibility results
showed that the susceptibility levels of 2 debris flow catchments were high, 6 were moderate and 13 were low. The assessment results were consistent with the field investigation. Finally, a comprehensive assessment including
classification and susceptibility evaluation of debris flow was obtained,
which was useful for risk mitigation and land use planning in the study area and provided a reference for the research on related issues in other
areas.
Landslides cause huge damage to social economy and human beings every year. Landslide susceptibility mapping (LSM) occupies an important position in land use and risk management. This study is to investigate a hybrid model which makes full use of the advantage of supervised learning model (SLM) and unsupervised learning model (ULM). Firstly, ten continuous variables were used to develop a ULM which consisted of factor analysis (FA) and k-means cluster for a preliminary landslide susceptibility map. Secondly, 351 landslides with “1” label were collected and the same number of non-landslide samples with “0” label were selected from the very low susceptibility area in the preliminary map, constituting a new priori condition for a SLM, and thirteen factors were used for the modeling of gradient boosting decision tree (GBDT) which represented for SLM. Finally, the performance of different models was verified using related indexes. The results showed that the performance of the pretreated GBDT model was improved with sensitivity, specificity, accuracy and the area under the curve (AUC) values of 88.60%, 92.59%, 90.60% and 0.976, respectively. It can be concluded that a pretreated model with strong robustness can be constructed by increasing the purity of samples.
Based on the coupled SPH-DEM-FEM numerical method, this paper analyzes the dynamic interaction of solid debris flow particle-liquid debris flow slurry-retaining dam in order to explore the dynamic response of retaining dam under the impact of the solid-liquid two-phase debris flow and delves into the process of the debris flow impact on the dam, the impact force of debris flow, and the elastic-plastic time-history characteristics of the dam under different slopes of trapezoidal grooves. The calculation results show that the coupled SPH-DEM-FEM method can vividly simulate the impact behavior of the solid-liquid two-phase debris flow on the dam, reproduce the impact, climbing, and siltation in the process of the debris flow impact; the dynamic time-history curve of the retaining dam is consistent with the law of the literature, and the result of the debris flow impact force obtained is close to that of the empirical formula. Moreover, this paper studies the impact force distribution of the debris flow impact process. The results have a certain reference value for the study of the dynamic response of the retaining dam under the impact of the solid-liquid two-phase debris flow and the engineering design of the debris flow-retaining dam.
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