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Research on landslide hazard assessment in data‑deficient areas: a case study of Tumen City, China

Li Xia, Cheng Jiulong, Yu Dehao, Han Yangchun

Acta Geophysica

2023

Vol. 71, no. 4

1763--1774

With the development of economy, the urbanization process is accelerated and the infrastructure construction is increased, which leads to the widespread occurrence of landslides in mountain areas all over the world. However, due to the complex geological environment or some other reasons, the lack of landslide-related data in some mountainous areas makes it more difficult to predict landslides. At the same time, the existing models have different prediction effects in different regions, and it is difficult for a single model to objectively and accurately evaluate landslide hazard. The purpose of this research is to complete the landslide hazard assessment (LHA) in data-deficient areas by proposed a combination model with help of remote sensing (RS) and geographic information system (GIS) technology. Firstly, 146 landslides and 10 LHA conditioning factors in Tumen City were obtained by using RS, GIS and field investigation. To increase the amount of model training data, 386 landslides (including 146 landslides in Tumen City) in some areas of Yanbian Korean Autonomous Prefecture with similar landslide conditions to Tumen City were obtained. Secondly, three combination models for LHA are proposed, which make full use of the effective information provided by logistic regression (LR), artificial neural network (ANN) and support vector machine (SVM), and the evaluation effect and applicability of the three combination models are discussed. Finally, the three combination models and three single models of logistic regression (LR), artificial neural network (ANN), support vector machine (SVM) are analyzed and compared through the overall accuracy (OA), confusion matrix and landslide density. The results show that it can effectively complete the landslide hazard assessment in data-deficient areas with help of RS and GIS, and the three combination models proposed in this research are superior to the other three single models, and the evaluation effect of the LA-SVM combination model is the best.

Fine detection on water abundance of sandstone by joint inversion of seismic and CSAMT: a case study in the western Ordos Basin, China

Dong Yi, Cheng Jiulong, Wen Laifu, Cheng Peng, Li Fei, Jiao Junjun, Huang Qisong

Acta Geophysica

2022

Vol. 70, no 5

2045--2056

The Ningdong mining area in the western Ordos Basin, China, mainly mines coal seam in Yan'an group, where its overlying rock is a thick sandstone layer of the Middle Jurassic Zhiluo Formation. This rock layer poses a direct water hazard threat to the coal mining if it is water-rich. The water abundant rock layer in the upper strata of Zhiluo Formation forms a low-resistivity overburden layer, decreasing the resolution of controlled source audio magnetotelluric (CSAMT) method in detecting water-bearing in the lower part of Zhiluo Formation sandstone layer of coal seam direct roof. Therefore, under the influence of the low resistivity overburden of the upper sandstone, how to accurately detect the aquosity of the lower sandstone layer is of great importance to the safe mining of coal mines in the region. On the basis of CSAMT detection, combined with high-resolution seismic exploration method, the joint inversion of seismic and CSAMT is realized by using cross-gradient operation between the seismic wave impedance attributes clustered by particle swarm algorithm and CSAMT inversion model. The seismic data fitting term in the joint inversion objective function is discarded, and the pseudo-2D inversion method is used for CSAMT to reduce the calculation cost of the inversion. A 3D geological model conforming to the hydrogeological characteristics of the Ningdong mining area is established, and the joint inversion test between seismic and CSAMT is conducted, proving the feasibility and applicability of joint inversion to detect the water enrichment of sandstone in this area. The accuracy of the seismic and CSAMT joint inversion results is verified by combining the engineering example of water abundance detection in the sandstone layer in Maiduoshan coal mine that accorded with the typical hydrogeological characteristics of Ningdong mining area and the results of later downhole drilling exposures, which is remarkably better than the single method. The research shows that the joint inversion of seismic and CSAMT can accurately identify the water abundance of the lower sandstone layer and its range under the influence of the upper low resistance sandstone overburden and achieve the purpose of fine detection of the water abundances of the lower sandstone layer of the Zhiluo Formation. The joint inversion can provide important safety geological guarantee for the mining of coal seams in the Ningdong mining area in the western part of Ordos Basin.