Spatial modeling of ground subsidence susceptibility along Al-Shamal train pathway in Saudi Arabia

Abstract

Al-Shamal train pathway, which is extended between Saudi Arabia and Jordan, is prone to geo-hazards due to the geological features, proximity to faults, earthquake epicenter, and the human activities along the pathway. The objectives of this study are to shed light on the ground subsidence susceptibility along Al-Shamal train pathway in Qarrayat city in Saudi Arabia and develop a ground subsidence susceptibility model to determine the prone areas to the impacts of ground subsidence to mitigate and avoid the loss of life and property. This study integrated the various data types to map the subsidence susceptibility along Al-Shamal train pathway. Nine ground subsidence causative parameters were selected as subsidence controlling factors in the study area including lithology, land cover/land use, elevation, slope, aspect, annual average rainfall, distance to faults, distance to earthquake epicenter, and distance to streams. The analytical hierarchy process is applied to obtain accurate weight to each criterion through the distribution of online Google form questionnaire to experts in different expertise and get their judgments on the weights of ground subsidence causative parameters in the study area. A subsidence susceptibility index was derived by classifying susceptible maps into five classes, namely, very low, low, moderate, high, and very high using the statistical distribution analysis. The results revealed that the study area is subjected to moderate susceptibility with about 32.56. A total of 29.8 and 11.52% of the study area had very low and low susceptibilities, respectively, and 8.44 and 17.68% had very high and high susceptibilities, respectively. The results were validated using the receiver operating characteristic using previous ground subsidence locations. The area under the curve showed 0.971, which is equivalent to 97.1%. Consequently, the findings of the study are thought to be beneficial to managers and decision makers for future planning, mitigating, and preventing subsidence in the study area.

Keywords

• geohazards
• multicriteria decision analysis
• al-shamal train pathway