Kinematics and Controlling Factors of Slow-Moving Landslides in Central Texas: A Multisource Data Fusion Approach

Esayas Gebremichael, Rosbeidy Hernandez, Helge Alsleben, Mohamed Ahmed, Richard Denne, Omar Harvey
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Abstract

The Austin metropolitan area has experienced unprecedented economic and population growth over the past two decades. This rapid growth is leading communities to settle in areas susceptible to landslides, necessitating a comprehensive analysis of landslide risks and the development of early warning systems. This could be accomplished with better confidence for slow-moving landslides, whose occurrences could be forecasted by monitoring precursory ground displacement. This study employed a combination of ground- and satellite-based observations and techniques to assess the kinematics of slow-moving landslides and identify the controlling and triggering factors that contribute to their occurrence. By closely examining landslide events in the Shoal Creek area, potential failure modes across the study area were inferred. The findings revealed that landslide-prone areas are undergoing creep deformation at an extremely slow rate (up to −4.29 mm/yr). These areas lie on moderate to steep slopes (>22°) and are predominantly composed of clay-rich units belonging to the Del Rio and Eagle Ford formations. Based on the incidents at Shoal Creek, episodes of intense rainfall acting on the landslide-prone areas are determined to be the main trigger for landslide processes in the region.
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德克萨斯州中部缓慢移动的山体滑坡的运动学和控制因素:多源数据融合方法
在过去二十年里,奥斯汀大都会地区经历了前所未有的经济和人口增长。这种快速增长导致一些社区在容易发生山体滑坡的地区定居,因此有必要对山体滑坡风险进行全面分析,并开发早期预警系统。对于缓慢移动的山体滑坡,可以通过监测前兆地面位移来预测其发生情况,从而更有把握地实现这一目标。这项研究综合利用地面和卫星观测数据和技术,评估了慢速滑坡的运动学特性,并确定了导致滑坡发生的控制和触发因素。通过仔细研究浅溪地区的滑坡事件,推断出整个研究区域的潜在破坏模式。研究结果表明,山体滑坡易发区正在以极其缓慢的速度(最多-4.29 毫米/年)发生蠕变变形。这些地区位于中等至陡峭的斜坡上(>22°),主要由属于德尔里奥和鹰滩地层的富含粘土的地层组成。根据 Shoal Creek 发生的事件,可以确定作用于滑坡易发区的强降雨事件是该地区滑坡过程的主要触发因素。
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