基于土壤水分和地貌数据的降雨诱发滑坡灾害分析

IF 2.8 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Daniel M. Francis, L. Sebastian Bryson
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引用次数: 0

摘要

降雨引发的山体滑坡威胁着住宅和民用基础设施。由于极端降雨事件随着气候变率的增加而增加,因此有效监测这些事件的必要性也在增加。然而,滑坡发生的物理监测需要昂贵的仪器,覆盖大面积。因此,需要一种大规模空间监测的手段。本文对已知空间分布的降雨诱发浅层崩塌滑坡进行了边坡无限稳定性分析。考虑到所研究的浅层滑坡的适用性,选择了无限边坡分析。研究了空间地貌和时空土壤水分数据的作用。这些分析的基本假设是,土壤湿度将作为降雨诱发滑坡的水力力学前兆。这些分析的大部分地貌数据是通过网络数据库获得的。相反,观察到摩擦角的测量没有空间可用性。为了解决这个问题,开发了人工神经网络(ANN)机器学习工作流程来产生这些必要的测量。对于时空土壤湿度,利用土地信息系统(LIS)对NOAH 3.6 LSM和NASA SMAP L3SMP_E水分估算值进行同化。LIS工作流程产生了不同深度和精细分辨率下的土壤湿度估计。随着空间地貌和时空土壤水分的可用性,本研究转向了相关的稳定性分析。这些分析集中在美国肯塔基州东部的一个地区,该地区经历了一次极端降雨和随后的山体滑坡事件。通过这些分析,大多数发生的滑坡能够在观测到的土壤湿度增加的地区被发现。因此,本研究证实了土壤水分可以作为降雨诱发滑坡发生的水力学前兆的基本假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Rainfall-induced landslide hazard analyses using spatiotemporal retrievals of soil moisture and geomorphologic data

Rainfall-induced landslide hazard analyses using spatiotemporal retrievals of soil moisture and geomorphologic data

Rainfall-induced landslides threaten residential and civil infrastructure. As extreme rainfall events increase with climatological variability, so does the need to effectively monitor these occurrences. However, physical monitoring of landslide occurrence requires costly instrumentation over vast areas. Therefore, a means for large scale spatial monitoring is desired. This study conducts infinite slope stability analyses on known spatially distributed rainfall-induced shallow colluvial landslides. Infinite slope analyses were chosen due to applicability to the investigated shallow landslides. These analyses were investigated as functions of spatial geomorphologic and spatiotemporal soil moisture data. The underlying assumption of these analyses was that soil moisture would act as a hydro-mechanical precursor for rainfall-induced landslides. A majority of geomorphologic data for these analyses was obtained via web databases. Contrarily, it was observed that measurements of friction angle were not spatially available. To remedy this, an Artificial Neural Network (ANN) machine learning workflow was developed to yield these requisite measurements. For spatiotemporal soil moisture, the Land Information System (LIS) was utilized to conduct assimilation of NOAH 3.6 LSM and NASA SMAP L3SMP_E moisture estimates. The LIS workflow yielded soil moisture estimates at various depths and fine resolutions. With spatial geomorphologic and spatiotemporal soil moisture available, this study moved towards the associated stability analyses. These analyses were focused upon a region of Eastern Kentucky, USA, which experienced an extreme rainfall and subsequent landslide event. Through these analyses, a majority of occurred landslides were able to be detected in areas observed to experience increases in soil moisture. Therefore, this study confirmed the underlying assumption that soil moisture can serve as a hydro-mechanical precursor for rainfall-induced landslide occurrence.

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来源期刊
Environmental Earth Sciences
Environmental Earth Sciences 环境科学-地球科学综合
CiteScore
5.10
自引率
3.60%
发文量
494
审稿时长
8.3 months
期刊介绍: Environmental Earth Sciences is an international multidisciplinary journal concerned with all aspects of interaction between humans, natural resources, ecosystems, special climates or unique geographic zones, and the earth: Water and soil contamination caused by waste management and disposal practices Environmental problems associated with transportation by land, air, or water Geological processes that may impact biosystems or humans Man-made or naturally occurring geological or hydrological hazards Environmental problems associated with the recovery of materials from the earth Environmental problems caused by extraction of minerals, coal, and ores, as well as oil and gas, water and alternative energy sources Environmental impacts of exploration and recultivation – Environmental impacts of hazardous materials Management of environmental data and information in data banks and information systems Dissemination of knowledge on techniques, methods, approaches and experiences to improve and remediate the environment In pursuit of these topics, the geoscientific disciplines are invited to contribute their knowledge and experience. Major disciplines include: hydrogeology, hydrochemistry, geochemistry, geophysics, engineering geology, remediation science, natural resources management, environmental climatology and biota, environmental geography, soil science and geomicrobiology.
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