Unraveling the hydraulic properties of loess for landslide prediction: A study on variations in loess landslides in Lanzhou, Dingxi, and Tianshui, China

ABSTRACT: Loess has distinctive characteristics, leading to frequent landslide disasters and posing serious threats to the lives and properties of local residents. The involvement of water represents a critical factor in inducing loess landslides. This study focuses on three neighboring cities seque...

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Main Authors: Gao-chao Lin, Wei Liu, Xing Su
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-04-01
Series:China Geology
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Online Access:http://www.sciencedirect.com/science/article/pii/S2096519224001101
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author Gao-chao Lin
Wei Liu
Xing Su
author_facet Gao-chao Lin
Wei Liu
Xing Su
author_sort Gao-chao Lin
collection DOAJ
description ABSTRACT: Loess has distinctive characteristics, leading to frequent landslide disasters and posing serious threats to the lives and properties of local residents. The involvement of water represents a critical factor in inducing loess landslides. This study focuses on three neighboring cities sequentially situated on the Loess Plateau along the direction of aeolian deposition of loess, namely Lanzhou, Dingxi, and Tianshui, which are densely populated and prone to landslide disasters. The variations in hydraulic properties, including water retention capacity and permeability, are investigated through Soil Water Characteristic Curve (SWCC) test and hydraulic conductivity test. The experimental findings revealed that Tianshui loess exhibited the highest water retention capacity, followed by Dingxi loess, while Lanzhou loess demonstrated the lowest water retention capacity. Contrastingly, the results for the saturated permeability coefficient were found to be the opposite: Tianshui loess showed the lowest permeability, whereas Lanzhou loess displayed the highest permeability. These results are supported and analyzed by scanning electron microscopy (SEM) observation. In addition, the water retention capacity is mathematically expressed using the van Genuchten model and extended to predict unsaturated hydraulic properties of loess. The experimental results exhibit a strong accordance with one another and align with the regional distribution patterns of disasters.
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spelling doaj-art-499e0e33a10e44b9a54dfe5e14376b682025-08-20T03:33:18ZengKeAi Communications Co., Ltd.China Geology2589-94302024-04-017229130210.31035/cg2024006Unraveling the hydraulic properties of loess for landslide prediction: A study on variations in loess landslides in Lanzhou, Dingxi, and Tianshui, ChinaGao-chao Lin0Wei Liu1Xing Su2School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, AustraliaInstitute of Transportation, Inner Mongolia University, Hohhot 010070, China; Corresponding author:Institute of Geological Hazards Prevention, Gansu Academy of Sciences, Lanzhou 730000, ChinaABSTRACT: Loess has distinctive characteristics, leading to frequent landslide disasters and posing serious threats to the lives and properties of local residents. The involvement of water represents a critical factor in inducing loess landslides. This study focuses on three neighboring cities sequentially situated on the Loess Plateau along the direction of aeolian deposition of loess, namely Lanzhou, Dingxi, and Tianshui, which are densely populated and prone to landslide disasters. The variations in hydraulic properties, including water retention capacity and permeability, are investigated through Soil Water Characteristic Curve (SWCC) test and hydraulic conductivity test. The experimental findings revealed that Tianshui loess exhibited the highest water retention capacity, followed by Dingxi loess, while Lanzhou loess demonstrated the lowest water retention capacity. Contrastingly, the results for the saturated permeability coefficient were found to be the opposite: Tianshui loess showed the lowest permeability, whereas Lanzhou loess displayed the highest permeability. These results are supported and analyzed by scanning electron microscopy (SEM) observation. In addition, the water retention capacity is mathematically expressed using the van Genuchten model and extended to predict unsaturated hydraulic properties of loess. The experimental results exhibit a strong accordance with one another and align with the regional distribution patterns of disasters.http://www.sciencedirect.com/science/article/pii/S2096519224001101LoessLandslideHydraulic propertiesWater retention capacity and permeabilitySoil Water Characteristic Curve (SWCC)Hydraulic conductivity
spellingShingle Gao-chao Lin
Wei Liu
Xing Su
Unraveling the hydraulic properties of loess for landslide prediction: A study on variations in loess landslides in Lanzhou, Dingxi, and Tianshui, China
China Geology
Loess
Landslide
Hydraulic properties
Water retention capacity and permeability
Soil Water Characteristic Curve (SWCC)
Hydraulic conductivity
title Unraveling the hydraulic properties of loess for landslide prediction: A study on variations in loess landslides in Lanzhou, Dingxi, and Tianshui, China
title_full Unraveling the hydraulic properties of loess for landslide prediction: A study on variations in loess landslides in Lanzhou, Dingxi, and Tianshui, China
title_fullStr Unraveling the hydraulic properties of loess for landslide prediction: A study on variations in loess landslides in Lanzhou, Dingxi, and Tianshui, China
title_full_unstemmed Unraveling the hydraulic properties of loess for landslide prediction: A study on variations in loess landslides in Lanzhou, Dingxi, and Tianshui, China
title_short Unraveling the hydraulic properties of loess for landslide prediction: A study on variations in loess landslides in Lanzhou, Dingxi, and Tianshui, China
title_sort unraveling the hydraulic properties of loess for landslide prediction a study on variations in loess landslides in lanzhou dingxi and tianshui china
topic Loess
Landslide
Hydraulic properties
Water retention capacity and permeability
Soil Water Characteristic Curve (SWCC)
Hydraulic conductivity
url http://www.sciencedirect.com/science/article/pii/S2096519224001101
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