{"title":"Spatial-temporal evolution of landslides spanning the impoundment of Baihetan mega hydropower project revealed by satellite radar interferometry","authors":"Jiaming Yao , Teng Wang , Xin Yao","doi":"10.1016/j.rse.2025.114668","DOIUrl":null,"url":null,"abstract":"<div><div>Reservoir landslides are the focus of geohazards associated with mega hydropower projects and have been extensively studied by monitoring their post-impoundment deformation. However, how landslide deformation changes before, during, and after impoundment is rarely known. Using satellite radar interferometry, we map 200 active landslides with their time-series deformation spanning the impoundment of Baihetan, the second-largest hydropower project globally. We define the amplitude of seasonal fluctuation (ASF) to analyze the impact of rainfall and water level on seasonal landslide velocities before and after impoundment. Interestingly, although landslides are overall accelerated, a reduction in seasonal fluctuation is apparent after the impoundment. We argue that the project elevated water levels during the dry season, only promoting landslide motion when they were kept stable before impoundment. We also find the 32 newly formed landslides are more likely to develop on slopes with structures related to river flow direction, emphasizing the role of the raised water in triggering new landslides. These findings reveal how landslides respond to mega hydropower projects, facilitating disaster risk management and resettlement policy regulation.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114668"},"PeriodicalIF":11.1000,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425725000720","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Reservoir landslides are the focus of geohazards associated with mega hydropower projects and have been extensively studied by monitoring their post-impoundment deformation. However, how landslide deformation changes before, during, and after impoundment is rarely known. Using satellite radar interferometry, we map 200 active landslides with their time-series deformation spanning the impoundment of Baihetan, the second-largest hydropower project globally. We define the amplitude of seasonal fluctuation (ASF) to analyze the impact of rainfall and water level on seasonal landslide velocities before and after impoundment. Interestingly, although landslides are overall accelerated, a reduction in seasonal fluctuation is apparent after the impoundment. We argue that the project elevated water levels during the dry season, only promoting landslide motion when they were kept stable before impoundment. We also find the 32 newly formed landslides are more likely to develop on slopes with structures related to river flow direction, emphasizing the role of the raised water in triggering new landslides. These findings reveal how landslides respond to mega hydropower projects, facilitating disaster risk management and resettlement policy regulation.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.