TY - JOUR

T1 - Reactivation of an old landslide in north–central Iran following reservoir impoundment

T2 - Results from multisensor satellite time-series analysis

AU - Vassileva, Magdalena

AU - Motagh, Mahdi

AU - Roessner, Sigrid

AU - Xia, Zhuge

N1 - Funding Information: The authors want to dedicate this work in memory to their late colleague Dr. Hans-Ulrich Wetzel, a geologist and pioneer in the use of remote sensing in geology who worked for the German Research Centre for Geosciences since its foundation in 1992. The authors acknowledge the Geological Survey of Iran for the geological map. The authors acknowledged the Copernicus programme for the free access to Sentinel-1 data available on the U.S. Geological Survey for Landsat 8 Collection 1 Tier 1 orthorectified scenes freely available on https://earthexplorer.usgs.gov/. The authors acknowledge The Planet Lab PBC, 2017, for providing the PlanetScope data via the Planet application program interface: In Space for Life on Earth. San Francisco, CA. https://api.planet.comand] the USGS Earth Resources Observation and Science (EROS) Center for creating and making freely available CHIRPS rainfall dataset. This work was partially supported by Helmholtz Imaging Platform (project: MultiSaT4SLOWS). Funding Information: The authors acknowledge the Geological Survey of Iran for the geological map. The authors acknowledged the Copernicus programme for the free access to Sentinel-1 data available on the U.S. Geological Survey for Landsat 8 Collection 1 Tier 1 orthorectified scenes freely available on https://earthexplorer.usgs.gov/ . The authors acknowledge The Planet Lab PBC, 2017, for providing the PlanetScope data via the Planet application program interface: In Space for Life on Earth. San Francisco, CA. https://api.planet.comand ] the USGS Earth Resources Observation and Science (EROS) Center for creating and making freely available CHIRPS rainfall dataset. This work was partially supported by Helmholtz Imaging Platform (project: MultiSaT4SLOWS).

PY - 2023/12/20

Y1 - 2023/12/20

N2 - Water impoundment combined with more frequent precipitation extremes due to climate change increases landslide hazards on the slopes surrounding dam reservoirs. In situ monitoring systems in these potential landslide-prone areas are often unavailable, making landslide failures challenging to forecast. This paper describes a multisensor and multivariate remote sensing approach using data from Envisat, Sentinel-1, Landsat and PlanetScope satellites to reconstruct the spatiotemporal evolution of the mechanism and causes of the March 2019 landslide failure backside of the dam reservoir in Hoseynabad-e Kalpush village, north–central Iran. Statistical analysis and time series clustering are performed to derive the main landslide kinematic features from multitemporal interferometric synthetic aperture radar (MT-InSAR) analysis. We also exploit GIS and wavelet analysis to correlate potential external driving factors with landslide kinematics. Envisat and Sentinel-1 MT-InSAR analyses revealed that a previously stable old landslide was reactivated following reservoir impoundment in early 2013. As the reservoir water level rose during the following years up to 34 m in 2019, the landslide displacement rate gradually increased from 3.5 cm/yr to 8.4 cm/yr, and the destabilization gradually propagated upslope. At this stage, seasonal precipitation effects were detected only in the vertical component, indicating swelling and shrinkage movements of the shallower soil layer. The reactivated landslide accelerated and catastrophically failed following the exceptional precipitation in early 2019, producing a horizontal shift of >40 m, detected with optical image digital correlation. In the aftermath, the landslide continued to move with a decreasing trend until final stabilization in October 2021. Our study demonstrates how combined observations derived from multisensor satellite remote sensing data can be used to assess landslide precursors and kinematics, as well as the influence of climatic and anthropogenic factors on the instability of slopes surrounding water reservoirs. This is especially relevant in data-scarce areas.

AB - Water impoundment combined with more frequent precipitation extremes due to climate change increases landslide hazards on the slopes surrounding dam reservoirs. In situ monitoring systems in these potential landslide-prone areas are often unavailable, making landslide failures challenging to forecast. This paper describes a multisensor and multivariate remote sensing approach using data from Envisat, Sentinel-1, Landsat and PlanetScope satellites to reconstruct the spatiotemporal evolution of the mechanism and causes of the March 2019 landslide failure backside of the dam reservoir in Hoseynabad-e Kalpush village, north–central Iran. Statistical analysis and time series clustering are performed to derive the main landslide kinematic features from multitemporal interferometric synthetic aperture radar (MT-InSAR) analysis. We also exploit GIS and wavelet analysis to correlate potential external driving factors with landslide kinematics. Envisat and Sentinel-1 MT-InSAR analyses revealed that a previously stable old landslide was reactivated following reservoir impoundment in early 2013. As the reservoir water level rose during the following years up to 34 m in 2019, the landslide displacement rate gradually increased from 3.5 cm/yr to 8.4 cm/yr, and the destabilization gradually propagated upslope. At this stage, seasonal precipitation effects were detected only in the vertical component, indicating swelling and shrinkage movements of the shallower soil layer. The reactivated landslide accelerated and catastrophically failed following the exceptional precipitation in early 2019, producing a horizontal shift of >40 m, detected with optical image digital correlation. In the aftermath, the landslide continued to move with a decreasing trend until final stabilization in October 2021. Our study demonstrates how combined observations derived from multisensor satellite remote sensing data can be used to assess landslide precursors and kinematics, as well as the influence of climatic and anthropogenic factors on the instability of slopes surrounding water reservoirs. This is especially relevant in data-scarce areas.

KW - Dam reservoir

KW - Digital image correlation

KW - Landslide

KW - MT-InSAR

KW - Satellite remote sensing

KW - Time-series analysis

UR - http://www.scopus.com/inward/record.url?scp=85178056703&partnerID=8YFLogxK

U2 - 10.1016/j.enggeo.2023.107337

DO - 10.1016/j.enggeo.2023.107337

M3 - Article

AN - SCOPUS:85178056703

VL - 327

JO - Engineering geology

JF - Engineering geology

SN - 0013-7952

M1 - 107337

ER -