Slow-moving landslides move downslope at velocities that range from mm year−1 to m year−1. Such deformations can be measured using satellite-based synthetic aperture radar interferometry (InSAR). We developed a new method to systematically detect and quantify accelerations and decelerations of slowly deforming areas using InSAR displacement time series. The displacement time series are filtered using an outlier detector and subsequently piecewise linear functions are fitted to identify changes in the displacement rate (i.e., accelerations or decelerations). Grouped accelerations and decelerations are inventoried as indicators of potential unstable areas. We tested and refined our new method using a high-quality dataset from the Mud Creek landslide, CA, USA. Our method detects accelerations and decelerations that coincide with those previously detected by manual examination. Second, we tested our method in the region around the Mazar dam and reservoir in Southeast Ecuador, where the time series data were of considerably lower quality. We detected accelerations and decelerations occurring during the entire study period near and upslope of the reservoir. Application of our method results in a wealth of information on the dynamics of the surface displacement of hillslopes and provides an objective way to identify changes in displacement rates. The displacement rates, their spatial variation, and the timing of accelerations and decelerations can be used to study the physical behavior of a slow-moving slope or for regional hazard assessment by linking the timing of changes in displacement rates to landslide causal and triggering factors.

The high landslide risk potential along the steep hillslopes of the Eastern Andes in Ecuador provides challenges for hazard mitigation, especially in areas with hydropower dams and reservoirs. The objective of this study was to characterize, understand, and quantify the mechanisms driving the motions of the Guarumales landslide. This 1.5 km2 deep-seated, slow-moving landslide is actively moving and threatening the “Paute Integral” hydroelectric complex. Building on a long time series of measurements of surface displacement, precipitation, and groundwater level fluctuations, we analyzed the role of predisposing conditions and triggering factors on the stability of the landslide. We performed an analysis of the time series of measured groundwater levels and drainage data using transfer functions. The geological interpretation of the landslide was further revised based on twelve new drillings. This demonstrated a locally complex system of colluvium deposits overlying a schist bedrock, reaching up to 100 m. The measured displacement rates were nearly constant at ~50 mm/year over the 18 years of study. However, the measurement accuracy and time resolution were too small to identify possible acceleration or deceleration phases in response to hydro-meteorological forcing. The groundwater and slope drainage data showed a lagged response to rainfall. Finally, we developed a conceptual model of the Guarumales landslide, which we hope will improve our understanding of the many other deep-seated landslides present in the Eastern Andes.

<p>Regional-scale landslide deformation can be measured using satellite-based synthetic aperture radar interferometry (InSAR). Our study focuses on the quantification of displacements of slow-moving landslides that impact a hydropower dam and reservoir in the tropical Ecuadorian Andes. We constructed ground surface deformation time series using data from the Copernicus Sentinel-1 A/B satellites between 2016 and 2020. We developed a new approach to automatically detect the onset of accelerations and/or decelerations within each active landslide. Our approach approximates the movement of a pixel as a piecewise linear function. Multiple linear segments are fitted to the cumulative deformation time series of each pixel. Each linear segment represents a constant movement. The point where one linear segment is connected to another linear segment represents the time when the pixel’s rate of movement has changed from one value to another value and is referred to as a breakpoint. As such, the breakpoints represent moments of acceleration or deceleration. Three criteria are used to determine the number of breakpoints: the timing and uncertainty of the breakpoints, the confidence intervals of the fitted segments’ slopes, and the Akaike Information Criterion (AIC). The suitable number of breakpoints for each pixel (i.e., the number of accelerations or decelerations) is determined by finding the largest number of breakpoints that complies with the three listed criteria. The application of this approach to landslides results in a wealth of information on the surface displacement of a slope and an objective way to identify changes in displacement rates. The displacement rates, their spatial variation, and the timing of acceleration and deceleration can further be used to study the physical behavior of a slow-moving slope or for (regional) hazard assessment linking the onset of change in displacement rate to causal and triggering factors.</p>