Slow-moving landslides are hydrologically driven. Yet, landslide sensitivity to precipitation, and in particular, precipitation extremes, is difficult to constrain because landslides occur under diverse hydroclimatological conditions. Here we use standardized open-access satellite radar interferometry data to quantify the sensitivity of 38 landslides to both a record drought and extreme rainfall that occurred in California between 2015 and 2020. These landslides are hosted in similar rock types, but span more than ∼2 m/yr in mean annual rainfall. Despite the large differences in hydroclimate, we found these landslides exhibited surprisingly similar behaviors and hydrologic sensitivity, which was characterized by faster (slower) than average velocities during wetter (drier) than average years, once the impact of the drought diminished. Our findings may be representative of future landslide behaviors in California where precipitation extremes are predicted to become more frequent with climate change.

Mapping and monitoring landslides in remote areas with steep and mountainous terrain is logistically challenging, expensive, and time consuming. Yet, in order to mitigate hazards and prevent loss of life in these areas, and to better understand landslide processes, high-resolution measurements of landslide activity are necessary. Satellite-based synthetic aperture radar interferometry (InSAR) provides millimeter-scale measurements of ground surface deformation that can be used to identify and monitor landslides in remote areas where ground-based monitoring techniques are not feasible. Here we present a novel InSAR deformation detection approach, which uses double difference time-series with local and regional spatial filters and pixel clustering methods to identify and monitor slow-moving landslides without making a priori assumptions of the location of landslides. We apply our analysis to freely available Copernicus Sentinel-1 satellite data acquired between 2014 and 2017 centered on the Trishuli River drainage basin in Nepal. We found a minimum of 6 slow-moving landslides that all occur within the Ranimatta lithologic formation (phyllites, metasandstones, metabasics). These landslides have areas ranging from 0.39 to 1.66 km2 and long-term dry-season displacement rates ranging from 2.1 to 8.8 cm/yr. Due to periods of low coherence during the monsoon season (June – September) each year, and following the 25 April 2015 Mw7.8 Gorkha earthquake, our time series analysis is limited to the 2014–2015 and 2016–2017 dry seasons (September–May). We found that each of the landslides displayed slightly higher rates during the 2014 period, likely as a result of higher cumulative rainfall that fell during the 2014 monsoon season. Although we do not have high quality InSAR data to show the landslide evolution directly following the Gorkha earthquake, the similar rates of movement before (2014–2015) and after (2016–2017) Gorkha suggest the earthquake had negligible long-term impact on these landslides. Our findings highlight the potential for region-wide mapping of slow-moving landslides using freely available remote sensing data in remote areas such as Nepal and future work will benefit from expanding our methodology to other regions around the world.

Understanding the evolution of continental deformation zones relies on quantifying spatial and temporal changes in deformation rates of tectonic structures. Along the eastern boundary of the Pamir-Tian Shan collision zone, we constrain secular variations of rock uplift rates for a series of five Quaternary detachment- and fault-related folds from their initiation to the modern day. When combined with GPS data, decomposition of interferometric synthetic aperture radar time series constrains the spatial pattern of surface and rock uplift on the folds deforming at decadal rates of 1–5 mm/yr. These data confirm the previously proposed basinward propagation of structures during the Quaternary. By fitting our geodetic rates and previously published geologic uplift rates with piecewise linear functions, we find that gradual rate changes over >100 kyr can explain the interferometric synthetic aperture radar observations where changes in average uplift rates are greater than ~1 mm/yr among different time intervals (~101, 104–5, and 105–6 years).

Global sea level provides an important indicator of the state of the warming climate, but changes in regional sea level are most relevant for coastal communities around the world. With improvements to the sea-level observing system, the knowledge of regional sea-level change has advanced dramatically in recent years. Satellite measurements coupled with in situ observations have allowed for comprehensive study and improved understanding of the diverse set of drivers that lead to variations in sea level in space and time. Despite the advances, gaps in the understanding of contemporary sea-level change remain and inhibit the ability to predict how the relevant processes may lead to future change. These gaps arise in part due to the complexity of the linkages between the drivers of sea-level change. Here we review the individual processes which lead to sea-level change and then describe how they combine and vary regionally. The intent of the paper is to provide an overview of the current state of understanding of the processes that cause regional sea-level change and to identify and discuss limitations and uncertainty in our understanding of these processes. Areas where the lack of understanding or gaps in knowledge inhibit the ability to provide the needed information for comprehensive planning efforts are of particular focus. Finally, a goal of this paper is to highlight the role of the expanded sea-level observation network-particularly as related to satellite observations-in the improved scientific understanding of the contributors to regional sea-level change.