1 Introduction
A foundational paradigm in landslide science is that precipitation
triggers landslides. Precipitation promotes slope instability as water
flows through the ground and raises the water table, or creates perched
water tables, and as a result, increases pore-water pressures, reduces
the effective normal stress (normal stress minus pore-water pressure),
and reduces the frictional strength of the hillslope (Bogaard & Greco,
2016; Terzaghi, 1951). Once a hillslope fails as a landslide it can
accelerate rapidly and fail catastrophically (Iverson et al., 2015;
Jibson, 2006; Shugar et al., 2021), move downslope slowly for years to
hundreds of years (Mackey et al., 2009; Nereson & Finnegan, 2019;
Rutter & Green, 2011), or move slowly for a period of time before
stabilizing or failing catastrophically (Agliardi et al., 2020;
Handwerger, Huang, et al., 2019; Iverson, 2005; Kilburn & Petley,
2003). These different behavioral modes have important consequences for
hazard assessment because fast-moving landslides can move at rates up to
tens of meters per second and can easily claim lives (Iverson et al.,
2015; Shugar et al., 2021), while slow-moving landslides move at rates
of meters per year or less and can damage infrastructure (Lacroix,
Handwerger, et al., 2020; Merriam, 1960).
Persistently active slow-moving landslides are well-suited for exploring
hydrologic controls on landslide motion because they are relatively easy
to monitor (compared to landslides with catastrophic failures), occur in
wet and dry environments around the world where water is delivered by
rainfall (Bayer et al., 2018; Malet et al., 2002), snowmelt (Coe et al.,
2003; Matsuura et al., 2008), or irrigation (Lacroix, Dehecq, et al.,
2020; Merriam, 1960), and their motion is closely linked to local
groundwater conditions (Corominas et al., 2005; Iverson & Major, 1987;
Murphy et al., 2022). Furthermore, the hydrologic controls on
slow-moving landslides, via pore pressure changes, are akin to the
hydrologic controls on faults (Bhattacharya & Viesca, 2019; Cappa et
al., 2019), glaciers (Minchew & Meyer, 2020; Moon et al., 2014), and
rock glaciers (Cicoira et al., 2019; Kenner et al., 2017), and therefore
investigating these landslides allows us to better understand each
system.
Previous investigations on the hydrologic controls on slow-moving
landslides have shown that precipitation causes slow-moving landslides
to accelerate once the pore-water pressures have increased to sufficient
levels in the landslide body and decelerate when the pore-water
pressures drop (Finnegan et al., 2021; Iverson & Major, 1987; Malet et
al., 2002). Thus, slow-moving landslides can slow down or stop moving
during dry periods, and speed up, reactivate, or fail catastrophically
during wet periods (Bennett, Roering, et al., 2016; Handwerger,
Fielding, et al., 2019; McSaveney & Griffiths, 1987; Nereson &
Finnegan, 2019). The hydrologic response of landslides can also be
size-dependent where larger and thicker landslides are somewhat less
sensitive to daily to annual changes in rainfall compared to smaller and
thinner landslides that typically experience greater swings in
pore-water pressure (Bennett, Roering, et al., 2016; Handwerger,
Fielding, et al., 2019). Indeed, this is an expected consequence of pore
water transmission in saturated ground (Iverson and Major, 1987).
However, recent work by Finnegan et al. (2021) shows nearly
instantaneous pore pressure transmission to depth once the vadose zone
of the Oak Ridge landslide, California becomes saturated each year,
which suggests vadose zone thickness, rather than total landslide
thickness, may be the relevant length scale controlling the landslide
response in settings where the surface of a landslide becomes
unsaturated, for example in locations with highly seasonal rainfall
delivery. Nonetheless, both climate and landslide size may govern the
hydrologic sensitivity of landslides.
Satellite-based interferometric synthetic aperture radar (InSAR) data
can be analyzed alongside precipitation and groundwater data and used to
inventory and monitor landslides with the high spatial and temporal
resolution necessary to explore hydrologic controls on landslide motion
(Bayer et al., 2018; Cohen-Waeber et al., 2018; Handwerger et al.,
2013). The open-access data collected by Copernicus Sentinel-1 A/B
satellites, in particular, has revolutionized InSAR studies on
landslides (Bayer et al., 2018; Carlà et al., 2019; Handwerger, Huang,
et al., 2019; Intrieri et al., 2017; Liu et al., 2021; Raspini et al.,
2018), and other ground surface deformation (Cigna & Tapete, 2021;
Huang et al., 2017; Lundgren et al., 2020; Strozzi et al., 2020), and
has led to the development of automated InSAR processing systems that
produce derived higher-level standard products that can be used for
scientific research (Buzzanga et al., 2020; Dehls et al., 2019; Jones et
al., 2021; Lazecký et al., 2020). These derived standard products will
become especially important as the volume of InSAR data continues to
grow, making it increasingly challenging to process and download InSAR
data for large regions on a personal computer. Furthermore, the recent
push to provide open-access standardized InSAR products, along with a
suite of tools to analyze these data (e.g., Morishita et al., 2020;
Yunjun et al., 2019), increases data accessibility to the broader
geoscience community, which will undoubtedly lead to major scientific
advances.
In this study we analyze open-access standardized Sentinel-1
interferograms automatically processed by the JPL-Caltech Advanced Rapid
Imaging and Analysis (ARIA) Center for Natural Hazards project (Bekaert
et al., 2019) to identify and monitor landslides in both wet and dry
climates in California, USA. California has a large quantity of active
slow-moving landslides and has been a major focus area for landslide
investigations for decades (Iverson & Major, 1987; Keefer & Johnson,
1983; Kelsey, 1978; Merriam, 1960). Slow-moving landslides in California
exhibit distinct seasonal kinematic patterns (Cohen-Waeber et al., 2018;
Finnegan et al., 2021; Handwerger et al., 2013; Iverson & Major, 1987)
that are a consequence of the regions Mediterranean climate with mild
wet winters and hot dry summers, and multi-year kinematic changes that
result from precipitation deficits or surplus (Bennett, Roering, et al.,
2016; Booth et al., 2020; Mackey et al., 2009; Nereson & Finnegan,
2019). California also has a large rainfall gradient from north to south
and west to east, with parts of northern California receiving
> 3000 mm/yr of rainfall and parts of southern California
receiving < 200 mm/yr (Figure 1a). There are slow-moving
landslides in both wet and dry regions of California, which presents an
opportunity to examine how variability in hydroclimatology controls
landslide behaviors.