A time-lapse camera was used to document periodic reactivation of a complex landslide on a steep coastal bluff in Mukilteo, Washington. This landslide is one of four monitoring sites initiated by the U.S Geological Survey to investigate hill-slope hydrology and landslide hazards affecting the railway corridor along the eastern shore of Puget Sound between the cities of Seattle and Everett (Mirus et al., 2016; Smith et al. 2017). The camera was installed in the crown of the landslide above the main scarp facing roughly North, with a field of view that includes the head of the landslide body and a minor scarp below. The attached file ‘CameraLocation.PNG’ provides an overview figure of the landslide and the camera’s location relative to the different monitoring stations. It recorded imagery from August 19th, 2015 through May 25th, 2016. The time-lapse photos were taken three times daily (at 9 am, 12 pm, and 4 pm, PST) and stored onsite on a memory card; corresponding intervals between the photographs were 3 hours, 4 hours, and 17 hours (overnight). The time-lapse photos were compiled into a video and five periods of distinct ground movement were identified. Apparent slow and consistent slope-surface movements are recorded during these periods, but subsequent site visits suggest that these slow displacements indirectly triggered topples and debris-avalanche movements both up slope and down slope of the camera’s field of view. The approximate sizes of topples and debris avalanches were on the order of 10^5 –10^7 cubic centimetres. The video captures slope movements during the time periods of December 8–9, 2015; January 21–30, 2016; and March 9–14, 2016. In addition, the video shows two seemingly “instantaneous” events during the nights of March 23 and March 26. Each of these periods of slope movement also correspond to observed rainfall events and associated subsurface hydrologic responses documented elsewhere (Mirus et al. 2017; Smith et al. 2017). The time-lapse video can be found in the attached .mp4 file "mukilteo_timelapse_video.mp4" The individual time-lapse photos can be downloaded from the attached zip file "mukilteo_timelapse_photos.zip." More detailed information about the camera and settings used can be found in the metadata file. The following citations relate to reports that provides background information and are intended to accompany this data release. Mirus, B. B., Smith, J. B., Stark, B., Lewis, Y., Michel, A., & Baum, R. L. (2016). Assessing landslide potential on coastal bluffs near Mukilteo, Washington—Geologic site characterization for hydrologic monitoring. (U.S. Geological Survey Open-File Rep., 2016-1082, 28). Reston, VA: U.S. Geological Survey. https://doi.org/10.3133/ofr20161082 Smith, J. B., Baum, R. L., Mirus, B. B., Michel, A., & Stark, B. (2017). Results of hydrologic monitoring on landslide-prone coastal bluffs near Mukilteo, Washington (U.S. Geological Survey Open-File Rep., 2017–1095, 47 p.). Reston, VA: U.S. Geological Survey. https://doi.org/10.3133/ofr20171095 Mirus, B. B., Smith, J. B., & Baum, R. L. (2017). Hydrologic impacts of landslide disturbances: implications for remobilization and hazard persistence. Water Resources Research, 53. https://doi.org/10.1002/2017WR020842

The West Hills of Portland, in the southern Tualatin Mountains, trend northwest along the west side of Portland, Oregon. These silt-mantled mountains receive significant wet-season precipitation and are prone to sliding during wet conditions, occasionally resulting in significant property damage or casualties. In an effort to develop a baseline for interpretive analysis of the groundwater response to rainfall, an automated monitoring system was installed in 2006 to measure rainfall, pore-water pressure, soil suction, soil-water potential, and volumetric water content at 15-minute intervals. The data show a cyclical pattern of groundwater and moisture content levels—wet from October to May and dry between June and September. Saturated soil conditions tend to last throughout the wet season. This release presents data collected from January 10, 2006, through January 23,2017.

This data release includes time-series data and qualitative descriptions from a monitoring station on a steep, landslide-prone slope above the City of Sitka, Alaska. On August 18, 2015, heavy rainfall triggered around 60 landslides in and around Sitka. These landslides moved downslope rapidly; several were damaging, and one demolished a home on South Kramer Avenue and killed three people. On September 16-18, 2019, the U.S. Geological Survey installed instrumentation at a site near the initiation zones of these landslides and other previous landslides on the west face of Harbor Mountain. The station consists of an electronics enclosure, a mounted rain gage, and two instrumented soil pits. Instruments record continuous measurements of precipitation, air temperature, volumetric water content, pore-water pressure, soil temperature, and soil matric potential at five-minute intervals. Soil pits were dug as deep as possible into the soil mantle for installation of the hydrologic monitoring instruments. Extensive probing with a 1.2-m-long piece of rebar to the point of refusal confirmed that the bottom of each hole was near the top of bedrock or compact till. The first soil pit (SP1), located at N 57.08551, W 135.35936, is about 1 m downslope from the north rim of the drainage hollow. SP1 is about 60 cm deep with the upper 12-15 cm in dark brown, moist, silty sand with large concentration of plant roots. Below 15 cm, to bottom of hole, consists of abundant gray sandstone clasts in silty sand matrix, which ranges in color from orange-brown, brown, to gray. The SP1 sensor array consists of a water potential sensor and soil moisture sensor at 25 cm depth, a second soil moisture sensor at 50 cm depth, and a pressure transducer near bottom of hole with a port at ~55 cm depth. The second soil pit (SP2), located at N 57.08548, W 135.35933, is about 5 m downslope from the north rim of the drainage hollow and is 65 cm deep. The top of hard material (bedrock or till) was about 70 cm deep, but there was free water at a depth of about 50-55 cm. Material throughout the depth of the hole was moist sandy silty clay of a gelatinous consistency. Color ranged from orange-brown to dark brown. Very few stones were present. These soils were interpreted as transported/mixed, weathered volcanic ash (Jacqueline Foss, USDA Forest Service, personal communication, 2019). The SP2 sensor array consists of soil moisture sensors at 25 and 40 cm depth, and a pressure transducer lying on the bottom of the hole, with a port at about 60 cm depth. A Campbell Scientific CR1000 datalogger is used to collect continuous data from these sensors. The datalogger and modem are contained in a sealed, weather-resistant fiberglass enclosure. The CR1000 datalogger contains an internal thermistor that continuously measures temperature. Additionally, an air temperature sensor was installed to collect continuous air temperature data. A tipping bucket rain gage installed in a clearing about 10 m northwest of the logger enclosure collects precipitation data. The maximum resolution of the rain gauge is 0.2 mm; that is, one tip of the bucket represents 0.2 mm. Four METER ECH20 EC-5 sensors are used to collect soil moisture data. Pore-water pressures are measured using two Campbell Scientific CS-451 pressure transducers. A METER MPS-6 water potential sensor in SP1 is used to collect soil matric potential. This sensor’s measurements range from -100,000 to -9 kPa was exceeded for the duration of the monitoring period. Recorded values appear to hover around the sensor’s upper limit (-9 kPa), with the exception of September 2019 when the station was first installed and a few brief periods in July 2022 when conditions were sufficiently dry for matric potentials to drop below -9 kPa. The water potential sensor and pressure sensors have integrated thermistors and the associated temperature readings are included. Several factors that may influence data consistency and/or quality should be

This data release includes time-series data and qualitative descriptions from a monitoring station on a steep, landslide-prone slope above the City of Sitka, Alaska. On August 18, 2015, heavy rainfall triggered around 60 landslides in and around Sitka. These landslides moved downslope rapidly; several were damaging, and one demolished a home on South Kramer Avenue and killed three people. On September 16-18, 2019, the U.S. Geological Survey installed instrumentation at a site near the initiation zones of these landslides and other previous landslides on the west face of Harbor Mountain. The station consists of an electronics enclosure, a mounted rain gage, and two instrumented soil pits. Instruments record continuous measurements of precipitation, air temperature, volumetric water content, pore-water pressure, soil temperature, and soil matric potential at five-minute intervals. Soil pits were dug as deep as possible into the soil mantle for installation of the hydrologic monitoring instruments. Extensive probing with a 1.2-m-long piece of rebar to the point of refusal confirmed that the bottom of each hole was near the top of bedrock or compact till. The first soil pit (SP1), located at N 57.08551, W 135.35936, is about 1 m downslope from the north rim of the drainage hollow. SP1 is about 60 cm deep with the upper 12-15 cm in dark brown, moist, silty sand with large concentration of plant roots. Below 15 cm, to bottom of hole, consists of abundant gray sandstone clasts in silty sand matrix, which ranges in color from orange-brown, brown, to gray. The SP1 sensor array consists of a water potential sensor and soil moisture sensor at 25 cm depth, a second soil moisture sensor at 50 cm depth, and a pressure transducer near bottom of hole with a port at ~55 cm depth. The second soil pit (SP2), located at N 57.08548, W 135.35933, is about 5 m downslope from the north rim of the drainage hollow and is 65 cm deep. The top of hard material (bedrock or till) was about 70 cm deep, but there was free water at a depth of about 50-55 cm. Material throughout the depth of the hole was moist sandy silty clay of a gelatinous consistency. Color ranged from orange-brown to dark brown. Very few stones were present. These soils were interpreted as transported/mixed, weathered volcanic ash (Jacqueline Foss, USDA Forest Service, personal communication, 2019). The SP2 sensor array consists of soil moisture sensors at 25 and 40 cm depth, and a pressure transducer lying on the bottom of the hole, with a port at about 60 cm depth. A Campbell Scientific CR1000 datalogger is used to collect continuous data from these sensors. The datalogger and modem are contained in a sealed, weather-resistant fiberglass enclosure. The CR1000 datalogger contains an internal thermistor that continuously measures temperature. Additionally, an air temperature sensor was installed to collect continuous air temperature data. A tipping bucket rain gage installed in a clearing about 10 m northwest of the logger enclosure collects precipitation data. The maximum resolution of the rain gauge is 0.2 mm; that is, one tip of the bucket represents 0.2 mm. Four METER ECH20 EC-5 sensors are used to collect soil moisture data. Pore-water pressures are measured using two Campbell Scientific CS-451 pressure transducers. A METER MPS-6 water potential sensor in SP1 is used to collect soil matric potential. This sensor’s measurements range from -100,000 to -9 kPa was exceeded for the duration of the monitoring period. Recorded values appear to hover around the sensor’s upper limit (-9 kPa), with the exception of September 2019 when the station was first installed and a few brief periods in July 2022 when conditions were sufficiently dry for matric potentials to drop below -9 kPa. The water potential sensor and pressure sensors have integrated thermistors and the associated temperature readings are included. Several factors that may influence data consistency and/or quality should be

We performed hourly monitoring of conditions at the Two Towers landslide located in northern California near the town of Zenia. Monitored conditions included rainfall, groundwater head, horizontal total stress, horizontal effective stress, vertical soil deformation, and subsurface displacement. Data were acquired November 11, 2014–July 22, 2017, except for times during which power failure occurred; data for these times are given as “NAN” (not a number). Rainfall data are provided in millimeters during the past hour (mm/hr). Groundwater heads are provided in meters (m) above the landslide base. Horizontal stresses are provided in kilopascals (kPa). Vertical soil deformation data are provided in terms of length (centimeters, cm) of the sensor. Cumulative landslide displacement is provided in millimeters (mm). Rainfall was measured at the landslide middle monitoring location using a tipping-bucket rain gauge with resolution of 0.254 mm and accuracy of ±2% to 250 mm/hr (resolutions and accuracies stated herein are as specified by sensor manufacturers and accounting for datalogger resolution). A vibrating-wire total-stress plate sensor was installed with near-vertical orientation in the floor of an excavated pit at the middle monitoring location. This sensor measured total horizontal stress applied to its 230-mm-diameter surface with resolution of 0.014 kPa and accuracy of ±0.069 kPa. The sensor was installed within a slot slightly wider than the plate itself with its center at a depth of 1.83 m, and a vibrating-wire fluid pressure transducer with the same resolution and accuracy as the total stress sensor was installed adjacent to the cell to measure fluid pressure and therefore provide a means of calculating horizontal effective stress. The pit was backfilled after sensor installation with material removed during its excavation. The remaining sensors were installed within 6.35-cm-diameter holes bored using hand equipment. These included electronic, vibrating-wire fluid pressure transducers (piezometers) with resolutions of 0.014 kPa and 0.086 kPa, and respective accuracies of ±0.069 kPa and ±0.344 kPa. Boreholes were backfilled above transducers first with ~0.3 m of material obtained during boring followed by bentonite granules to the ground surface. Piezometers were installed at depths of 3.66 m and 6.07 m at the upper monitoring location, 3.95 m and 5.69 m at the middle monitoring location, and 2.62 and 3.66 m at the lower monitoring location. Landslide basal depths were identified at approximately 6.3 m, 7.9 m, and 3.6 m at the upper, middle, and lower monitoring locations, respectively. A 30.48-cm-long biaxial tilt sensor installed within PVC casing (slope inclinometer) was used to monitor landslide displacement at the lower monitoring location. The slope inclinometer has 0.003 mm displacement resolution and long-term displacement accuracy of ±0.23 mm. A vibrating-wire length sensor was installed in a borehole to measure near-surface vertical deformation at the middle monitoring location. This sensor measured length with 0.0375 mm resolution and ±0.15 mm accuracy. The sensor’s upper and lower ends were anchored within cement grout such that its length was measured over a depth range (at installation) of 0.20-1.72 m. All sensors contain thermistors and readings are temperature compensated, with the exception of the rain gauge. These data support a study described in Schulz, W.H., Smith, J.B., Wang, G., Jiang, Y., and Roering, J.J., 2018, Clayey landslide initiation and acceleration strongly modulated by soil swelling: Geophysical Research Letters, DOI:10.1002/2017GL076807.

We performed hourly monitoring of conditions at the Two Towers landslide located in northern California near the town of Zenia. Monitored conditions included rainfall, groundwater head, horizontal total stress, horizontal effective stress, vertical soil deformation, and subsurface displacement. Data were acquired November 11, 2014–July 22, 2017, except for times during which power failure occurred; data for these times are given as “NAN” (not a number). Rainfall data are provided in millimeters during the past hour (mm/hr). Groundwater heads are provided in meters (m) above the landslide base. Horizontal stresses are provided in kilopascals (kPa). Vertical soil deformation data are provided in terms of length (centimeters, cm) of the sensor. Cumulative landslide displacement is provided in millimeters (mm). Rainfall was measured at the landslide middle monitoring location using a tipping-bucket rain gauge with resolution of 0.254 mm and accuracy of ±2% to 250 mm/hr (resolutions and accuracies stated herein are as specified by sensor manufacturers and accounting for datalogger resolution). A vibrating-wire total-stress plate sensor was installed with near-vertical orientation in the floor of an excavated pit at the middle monitoring location. This sensor measured total horizontal stress applied to its 230-mm-diameter surface with resolution of 0.014 kPa and accuracy of ±0.069 kPa. The sensor was installed within a slot slightly wider than the plate itself with its center at a depth of 1.83 m, and a vibrating-wire fluid pressure transducer with the same resolution and accuracy as the total stress sensor was installed adjacent to the cell to measure fluid pressure and therefore provide a means of calculating horizontal effective stress. The pit was backfilled after sensor installation with material removed during its excavation. The remaining sensors were installed within 6.35-cm-diameter holes bored using hand equipment. These included electronic, vibrating-wire fluid pressure transducers (piezometers) with resolutions of 0.014 kPa and 0.086 kPa, and respective accuracies of ±0.069 kPa and ±0.344 kPa. Boreholes were backfilled above transducers first with ~0.3 m of material obtained during boring followed by bentonite granules to the ground surface. Piezometers were installed at depths of 3.66 m and 6.07 m at the upper monitoring location, 3.95 m and 5.69 m at the middle monitoring location, and 2.62 and 3.66 m at the lower monitoring location. Landslide basal depths were identified at approximately 6.3 m, 7.9 m, and 3.6 m at the upper, middle, and lower monitoring locations, respectively. A 30.48-cm-long biaxial tilt sensor installed within PVC casing (slope inclinometer) was used to monitor landslide displacement at the lower monitoring location. The slope inclinometer has 0.003 mm displacement resolution and long-term displacement accuracy of ±0.23 mm. A vibrating-wire length sensor was installed in a borehole to measure near-surface vertical deformation at the middle monitoring location. This sensor measured length with 0.0375 mm resolution and ±0.15 mm accuracy. The sensor’s upper and lower ends were anchored within cement grout such that its length was measured over a depth range (at installation) of 0.20-1.72 m. All sensors contain thermistors and readings are temperature compensated, with the exception of the rain gauge. These data support a study described in Schulz, W.H., Smith, J.B., Wang, G., Jiang, Y., and Roering, J.J., 2018, Clayey landslide initiation and acceleration strongly modulated by soil swelling: Geophysical Research Letters, DOI:10.1002/2017GL076807.

This data release includes the detailed results from laboratory testing of colluvium and landslide deposit specimens collected from coastal bluffs near Mukilteo, Washington. The specimens were collected as part of a larger effort to characterize the potential for shallow landslide initiation along the Puget Sound Railway corridor between the cities of Everett and Seattle. The details of the specimen collection and research objectives of the study are provided in: “Assessing Landslide Potential on Coastal Bluffs near Mukilteo, Washington—Geologic Site Characterization for Hydrologic Monitoring” (doi:10.3133/ofr20161082). Laboratory experiments includes test to estimate the following properties: specific gravity, porosity, bulk and grain densities, grain-size distributions, in situ volumetric water content, liquid and plastic limits, saturated hydraulic conductivity, water-retention and unsaturated hydraulic conductivity relations, and soil strength properties. The testing of the specimens was performed by Cooper Testing Labs Inc. in Palo Alto, California, and by York Lewis at Colorado School of Mines in Golden, Colorado. The following citations relate to this data release. Mirus, B.B., Smith, J.B., Stark, Benjamin, Lewis, York, Michel, Abigail, and Baum, R.L., 2016, Assessing landslide potential on coastal bluffs near Mukilteo, Washington—Geologic site characterization for hydrologic monitoring: U.S. Geological Survey Open-File Report 2016–1082, 28 p., http://dx.doi.org/10.3133/ofr20161082. van Genuchten, MTh., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils: Soil Science Society America Journal, vol. 44, p. 892-898. Wayllace, A., and Lu, N., 2012, A transient water release and imbibitions method for rapidly measuring wetting and drying soil water retention and hydraulic conductivity functions: Geotechnical Testing Journal, vol. 35, doi: 10.1520/GTJ103596.

Pluvials can have dramatic impacts on the shoreline bluffs of Lake Michigan due to increases in both shallow subsurface moisture conditions related to the prolonged wet weather pattern and wave erosion as the lake level rises. These changes can result in an increased frequency and magnitude of slope failures. During the most recent pluvial, the monthly average level of Lake Michigan rose 1.9 m from a record low in January 2013 to a near record high in June-July 2020. To assess the impacts on coastal bluffs from slope failures during the recent pluvial, an inventory of landslides was completed, including slope failures active during the early part of the pluvial, on the coastal bluffs of South Manitou Island, part of the Sleeping Bear Dunes National Lakeshore in Michigan. Landslides were mapped using high-resolution orthoimagery, collected in April 2012, and high-resolution topography derived from two LiDAR data sets, the first collected in December 2014 and the second collected between November 2015 and March 2016. This data release presents geographic information system (GIS) data, provided as line and polygon shapefiles (.shp), depicting landslides and related landforms and features. Polygon map data delineates the areas of deposits, source areas, and related landforms (such as alluvial fans and colluvial aprons). Scarps (such as headscarps and minor scarps) are presented as hachured line data. An attribute file is included providing a definition of the mapped units and a brief description of the approach used in the mapping.

Pluvials can have dramatic impacts on the shoreline bluffs of Lake Michigan due to increases in both shallow subsurface moisture conditions related to the prolonged wet weather pattern and wave erosion as the lake level rises. These changes can result in an increased frequency and magnitude of slope failures. During the most recent pluvial, the monthly average level of Lake Michigan rose 1.9 m from a record low in January 2013 to a near record high in June-July 2020. To assess the impacts on coastal bluffs from slope failures during the recent pluvial, an inventory of landslides was completed, including slope failures active during the early part of the pluvial, on the coastal bluffs of South Manitou Island, part of the Sleeping Bear Dunes National Lakeshore in Michigan. Landslides were mapped using high-resolution orthoimagery, collected in April 2012, and high-resolution topography derived from two LiDAR data sets, the first collected in December 2014 and the second collected between November 2015 and March 2016. This data release presents geographic information system (GIS) data, provided as line and polygon shapefiles (.shp), depicting landslides and related landforms and features. Polygon map data delineates the areas of deposits, source areas, and related landforms (such as alluvial fans and colluvial aprons). Scarps (such as headscarps and minor scarps) are presented as hachured line data. An attribute file is included providing a definition of the mapped units and a brief description of the approach used in the mapping.

This data release includes 2014 time-series data from three debris-flow monitoring stations at Chalk Cliffs in Chaffee County, Colorado, USA. The data were collected to help identify the triggering conditions, magnitude, and mobility of debris flows at the site. The three stations are located sequentially along a channel draining the 0.3 km^2 study area. The Upper, Middle, and Lower stations have respective drainage areas of 0.06, 0.16, and 0.24 km^2. The location (UTM zone 13) of each station is: 396826E/4287851N (Upper), 396893E/ 4287815N (Middle), and 396929E/4287712N (Lower). See also “ChalkStationLocations.jpg” in the README.zip file. The 2014 data includes three types of time series: (1) 1-minute time series of rainfall recorded by tipping bucket rain gages at each station, (2) 10-Hz time series of flow stage recorded by laser distance meters at each station, and (3) 333-Hz time series of ground vibrations and basal normal force at the Upper station only. Ground vibrations were recorded by two 4.5 Hz triaxial geophones separated by 18 m along the channel. Basal normal force was recorded by a 232 cm^2 force plate installed in the bedrock channel bed directly beneath the laser distance meter. The 10-Hz stage data is collected only when it is raining due to data storage limitations. Similarly, the 333-Hz ground motion and force data are provided only during significant flow events. These events occurred on 4 July 2014, 31 July 2014, 1 August 2014, 4 August 2014, and 6 August 2014. The first three events are primarily debris flows and the last two events are debris floods. Note that the rain gage at the Lower station, which is partially shielded by a near-vertical cliff, is used primarily as a trigger for sampling 10-Hz stage data rather than providing an accurate representation of rainfall at the station. Details of the sensors and photos of each station are contained in the “README.zip” file. The file also contains formulas for (1) converting the distance between the laser and the flow surface (or stationary bed surface) to stage above the datum for each station, and (2) converting the raw voltage readings from the geophones and force plate transducer into engineering units of ground velocity and normal force, respectively. Additional details of the study are provided in the journal articles: McCoy, S. W., J. W. Kean, J. A. Coe, G. E. Tucker, D. M. Staley, and T. A. Wasklewicz (2012), Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment, J. Geophys. Res., 117, F03016, doi:10.1029/2011JF002278. Kean, J. W., J. A. Coe, V. Coviello, J. B. Smith, S. W. McCoy, and M. Arattano (2015), Estimating rates of debris flow entrainment from ground vibrations, Geophys. Res. Lett., 42, doi:10.1002/2015GL064811.