A hydrologic monitoring network was installed to investigate landslide hazards affecting the railway corridor along the eastern shore of Puget Sound between Seattle and Everett, near Mukilteo, Washington. During the summer of 2015, the U.S. Geological Survey installed instrumentation at four sites to measure rainfall and air temperature every 15 minutes. Two of the four sites are installed on contrasting coastal bluffs, one landslide scarred and one vegetated. At these two sites, in addition to rainfall and air temperature, volumetric water content, pore pressure, soil suction, soil temperature (via hydrologic instrumentation), and barometric pressure were measured every 15 minutes. The instrumentation was designed to supplement landslide-rainfall thresholds developed by the U.S. Geological Survey with a long-term goal of advancing the understanding of the relationship between landslide potential and hydrologic forcing along the coastal bluffs. Additionally, the system was designed to function as a prototype monitoring system to evaluate criteria for site selection, instrument selection, and placement of instruments. Two files are included with this release. A comma separated value (csv) file contains monitoring data for the time-periods described by its name, for example 20150711_20160809.csv contains data for the period between July 11, 2015 and August 9, 2016. A read-me file (readme.doc) describes the sensor naming convention used for column names in the data files. The following citation relates to a report that provides background information and is intended to accompany this data release. Smith, J.B.; Baum, R.L.; Mirus, Benjamin B.; Michel, Abigail R.; Stark, Ben, 2017, Results of Hydrologic Monitoring on Landslide-Prone Coastal Bluffs Near Mukilteo Washington: U.S. Geological Survey Open-File Report 2017-1095, 50 p., http://dx.doi.org/10.3133/ofr20171095

A hydrologic monitoring network was installed to investigate landslide hazards affecting the railway corridor along the eastern shore of Puget Sound between Seattle and Everett, near Mukilteo, Washington. During the summer of 2015, the U.S. Geological Survey installed instrumentation at four sites to measure rainfall and air temperature every 15 minutes. Two of the four sites are installed on contrasting coastal bluffs, one landslide scarred and one vegetated. At these two sites, in addition to rainfall and air temperature, volumetric water content, pore pressure, soil suction, soil temperature (via hydrologic instrumentation), and barometric pressure were measured every 15 minutes. The instrumentation was designed to supplement landslide-rainfall thresholds developed by the U.S. Geological Survey with a long-term goal of advancing the understanding of the relationship between landslide potential and hydrologic forcing along the coastal bluffs. Additionally, the system was designed to function as a prototype monitoring system to evaluate criteria for site selection, instrument selection, and placement of instruments. Two files are included with this release. A comma separated value (csv) file contains monitoring data for the time-periods described by its name, for example 20150711_20160809.csv contains data for the period between July 11, 2015 and August 9, 2016. A read-me file (readme.doc) describes the sensor naming convention used for column names in the data files. The following citation relates to a report that provides background information and is intended to accompany this data release. Smith, J.B.; Baum, R.L.; Mirus, Benjamin B.; Michel, Abigail R.; Stark, Ben, 2017, Results of Hydrologic Monitoring on Landslide-Prone Coastal Bluffs Near Mukilteo Washington: U.S. Geological Survey Open-File Report 2017-1095, 50 p., http://dx.doi.org/10.3133/ofr20171095

This dataset contains a point cloud (Slumgullion_PointCloud.laz), 1-meter digital surface model (Slumgullion_DSM.tif), and orthoimagery (0.1-meter resolution) (Slumgullion_Ortho.tif) of the active portion of the Slumgullion landslide in Lake City, Colorado. The Slumgullion landslide is a translational slide with a continuously moving, active portion and an inactive portion. 896 photos from a Sony A7R Mark IV, RGB61 camera mounted on a Wingtra 1 GEN II fixed-wing uncrewed aerial vehicle (UAV) were collected on June 3, 2024 (Slumgullion_UAV_Images_Geotags.zip). The images were georeferenced using post-possessed kinematics (PPK) from the onboard Global Positioning System (GPS) of the aircraft with corrections from a concurrently operating base station within the study area. The point cloud and digital surface model products were created from the georeferenced photos from four UAV flights using Structure-from-Motion (SfM) photogrammetry techniques with the software Agisoft Metashape (v. 2.1.0 build 17532). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

This dataset contains a point cloud (Slumgullion_PointCloud.laz), 1-meter digital surface model (Slumgullion_DSM.tif), and orthoimagery (0.1-meter resolution) (Slumgullion_Ortho.tif) of the active portion of the Slumgullion landslide in Lake City, Colorado. The Slumgullion landslide is a translational slide with a continuously moving, active portion and an inactive portion. 896 photos from a Sony A7R Mark IV, RGB61 camera mounted on a Wingtra 1 GEN II fixed-wing uncrewed aerial vehicle (UAV) were collected on June 3, 2024 (Slumgullion_UAV_Images_Geotags.zip). The images were georeferenced using post-possessed kinematics (PPK) from the onboard Global Positioning System (GPS) of the aircraft with corrections from a concurrently operating base station within the study area. The point cloud and digital surface model products were created from the georeferenced photos from four UAV flights using Structure-from-Motion (SfM) photogrammetry techniques with the software Agisoft Metashape (v. 2.1.0 build 17532). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

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 contains displacement and pore-water pressure data from a field experiment performed November 14, 2003, at Mount Kaba-san, Japan. This experiment generated a shallow landslide, induced by water infiltration from overhead sprinkling, that mobilized into a debris flow. More information about this experiment can be found in Ochiai and others (2004). Extensometer data recorded the ground-surface locations (displacement) and pressure transducers recorded dynamic pore-water pressures within the hillslope leading up to and through rapid failure. Data were recorded at a 100-Hz sampling frequency on a National Instruments data-acquisition system. The accompanying cross-sectional diagram (Japan_exp_cross-section.png) illustrates the general instrument configuration at the start of the experiment. Extensometers (linear position transducers) were attached to the overhead sprinkling structure and their wire cables (that extend with displacement) were attached to ground anchors downslope of the instruments. These instruments with retractable wire rope cables were manufactured by UniMeasure. Extensometer 4 had a longer wire length to better record the transition from slow sliding motion to rapid debris flow. Extensometer Model Approx. wire length range (m) 3 JX-PA-80-N11-11S-111 2 4 HX-PA-400 8 5 JX-PA-80-N11-11S-111 2 Piezometers were directly buried pressure transducers encased in custom-built cylindrical housings (43 mm in diameter, 93 mm long) with sintered filters at their bases (refer to Japan_exp_piezometer_images.jpg). The transducers within the enclosures were manufactured by Druk, model PDCR800, with a range of 70 kiloPascals (kPa) gauge pressure. Each enclosure had two sealable tubes that extended to the ground surface after burial. These tubes allowed water to be injected into the enclosure through one tube and air to escape out the other tube. This configuration enabled full water saturation of the enclosed transducer sensors, rapid pressure transmission to the sensor diaphragms, and better recording of dynamic responses during rapid failure. This data release contains the following files: (1) Metadata for this data release. (2) Data (in csv format) from the entire experiment (until about six minutes after rapid failure) downsampled to 1-Hz for ease of viewing and plotting. Time in seconds denotes time after overhead sprinkling commenced. (3) Data (in csv format) from the rapid-failure period (24620-24640 seconds) at 100-Hz to portray dynamic responses during rapid failure. (4) Image of experiment cross section showing instrument locations and landslide failure mass. (5) Images of piezometers consisting of pressure transducers and enclosures. Extensometer data is presented as raw recorded position (m) and corrected position (m) to reflect downslope, rather than oblique, displacement. Refer to Processing Steps in the metadata for more information on extensometer data corrections. Pore-pressure data is presented in recorded centimeters of head and converted to kPa. Reference cited Ochiai, H., Okada, Y., Furuya, G., Okura, Y., Matsui, T., Sammori, T., Terajima, T. and Sassa, K., 2004, A fluidized landslide on a natural slope by artificial rainfall: Landslides, v. 1, p. 211-219.

This data release contains displacement and pore-water pressure data from a field experiment performed November 14, 2003, at Mount Kaba-san, Japan. This experiment generated a shallow landslide, induced by water infiltration from overhead sprinkling, that mobilized into a debris flow. More information about this experiment can be found in Ochiai and others (2004). Extensometer data recorded the ground-surface locations (displacement) and pressure transducers recorded dynamic pore-water pressures within the hillslope leading up to and through rapid failure. Data were recorded at a 100-Hz sampling frequency on a National Instruments data-acquisition system. The accompanying cross-sectional diagram (Japan_exp_cross-section.png) illustrates the general instrument configuration at the start of the experiment. Extensometers (linear position transducers) were attached to the overhead sprinkling structure and their wire cables (that extend with displacement) were attached to ground anchors downslope of the instruments. These instruments with retractable wire rope cables were manufactured by UniMeasure. Extensometer 4 had a longer wire length to better record the transition from slow sliding motion to rapid debris flow. Extensometer Model Approx. wire length range (m) 3 JX-PA-80-N11-11S-111 2 4 HX-PA-400 8 5 JX-PA-80-N11-11S-111 2 Piezometers were directly buried pressure transducers encased in custom-built cylindrical housings (43 mm in diameter, 93 mm long) with sintered filters at their bases (refer to Japan_exp_piezometer_images.jpg). The transducers within the enclosures were manufactured by Druk, model PDCR800, with a range of 70 kiloPascals (kPa) gauge pressure. Each enclosure had two sealable tubes that extended to the ground surface after burial. These tubes allowed water to be injected into the enclosure through one tube and air to escape out the other tube. This configuration enabled full water saturation of the enclosed transducer sensors, rapid pressure transmission to the sensor diaphragms, and better recording of dynamic responses during rapid failure. This data release contains the following files: (1) Metadata for this data release. (2) Data (in csv format) from the entire experiment (until about six minutes after rapid failure) downsampled to 1-Hz for ease of viewing and plotting. Time in seconds denotes time after overhead sprinkling commenced. (3) Data (in csv format) from the rapid-failure period (24620-24640 seconds) at 100-Hz to portray dynamic responses during rapid failure. (4) Image of experiment cross section showing instrument locations and landslide failure mass. (5) Images of piezometers consisting of pressure transducers and enclosures. Extensometer data is presented as raw recorded position (m) and corrected position (m) to reflect downslope, rather than oblique, displacement. Refer to Processing Steps in the metadata for more information on extensometer data corrections. Pore-pressure data is presented in recorded centimeters of head and converted to kPa. Reference cited Ochiai, H., Okada, Y., Furuya, G., Okura, Y., Matsui, T., Sammori, T., Terajima, T. and Sassa, K., 2004, A fluidized landslide on a natural slope by artificial rainfall: Landslides, v. 1, p. 211-219.

This data set provides a polygon shapefile delineating relatively large, slow-moving (4-17 cm/year in the radar line-of-sight direction) landslides in the continental U.S. western coastal states (California, Oregon, and Washington). The polygons also are provided in a Google Earth .kmz file. Delineated landslides were identified from displacement signals captured by InSAR (Interferometric Synthetic Aperture Radar) interferograms of ALOS PALSAR (Advanced Land Observing Satellite; Phased Array type L-band Synthetic Aperture Radar) images between 2007 and 2011, and ALOS-2 PALSAR-2 images between 2015 and 2019. The ALOS PALSAR images utilized cover the three states entirely; the ALOS-2 PALSAR images utilized cover primarily the western half of the study area where 97.6% of the identified landslides are located. The Scene IDs of the used ALOS and ALOS-2 images are provided in text files. The 1/3 arc-second National Elevation Datasets from the U.S. Geological Survey (https://apps.nationalmap.gov/downloader/, last accessed November 12, 2020), and optical images available from Google Earth were utilized to assist in landslide identification. Each polygon in the shapefile outlines the active area of a landslide. The active areas identified for a given landslide using the ALOS PALSAR and ALOS-2 PALSAR-2 interferograms differ slightly in some cases. For these, we used the larger polygon as the landslide boundary. The shapefile attribute table indicates which data were used to identify the landslide (“Comments”), and this is also indicated by the “Flag” field of the table, where values of 1, 2, and 3 indicate ALOS, ALOS2, and both datasets, respectively; a flag value of 4 was assigned for rock glaciers, which were only identified using ALOS data. The attribute table also provides areas of each polygon in square meters. These data support a study described in: Xu, Y., Schulz, W.H., Lu, Z., Kim, J., and Baxstrom, K., 2021, Geologic controls of slow-moving landslides near the U.S. west coast: Landslides, doi:10.1007/s10346-021-01732-3

This data set provides a polygon shapefile delineating relatively large, slow-moving (4-17 cm/year in the radar line-of-sight direction) landslides in the continental U.S. western coastal states (California, Oregon, and Washington). The polygons also are provided in a Google Earth .kmz file. Delineated landslides were identified from displacement signals captured by InSAR (Interferometric Synthetic Aperture Radar) interferograms of ALOS PALSAR (Advanced Land Observing Satellite; Phased Array type L-band Synthetic Aperture Radar) images between 2007 and 2011, and ALOS-2 PALSAR-2 images between 2015 and 2019. The ALOS PALSAR images utilized cover the three states entirely; the ALOS-2 PALSAR images utilized cover primarily the western half of the study area where 97.6% of the identified landslides are located. The Scene IDs of the used ALOS and ALOS-2 images are provided in text files. The 1/3 arc-second National Elevation Datasets from the U.S. Geological Survey (https://apps.nationalmap.gov/downloader/, last accessed November 12, 2020), and optical images available from Google Earth were utilized to assist in landslide identification. Each polygon in the shapefile outlines the active area of a landslide. The active areas identified for a given landslide using the ALOS PALSAR and ALOS-2 PALSAR-2 interferograms differ slightly in some cases. For these, we used the larger polygon as the landslide boundary. The shapefile attribute table indicates which data were used to identify the landslide (“Comments”), and this is also indicated by the “Flag” field of the table, where values of 1, 2, and 3 indicate ALOS, ALOS2, and both datasets, respectively; a flag value of 4 was assigned for rock glaciers, which were only identified using ALOS data. The attribute table also provides areas of each polygon in square meters. These data support a study described in: Xu, Y., Schulz, W.H., Lu, Z., Kim, J., and Baxstrom, K., 2021, Geologic controls of slow-moving landslides near the U.S. west coast: Landslides, doi:10.1007/s10346-021-01732-3