Geology topics

Rex L. Baum

Publications and source records attributed to Rex L. Baum.

At least 19 recordsLinked to original sources

USGS2026

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Utuado Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019) when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2–4). In Utuado Municipio, about 18,000 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiate (for example, Jibson, 1986; Bessette-Kirton and others, 2019a, 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (fig. 3A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines, are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (fig. 4) as well as bury roadways (fig. 3A, C). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving liquefied masses (debris flows), which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others [2020] ). This hazard map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 399 millimeters of rainfall fell across Utuado during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase. The map does not show potential landslide locations in the karst terrain of northern Utuado (Bawiec, 1999) because Hurricane María-induced landslides were very sparse in this region (Hughes and others, 2019; Baxstrom and others, 2021a), even though rainfall amounts were similar to those in other parts of Utuado. Based on data from Hughes and others (2019), landslides were about 10 times more likely to occur outside of the karst terrane than within it, and our preliminary analyses indicated relatively low susceptibility to rainfall-induced landslide hazards within the karst. Landslide-prone soils appear to be poorly developed on the very steep slopes present in the karst region, where weathering by dissolution appears to dominate.

Puerto Rico, Utuado Municipio↗

USGS2026

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Naranjito Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019), when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2–4). In Naranjito Municipio, about 2,000 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense-rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiated (for example, Jibson, 1986; Bessette-Kirton and others, 2019a; 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (figs. 3B, 4A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move, or runout, very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (figs. 3A, 4A, C) as well as bury roadways (fig. 4A). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving debris flows, which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others, 2020). This map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 529 millimeters of rainfall fell across Naranjito during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase.

Naranjito Municipio, Puerto Rico↗

USGS2026

Map depicting locations susceptible to landslide hazards triggered by prolonged intense rainfall, Lares Municipio, Puerto Rico

Introduction Landslides commonly occur in Puerto Rico during or soon after rainstorms with prolonged intense rainfall. Rainfall-triggered landslides present significant hazards to the built environment and human safety (for example, Jibson, 1986; Larsen and Torres Sanchez, 1992; Bessette-Kirton and others, 2019a). These hazards were illustrated during September 2017 (Hughes and others, 2019), when Hurricane María triggered more than 70,000 landslides across Puerto Rico (fig. 1), causing loss of life and widespread destruction (figs. 2 and 3). In Lares Municipio, about 3,500 landslides were observed after Hurricane María (Hughes and others, 2019). Most intense-rainfall-triggered landslides in Puerto Rico occur in soil overlying bedrock and travel downslope from where they initiated (for example, Jibson, 1986; Bessette-Kirton and others, 2019a; 2020). Hazards to human life and infrastructure can differ substantially between where landslides initiate and where they travel. At landslide initiation locations, the ground breaks up (fails) as it moves downslope, removing support for buildings, roadways, and other structures located upon the landslides (figs. 2, 3A, B). This ground failure often causes structures to collapse and suffer severe damage or complete destruction, rendering building occupants at extreme risk. Roadways and other vital infrastructure, such as water, power, and communication lines are often severed. During intense rainfall events, landslide initiation and movement downslope can occur in seconds to hours. Downslope from where they initiate, landslides in Puerto Rico often move, or runout, very rapidly (faster than a person can walk or run) and can impact and destroy or fill structures with mud and debris (figs. 3A, C) as well as bury roadways (fig. 3A). Moving landslides present extreme hazards to human safety; some fatalities during Hurricane María resulted from mud and debris that flowed through windows and doors of a home and buried occupants. Many landslides in Puerto Rico become fast-moving debris flows, which are especially common in channels where they can quickly travel kilometers downstream. Multiple debris flows may occur in a channel during a single rainstorm (some channels experienced more than 50 debris flows during Hurricane María; Bessette-Kirton and others, 2020). This map separately depicts locations and the relative likelihood of where landslides may initiate, where they may move downslope, and where channelized debris flows may travel during or soon after intense rainfall like that during Hurricane María. An estimated average of 256 millimeters of rainfall fell across Lares during September 19–21, 2017 (Ramos-Scharrón and Arima, 2019). Lower rainfall amounts, durations, and intensities also trigger landsliding in Puerto Rico, although landslides and debris flows become more numerous as rainfall intensities, durations, and cumulative amounts increase. The map does not show potential landslide locations in the karst terrain of northern Lares (Bawiec, 1999) because Hurricane María-induced landslides were very sparse in this region (Hughes and others, 2019; Baxstrom and others, 2021a), even though rainfall amounts were similar to those in other parts of Lares. Based on data from Hughes and others (2019), landslides were about ten times more likely to occur outside of the karst terrane than within it, and our preliminary analyses indicate relatively low susceptibility to rainfall-induced landslide hazards within the karst. Landslide-prone soils appear to be poorly developed on the very steep slopes present in the karst region, where weathering by dissolution appears to dominate.

Lares Municipio, Puerto Rico↗

USGS2024

Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico

Hurricane Maria induced about 70 000 landslides throughout Puerto Rico, USA, including thousands each in three municipalities situated in Puerto Rico's rugged Cordillera Central range. By combining a nonlinear soil-depth model, presumed wettest-case pore pressures, and quasi-three-dimensional (3D) slope-stability analysis, we developed a landslide susceptibility map that has very good performance and continuous susceptibility zones having smooth, buffered boundaries. Our landslide susceptibility map enables assessment of potential ground-failure locations and their use as landslide sources in a companion assessment of inundation and debris-flow runout. The quasi-3D factor of safety, F 3 , showed strong inverse correlation to landslide density (high density at low F 3 ). Area under the curve (AUC) of true positive rate (TPR) versus false positive rate (FPR) indicated success of F 3 in identifying head-scarp points (AUC = 0.84) and source-area polygons (0.85 ≤ AUC ≤ 0.88). The susceptibility zones enclose specific percentages of observed landslides. Thus, zone boundaries use successive F 3 levels for increasing TPR of landslide head-scarp points, with zones bounded by F 3 at TPR = 0.75, very high; F 3 at TPR = 0.90, high; and the remainder moderate to low. The very high susceptibility zone, with 118 landslides km −2 , covered 23 % of the three municipalities. The high zone (51 landslides km −2 ) covered another 10 %.

Puerto Rice↗

USGS2023

Distribution of large boulders on the deposit of the West Salt Creek rock avalanche, western Colorado

On May 25, 2014, a 54.5-million cubic meter rock avalanche in the West Salt Creek valley, Mesa County, Colorado, traveled 4.6 kilometers, leaving a deposit that covers about 2.2 square kilometers. To check the particle-size distribution of the deposit for information about the high mobility of the avalanche, we estimated boulder distribution density for the entire deposit by counting 1-meter (m) or larger diameter boulders of sedimentary rock derived from the Green River Formation that are visible in high-resolution imagery collected from the area in July 2014. Basalt boulders were excluded from the count because field observations indicated that they generally stayed intact as the avalanche moved downslope, whereas sedimentary boulders showed evidence of fragmentation during downslope movement. Variable clarity, contrast, and resolution of the imagery precluded mapping smaller boulders. Experimentation with 5-, 10-, and 20-m resolution grids indicated that a 20-m resolution grid showed the spatial pattern of boulder density across the deposit at a scale that allowed statistically meaningful variations to be determined. In addition to counting the boulders in each 20×20-m grid cell, six categories of successively increasing boulder distribution density were created to help visualize variations in the distribution of 1 meter or larger boulders across the avalanche deposit. Analysis indicates that boulder distribution density gradually decreases with increasing distance from the avalanche source.

Colorado↗

USGS2021

HydroMet: A new code for automated objective optimization of hydrometeorological thresholds for landslide initiation

Landslide detection and warning systems are important tools for mitigation of potential hazards in landslide prone areas. Traditionally, warning systems for shallow landslides have been informed by rainfall intensity-duration thresholds. More recent advances have introduced the concept of hydrometeorological thresholds that are informed not only by rainfall, but also by subsurface hydrological measurements. Previously, hydrometeorological thresholds have been shown to improve capabilities for forecasting shallow landslides, and they may ultimately be adapted to more generalized landslide forecasting. We present HydroMet, a code developed in Python by the U.S. Geological Survey, which allows users to guide the automated estimation of hydrometeorological thresholds for a site or area of interest, with the flexibility to select preferred threshold variables for the antecedent hydrologic conditions and the triggering meteorological conditions. Users can import hydrologic time-series data, including rainfall, soil-water content, and pore-water pressure, along with the times of known landslide occurrences, and then conduct objective optimization of warning thresholds using receiver operating characteristics. HydroMet presents many additional options, including selecting the threshold formula, the timescale of possible threshold variables, and the skill statistics used for optimization. Users can develop dual-stage thresholds for watch and warning alerts, with a lower, risk-averse threshold to avoid missed alarms and a less conservative threshold to minimize false alarms. Users may also choose to split their inventory data into calibration and evaluation subsets to independently evaluate the performance of optimized thresholds. We present output and applications of HydroMet using monitoring data from landslide-prone areas in the U.S. to demonstrate its utility and ability to produce thresholds with limited missed and false alarms for informing the next generation of reliable landslide warning systems.

Water↗

USGS2021

When hazard avoidance is not an option: Lessons learned from monitoring the postdisaster Oso landslide, USA

On 22 March 2014, a massive, catastrophic landslide occurred near Oso, Washington, USA, sweeping more than 1 km across the adjacent valley flats and killing 43 people. For the following 5 weeks, hundreds of workers engaged in an exhaustive search, rescue, and recovery effort directly in the landslide runout path. These workers could not avoid the risks posed by additional large-scale slope collapses. In an effort to ensure worker safety, multiple agencies cooperated to swiftly deploy a monitoring and alerting system consisting of sensors, automated data processing and web-based display, along with defined communication protocols and clear calls to action for emergency management and search personnel. Guided by the principle that an accelerating landslide poses a greater threat than a steadily moving or stationary mass, the system was designed to detect ground motion and vibration using complementary monitoring techniques. Near real-time information was provided by continuous GPS, seismometers/geophones, and extensometers. This information was augmented by repeat-assessment techniques such as terrestrial and aerial laser scanning and time-lapse photography. Fortunately, no major additional landsliding occurred. However, we did detect small headscarp failures as well as slow movement of the remaining landslide mass with the monitoring system. This was an exceptional response situation and the lessons learned are applicable to other landslide disaster crises. They underscore the need for cogent landslide expertise and ready-to-deploy monitoring equipment, the value of using redundant monitoring techniques with distinct goals, the benefit of clearly defined communication protocols, and the importance of continued research into forecasting landslide behavior to allow timely warning.

Washington↗

USGS2021

Incorporating the effects of complex soil layering and thickness local variability into distributed landslide susceptibility assessments

Incorporating the influence of soil layering and local variability into the parameterizations of physics-based numerical models for distributed landslide susceptibility assessments remains a challenge. Typical applications employ substantial simplifications including homogeneous soil units and soil-hydraulic properties assigned based only on average textural classifications; the potential impact of these assumptions is usually disregarded. We present a multi-scale approach for parameterizing the distributed Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model that accounts for site-specific spatial variations in both soil thickness and complex layering properties by defining homogeneous soil properties that vary spatially for each model grid cell. These effective properties allow TRIGRS to accurately simulate the timing and distribution of slope failures without any modification of the model structure. We implemented this approach for the carbonate ridge of Sarno Mountains (southern Italy) whose slopes are mantled by complex layered soils of pyroclastic origin. The urbanized foot slopes enveloping these mountains are among the most landslide-prone areas of Italy and have been subjected to repeated occurrences of damaging and deadly rainfall-induced flow-type shallow landslides. At this scope, a primary local-scale application of TRIGRS was calibrated on physics-based rainfall thresholds, previously determined by a coupled VS2D (version 1.3) hydrological modeling and slope stability analysis. Subsequently, by taking into account the spatial distribution of soil thickness and vertical heterogeneity of soil hydrological and mechanical properties, a distributed assessment of landslide hazard was carried out by means of TRIGRS. The combination of these approaches led to the spatial assessment of landslide hazard under different hypothetical rainfall intensities and antecedent hydrological conditions. This approach to parameterizing TRIGRS can be adapted to other spatially variable soil layering and thickness to improve hazard assessments.

Mount Vesuvius↗

USGS2020

Rapid sensitivity analysis for reducing uncertainty in landslide hazard assessments

One of the challenges in assessing temporal and spatial aspects of landslide hazard using process-based models is estimating model input parameters, especially in areas where limited measurements of soil and rock properties are available. In an effort to simplify and streamline parameter estimation, development of a simple, rapid approach to sensitivity analysis relies on field measurements of landslide characteristics, especially slope and depth. This method is demonstrated for a case study in Puerto Rico where widespread destruction resulted from tens of thousands of debris flows induced by Hurricanes Irma and María in Puerto Rico in 2017. The approach can be applied to estimation of shear strength as well as hydrologic parameters that control infiltration and flow of water in the subsurface and ultimately the timing of landslides resulting from heavy rainfall. Results narrow the possible range of cohesion and friction parameters as well as hydraulic conductivity and other soil water parameters by counting the fraction of field observations that can be explained by each combination of parameters. For cases studied in Puerto Rico, the method identified combinations of cohesion and friction values that explain more than 80–90% of observed landslide source areas.

Puerto Rico↗

USGS2020

Progress and lessons learned from responses to landslide disasters

Landslides have the incredible power to transform landscapes and also, tragically, to cause disastrous societal impacts. Whereas the mechanics and effects of many landslide disasters have been analyzed in detail, the means by which landslide experts respond to these events has garnered much less attention. Herein, we evaluate nine landslide response case histories conducted by the U.S. Geological Survey over the past two decades and summarize the event history, the response conducted, and the lessons learned from each event. We group the responses into three categories—providing event context from past events, addressing ongoing hazards, and acquiring data for the future—and present the nine case studies accordingly. We also summarize the progress in landslide response that has been made over the past two decades, including insights and advancements on the preparation for such events, the use of new technologies, and the importance of clear communication between all parties during disasters. We believe that exchanging and sharing experiences such as these will promote more clear and successful approaches for responses to landslide disasters in the future.

Book chapter↗

USGS2020

Landslides across the United States: Occurrence, susceptibility, and data limitations

Detailed information about landslide occurrence is the foundation for advancing process understanding, susceptibility mapping, and risk reduction. Despite the recent revolution in digital elevation data and remote sensing technologies, landslide mapping remains resource intensive. Consequently, a modern, comprehensive map of landslide occurrence across the United States (USA) has not been compiled. As a first step toward this goal, we present a national-scale compilation of existing, publicly available landslide inventories. This geodatabase can be downloaded in its entirety or viewed through an online, searchable map, with parsimonious attributes and direct links to the contributing sources with additional details. The mapped spatial pattern and concentration of landslides are consistent with prior characterization of susceptibility within the conterminous USA, with some notable exceptions on the West Coast. Although the database is evolving and known to be incomplete in many regions, it confirms that landslides do occur across the country, thus highlighting the importance of our national-scale assessment. The map illustrates regions where high-quality mapping has occurred and, in contrast, where additional resources could improve confidence in landslide characterization. For example, borders between states and other jurisdictions are quite apparent, indicating the variation in approaches to data collection by different agencies and disparity between the resources dedicated to landslide characterization. Further investigations are needed to better assess susceptibility and to determine whether regions with high relief and steep topography, but without mapped landslides, require further landslide inventory mapping. Overall, this map provides a new resource for accessing information about known landslides across the USA.

Landslides↗

USGS2019

Physically based estimation of rainfall thresholds triggering shallow landslides in volcanic slopes of southern Italy

On the 4th and 5th of March 2005, about 100 rainfall-induced landslides occurred along volcanic slopes of Camaldoli Hill in Naples, Italy. These started as soil slips in the upper substratum of incoherent and welded volcaniclastic deposits, then evolved downslope according to debris avalanche and debris flow mechanisms. This specific case of slope instability on complex volcaniclastic deposits remains poorly characterized and understood, although similar shallow landsliding phenomena have largely been studied in other peri-volcanic areas of the Campania region underlain by carbonate bedrock. Considering the landslide hazard in this urbanized area, this study focused on quantitatively advancing the understanding of the predisposing factors and hydrological conditions contributing to the initial landslide triggering. Borehole drilling, trial pits, dynamic penetrometer tests, topographic surveys, and infiltration tests were conducted on a slope sector of Camaldoli Hill to develop a geological framework model. Undisturbed soil samples were collected for laboratory testing to further characterize hydraulic and geotechnical properties of the soil units identified. In situ soil pressure head monitoring probes were also installed. A numerical model of two-dimensional variably saturated subsurface water flow was parameterized for the monitored hillslope using field and laboratory data. Based on the observed soil pressure head dynamics, the model was calibrated by adjusting the evapotranspiration parameters. This physically based hydrologic model was combined with an infinite-slope stability analysis to reconstruct the critical unsaturated/saturated conditions leading to slope failure. This coupled hydromechanical numerical model was then used to determine intensity–duration (I-D) thresholds for landslide initiation over a range of plausible rainfall intensities and topographic slope angles for the region. The proposed approach can be conceived as a practicable method for defining a warning criterion in urbanized areas threatened by rainfall-induced shallow landslides, given the unavailability of a consistent inventory of past landslide events that prevents a rigorous empirical analysis.

Water↗

USGS2019

Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations

In the past decades, many different approaches have been developed in the literature to quantify the load-carrying capacity and geotechnical stability (or the Factor of Safety, F_s) of variably saturated hillslopes. Much of this work has focused on a deterministic characterization of hillslope stability. Yet, simulated F_s values are subject to considerable uncertainty due to our inability to characterize accurately the soil mantle’s properties (hydraulic, geotechnical and geomorphologic) and spatiotemporal variability of the moisture content of the hillslope interior. This is particularly true at larger spatial scales. Thus, uncertainty-incorporating analyses of physically based models of rain-induced landslides are rare in the literature. Such landslide modeling is typically conducted at the hillslope scale using gauge-based rainfall forcing data with rather poor spatiotemporal coverage. For regional landslide modeling, the specific advantages and/or disadvantages of gauge-only, radar-merged and satellite-based rainfall products are not clearly established. Here, we compare and evaluate the performance of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) model for three different rainfall products using 112 observed landslides in the period between 2004 and 2011 from the North Carolina Geological Survey database. Our study includes the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Version 7 (TMPA V7), the North American Land Data Assimilation System Phase 2 (NLDAS-2) analysis, and the reference ‘truth’ Stage IV precipitation. TRIGRS model performance was rather inferior with the use of literature values of the geotechnical parameters and soil hydraulic properties from ROSETTA using soil textural and bulk density data from SSURGO (Soil Survey Geographic database). The performance of TRIGRS improved considerably after Bayesian estimation of the parameters with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm using Stage IV precipitation data. Hereto, we use a likelihood function that combines binary slope failure information from landslide event and ‘null’ periods using multivariate frequency distribution-based metrics such as the False Discovery and False Omission Rates. Our results demonstrate that the Stage IV-inferred TRIGRS parameter distributions generalize well to TMPA and NLDAS-2 precipitation data, particularly at sites with considerably larger TMPA and NLDAS-2 rainfall amounts during landslide events than null periods. TRIGRS model performance is then rather similar for all three rainfall products. At higher elevations, however, the TMPA and NLDAS-2 precipitation volumes are insufficient and their performance with the Stage IV-derived parameter distributions indicate their inability to accurately characterize hillslope stability.

North Carolina↗

USGS2019

Constraining parameter uncertainty in modeling debris-flow initiation during the September 2013 Colorado Front Range storm

The occurrence of debris flows during the September 2013 northern Colorado floods took the emergency management community by surprise. The September 2013 debris flows in the Colorado Front Range initiated from shallow landslides in colluvium. Most occurred on south- and east-facing slopes on the walls of steep canyons in crystalline rocks and on sedimentary hogbacks. Previous studies showed that most debris flows occurred in areas of high storm-total rainfall and that strength added by tree roots accounts for the low number of landslides in densely forested areas. Given the lack of rainfall thresholds for debris flow occurrence in northern Colorado, we want to parameterize a numerical model to assess potential for debris flows in advance of heavy rainfall. Natural Resources Conservation Service (NRCS) soil mapping of the area, supplemented by laboratory testing and field measurements, indicates that soil textures and hydraulic properties of landslide source materials vary considerably over the study area. As a step toward modeling storm response, available soil and geologic mapping have been interpreted to define zones of relatively homogeneous properties. A new, simplified modeling approach for evaluating model input parameters in the context of slope and depth of observed debris flow source areas and recorded debris-flow inducing rainfall helps narrow the range of possible parameters to those most likely to produce model results consistent with observed debris flow initiation. Initial results have narrowed the strength parameters to about one third of possible combinations of cohesion and internal friction angle and narrowed hydraulic conductivity to a range spanning slightly more than one order of magnitude.

Colorado↗

USGS2018

Field and laboratory hydraulic characterization of landslide-prone soils in the Oregon Coast Range and implications for hydrologic simulation

Unsaturated zone flow processes are an important focus of landslide hazard estimation. Differences in soil hydraulic behavior between wetting and drying conditions (i.e., hydraulic hysteresis) may be important in landslide triggering. Hydraulic hysteresis can complicate soil hydraulic parameter estimates and impact prediction capability. This investigation focused on hydraulic property estimation for soil in a landslide‐prone area where the relative importance of hysteresis is unclear. Laboratory measurements of soil‐water retention from field soils in the Oregon Coast Range during wetting and drying show that pronounced hydraulic hysteresis is present. In contrast, a 4‐yr field data record of pore‐water pressure and soil‐water content from multiple soil pits at the same landslide‐prone area shows relatively minor hydraulic hysteresis compared with the laboratory estimates. Simulated subsurface hydrologic response parameterized using estimates from field data more closely matched hydrologic observations relative to model parameterization based on laboratory analysis of repacked soil samples. Our results suggest that (i) unsaturated hydraulic parameter estimates based on in situ field data, as opposed to laboratory measurements alone, may lead to more accurate simulation of the hydrologic response to rainfall, (ii) in situ data of soil‐water retention may need to include values at both high suctions and near saturation to improve estimates of soil hydraulic parameters for slope failure applications, and (iii) laboratory measurements of soil‐water retention made under dynamic conditions may overestimate hydraulic hysteresis.

Oregon↗

USGS2018

Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning

Early warning for rainfall-induced shallow landsliding can help reduce fatalities and economic losses. Although these commonly occurring landslides are typically triggered by subsurface hydrological processes, most early warning criteria rely exclusively on empirical rainfall thresholds and other indirect proxies for subsurface wetness. We explore the utility of explicitly accounting for antecedent wetness by integrating real-time subsurface hydrologic measurements into landslide early warning criteria. Our efforts build on previous progress with rainfall thresholds, monitoring, and numerical modeling along the landslide-prone railway corridor between Everett and Seattle, Washington, USA. We propose a modification to a previously established recent versus antecedent (RA) cumulative rainfall thresholds by replacing the antecedent 15-day rainfall component with an average saturation observed over the same timeframe. We calculate this antecedent saturation with real-time telemetered measurements from five volumetric water content probes installed in the shallow subsurface within a steep vegetated hillslope. Our hybrid rainfall versus saturation (RS) threshold still relies on the same recent 3-day rainfall component as the existing RA thresholds, to facilitate ready integration with quantitative precipitation forecasts. During the 2015–2017 monitoring period, this RS hybrid approach has an increase of true positives and a decrease of false positives and false negatives relative to the previous RA rainfall-only thresholds. We also demonstrate that alternative hybrid threshold formats could be even more accurate, which suggests that further development and testing during future landslide seasons is needed. The positive results confirm that accounting for antecedent wetness conditions with direct subsurface hydrologic measurements can improve thresholds for alert systems and early warning of rainfall-induced shallow landsliding.

Landslides↗

USGS2018

THRESH—Software for tracking rainfall thresholds for landslide and debris-flow occurrence, user manual

Precipitation thresholds are used in many areas to provide early warning of precipitation-induced landslides and debris flows, and the software distribution THRESH is designed for automated tracking of precipitation, including precipitation forecasts, relative to thresholds for landslide occurrence. This software is also useful for analyzing multiyear precipitation records to compare timing of threshold exceedance with dates and times of historical landslides. This distribution includes the main program THRESH for comparing precipitation to several kinds of thresholds, two utility programs, and a small collection of Python and shell scripts to aid the automated collection and formatting of input data and the graphing and further analysis of output results. The software programs can be deployed on computing platforms that support Fortran 95, Python 2, and certain Unix commands. The software handles rainfall intensity-duration thresholds, cumulative recent-antecedent precipitation thresholds, and peak intensity thresholds as well as various measures of antecedent precipitation. Users should have predefined rainfall thresholds before running THRESH.

Techniques and Methods↗

USGS2017

Hydrologic impacts of landslide disturbances: Implications for remobilization and hazard persistence

Landslides typically alter hillslope topography, but may also change the hydrologic connectivity and subsurface water-storage dynamics. In settings where mobile materials are not completely evacuated from steep slopes, influences of landslide disturbances on hillslope hydrology and susceptibility to subsequent failures remain poorly characterized. Since landslides often recur at the site of previous failures, we examine differences between a stable vegetated hillslope (VH) and a recent landslide (LS). These neighboring hillslopes exhibit similar topography and are situated on steep landslide-prone coastal bluffs of glacial deposits along the northeastern shore of Puget Sound, Washington. Our control hillslope, VH, is mantled by a heterogeneous colluvium, supporting a dense forest. In early 2013, our test hillslope, LS, also supported a forest before a landslide substantially altered the topography and disturbed the hillslope. In 2015, we observed a clay-rich landslide deposit at LS with sparse vegetation and limited root reinforcement, soil structures, and macropores. Our characterization of the sites also found matrix porosity and hydraulic conductivity are both lower at LS. Continuous monitoring during 2015-2016 revealed reduced effective precipitation at VH (due to canopy interception), an earlier seasonal transition to near-saturated conditions at LS, and longer persistence of positive pore pressures and slower drainage at LS (both seasonally and between major storm events). These differences, along with episodic, complex slope failures at LS support the hypothesis that, despite a reduced average slope, other disturbances introduced by landsliding may promote the hydrologic conditions leading to slope instability, thus contributing to the persistence of landslide hazards.

Washington↗