Ben Mirus
My research focuses on landslide hydrology and thresholds for landslide warning systems. My background is in hillslope hydrology and numerical modeling of surface and near-surface hydrological processes, which I apply to improve quantitative characterization of landslide initiation potential. I manage several real-time landslide monitoring sites and the national landslide inventory database.
PROFESSIONAL EXPERIENCE
2015-present Research Geologist, Landslides Hazards Program, USGS, Golden, CO
2013-2014 Assistant Professor, Department of Geological Sciences, University of North Carolina, Chapel Hill, NC
2010-2013 Hydrologist, Unsaturated Zone Flow Project, USGS, Menlo Park, CA
2005-2009 Physical Scientist, Unsaturated Zone Flow Project, USGS, Menlo Park, CA
EDUCATION
2009 Ph.D. in Hydrogeology, Stanford University, Stanford, CA
2001 B.A. in Geology, Pomona College, Claremont, CA
Science and Products
Landslide Mechanisms and Forecasting
Sitka, AK
Seattle Area, Washington
Portland, Oregon
Knife Ridge, Elliott State Forest, Oregon
Poplar Cove, Nantahala National Forest, North Carolina
Mooney Gap, Coweeta Experimental Forest, North Carolina
Bent Creek Experimental Forest, North Carolina
Landslides Can Cause More Landslides
Integrating Disparate Spatial Datasets from Local to National Scale for Open-Access Web-Based Visualization and Analysis: A Case Study Compiling U.S. Landslide Inventories
Hydrologic monitoring data in steep, landslide-prone terrain, Sitka, Alaska, USA
Landslide Inventories across the United States version 2
Hydrologic, slope movement, and soil property data from the coastal bluffs of the Atlantic Highlands, New Jersey, 2016-2018
Soil moisture monitoring following the 2009 Station Fire, California, USA, 2016-2019
Hillslope hydrologic monitoring data following Hurricane Maria in 2017, Puerto Rico, July 2018 to June 2020
Time-lapse photography of an active coastal-bluff landslide, Mukilteo, Washington, August 2015 - May 2016
Hillslope hydrologic monitoring data following the 2009 Station Fire, Los Angeles County, California, November 2015 to June 2017
Results of Hydrologic Monitoring on Landslide-prone Coastal Bluffs near Mukilteo, Washington
Lab tests for specimens from Mukilteo, WA, 2016
Slope Unit Maker (SUMak): An efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA
Mapping landslide susceptibility over large regions with limited data
Prolonged influence of urbanization on landslide susceptibility
National strategy for landslide loss reduction
Constructing a large-scale landslide database across heterogeneous environments using task-specific model updates
Clays are not created equal: How clay mineral type affects soil parameterization
HydroMet: A new code for automated objective optimization of hydrometeorological thresholds for landslide initiation
Evaluation of techniques for mitigating snowmelt infiltration-induced landsliding in a highway embankment
Rapid-response unsaturated zone hydrology: Small-scale data, small-scale theory, big problems
Numerical analysis of the effect of subgrid variability in a physically based hydrological model on runoff, soil moisture, and slope stability
Incorporating the effects of complex soil layering and thickness local variability into distributed landslide susceptibility assessments
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
- Science
Landslide Mechanisms and Forecasting
When and where will landslides happen? How far will they go, how big and how fast will they be? These questions are difficult to answer because many factors contribute to landslide occurrence, magnitude, and mobility; some factors remain unknown, while nearly all are very difficult to quantify and account for. Researchers use surface, subsurface, remote sensing, and laboratory observations along...Sitka, AK
On August 18, 2015, heavy rainfall triggered around 60 landslides in and around the city of Sitka, AK. The landslides moved downslope rapidly; several were damaging and one of these demolished a home on South Kramer Avenue killing three people.Seattle Area, Washington
Monitoring at this site is for researching rainfall thresholds for forecasting landslide potential. Shallow landslides are common on coastal bluffs overlooking Puget Sound.Portland, Oregon
Landslides in the West Hills of Portland pose a hazard to people and property.Knife Ridge, Elliott State Forest, Oregon
The USGS and its cooperators have installed instruments in a steep hillside about 20 km southeast of Reedsport in the Elliott State Forest.Poplar Cove, Nantahala National Forest, North Carolina
The USGS and its cooperators have installed instruments in a steep hillside about 17.5 km southwest of Franklin, NC in the Nantahala National Forest.Mooney Gap, Coweeta Experimental Forest, North Carolina
The USGS and its cooperators have installed instruments in a steep hillside about 16 km southeast of Otto, NC in the Coweeta Experimental Forest.Bent Creek Experimental Forest, North Carolina
The USGS and its cooperators have installed instruments in a steep hillside about 38.5 km south of Asheville, NC in the Bent Creek Experimental Forest.Landslides Can Cause More Landslides
Release Date: MAY 15, 2018 The deadliest individual landslides in the U.S. recently were in places where there had previously been a landslide. Why do landslides happen in the same place instead of on nearby slopes that appear to be just as likely, if not more likely, to slide?Integrating Disparate Spatial Datasets from Local to National Scale for Open-Access Web-Based Visualization and Analysis: A Case Study Compiling U.S. Landslide Inventories
Spatial data on landslide occurrence across the U.S. varies greatly in quality, accessibility, and extent. This problem of data variability is common across USGS Mission Areas; it presents an obstacle to developing national-scale products and to identifying areas with relatively good/bad data coverage. We compiled available data of known landslides into a national-scale, searchable online map, whi - Data
Hydrologic monitoring data in steep, landslide-prone terrain, Sitka, Alaska, USA
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 SepteLandslide Inventories across the United States version 2
Landslides are damaging and deadly, and they occur in every U.S. state. However, our current ability to understand landslide hazards at the national scale is limited, in part because spatial data on landslide occurrence across the U.S. varies greatly in quality, accessibility, and extent. Landslide inventories are typically collected and maintained by different agencies and institutions, usually wHydrologic, slope movement, and soil property data from the coastal bluffs of the Atlantic Highlands, New Jersey, 2016-2018
Seasonal variations in vegetation, rainfall, and soil moisture conditions have the potential to impact the slope stability of locally forested coastal bluffs in the Atlantic Highlands of New Jersey. Both the seasonality and rainfall amounts of the two types of storms that induce shallow landslides in the area vary considerably. Most of the documented historical landslides are the result of heavy rSoil moisture monitoring following the 2009 Station Fire, California, USA, 2016-2019
This data release includes 2016-2019 soil moisture timeseries for two drainage basins ("Arroyo Seco" and "Dunsmore Canyon") that burned during the 2009 Station Fire in Los Angeles County, California, USA. The Arroyo Seco (0.01 km2) and Dunsmore Canyon (0.5 km2) drainages include two soil pits, one located near the drainage divide and another near the basin outlet. Following the naming convention eHillslope hydrologic monitoring data following Hurricane Maria in 2017, Puerto Rico, July 2018 to June 2020
This data release includes time-series, qualitative descriptions, and laboratory testing data from two monitoring stations installed in Puerto Rico following Hurricane Maria in 2017, which led to tens of thousands of landslides across the island (Bessette-Kirton et al., 2017). The stations were installed in July of 2018 to investigate subsurface hydrologic response to rainfall and develop a quantiTime-lapse photography of an active coastal-bluff landslide, Mukilteo, Washington, August 2015 - May 2016
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 eHillslope hydrologic monitoring data following the 2009 Station Fire, Los Angeles County, California, November 2015 to June 2017
This data release includes time-series data from two monitoring stations in drainage basins burned in the 2009 Station Fire, Los Angeles County, California. Both stations are located near the upper boundary of their respective watershed and were installed to study the effects of vegetation recovery on hillslope hydrology and debris-flow occurrence. The data include 1-minute time series of rainfallResults of Hydrologic Monitoring on Landslide-prone Coastal Bluffs near Mukilteo, Washington
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 contLab tests for specimens from Mukilteo, WA, 2016
This data release includes the detailed results from laboratory testing of colluvium and landslide deposit specimens collected from coastal bluffs near Mukilteo, Washington. - Publications
Filter Total Items: 46
Slope Unit Maker (SUMak): An efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), andAuthorsJacob Bryson Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Ben Leshchinsky, Matthew CrawfordLandslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA
Probabilistic models to inform landslide early warning systems often rely on rainfall totals observed during past events with landslides. However, these models are generally developed for broad regions using large catalogs, with dozens, hundreds, or even thousands of landslide occurrences. This study evaluates strategies for training landslide forecasting models with a scanty record of landslide-tAuthorsAnnette Patton, Lisa Luna, Josh J. Roering, Aaron Jacobs, Oliver Korup, Benjamin B. MirusMapping landslide susceptibility over large regions with limited data
Landslide susceptibility maps indicate the spatial distribution of landslide likelihood. Modeling susceptibility over large or diverse terrains remains a challenge due to the sparsity of landslide data (mapped extent of known landslides) and the variability in triggering conditions. Several different data sampling strategies of landslide locations used to train a susceptibility model are used to mAuthorsJacob Bryson Woodard, Benjamin B. Mirus, Matthew Crawford, Dani Or, Ben Leshchinsky, Kate E. Allstadt, Nathan J. WoodProlonged influence of urbanization on landslide susceptibility
Landslides pose a threat to life and infrastructure and are influenced by anthropogenic modifications associated with land development. These modifications can affect susceptibility to landslides, and thus quantifying their influence on landslide occurrence can help design sustainable development efforts. Although landslide susceptibility has been shown to increase following urban expansion, the lAuthorsTyler Rohan, Eitan Shelef, Benjamin B. Mirus, Tim ColemanNational strategy for landslide loss reduction
Executive SummaryLandslide hazards are present in all 50 States and most U.S. territories, and they affect lives, property, infrastructure, and the environment. Landslides are the downslope movement of earth materials under the force of gravity. They can occur without any obvious trigger. Widespread or severe landslide events are often driven by such hazards as hurricanes, earthquakes, volcanicAuthorsJonathan W. Godt, Nathan J. Wood, Alice Pennaz, Connor M. Dacey, Benjamin B. Mirus, Lauren N. Schaefer, Stephen L. SlaughterConstructing a large-scale landslide database across heterogeneous environments using task-specific model updates
Preparation and mitigation efforts for widespread landslide hazards can be aided by a large-scale, well-labeled landslide inventory with high location accuracy. Recent smallscale studies for pixel-wise labeling of potential landslide areas in remotely-sensed images using deep learning (DL) showed potential but were based on data from very small, homogeneous regions with unproven model transferabilAuthorsSavinay Nagendra, Daniel Kifer, Benjamin B. Mirus, Te Pei, Kathryn Lawson, Srikanth Banagere Manjunatha, Weixin Li, Hien Nguyen, Tong Qiu, Sarah Tran, Chaopeng ShenClays are not created equal: How clay mineral type affects soil parameterization
Clay minerals dominate the soil colloidal fraction and its specific surface area. Differences among clay mineral types significantly influence their effects on soil hydrological and mechanical behavior. Presently, the soil clay content is used to parameterize soil hydraulic and mechanical properties (SHMP) for land surface models while disregarding the type of clay mineral. This undifferentiated uAuthorsPeter Lehmann, Ben Leshchinsky, Surya Gupta, Benjamin B. Mirus, Samuel Bickel, Ning Lu, Dani OrHydroMet: 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 meaAuthorsJacob L. Conrad, Michael D. Morphew, Rex L. Baum, Benjamin B. MirusEvaluation of techniques for mitigating snowmelt infiltration-induced landsliding in a highway embankment
Infiltration-induced landslides threaten transportation infrastructure around the world, and impose both direct costs through repair and remediation work and indirect costs through lost economic activity. Therefore, finding the most cost-effective techniques to mitigate slope failures that can impact critical infrastructure links is desirable. The Straight Creek landslide, which affects a segmentAuthorsEric Hinds, Ning Lu, Benjamin B. Mirus, Jonathan W. Godt, Alexandra WayllaceRapid-response unsaturated zone hydrology: Small-scale data, small-scale theory, big problems
The unsaturated zone (UZ) extends across the Earth’s terrestrial surface and is central to many problems related to land and water resource management. Flow of water through the UZ is typically thought to be slow and diffusive, such that it could attenuate fluxes and dampen variability between atmospheric inputs and underlying aquifer systems. This would reduce water resource vulnerability to contAuthorsJohn R. Nimmo, Kimberlie Perkins, Michelle R. Plampin, Michelle A. Walvoord, Brian A. Ebel, Benjamin B. MirusNumerical analysis of the effect of subgrid variability in a physically based hydrological model on runoff, soil moisture, and slope stability
In coarse resolution hydrological modeling we face the problem of subgrid variability, the effects of which are difficult to express and are often hidden in the parameterization and calibration. We present a numerical experiment with the physically based hydrological model ParFlow‐CLM with which we quantify the effect of subgrid heterogeneities in headwater catchments within the cell size typicallAuthorsE. Leonarduzzi, R. M. Maxwell, Benjamin B. Mirus, P. MolnarIncorporating 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 oAuthorsF. Fusco, Benjamin B. Mirus, Rex L. Baum, D. Calcaterra, P. De VitaNon-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.