Landslides pose a threat to people, buildings, infrastructure, and natural and cultural resources. However, there remains very little quantitative characterization of the impacts of landslides. We seek a Mendenhall to develop a better understanding of how communities across the U.S. are exposed to and impacted by landslides to better prepare and mitigate against future landslide risk.
Description of the Research Opportunity
Landslides pose a significant threat to people, buildings, essential facilities and infrastructure, and natural and cultural resources, but the actual and potential impacts of this relatively distributed and compounding hazard remain poorly documented. There has been very little quantitative characterization of the direct and indirect impacts of landslides including casualties, economic losses, or long-term disruptions caused by these events. Attempts to quantify these impacts have resulted in highly uncertain estimates likely due to a lack of a standardized approach for reporting landslide impacts. There is a complete lack of synthesis across individual case studies or regional summaries of landslide-related losses. This lack of data and meta-analysis leads to a lack of understanding of how communities have been impacted both in the long and short term after a landslide event. This also leads to a lack of understanding of how underserved communities may be disproportionately affected by landslide events in the United States.
Understanding of disaster losses related to landslides is complicated by the complex, diffuse, and hyper-local nature of the hazard itself. The vast land surface area, diverse geologic terrain, and variety of landslide types within the U.S., coupled with different hydroclimatic and ecological regions, complicate USGS efforts to understand the spatial and temporal variability in landslide hazards and their corresponding impacts across the nation (Mirus et al., 2020). Efforts to characterize landslide potential at the national and global scales have been pursued for some time now (Radbruch-Hall et al., 1982; Godt et al., 2012; Tanyas et al., 2017; Kirschbaum and Stanley, 2018; Jia et al., 2021), and the research community’s understanding of landslide hazards, data limitations, and research opportunities is still evolving (Mirus et al., 2020; Emberson et al., 2020).
In the United States the number of lives lost as a direct result of landsliding is relatively small compared to other regions of the globe (Froude and Petley, 2018), and fortunately, the number appears to be decreasing from 25-50 fatalities per year in the late twentieth Century (see National Research Council, 1985; Schuster, 1996) to around seven per year in recent decades (see Mirus et al, 2020). Assessments of economic losses are also in need of revision as they are likely greater than previous estimates. Existing calculations of economic costs of landslides are based in part on landslide-related losses to private dwellings in southern California, which were subsequently extrapolated across the country (Slosson and Krohn, 1978), resulting in projected private losses of approximately $400M in 1971 US dollars, or $3B in 2023 US dollars (based on www.usinflationcalculator.com). This extrapolation is potentially a conservative number, considering that more recent estimates of landslide-related losses in just the city of Portland, Oregon, indicate that landslides result in direct losses between at least $1.5M US dollars during typical winters and as high as $84M in more extreme weather years (Burns et al. 2017). In Kentucky, estimates of the direct costs to repair roads and private residences damaged by landslides are approximately $10–20M US dollars annually (Crawford, 2014). However, in both these cases, the indirect losses due to reduced economic productivity and other landslide-related costs are excluded as these remain exceedingly difficult to estimate and have not been reported. Further, the proportionate loss to households has also not been calculated. Regrettably, the indirect impacts of landslides are potentially even more significant during extreme triggering events such as major storms or earthquakes. For example, in September 2017 Hurricane Maria triggered extensive flooding as well as over 70,000 landslides across the Island of Puerto Rico (Hughes et al., 2019), which disrupted roads, electricity, and other critical infrastructure. While the official death toll reported was 64, this number was revisited and eventually determined that the resulting increased mortality claimed several thousands of lives across the Island (Kishore et al., 2018), and it is highly plausible that many of these were fatalities that were an indirect result of landslide damage or destruction of critical infrastructure.
Updated estimates of both direct and indirect losses are needed for the range of typical and severe landslide weather conditions across the U.S., These estimates will become increasingly important as landslide losses are expected to grow with ongoing climate change, increasing disturbances such as wildfire, and populations expanding into landslide-prone terrain (Leshchinsky et al. 2017; Mirus et al. 2017). As the adage goes, you cannot manage what you cannot measure. Without national-scale, data driven estimates of direct and indirect landslide loss, it is impossible to truly understand the extent of landslide risk to the nation and to develop mitigation and preparedness strategies to reduce these losses. It will also remain difficult to address the disproportionate affect landslides may have on underserved populations without understanding the extent and proportion of losses incurred by these populations.
The primary objective of the research opportunity is to develop a better understanding of how communities across the U.S. are exposed to and impacted by landslides. The opportunity is broad and could address a wide range of topics or geographic areas to improve national understanding of variations in landslide impacts, ultimately to better prepare and mitigate against future landslide risk. This objective could be achieved by leveraging existing databases, such as the U.S. landslide inventory compilation (Belair et al, 2022), a preliminary compilation of reported damage and loss from across the country as well as preliminary information on population exposure to landslides in the U.S. at the census tract scale. Census tract scale information on underserved communities in the U.S. is also available via the U.S. Council on Environmental Quality’s Climate and Economic Justice Screening Tool. The candidate could also draw on existing approaches from other hazards such as floods or earthquakes, which are more advanced in terms of quantifying and estimating impacts. Approaches to achieve the research objective using the aforementioned data or information include:
contributing to efforts to determine long-term outcomes of populations affected by landslide disasters using case studies, participatory research, and/or longitudinal Census data;
leveraging existing datasets of landslide occurrence (Belair et al., 2022) and applying existing and emerging landslide susceptibility models (Godt et al., 2012; Mirus et al., 2023 - in prep) to explore spatial and temporal variations in landslide frequency and occurrence across the country and assess the differences in the cost and impacts of landslides across different communities from rural to urban settings;
developing empirical, conceptual, or statistical models to extrapolate between isolated case studies and reports to develop a better national-scale picture of landslide losses;
exploring which communities may be more or less affected by landslide disasters as climate change exacerbates these events (e.g., Leshchinsky et al., 2017),
exploring trends in past losses or methods for extrapolating losses into the future, given different scenarios for land-use and infrastructure development;
collaborating with the USGS Risk Project to identify the most useful data sources on damage and loss, establish a systematic and replicable method for estimating damage from new reports to ensure long-term quantitative records are available in the future.
The research opportunity provides many avenues for innovative research and original contributions to identify suitable approaches for characterizing landslide impacts and associated costs. The successful Mendenhall Fellow can leverage a variety of existing data, powerful computational resources, and a range of expertise from across USGS programs to enhance the ability of the USGS to understand landslide risk and losses across the entire U.S., and to provide actionable data and information to reduce future impacts.
The USGS Landslide Hazards Program (LHP) is dedicated to improving scientific understanding of landslides, while also developing tools and assessments that support external partners in their efforts to mitigate losses from landslides and to prepare at-risk communities. With the recent signing of the National Landslides Preparedness Act into law, the new USGS national strategy for landslide loss reduction (Godt et al., 2022), and establishment of a Landslide Disaster Assistance Team (LDAT), the proposed research opportunity will tie directly into ongoing USGS-led efforts to protect the safety, security, and economic well-being across the Nation and globally. This research will also directly tie into a wider effort by the USGS Risk Project to develop a holistic understanding of disaster losses related to hazards for which the USGS is lead agency.
Interested applicants are strongly encouraged to contact the Research Advisor(s) early in the application process to discuss project ideas.
Belair, G.M., Jones, E.S., Slaughter, S.L., and Mirus, B.B., 2022, Landslide Inventories across the United States version 2. U.S. Geological Survey data release. https://doi.org/10.5066/P9FZUX6N.
Burns, W. J., Calhoun, N. C., Franczyk, J. J., Koss, E. J., & Bordal, M. G., 2017, Estimating losses from landslides in Oregon. Landslides: putting experience, knowledge and emerging technologies into practice. Association of Environmental & Engineering Geologists (AEG), Special Publication, 27, 473-482.
Crawford M.M., 2014, Kentucky Geological Survey landslide inventory: from design to application. Kentucky Geological Survey information circular 31, Series XII, ISSN 0075-5583.
Emberson, R., Kirschbaum, D., & Stanley, T., 2020, New global characterisation of landslide exposure. Natural Hazards and Earth System Sciences, 20(12), 3413-3424.
Froude, M. J., & Petley, D. N., 2018, Global fatal landslide occurrence from 2004 to 2016. Natural Hazards and Earth System Sciences, 18(8), 2161-2181.
Godt, J. W., Coe, J. A., Baum, R. L., Highland, L. M., Keaton, J. R., & Roth Jr, R. J., 2012, Prototype landslide hazard map of the conterminous United States.
Godt, J.W., Wood, N.J., Pennaz, A.B., Dacey, C.M., Mirus, B.B, Schaefer, L.N., and Slaughter, S.L., 2022, National strategy for landslide loss reduction: U.S. Geological Survey Open-File Report, 2022–1075, 36 p., https://doi.org/10.3133/ofr20221075.
Hughes, K. S., Bayouth García, D., Martínez Milian, G. O., Schulz, W. H., & Baum, R. L., 2019, Map of slope-failure locations in Puerto Rico after Hurricane María. US Geological Survey data release.
Jia, G., Alvioli, M., Gariano, S. L., Marchesini, I., Guzzetti, F., & Tang, Q., 2021, A global landslide non-susceptibility map. Geomorphology, 389, 107804.
Kirschbaum, D., & Stanley, T., 2018, Satellite‐based assessment of rainfall‐triggered landslide hazard for situational awareness. Earth's Future, 6(3), 505-523.
Kishore et al., 2018, Mortality in Puerto Rico after Hurricane Maria. New England Journal of Medicine, 2018; 379:162-170 DOI: 10.1056/NEJMsa1803972
Leshchinsky, B., Olsen, M. J., Mohney, C., Glover-Cutter, K., et al., 2017, Mitigating coastal landslide damage. Science, 357, https://doi.org/10.1126/science.aao1722.
Mirus, B.B., Jones, E.S., Baum, R.L., Godt, J.W., Slaughter, S., et al., 2020, Landslides across the United States: Occurrence, Susceptibility, and Data Limitations. Landslides, https://doi.org/10.1007/s10346-020-01424-4.
Mirus, B.B., Smith, J.B., Baum, R.L., 2017, Hydrologic Impacts of Landslide Disturbances: Implications for Remobilization and Hazard Persistence. Water Resources Research, https://doi.org/10.1002/2017WR020842.
National Research Council, 2004, Partnerships for reducing landslide risk: assessment of the national landslide hazards mitigation strategy. National Academies Press.
Radbruch-Hall, D. H., Colton, R. B., Davies, W. E., Lucchitta, I., Skipp, B. A., & Varnes, D. J., 1982, Landslide overview map of the conterminous United States (No. 1183). US Geological Survey.
Schuster, R. L., 1996, Landslides: Investigation and Mitigation. Chapter 2 – Socioeconomic Significance of Landslides (No. 247).
Slosson, J. E., & Krohn, J. P., 1978, Southern California landslides of 1978 and 1980. Storms, floods, and debris flows in Southern California and Arizona, 17-1.
Tanyaş, H., Van Westen, C. J., Allstadt, K. E., Anna Nowicki Jessee, M., Görüm, T., Jibson, R. W., ... & Hovius, N., 2017, Presentation and analysis of a worldwide database of earthquake‐induced landslide inventories. Journal of Geophysical Research: Earth Surface, 122(10), 1991-2015.
Proposed Duty Station(s)
Areas of PhD
Risk analysis, civil engineering, geography, landslides, data and information science, statistics, economics, sociology or related fields (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).
Applicants must meet one of the following qualifications: Research Physical Scientist, Research Geologist, Research Civil Engineer, Research Economist, Research Social Scientist, Research Statistician
(This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant's background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)