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Plenary: Progress in Regional Landslide Hazard Assessment—Examples from the USA

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Landslide Science for a Safer Geoenvironment

Abstract

Landslide hazard assessment at local and regional scales contributes to mitigation of landslides in developing and densely populated areas by providing information for (1) land development and redevelopment plans and regulations, (2) emergency preparedness plans, and (3) economic analysis to (a) set priorities for engineered mitigation projects and (b) define areas of similar levels of hazard for insurance purposes. US Geological Survey (USGS) research on landslide hazard assessment has explored a range of methods that can be used to estimate temporal and spatial landslide potential and probability for various scales and purposes. Cases taken primarily from our work in the U.S. Pacific Northwest illustrate and compare a sampling of methods, approaches, and progress. For example, landform mapping using high-resolution topographic data resulted in identification of about four times more landslides in Seattle, Washington, than previous efforts using aerial photography. Susceptibility classes based on the landforms captured 93 % of all historical landslides (all types) throughout the city. A deterministic model for rainfall infiltration and shallow landslide initiation, TRIGRS, was able to identify locations of 92 % of historical shallow landslides in southwest Seattle. The potentially unstable areas identified by TRIGRS occupied only 26 % of the slope areas steeper than 20°. Addition of an unsaturated infiltration model to TRIGRS expands the applicability of the model to areas of highly permeable soils. Replacement of the single cell, 1D factor of safety with a simple 3D method of columns improves accuracy of factor of safety predictions for both saturated and unsaturated infiltration models. A 3D deterministic model for large, deep landslides, SCOOPS, combined with a three-dimensional model for groundwater flow, successfully predicted instability in steep areas of permeable outwash sand and topographic reentrants. These locations are consistent with locations of large, deep, historically active landslides. For an area in Seattle, a composite of the three maps illustrates how maps produced by different approaches might be combined to assess overall landslide potential. Examples from Oregon, USA, illustrate how landform mapping and deterministic analysis for shallow landslide potential have been adapted into standardized methods for efficiently producing detailed landslide inventory and shallow landslide susceptibility maps that have consistent content and format statewide.

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References

  • Aleotti P, Chowdury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Env 58:21–44

    Article  Google Scholar 

  • Artim ER (1976) Slope stability map of Thurston County, Washington. Geologic Map GM-15, Division of Geology and Earth Resources, Washington Department of Natural Resources, Olympia, WA, USA, 1:125,000

    Google Scholar 

  • Baum RL, Coe JA, Godt JW, Harp EL, Reid ME, Savage WZ, Schulz WH, Brien DL, Chleborad AF, McKenna JP, Michael JA (2005) Regional landslide-hazard assessment for Seattle, Washington, USA. Landslides 2(4):266–279. doi:10.1007/s10346-005-0023-y

    Article  Google Scholar 

  • Baum RL, Savage WZ, Godt JW (2008) TRIGRS—A FORTRAN program for transient rainfall infiltration and grid‐based regional slope‐stability analysis, version 2.0. US Geological Survey Open‐File Rep 2008‐1159. http://pubs.er.usgs.gov/publication/ofr20081159

  • Baum RL, Godt JW, Savage WZ (2010) Estimating the timing and location of shallow rainfall‐induced landslides using a model for transient, unsaturated infiltration. J Geophys Res 115:F03013. doi:10.1029/2009JF001321

    Google Scholar 

  • Baum RL, Godt JW, Coe JA, Reid ME (2012) Assessment of shallow landslide potential using 1-D and 3-D slope stability analysis. In: Eberhardt E, Froese C, Turner AK, Leroueil S (eds) Landslides and engineered slopes: protecting society through improved understanding. Taylor & Francis, London, pp 1667–1672

    Google Scholar 

  • Berti M, Simoni A (2007) Prediction of debris flow inundation areas using empirical mobility relationships. Geomorphology 90(1–2):144–161

    Article  Google Scholar 

  • Borga M, Fontana GD, Ros DD, Marchi L (1998) Shallow landslide hazard assessment using a physically based model and digital elevation data. Environ Geol 35(2–3):81–88. doi:10.1007/s002540050295

    Article  Google Scholar 

  • Brabb EE, Pampeyan EH, Bonilla MG (1972) Landslide susceptibility in San Mateo County, California. US Geological Survey Miscellaneous Field Studies Map 360, 1:24,000

    Google Scholar 

  • Brien DL, Reid ME (2007) Modeling 3-D slope stability of coastal bluffs using 3-D ground-water flow, southwestern Seattle, Washington. US Geological Survey Scientific Investigations Report 2007-5092. http://pubs.usgs.gov/sir/2007/5092/

  • Brien DL, Reid ME (2008) Assessing deep-seated landslide susceptibility using 3-D groundwater and slope-stability analyses, southwestern Seattle, Washington. In: Baum RL, Godt JW, Highland LM (eds) Engineering geology and landslides of the Seattle, Washington, area, vol 20, Geological Society of America reviews in engineering geology. Geological Society of America, Boulder, pp 83–101. doi:10.1130/2008.4020(05)

    Google Scholar 

  • Burns WJ (2007) Comparison of remote sensing data-sets for the establishment of a landslide mapping protocol in Oregon. Conference presentations, 1st North American landslide conference, AEG Special Publication 23, Vail, CO

    Google Scholar 

  • Burns WJ, Madin IP (2009) Protocol for inventory mapping of landslide deposits from light detection and ranging (LiDAR) imagery. Oregon Department of Geology and Mineral Industries Special Paper 42

    Google Scholar 

  • Burns WJ, Madin IP, Mickelson KA (2012) Protocol for shallow landslide susceptibility mapping. Oregon Department of Geology and Mineral Industries Special Paper 45

    Google Scholar 

  • Cannon SH, Gartner JE, Rupert MG, Michael JA, Rea AH, Parrett C (2010) Predicting the probability and volume of postwildfire debris flows in the intermountain western United States. Bull Geol Soc Am 122(1–2):127–144

    Article  Google Scholar 

  • Carrara A (1983) Multivariate models for landslide hazard evaluation. Math Geol 15(3):403–426

    Article  Google Scholar 

  • Carrara A, Cardinali M, Detti R, Guzzetti F, Pasqui V, Reichenbach P (1991) GIS techniques and statistical models in evaluating landslide hazard. Earth Surf Process Landforms 16:427–445

    Article  Google Scholar 

  • Carrara A, Guzzetti F, Cardinali M, Reichenbach P (1999) Use of GIS technology in the prediction and monitoring of landslide hazard. Nat Hazards 20:117–135. doi:10.1023/A:1008097111310

    Article  Google Scholar 

  • Catani F, Segoni S, Falorni G (2010) An empirical geomorphology‐based approach to the spatial prediction of soil thickness at catchment scale. Water Resour Res 46, W05508. doi:10.1029/2008WR007450

    Google Scholar 

  • Chung CF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30:451–472. doi:10.1023/B:NHAZ.0000007172.62651.2b

    Article  Google Scholar 

  • Chung CJ, Fabbri A, van Westen CJ (1995) Multivariate regression analysis for landslide hazard zonation. In: Carrara A, Guzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer Publications, Dordrecht, pp 107–133

    Chapter  Google Scholar 

  • Coe JA, Michael JA, Crovelli RA, Savage WZ, Laprade WT, Nashem WD (2004a) Probabilistic assessment of precipitation-triggered landslides using historical records of landslide occurrence, Seattle, Washington. Environ Eng Geosci 10(2):103–122

    Article  Google Scholar 

  • Coe JA, Godt JW, Baum RL, Bucknam RC, Michael JA (2004b) Landslide susceptibility from topography in Guatemala. In: Lacerda WA et al (eds) Landslides, evaluation and stabilization. Proceedings of the 9th international symposium on landslides, vol 1. Rio de Janeiro, pp 69–79

    Google Scholar 

  • Crosta GB, Frattini R (2003) Distributed modeling of shallow landslides triggered by intense rainfall. Nat Hazards Earth Syst Sci 3:81–93

    Article  Google Scholar 

  • Dai FC, Lee CF (2003) A spatiotemporal probabilistic modelling of storm induced shallow landsliding using aerial photographs and logistic regression. Earth Surf Process Landforms 28(5):527–545

    Article  Google Scholar 

  • Dai FC, Lee CF, Ngai YY (2002) Landslide risk assessment and management: an overview. Eng Geol 64(1):65–87

    Article  Google Scholar 

  • Dietrich WE, Reiss R, Hsu M-L, Montgomery DR (1995) A process-based model for colluvial soil depth and shallow landsliding using digital elevation data. Hydrol Process 9:383–400. doi:10.1002/hyp.3360090311

    Article  Google Scholar 

  • Ellen SD, Mark RK, Cannon SH, Knifong DL (1993) Map of debris-flow hazard in the Honolulu District of Oahu, Hawaii. US Geological Survey Open-File Report, pp 93–213, 1:30,000

    Google Scholar 

  • Falaschi F, Giacomelli F, Federici PR, Puccinelli A, D’Amato Avanzi G, Pochini A, Ribolini A (2009) Logistic regression versus artificial neural networks: landslide susceptibility evaluation in a sample area of the Serchio River valley, Italy. Nat Hazards 50:551–569. doi:10.1007/s11069-009-9356-5

    Article  Google Scholar 

  • Fawcett T (2006) An introduction to ROC analysis. Pattern Recognit Lett 27:861–874

    Article  Google Scholar 

  • Felicísimo ÁM, Cuartero A, Remondo J, Quirós E (2013) Mapping landslide susceptibility with logistic regression, multiple adaptive regression splines, classification and regression trees, and maximum entropy methods: a comparative study. Landslides 10(2):175–189

    Article  Google Scholar 

  • Franciss FO (2004) Landslide hazard assessment on hilly terrain. In: Lacerda WA, Ehrlich M, Fontoura SAB, Sayão ASF (eds) Landslides—evaluation and stabilization. Proceedings of the 9th international symposium on landslides, vol 1. Balkema, Rio de Janeiro, Brazil, pp 143–150

    Google Scholar 

  • Frattini P, Crosta GB, Fusi N, Dal Negro P (2004) Shallow landslides in pyroclastic soils, a distributed modeling approach for hazard assessment. Eng Geol 73(3–4):277–295. doi:10.1016/j.enggeo.2004.01.009

    Article  Google Scholar 

  • Gioia E, Speranza G, Ferretti M, Marincioni F, Godt JW, Baum RL (2013) Rainfall induced shallow landslide forecasting in large areas: application of the TRIGRS model over a broad area of post-orogenic Quaternary sediments (Abstract). Geol Soc Am Abs Prog 45(7):775

    Google Scholar 

  • Godt JW, McKenna JP (2008) Numerical modeling of rainfall thresholds for shallow landsliding in the Seattle, Washington, area. In: Baum RL, Godt JW, Highland LM (eds) Engineering geology and landslides of the Seattle, Washington, area, vol 20, Geological Society of America reviews in engineering geology. Geological Society of America, Boulder, CO, pp 121–135. doi:10.1130/2008.4020(07)

    Google Scholar 

  • Godt JW, Schulz WH, Baum RL, Savage WZ (2008a) Modeling rainfall conditions for shallow landsliding in Seattle, Washington. In: Baum RL, Godt JW, Highland LM (eds) Engineering geology and landslides of the Seattle, Washington, area, vol 20, Geological Society of America reviews in engineering geology. Geological Society of America, Boulder, pp 137–152. doi:10.1130/2008.4020(08)

    Google Scholar 

  • Godt JW, Baum RL, Savage WZ, Salciarini D, Schulz WH, Harp EL (2008b) Transient deterministic shallow landslide modeling: requirements for susceptibility and hazard assessments in a GIS framework. Eng Geol 102:214–226. doi:10.1016/j.enggeo.2008.03.019

    Article  Google Scholar 

  • Godt JW, Coe JA, Baum RL, Highland LM, Keaton JR, Roth RJ Jr (2012) Prototype landslide hazard map of the conterminous United States. In: Eberhardt E, Froese C, Turner AK, Leroueil S (eds) Landslides and engineered slopes: protecting society through improved understanding. Taylor & Francis Group, London, pp 245–250

    Google Scholar 

  • Griswold JP, Iverson RM (2008) Mobility statistics and automated hazard mapping for debris flows and rock avalanches. US Geological Survey Scientific Investigations Report: 2007-5276

    Google Scholar 

  • Guzzetti F, Carrara A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology 31(1–4):181–216. doi:10.1016/S0169-555X(99)00078-1

    Article  Google Scholar 

  • Haneberg WC (2008) Elevation errors in a LiDAR digital elevation model of West Seattle and their effects on slope stability calculations. In: Baum RL, Godt JW, Highland LM (eds) Engineering geology and landslides of the Seattle, Washington, area, vol 20, Geological Society of America reviews in engineering geology. Geological Society of America, Boulder, CO, pp 55–65. doi:10.1130/2008.4020(03)

    Google Scholar 

  • Harbaugh AW, Banta ER, Hill MC, McDonald MG (2000) MODFLOW-2000, the US Geological Survey modular ground-water model—user guide to modularization concepts and the ground-water flow process. US Geological Survey Open-File Report 00-92

    Google Scholar 

  • Harp EL, Noble MA (1993) An engineering rock classification to evaluate seismic rock-fall susceptibility and its application to the Wasatch Front. Bull Assoc Eng Geol 30:293–319

    Google Scholar 

  • Harp EL, Michael JA, Laprade WT (2006) Shallow-landslide hazard map of Seattle, Washington. US Geological Survey Open-File Report 2006-1139. http://pubs.usgs.gov/of/2006/1139/

  • Harp EL, Michael JA, Laprade WT (2008) Shallow landslide hazard map of Seattle, Washington. In: Baum RL, Godt JW, Highland LM (eds) Engineering geology and landslides of the Seattle, Washington, area, vol 20, Geological Society of America reviews in engineering geology. Geological Society of America, Boulder, CO, pp 67–82. doi:10.1130/2008.4020(04)

    Google Scholar 

  • Harp EL, Reid ME, McKenna JP, Michael JA (2009) Mapping of hazard from rainfall-triggered landslides in developing countries: examples from Honduras and Micronesia. Eng Geol 104:295–311

    Article  Google Scholar 

  • Harp EL, Keefer DK, Sato HP, Yagi H (2011) Landslide inventories: the essential part of seismic landslide hazard analyses. Eng Geol. doi:10.1016/j.enggeo.2010.06.013

    Google Scholar 

  • Harp EL, Hartzell SH, Jibson RW, Ramirez-Guzman L (2012) Relation of landslides triggered by the Kiholo Bay earthquake and modeled ground motion. In: Eberhardt E, Froese C, Turner AK, Leroueil S (eds) Landslides and engineered slopes: protecting society through improved understanding. CRC, London, pp 507–510

    Google Scholar 

  • Ho J-Y, Lee KT, Chang TC, Wang Z-Y, Liao Y-H (2012) Influences of spatial distribution of soil thickness on shallow landslide prediction. Eng Geol 124:38–46

    Article  Google Scholar 

  • Jibson RW, Harp EL, Michael JA (2000) A method for producing digital probabilistic seismic landslide hazard maps. Eng Geol 58:271–289

    Article  Google Scholar 

  • Kirschbaum DB, Adler R, Hong Y, Hill S, Lerner-Lam AL (2010) A global landslide catalog for hazard applications—method, results and limitations. Nat Hazards 52(3):561–575

    Article  Google Scholar 

  • Laprade WT, Kirkland TE, Nashem WD, Robertson CA (2000). Seattle landslide study. Shannon & Wilson, Inc. Internal Report W-7992 -01. 164 pp. http://www.seattle.gov/dpd/cms/groups/pan/@pan/documents/web_informational/dpdp025740.pdf

  • Lee S, Ryu J-H, Min K, Won J-S (2003) Landslide susceptibility analysis using GIS and artificial neural network. Earth Surf Process Landforms 28(12):1361–1376

    Article  Google Scholar 

  • Lu P, Rosenbaum MS (2003) Artificial neural networks and grey systems for the prediction of slope stability. Nat Hazards 30(3):383–398

    Article  Google Scholar 

  • Magirl CS, Griffiths PG, Webb RH (2010) Analyzing debris flows with the statistically calibrated empirical model LAHARZ in southeastern Arizona, USA. Geomorphology 119:111–124

    Article  Google Scholar 

  • Miller RD (1973) Map showing relative slope stability in part of west-central King County, Washington. US Geological Survey Miscellaneous Investigations Series Map, I-852-A, 1:48,000

    Google Scholar 

  • Miller DJ (1995) Coupling GIS with physical models to assess deep-seated landslide hazards. Environ Eng Geosci 1(3):263–276

    Google Scholar 

  • Montgomery DR, Dietrich WE (1994) A physically based model for the topographic control on shallow landsliding. Water Resour Res 30(4):1153–1171. doi:10.1029/93WR02979

    Article  Google Scholar 

  • Montgomery DR, Sullivan K, Greenberg HM (1998) Regional test of a model for shallow landsliding. Hydrol Process 12(6):943–955. doi:10.1002/(SICI)1099-1085(199805)12:6,943:AID-HYP664.3.0.CO;2-Z

    Article  Google Scholar 

  • Ohlmacher GC, Davis JC (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69(3–4):331–343

    Article  Google Scholar 

  • Pack RT, Tarboton DG, Goodwin CN (1998) The SINMAP approach to terrain stability mapping. In: Proceedings of the 8th international congress of the international association of engineering geology and the environment, Vancouver, British Columbia, Canada, September 21–25, vol 2. AA Balkema, Rotterdam, pp 1157–1165

    Google Scholar 

  • Pelletier JD, Rasmussen C (2009) Geomorphically based predictive mapping of soil thickness in upland watersheds. Water Resour Res 45, W09417. doi:10.1029/2008WR007319

    Google Scholar 

  • Petley D (2012) Global patterns of loss of life from landslides. Geology 40(10):927–930

    Article  Google Scholar 

  • Raia S, Alvioli M, Rossi M, Baum RL, Godt JW, Guzzetti F (2013) Improving predictive power of physically based rainfall-induced shallow landslide models: A probabilistic approach. Geosci Model Dev Discuss 6:1367–1426. doi:10.5194/gmdd-6-1367-2013

    Article  Google Scholar 

  • Reid ME, Christian SB, Brien DL (2000) Gravitational stability of three-dimensional stratovolcano edifices. J Geophys Res 105(B3):6043–6056. doi:10.1029/1999JB900310

    Article  Google Scholar 

  • Reid ME, Sisson TW, Brien DL (2001) Volcano collapse promoted by hydrothermal alteration and edifice shape, Mount Rainier, Washington. Geology 29(9):779–782

    Article  Google Scholar 

  • Reid ME, Brien DL, Waythomas CF (2010) Preliminary slope-stability analysis of Augustine Volcano. In: Power JA, Coombs ML, Freymueller JT (eds) The 2006 Eruption of Augustine Volcano, Alaska, US Geological Survey Professional Paper 1769, pp 321–332. http://pubs.usgs.gov/pp/1769/chapters/p1769_chapter14.pdf

  • Roering JJ (2008) How well can hillslope evolution models “explain” topography? Simulating soil transport and production with high-resolution topographic data. Geol Soc Am Bull 120(9/10):1248–1262. doi:10.1130/B26283.1

    Article  Google Scholar 

  • Roering JJ, Stimely LL, Mackey BH, Schmidt DA (2009) Using DInSAR, airborne LiDAR, and archival air photos to quantify landsliding and sediment transport. Geophys Res Lett 36(19). doi: 10.1029/2009GL040374

  • Salciarini D, Godt JW, Savage WZ, Baum RL, Conversini P (2008) Modeling landslide recurrence in Seattle, Washington, USA. Eng Geol 102(3–4):227–237. doi:10.1016/j. enggeo.2008.03.013

    Article  Google Scholar 

  • Savage WZ, Godt JW, Baum RL (2003) A model for spatially and temporally distributed shallow landslide initiation by rainfall infiltration. In: Rickenmann D, Chen C (eds) Debris-flow hazards mitigation: mechanics, prediction, and assessment. Mill Press, Rotterdam, pp 179–187

    Google Scholar 

  • Savage WZ, Godt JW, Baum RL (2004) Modeling time-dependent aerial slope stability. In: Lacerda WA, Erlich M, Fontoura SAB, Sayao ASF (eds) Landslides—evaluation and stabilization. Proceedings of the 9th international symposium on landslides, vol 1. Balkema, London, pp 23–36

    Google Scholar 

  • Schilling S P (1998) LAHARZ; GIS programs for automated mapping of lahar-inundation hazard zones. US Geological Survey Open-File Report 98-638

    Google Scholar 

  • Schulz WH (2004) Landslides mapped using LiDAR imagery, Seattle, Washington. US Geological Survey Open-File Report 2004-1396

    Google Scholar 

  • Schulz WH (2007) Landslide hazards revealed by LiDAR imagery, Seattle, Washington. Eng Geol 89(1–2):67–87

    Article  Google Scholar 

  • Schulz WH, Lidke DJ, Godt JW (2008) Modeling the spatial distribution of landslide-prone colluvium and shallow groundwater on hillslopes of Seattle, WA. Earth Surf Process Landforms 33:123–141

    Article  Google Scholar 

  • Simoni S, Zanotti F, Bertoldi G, Rigon R (2008) Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop‐FS. Hydrol Process 22(4):532–545. doi:10.1002/hyp.6886

    Article  Google Scholar 

  • Soeters R, van Westen CJ (1996) Slope instability recognition, analysis, and zonation. In: Turner AK, Schuster RL (eds) Landslides, investigation and mitigation. Transportation Research Board Special Report 247. National Research Council, Washington, DC, pp 129–177

    Google Scholar 

  • Suzen ML, Doyuran V (2003) A comparison of the GIS based landslide susceptibility assessment methods: multivariate versus bivariate. Environ Geol. doi:10.1007/s00254-003-0917-8

    Google Scholar 

  • Swets J (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293

    Article  CAS  Google Scholar 

  • Troost KG, Booth DB, Wisher AP, Shimel SA (2005) The geologic map of Seattle–A progress report. US Geological Survey Open-file Report 2005-1252

    Google Scholar 

  • van Beek LPH, van Asch TWJ (2004) Regional assessment of the effects of land‐use change on landslide hazard by means of physically based modeling. Nat Hazards 31:289–304

    Article  Google Scholar 

  • Van den Eeckhaut M, Vanwalleghem T, Poesen J, Govers G, Verstraeten G, Vandekerckhove L (2006) Prediction of landslide susceptibility using rare events logistic regression: a case‐study in the Flemish Ardennes (Belgium). Geomorphology 76:392–410

    Article  Google Scholar 

  • van Westen CJ, Terlien MTJ (1996) An approach towards deterministic landslide hazard analysis in GIS: a case study from Manizales (Colombia). Earth Surf Process Landforms 21(9):853–868

    Article  Google Scholar 

  • van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30(3):399–419

    Article  Google Scholar 

  • van Westen CJ, van Asch TWJ, Soeters R (2006) Landslide hazard and risk zonation—why is it still so difficult? Bull Eng Geol Env 65:167–184. doi:10.1007/s10064-005-0023-0

    Article  Google Scholar 

  • Varnes DJ (1981) The principles and practice of landslide hazard zonation. Bull Int Assoc Eng Geol 23:13–14

    Article  Google Scholar 

  • Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. UNESCO, Paris, 60 pp

    Google Scholar 

  • Wait TC (2001) Characteristics of deep-seated landslides in Seattle, Washington. M.S. thesis, Colorado School of Mines, Golden, CO

    Google Scholar 

  • Wu W, Sidle RC (1995) A distributed slope stability model for steep forested hillslopes. Water Resour Res 31:2097–2110

    Article  Google Scholar 

  • Xie M, Esaki T, Zhou G (2004) GIS-based probabilistic mapping of landslide lazard using a three-dimensional deterministic odel. Nat Hazards 33:265–282

    Article  Google Scholar 

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Acknowledgments

Jeff Coe and Kevin Schmidt (both USGS) provided constructive reviews of the manuscript.

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Baum, R.L., Schulz, W.H., Brien, D.L., Burns, W.J., Reid, M.E., Godt, J.W. (2014). Plenary: Progress in Regional Landslide Hazard Assessment—Examples from the USA. In: Sassa, K., Canuti, P., Yin, Y. (eds) Landslide Science for a Safer Geoenvironment. Springer, Cham. https://doi.org/10.1007/978-3-319-04999-1_2

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