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Implementation and integrated numerical modeling of a landslide early warning system: a pilot study in Colombia

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Abstract

Landslide early warning systems (EWS) are an important tool to reduce landslide risks, especially where the potential for structural protection measures is limited. However, design, implementation, and successful operation of a landslide EWS is complex and has not been achieved in many cases. Critical problems are uncertainties related to landslide triggering conditions, successful implementation of emergency protocols, and the response of the local population. We describe here the recent implementation of a landslide EWS for the Combeima valley in Colombia, a region particularly affected by landslide hazards. As in many other cases, an insufficient basis of data (rainfall, soil measurements, landslide event record) and related uncertainties represent a difficult complication. To be able to better assess the influence of the different EWS components, we developed a numerical model that simulates the EWS in a simplified yet integrated way. The results show that the expected landslide-induced losses depend nearly exponentially on the errors in precipitation measurements. Stochastic optimization furthermore suggests an increasing adjustment of the rainfall landslide-triggering threshold for an increasing observation error. These modeling studies are a first step toward a more generic and integrated approach that bears important potential for substantial improvements in design and operation of a landslide EWS.

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References

  • Basher R (2006) Global early warning systems for natural hazards: systematic and people-centered. Philos Trans R Soc 364:2167–2187. doi:10.1098/rsta.2006.1819

    Article  Google Scholar 

  • Caine N (1980) The rainfall intensity-duration control of shallow landslides and debris flows. Geogr Ann A 62:23–27. doi:10.2307/520449

    Article  Google Scholar 

  • Cepeda H, Murcia LA (1988) Mapa Preliminar de Amenaza Volcanica Potential del Nevado del Tolima, Colombia, S.A., Informe 2070, 50 pp. INGEOMINAS, Ministerio de Minas y Energía, Informe 2070a

  • Crosta GB, Frattini P (2003) Distributed modelling of shallow landslides triggered by intense rainfall. Nat Hazards Earth Syst Sci 3(1–2):81–93

    Article  Google Scholar 

  • Crozier MJ, Glade T (1999) Frequency and magnitude of landsliding: fundamental research issues. Z Geomorphol 115:141–155

    Google Scholar 

  • Dai FC, Lee CF (2001) Frequency–volume relation and prediction of rainfall-induced landslides. Eng Geol 59:253–266. doi:10.1016/S0013-7952(00)00077-6

    Article  Google Scholar 

  • Dow K, Cutter S (1998) Crying wolf: repeat responses to hurricane evacuation orders. Coast Manag 26:237–252. doi:10.1080/08920759809362356

    Article  Google Scholar 

  • Fritz S, Scholes RJ, Obersteiner M, Bouma J, Reyers BA (2008) Conceptual framework for assessing the benefits of a global earth observation system of systems. IEEE Syst J 2:338–348. doi:10.1109/JSYST.2008.926688

    Article  Google Scholar 

  • Glade T, Crozier M, Smith P (2000) Applying probability determination to refine landslide-triggering rainfall thresholds using an empirical “antecedent daily rainfall model”. Pure Appl Geophys 157:1059–1079. doi:10.1007/s000240050017

    Article  Google Scholar 

  • Godoy BF, Guerrero MV, Hoyos C, Núñez TA (1997) Análisis de la vulnerabilidad de líneas vitales y edificaciones estratégicas en la zona rural de la cuenca del Río Combeima – Municipio de Ibagué, Tolima – Evento avalancha, detonante lluvia, 139 pp. Universidad del Tolima, Facultad de Ingeniería Forestal

  • Guzzetti F, Perucacci S, Rossi M, Stark CP (2007) The rainfall thresholds for the initiation of landslides in central and southern Europe. Meteorol Atmos Phys. doi:10.1007/s00703-007-0262-7

  • Guzzetti F, Perucacci S, Rossi M, Stark CP (2008) The rainfall intensity-duration control of shallow landslides and debris flows: an update. Landslides 5:3–17. doi:10.1007/s10346-007-0112-1

    Article  Google Scholar 

  • Hong Y, Adler R, Huffman G (2006) Evaluation of the potential of NASA multi-satellite precipitation analysis in global landslide hazard assessment. Geophys Res Lett 33:L22402. doi:10.1029/2006GL028010

    Article  Google Scholar 

  • Hovius N, Stark CP, Allen PA (1997) Sediment flux from a mountain belt derived by landslide mapping. Geol Soc Am 25:231–234. doi:10.1130/0091-7613(1997)025<0231:SFFAMB>2.3.CO;2

    Google Scholar 

  • Huggel C, Ceballos JL, Ramírez J, Pulgarín B, Thouret JC (2007) Review and reassessment of hazards owing to volcano-ice interactions in Colombia. Ann Glaciol 45:128–136. doi:10.3189/172756407782282408

    Article  Google Scholar 

  • Hungr O, McDougall S, Wise M, Cullen M (2008) Magnitude–frequency relationships of debris flows and debris avalanches in relation to slope relief. Geomorphology 96:355–365. doi:10.1016/j.geomorph.2007.03.020

    Article  Google Scholar 

  • Iverson RM (2000) Landslide triggering by rain infiltration. Water Resour Res 36(7):1897–1910. doi:10.1029/2000WR900090

    Article  Google Scholar 

  • Iverson RM, Reid ME, LaHusen RG (1997) Debris-flow mobilization from landslides. Ann Rev Earth Planet Sci 25:85–138. doi:10.1146/annurev.earth.25.1.85

    Article  Google Scholar 

  • Keefer DK, Larsen MC (2007) Assessing landslide hazards. Science 316:1136–1138. doi:10.1126/science.1143308

    Article  Google Scholar 

  • Keefer DK, Wilson RC, Mark RK, Brabb EE, Brown WMIII, Ellen SD, Harp EL, Wieczorek GF, Alger CS, Zatkin RS (1987) Real-time landslide warning during heavy rainfall. Science 238:921–925. doi:10.1126/science.238.4829.921

    Article  Google Scholar 

  • Khabarov N, Moltchanova E, Obersteiner M (2008) Valuing weather observation systems for forest fire management. IEEE Syst J 2:349–357. doi:10.1109/JSYST.2008.925979

    Article  Google Scholar 

  • Larsen MC, Simon A (1993) A rainfall intensity-duration threshold for landslides in a humid-tropical environment, Puerto Rico. Geogr Ann A 75(1–2):13–23. doi:10.2307/521049

    Article  Google Scholar 

  • Marchi L, Arattano M, Deganutti AM (2002) Ten years of debris-flow monitoring in the Moscardo Torrent (Italian Alps). Geomorphology 46:1–17. doi:10.1016/S0169-555X(01)00162-3

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Petley DN, Higuchi T, Petley DJ, Bulmer MH, Carey J (2005) Development of progressive landslide failure in cohesive materials. Geology 33:201–204. doi:10.1130/G21147.1

    Article  Google Scholar 

  • Ramírez JM (2007) Sistema de información análisis de tormentas (SIAT). User Manual. Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM) Bogotá, 35 pp

  • Sorensen JH (2000) Hazard warning systems: review of 20 years of progress. Nat Hazards Rev 1(2):119–125. doi:10.1061/(ASCE)1527-6988(2000)1:2(119)

    Article  Google Scholar 

  • Spall JC, Hill SD, Stark DR (2006) Theoretical framework for comparing several stochastic optimization approaches. In: Calafiore G, Dabbene F (eds) Probabilistic and randomized methods for design under uncertainty. Springer, London, pp 99–117

    Chapter  Google Scholar 

  • Terlien MTJ (1998) The determination of statistical and deterministic hydrological landslide triggering thresholds. Environ Geol 35:124–130. doi:10.1007/s002540050299

    Article  Google Scholar 

  • Thouret J-C, Cantagrel JM, Robin C, Murcia A, Salinas R, Cepeda H (1995) Quaternary eruptive history and hazard-zone model at Nevado del Tolima and Cerro Machin volcanoes, Colombia. J Volcanol Geotherm Res 66:397–426. doi:10.1016/0377-0273(94)00073-P

    Article  Google Scholar 

  • Uppala SM et al (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131(612):2961–3012. doi:10.1256/qj.04.176

    Article  Google Scholar 

  • Whitehead JC (2003) One million dollars per mile? The opportunity costs of Hurricane evacuation. Ocean Coast 46(11–12):1069–1083. doi:10.1016/j.ocecoaman.2003.11.001

    Article  Google Scholar 

  • Wieczorek GF, Glade T (2005) Climatic factors influencing occurrence of debris flows. In: Jakob M, Hungr O (eds) Debris flow hazards and related phenomena. Springer, Berlin, Heidelberg, pp 325–362

    Chapter  Google Scholar 

  • Williamson RA, Hertzfeld HR, Cordes J, Logsdon JM (2002) The socioeconomic benefits of Earth science and applications research: reducing the risks and costs of natural disasters in the USA. Space Policy 18:57–65. doi:10.1016/S0265-9646(01)00057-1

    Article  Google Scholar 

  • Zschau J, Küppers AN (eds) (2003) Early warning systems for natural disaster reduction. Springer, Berlin, p 834

    Google Scholar 

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Acknowledgements

This research was supported by the Swiss Agency for Development and Cooperation and by the European Commission project GEO-BENE (http://www.geo-bene.eu), led by the International Institute for Applied Systems Analysis (IIASA). Collaborations with the Colombian Dirección General de Prevención y Atención de Desastres (DPAD), the Comité Regional de Prevención y Antención de Desastres del Tolima (CREPAD), the Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM), the Instituto Colombiano de Minería y Geología (INGEOMINAS), the Corporación Regional del Tolima (CORTOLIMA), and the Colombian Red Cross are much appreciated. We would furthermore like to thank Elena Moltchanova for useful discussions and support and Horst Machguth for support with ERA-40 data processing.

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Authors and Affiliations

  1. Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland

    Christian Huggel

  2. International Institute of Applied Systems Analysis, Laxenburg, Austria

    Nikolay Khabarov & Michael Obersteiner

  3. Swiss Agency for Development and Cooperation, Bogotá, Colombia

    Juan Manuel Ramírez

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  1. Christian Huggel
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  2. Nikolay Khabarov
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  3. Michael Obersteiner
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  4. Juan Manuel Ramírez
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Correspondence to Christian Huggel.

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Huggel, C., Khabarov, N., Obersteiner, M. et al. Implementation and integrated numerical modeling of a landslide early warning system: a pilot study in Colombia. Nat Hazards 52, 501–518 (2010). https://doi.org/10.1007/s11069-009-9393-0

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  • DOI: https://doi.org/10.1007/s11069-009-9393-0

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