Abstract
Landslides have become a frequent natural hazard and pressing severe environmental issues in Sri Lanka. The upward trend in high-intensity rainfall events, growing population, expansion of plantation, and lifelines increased the landslide risk of the country. Though developed countries adopted in risk assessment-based management, conversely, they rely on conventional landslide hazard assessment-based risk management. Therefore, this study is attempted to create a standardized landslide risk assessment framework, combining susceptibility and vulnerability. In the experimental design, landslide susceptibility was determined by nine (09) landslide causative factors, and fourteen (14) factors assessed for landslide vulnerability. Factors were prepared, standardized, and analyzed according to the level of contribution to susceptibility and vulnerability by using spatial multi-criteria evaluation method and entropy method under geographical information system. Spatial distribution of susceptibility and vulnerability were integrated to obtain the spatial distribution of risk. Analyses indicate that highly susceptible and high vulnerable areas are not demonstrated a high level of risk individually. However, a combination of them creates a high level of risk. The risk was classified into six classes, such as highest, high, moderate, low, lowest, and no risk. The highest-risk and high-risk zones of the area show 257 km2 (15%) and 21% (350 km2) of the total land area, respectively. Moderately risk zones take part 27% (446 km2). However, 22% (375 km2) of land area categorized as low or lowest risk and 15% (255 km2) under the no-risk. The study concluded that the developed framework is transparent and easy to update periodically by the local authorities. Hence, public policymakers can use the findings of this study to plan the future development of the region and the country. In contrast, risk assessment provides essential information to enhance national disaster risk reduction strategies.
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References
Abella EAC, Van Westen CJ (2007) Generation of a landslide risk index map for Cuba using spatial multi-criteria evaluation. Landslides 4:311–325. https://doi.org/10.1007/s10346-007-0087-y
Abraham MT, Pothuraju D, Satyam N (2019) Rainfall thresholds for prediction of landslides in Idukki, India: an empirical approach. Water 11:2113. https://doi.org/10.3390/w11102113
Aguilar BH, Rivera NR (2016) The production of vulnerability to landslides: the risk habitus in two landslide-prone neighborhoods in Teziutlan, Mexico. Invest Geográficas 90(7):27. https://doi.org/10.14350/rig.506
Althuwaynee OF, Pradhan B (2016) Semi-quantitative landslide risk assessment using GIS-based exposure analysis in Kuala Lumpur City. Geomatics Nat Hazards Risk 8:706–732. https://doi.org/10.1080/19475705.2016.1255670
Anderson MG, Holcombe E, Blake JR, Ghesquire F, Holm-Nielsen N, Fisseha T (2011) Reducing landslide risk in communities, evidence from the Eastern Caribbean. Appl Geogr 31:590–599. https://doi.org/10.1016/j.apgeog.2010.11.001
Antofie TE, Doherty B, Marin–Ferrer, M., 2018. Mapping of risk web-platforms and risk data: collection of good practices, EUR 29086 EN, Publications Office of the European Union, ISBN 978-92-79-80171-6. https://doi.org/10.2760/93157
Bandara RMS, Jayasingha P (2018) Landslide disaster risk reduction strategies and present achievements in Sri Lanka historical background of landslide research in Sri Lanka. Geosci Res 3:21–27. https://doi.org/10.22606/gr.2018.3300
Birkmann J (2006) Measuring vulnerability to promote disaster-resilient societies: conceptual frameworks and definitions, measuring vulnerability to natural hazards; towards disaster resilient societies. United Nations University Press, Tokyo, pp 9–54
Center for Research on the Epidemiology of Disasters (CRED) (2019) EM-DAT: The OFDA/CRED international disaster database. www.emdat.be/. Accessed 09 Sept 2019.
Clague JJ, Roberts NJ (2012) Landslide hazard and risk. In: Clague JJ, Stead D (eds) Landslides:types mechanisms and modeling, 1st-9 edn. Cambridge University Press, Cambridge
Cooray PG (1994) The precambrian of Sri Lanka: a historical review. Precambr Res 66(1–4):3–18. https://doi.org/10.1016/0301-9268(94)90041-8
Crozier MJ, Glade T (2005) Landslide hazard and risk: issues, concepts, and approach. In: Glade T, Anderson M, Crozier MJ (eds) Landslide hazard and risk. John Wiley & Sons, Chichester, UK, pp 1–40
Cutter SL, Ash KD, Emrich CT (2016) Urban-rural differences in disaster resilience. Ann Am Assoc Geogr 106:1236–1252. https://doi.org/10.1080/24694452.2016.1194740
Dai F, Lee C, Ngai Y (2002) Landslide risk assessment and management: an overview. Eng Geol 64:65–87. https://doi.org/10.1016/s0013-7952(01)00093-x
Department of Census & Statistics, Sri Lanka (DCSSL) (2016) Census of population, housing, and land use. Colombo, Department of Census & Statistics Ministry of Policy Planning and Economic Affairs, pp 187–280. https://www.statistics.gov.lk/PopHouSat. Accessed 25 Feb
Dissanayake D, Morimoto T, Ranagalage M, Murayama Y (2019) Land-use/land-cover changes and their impact on surface urban heat islands: case study of Kandy City, Sri Lanka. Climate 7:99. https://doi.org/10.3390/cli7080099
Dissanayake D, Morimoto T, Ranagalage M (2018) Accessing the soil erosion rate based on RUSLE model for sustainable land use management: a case study of the Kotmale watershed, Sri Lanka. Model Earth Syst Environ 4:1–16. https://doi.org/10.3390/cli7080099
Dissanayake D, Morimoto T, Murayama Y, Ranagalage M, Perera E (2020) Analysis of life quality in a tropical mountain city using a multi-criteria geospatial technique: a case study of Kandy City, Sri Lanka. Sustainability 12:2918. https://doi.org/10.3390/su12072918
Du Y, Ding Y, Li Z, Cao G (2015) The role of hazard vulnerability assessments in disaster preparedness and prevention in China. Mil Med Res 2:27–34. https://doi.org/10.1186/s40779-015-0059-9
Edirisooriya K (2019) Hazard risk assessment and management methodologies review: Sri Lanka. Int J Sci Res Public (IJSRP) 9:857–864. https://doi.org/10.29322/ijsrp.9.0
El Jazouli A, Barakat A, Khellouk R (2019) GIS-multicriteria evaluation using AHP for landslide susceptibility mapping in Oum Er Rbia high basin (Morocco). Geoenviron Disasters. https://doi.org/10.1186/s40677-019-0119-7
Estoque RC, Murayama Y, Ranagalage M, Hou H, Subasinghe S, Gong H, Simwanda M, Handayani HH, Zhang X (2017) Validating ALOS PRISM DSM-derived surface feature height: implications for urban volume estimation. Tsukuba Geoenviron Sci 13:13–22
Fell R (1994) Landslide risk assessment and acceptable risk. Can Geotech J 31:261–272
Fell R, Corominas J, Bonnard C, Cascini L, Leroi E, Savage WZ (2008) Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Eng Geol 102:85–98. https://doi.org/10.1016/j.enggeo.2008.03.022
Froude MJ, Petley DN (2018) Global fatal landslide occurrence from 2004 to 2016. Nat Hazards Earth Syst Sci 18(8):2161–2181. https://doi.org/10.5194/nhess-18-2161-2018
Galli M, Guzzetti F (2007) Landslide vulnerability criteria: a case study from Umbria, Central Italy. Environ Manag 40:649–664. https://doi.org/10.1007/s00267-006-0325
Glade T (2003) Landslide occurrence as a response to land use change: a review of evidence from New Zealand. CATENA 51(3–4):297–314. https://doi.org/10.1016/S0341-8162(02)00170-4
Gonçalves GC, Zêzere J (2018) Combining social vulnerability and physical vulnerability to analyze landslide risk at the municipal scale. Geosciences 8:294–317. https://doi.org/10.3390/geosciences8080294
Gunarathna BWGID, Jayasinghe AB, Mahanama PKS (2019) Assessing the impact of land use on triggering landslides: a case of Sabaragamuwa Province, Sri Lanka. Bhumi Plan Res J 6:15. https://doi.org/10.4038/bhumi.v6i2.42
Hemasinghe H, Rangali RSS, Deshapriya NL, Samarakoon L (2018) Landslide susceptibility mapping using logistic regression model (a case study in Badulla District, Sri Lanka). Procedia Eng 212:1046–1053. https://doi.org/10.1016/j.proeng.2018.01.35
Isaza Restrepo PA, Martínez Carvajal HE, Montoya CAH (2016) Methodology for quantitative landslide risk analysis in residential projects. Habitat Int 53:403–412. https://doi.org/10.1016/j.habitatint
Jaiswal P, Van Westen CJ, Jetten V (2011) Quantitative estimation of landslide risk from rapid debris slides on natural slopes in the Nilgiri hills. India. Nat Hazards Earth Syst Sci 11(6):1723–1743. https://doi.org/10.5194/nhess-11-1723-2011
Jayasingha P (2016) Social geology and landslide disaster risk reduction in Sri Lanka. J Tropical For Environ 6:1–13
Jayasinghe GJMSR, Wijekoon P, Gunatilake J (2017) Landslide susceptibility statistical models: a case study in Badulla district, Sri Lanka. Ceylon J Sci 46:26–41
Jayathilake D, Munasinghe D (2015) Quantitative landslide risk assessment and risk management. In: NBRO symposium on innovations for resilient environment. National Building Research Organization, Colombo Sri Lanka
Karnawati D, Fathani TF, Wilopo W, Andayani B (2018) TXT-tool 4.062-1.1: community hazard maps for landslide risk reduction. In: Sassa K, Tiwari B, Liu KF, McSaveney M, Strom A, Setiawan H (eds) Landslide dynamics: ISDR-ICL landslide interactive teaching tools. Springer, Cham
Kumari MAKK, Rajapakshe RMSD, Rajapaksha KMS (2016) Applicability of relative weights of existing landslide hazard zonation methodology for different Terrain conditions of Sri Lanka-case study in Kegalle District. In: Risk awareness & future challenges: NBRO International symposium 2016. National Building Research Organization, Colombo, Sri Lanka, 121– 126
Lee EM, Jones DKC (2004) In: Bromhead E, Dixon N, Ibsen M (eds) Landslide risk assessment, 1st edn. Thomas Telford Limited, London
Lee Y, Chi Y (2011) Rainfall-induced landslide risk at Lushan, Taiwan. Eng Geol 123:113–121. https://doi.org/10.1016/j.enggeo.2011.03.006
Lee EM (2015) Landslide risk assessment: the challenge of communicating uncertainty to decision-makers. Q J Eng GeolHydrogeol 49:21–35. https://doi.org/10.1144/qjegh2015-066
Li X, Wang K, Liu L, Xin J, Yang H, Gao C (2011) Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Procedia Eng 26:2085–2091. https://doi.org/10.1016/j.proeng.2011.11.2410
Lin Q, Wang Y, Liu T, Zhu Y, Sui Q (2017) The vulnerability of people to landslides: a case study on the relationship between the casualties and volume of landslides in China. Int J Environ Res Public Health 14:212–226. https://doi.org/10.3390/ijerph14020212
Malczewski J (1999) GIS and multi criteria decision analysis. Wiley, New York
Meng QS (1989) Information theory. Xi’an Jiaotong University Press, Xi’an, pp 19–36
Mondal S, Maiti R (2013) Integrating the analytical hierarchy process (AHP) and the frequency ratio (FR) model in landslide susceptibility mapping of Shiv-khola watershed, Darjeeling Himalaya. Int J Disaster Risk Sci 4:200–212. https://doi.org/10.1007/s13753-013-0021-y
Murillo-García F, Rossi M, Fiorucci F, Alcántara-Ayala I (2015) Engineering geology for society and territory. In: Lollino G, Giordan D, Crosta GB, Corominas J, Azzam R, Wasowski JNS (eds) Engineering geology for society and territory 2: landslide processes, 1st edn. Springer, Berlin, pp 1793–1998. https://doi.org/10.1007/978-3-319-09057-3
Nsengiyumva J, Luo G, Nahayo L, Huang X, Cai P (2018) Landslide susceptibility assessment using spatial multiCriteria evaluation model in Rwanda. Int J Environ Res Public Health 15:243266. https://doi.org/10.3390/ijerph15020243
O'Hare G, Rivas S (2005) The landslide hazard and human vulnerability in La Paz City, Bolivia. Geogr J 171:239–258
Papathoma-Köhle M, Neuhauser B, Ratzinger K, Wenzel H, Howes HH (2007) Elements at risk as a framework for assessing the vulnerability of communities to landslides. Nat Hazards Earth Syst Sci Elem 43:765–779
Pradhan AMS, Kim YT (2016) Evaluation of a combined spatial multi-criteria evaluation model and deterministic model for landslide susceptibility mapping. CATENA 140:125–139. https://doi.org/10.1016/j.catena.2016.01.022
Parise M (2001) Landslide mapping techniques and their use in the assessment of the landslide hazard. Phys Chem Earth C 26:697–703. https://doi.org/10.1016/s1464-1917(01)
Perera ENC, Jayawardana DT, Jayasinghe P (2017) A rainfall intensity-duration threshold for mass movement in Badulla, Sri Lanka. J Geosci Environ Prot 5:135–152. https://doi.org/10.4236/gep.2017.512010
Perera ENC, Jayawardana DT, Ranagalage M, Jayasinghe P (2018a) Spatial multi criteria evaluation (SMCE) model for landslide hazard zonation in tropical hilly environment: a case study from Kegalle. Geoinf Geostat Overview. https://doi.org/10.4172/2327-4581.S3-004
Perera ENC, Jayawardana DT, Jayasinghe P, Bandara RMS, Alahakoon N (2018b) Direct impacts of landslides on socio- economic systems: a case study from Aranayake, Sri Lanka. Geoenviron Disasters 5:45–57. https://doi.org/10.1186/s40677-018-0104
Perera ENC, Jayawardana DT, Ranagalage M, Jayasinghe P (2019a) Landslide vulnerability assessment based on entropy method: a case study from Kegalle District-Sri Lanka. Model Earth Syst Environ 128:1–15. https://doi.org/10.1007/s40808-019-00615
Perera ENC, Jayawardana DT, Ranagalage M (2019b) Post disaster recovery process of landslides in developing countries: a case study of Aranayake Landslide—Sri Lanka. Rev Environ Earth Sci 6:14–23. https://doi.org/10.18488/journal.80.2019.14.23
Prasad VS, Kousalya P (2017) Role of consistency in analytic hierarchy process—consistency improvement methods. Indian J Sci Technol 10:1–5. https://doi.org/10.17485/ijst/2017/v10i29/100784
Ranagalage M (2017) Landslide hazards assessment in Nuwara Eliya District in Sri Lanka. In: Proceedings of the Japanese Geographical meeting. 100336.
Ranagalage M, Dissanayake D, Murayama Y, Zhang X, Estoque RC, Perera E, Morimoto T (2018a) Quantifying surface urban heat island formation in the world heritage tropical mountain city of Sri Lanka. ISPRS Int J Geo-Inf 7:341. https://doi.org/10.3390/ijgi709034
Ranagalage M, Murayama Y, Dissanayake D, Simwanda M (2019a) The impacts of landscape changes on annual mean land surface temperature in the tropical mountain city of Sri Lanka: a case study of Nuwara Eliya (1996–2017). Sustainability 11:1–27. https://doi.org/10.3390/su11195517
Ranagalage M, Wang R, Gunarathna MHJP, Dissanayake D, Murayama Y, Simwanda M (2019b) Spatial forecasting of the landscape in rapidly urbanizing hill stations of South Asia: a case study of Nuwara Eliya, Sri Lanka (1996–2037). Remote Sens 11:1743. https://doi.org/10.3390/rs11151743
Ranagalage M, Estoque RC, Zhang X, Murayama Y (2018b) Spatial changes of urban heat island formation in the Colombo District, Sri Lanka: Implications for sustainability planning. Sustainability 10:1367. https://doi.org/10.3390/su10051367
Royal Society (1992) Risk: analysis, perception and management. Report of a Royal Society Study Group. Royal Society, London
Saaty RW (1987) The analytic hierarchy process—what it is and how it is used. Math Model 9:161–176. https://doi.org/10.1016/0270-0255(87)90473-8
Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15:234–281. https://doi.org/10.1016/0022-2496(77)90033-5
Samodra G, Chen G, Sartohadi J, Kasama K, Hadmoko DS (2012) Spatial pattern of socio-economic landslide vulnerability and its spatial prediction by means of GIS-Fuzzy Logic in Kayangan Catchment, Indonesia. In: Proceeding of international conference on disaster management, the 8th annual conference of IIIRR, 2012, Kumamoto, Japan
Sari DAP, Innaqa S, Safrilah (2017) Hazard, vulnerability and capacity mapping for landslides risk analysis using geographic information system (GIS). IOP Conf Ser Mater Sci Eng 209:012106. https://doi.org/10.1088/1757-899x/209/1/012106
Silva KT, Sivapragasam PP, Thages P. (2009) Caste discrimination and social justice in Sri Lanka: an overview. Working papers series. Retrieved from https://dalitstudies.org.in/wp/0906.pdf.
Singh A, Pal S, Kanungo DP, Pareek N (2017) An overview of recent developments in landslide vulnerability assessments presentation of a new conceptual framework. In: Mikos M, Yueping T, Yin Y, Sassa K (eds) Advancing culture of living with landslides, 1st edn. Springer, Italy, pp 1148–1197
Sterlacchini S, Frigerio S, Giacomelli P, Brambilla M (2007) Landslide risk analysis: a-disciplinary methodological approach. Nat Hazards Earth Syst Sci 7:657–675. https://doi.org/10.5194/nhess-7-657-2007
Sugathapala K, Vijekumara PA (2013) Importance of implementing landslide clearance process complementary to national physical plan 2030. In: 5th annual symposium: engineering in disaster resilience, National Building Research Organization, Ministry of Disaster Management, pp 78–86
Tomaszewski B (2014) Geographic information systems (GIS) for disaster management, 1st edn. Taylor & Francis Group, Milton Park, pp 147–160. https://doi.org/10.1201/b17851
United Nations Educational, Scientific and Cultural Organization (UNESCO) (1985) Landslide hazard zonation: a review of principles and practice. United Nations Educational Scientific and Cultural Organization, Paris
United Nations Office for Disaster Risk Reduction (UNISDR) (2017) Sendai framework for disaster risk reduction (UNISDR). https://www.unisdr.org/we/coordinate/sendai-framework, Accessed 14 Sept 2019.
Van Westen CJ, van Asch TWJ, Soeters R (2006) Landslide hazard and risk zonation—why is it still so difficult? Bull Eng Geol Environ 65:176–184
Vranken L, Vantilt G, Van Den Eeckhaut M, Vandekerckhove L, Poesen J (2014) Landslide risk assessment in a densely populated hilly area. Landslides 12:787–798. https://doi.org/10.1007/s10346-014-0506-9
Wijemannage AL, Ranagalage M, Perera ENC (2018) Comparison of spatial interpolation methods for rainfall data over Sri Lank. In: Asian conference in remote sensing, 17–21 Oct, Asian Association on Remote Sensing, Colombo
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The authors are grateful for the support of the Accelerating Higher Education Expansion and Development (AHEAD) project funded by the World Bank. We would like to acknowledge the anonymous reviewers and editors for their valuable comments and suggestions.
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Perera, E.N.C., Jayawardana, D.T., Ranagalage, M. et al. Introduce a framework for landslide risk assessment using geospatial analysis: a case study from Kegalle District, Sri Lanka. Model. Earth Syst. Environ. 6, 2415–2431 (2020). https://doi.org/10.1007/s40808-020-00811-z
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DOI: https://doi.org/10.1007/s40808-020-00811-z