Abstract
This paper presents rainfall-induced landslide thresholds and predicts landslide hazard in Kuala Lumpur metropolitan city and surrounding areas. Landslide events from 2000 to 2012 were collected. The long and short antecedent rainfall days were prepared for landslide and non-landslide days simultaneously. First, threshold analysis was conducted by using data obtained from rainfall stations located in highly urbanized areas of Kuala Lumpur metropolis. Six rainfall gauges were selected, and the study area was divided into six zones according to rainfall gauges: Taman Desa Station (TD-KL), Genting Klang (GK-KL), LDG Edinburgh Station (LDGE-KL), SG Raya Hulu Langat Station (SRHL-Slg), Puchong Drop Station (PD-Slg), and Bukit Antarabangsa (BTA-Slg). After the threshold analysis was conducted for different periods (10, 15, and 30 days) in each station, reliability index test was conducted to optimize the best threshold that limits the predicted events along the study period for each region. Second, the threshold analysis results were used as input in the Poisson probability model to estimate landslide temporal probability (P T). Third, the spatial probability (P S) analysis was prepared by using the evidential belief function multiplied by the P T to obtain the hazard maps for 1-, 3-, and 5-year scenarios. Finally, a validation process was conducted to test the prediction performance of the resultant hazard map for a 1- and 2-year prediction by using the landslide inventory of 2012 to early 2014, which was not included in the modeling of the hazard map. Results showed a valid correlation between the high and moderate hazardous areas for the six zones. The predicted hazard maps indicated a quantitative assessment of the prone areas and proved to be a valid disaster management tool. The produced hazard maps may play a vital role as input component in risk analysis.
This is a preview of subscription content, access via your institution.








References
Althuwaynee OF, Pradhan B (2014) An alternative technique for landslide inventory modeling based on spatial pattern characterization, geoinformation for informed decisions. Springer International Publishing pp 35–48
Althuwaynee OF, Pradhan B, Mahmud AR, Yusoff ZM (2012) Prediction of slope failures using bivariate statistical based index of entropy model, Humanities, Science and Engineering (CHUSER), 2012 I.E. Colloquium on IEEE, pp 362–367
Althuwaynee OF, Pradhan B, Lee S (2012) Application of an evidential belief function model in landslide susceptibility mapping. Comput Geosci 44:120–135
Althuwaynee OF, Pradhan B, Park HJ, Lee JH (2014a) A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping. Catena 114:21–36. doi:10.1016/j.catena.2013.10.011
Althuwaynee OF, Pradhan B, Park HJ, Lee JH (2014b) A novel ensemble decision-tree based CHi-squared automatic interaction detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping. Landslides. doi:10.1007/s10346-014-0466-0
Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65:15–31
Ayalew L, Yamagishi H, Ugawa N (2004) Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan. Landslides 1:73–81
Borga M, Vezzani C, Dalla Fontana G (2005) Regional rainfall depth–duration–frequency equations for an alpine region. Nat Hazards 36:221–235
Brand EW, Premchitt J, Phillipson HB (1984) Relationship between rainfall and landslides in Hong Kong. 4th Int Symp. on Landslides, Toronto, pp 377–384
Caine N (1980) The rainfall intensity: duration control of shallow landslides and debris flows. Geogr Ann A Phys Geogr 23–27
Cardinali M, Galli M, Guzzetti F, Ardizzone F, Reichenbach P, Bartoccini P (2006) Rainfall induced landslides in December 2004 in south-western Umbria, central Italy: types, extent, damage and risk assessment. Nat Hazards Earth Syst Sci 6:237–260
Chau K, Sze Y, Fung M, Wong W, Fong E, Chan L (2004) Landslide hazard analysis for Hong Kong using landslide inventory and GIS. Comput Geosci 30:429–443
Chleborad AF, Baum RL, Godt JW (2006) Rainfall thresholds for forecasting landslides in the Seattle, Washington, area- exceedance and probability, U. S. Geological Survey, open-file report 2006–1064
Chleborad AF, Baum RL, Godt JW, Powers PS (2008) A prototype system for forecasting landslides in the Seattle, Washington area. Geol Soc Am Rev Eng 20:103–120
Crovelli RA (2000) Probability models for estimation of number and costs of landslides, US Geological Survey, open file report 00–249. http://pubs.usgs.gov/of/2000/ofr-00-0249/ProbModels.html
Crozier MJ, Glade T (2006) Landslide hazard and risk: issues, concepts and approach. Landslide hazard and risk. Wiley, West Sussex, pp 1–40
De Vita P (2000) Fenomeni di instabilità delle coperture piroclastiche dei Monti Lattari, di Sarno e di Salerno (Campania) ed analisi degli eventi pluviometrici determinanti. Quad Geol Appl 7:213–235
Erener A, Düzgün HS (2013) A regional scale quantitative risk assessment for landslides: case of Kumluca watershed in Bartin, Turkey. Landslides 10:55–73
Evett SR, Tolk JA, Howell TA (2006) Soil profile water content determination: sensor accuracy, axial response, calibration, temperature dependence, and precision. Vadose Zone J 5:894
Farisham A (2007) Landslides in the hillside development in the Hulu Klang, Klang Valley. Post-graduate seminar, UTM, Skudai
Frattini P, Crosta G, Sosio R (2009) Approaches for defining thresholds and return periods for rainfall–triggered shallow landslides. Hydrol Process 23:1444–1460
Guzzetti F, Malamud BD, Turcotte DL, Reichenbach P (2002) Power-law correlations of landslide areas in central Italy. Earth Planet Sci Lett 195:169–183
Guzzetti F, Reichenbach P, Cardinali M, Galli M, Ardizzone F (2005) Probabilistic landslide hazard assessment at the basin scale. Geomorphology 72:272–299
Guzzetti F, Peruccacci S, Rossi M, Stark CP (2007) Rainfall thresholds for the initiation of landslides in central and southern Europe. Meteorog Atmos Phys 98:239–267
Huabin W, Gangjun L, Weiya X, Gonghui W (2005) GIS-based landslide hazard assessment: an overview. Prog Phys Geogr 29:548–567
Iverson RM (2000) Landslide triggering by rain infiltration. Water Resour Res 36:1897–1910
Jaapar ARB (2006) A framework of a national slope safety system for Malaysia, Universiti Kebangsaan Malaysia
Jaiswal P, van Westen CJ (2009) Estimating temporal probability for landslide initiation along transportation routes based on rainfall thresholds. Geomorphology 112:96–105
Jaiswal P, van Westen CJ, Jetten V (2010) Quantitative landslide hazard assessment along a transportation corridor in southern India. Eng Geol 116:236–250
Jakob M, Weatherly H (2003) A hydroclimatic threshold for landslide initiation on the North Shore Mountains of Vancouver, British Columbia. Geomorphology 54:137–156
Jamaludin S, Ali F (2011) An overview of some empirical correlations between rainfall and shallow landslides and their applications in Malaysia. Electron J Geotech Eng 16:1429–1440
Jamaludin S, Hussein AN (2006) Landslide hazard and risk assessment: the Malaysian experience, Notes
Keefer DK, Wilson RC, Mark RK, Brabb EE, Brown WM, Ellen SD, Harp EL, Wieczorek GF, Alger CS, Zatkin RS (1987) Real-time landslide warning during heavy rainfall. Science 238:921–925
Kemec S, Zlatanova S, Duzgun S (2009) Selecting 3D urban visualisation models for disaster management: a rule-based approach, Proceedings of TIEMS 2009 Annual Conference, June, pp 9–11
Lai SH, Mohd A, Mohd S, Law PL, Mah DYS (2008) Applications of GIS and remote sensing in the hydrological study of the upper Bernam river Basin, Malaysia. The Institution of Engineers, Malaysia 69(1):13–18
Lee ML, Ng KY, Huang YF, Li WC (2014) Rainfall-induced landslides in Hulu Kelang area, Malaysia. Nat Hazards 70:353–375
Lucà F, D’Ambrosio D, Robustelli G, Rongo R, Spataro W (2014) Integrating geomorphology, statistic and numerical simulations for landslide invasion hazard scenarios mapping: an example in the Sorrento Peninsula (Italy). Comput Geosci
Malamud BD, Turcotte DL, Guzzetti F, Reichenbach P (2004) Landslide inventories and their statistical properties. Earth Surf Process Landf 29:687–711
Nefeslioglu HA, Gokceoglu C (2011) Probabilistic risk assessment in medium scale for rainfall-induced earthflows: catakli catchment area (Cayeli, Rize, Turkey). Math Probl Eng 2011
Noor MJMM, Aziz AA, Suhadi RUR (1993) Effects of cemented rice husk ash mixtures on compaction, strength and durability of Melaka series lateritic soil. Universiti Pertanian Malaysia, Serdang. 28:735–745
Pasuto A, Silvano S (1998) Rainfall as a trigger of shallow mass movements. A case study in the Dolomites, Italy. Environ Geol 35:184–189
Pradhan B (2011) Manifestation of an advanced fuzzy logic model coupled with geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modelling. Environ Ecol Stat 18:471–493
Pradhan B, Lee S (2007) Utilization of optical remote sensing data and GIS tools for regional landslide hazard analysis using an artificial neural network model. Earth Sci Front 14:143–151
Pradhan B, Lee S (2010a) Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models. Environ Earth Sci 60:1037–1054
Pradhan B, Lee S (2010b) Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling. Environ Model Softw 25:747–759
Pradhan B, Oh HJ, Buchroithner M (2010a) Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area. Geomatics Nat Hazards Risk 1(3):199–223
Pradhan B, Youssef A, Varathrajoo R (2010b) Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model. Geo-spatial Information Science 13(2):93–102
Pradhan B, Mansor S, Pirasteh S, Buchroithner MF (2011) Landslide hazard and risk analyses at a landslide prone catchment area using statistical based geospatial model. Int J Remote Sens 32(14):4075–4087
Salciarini D, Godt JW, Savage WZ, Baum RL, Conversini P (2008) Modeling landslide recurrence in Seattle, Washington, USA. Eng Geol 102:227–237
Tien Bui D, Pradhan B, Lofman O, Revhaug I, Dick OB (2012) Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): a comparative assessment of the efficacy of evidential belief functions and fuzzy logic models. Catena 96:28–40
Tien Bui D, Pradhan B, Lofman O, Revhaug I, Dick ØB (2013) Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam. Nat Hazards 66:707–730
Varnes D (1984) The International Association of Engineering Geology Commission on Landslides and Other Mass Movements on Slopes. 1984. Landslide hazard zonation: a review of principles and practice. Natural Hazard. United Nations Educational, Scientific and Cultural Organization 3, 63
White I, Mottershead D, Harrison J (1996) Environmental systems, 2nd edn. Chapman & Hall, London
Wieczorek GF (1996) Landslide triggering mechanisms. Landslides Investig Mitig 76–90
Zezere J, Trigo R, Trigo I (2005) Shallow and deep landslides induced by rainfall in the Lisbon region (Portugal): assessment of relationships with the North Atlantic Oscillation. Nat Hazards Earth Syst Sci 5:331–344
Acknowledgments
The authors acknowledge and appreciate the provision of rainfall data by the Department of Irrigation and Drainage (DID), and Malaysian Meteorological Department (MMD) Malaysia, without which this study would not have been possible. Thanks to Paolo Frattini and another anonymous reviewer for their valuable comments which helped us to improve the quality of the manuscript. This research was supported by UPM University Research Grant (05-01-11-1283RU) to stimulate research under the RUGS scheme with project number 9344100.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Althuwaynee, O.F., Pradhan, B. & Ahmad, N. Estimation of rainfall threshold and its use in landslide hazard mapping of Kuala Lumpur metropolitan and surrounding areas. Landslides 12, 861–875 (2015). https://doi.org/10.1007/s10346-014-0512-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10346-014-0512-y
Keywords
- Landslide
- Threshold
- Antecedent rainfall
- GIS
- Remote sensing
- Hazard
- Malaysia