SpringerLink
Log in

Landslide susceptibility map** using precipitation data, Mazandaran Province, north of Iran

  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

Precipitation is a nonlinear and complex phenomenon and varies in time and space. It is also evident that there is a link between precipitation and shallow landslides, and precipitation is always considered as a landslide-triggering factor. This study aims to investigate the relationship between the characteristics of precipitation and the historical shallow landslides in Mazandaran Province, north of Iran. For this purpose, the spatial variability of rainfall was analyzed using monthly rainfall data collected at 15 synoptic stations distributed over the region between 1981 and 2014. Monthly precipitation and other derived parameters were used, and a hybrid model combining principal component analysis and cluster analysis (CA) was applied to all the precipitation parameters to regionalize the region into well-defined clusters in terms of precipitation and prove that there is a link between precipitation and the occurred slides. Then, the rotated PCs were combined and the precipitation characteristics map was produced. Demonstrating the linkage between the precipitation characteristics and the historical slides, the combined map can be considered as landslide susceptibility map. The accuracy of prediction was tested against a random guess and obtained as 77%. It is also noticeable that only 30% of the surface area of the study region in the landslide susceptibility map covers about 80% of the known landslides. The calculated measure suggests that the developed model well predicted the location of the occurred slides using only precipitation data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Arab Amiri M, Mesgari MS (2016) Spatial variability analysis of precipitation in northwest Iran. Arab J Geosci 9(11):1–10. doi:10.1007/s12517-016-2611-7

    Article  Google Scholar 

  • Arab Amiri M, Amerian Y, Mesgari MS (2016) Spatial and temporal monthly precipitation forecasting using wavelet transform and neural networks, Qara-Qum catchment, Iran. Arab J Geosci 9(5):1–18. doi:10.1007/s12517-016-2446-2

    Article  Google Scholar 

  • Atkinson PM, Massari R (1998) Generalised linear modelling of susceptibility to landsliding in the Central Apennines, Italy. Comput Geosci 24(4):373–385

    Article  Google Scholar 

  • Atkinson PM, Massari R (2011) Autologistic modelling of susceptibility to landsliding in the Central Apennines, Italy. Geomorphology 130(1):55–64

    Article  Google Scholar 

  • Brenning A (2005) Spatial prediction models for landslide hazards: review, comparison and evaluation. Nat Hazard Earth Syst Sci 5(6):853–862

    Article  Google Scholar 

  • Caliński T, Harabasz J (1974) A dendrite method for cluster analysis. Commun Stat Theory Methods 3(1):1–27

    Article  Google Scholar 

  • Cama M, Lombardo L, Conoscenti C, Agnesi V, Rotigliano E (2015) Predicting storm-triggered debris flow events: application to the 2009 Ionian Peloritan disaster (Sicily, Italy). Nat Hazards Earth Syst Sci 15(8):1785–1806

    Article  Google Scholar 

  • Cama M, Conoscenti C, Lombardo L, Rotigliano E (2016) Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy). Environ Earth Sci 75(3):1–21

    Article  Google Scholar 

  • Carrara A, Cardinali M, Guzzetti F, Reichenbach P (1995) GIS technology in map** landslide hazard. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Springer, Berlin, pp 135–175

    Chapter  Google Scholar 

  • Chowdhury RN (1976) Initial stresses in natural slope analysis, rock engineering for foundations and slopes. In: Rock engineering for foundations and slopes. ASCE Geotechnical Engineering Division, University of Colorado, pp 404–414

  • Chowdhury R, Bertoldi C (1977) Residual shear tests on soil from two natural slopes. Aus Geomech J G 7:1–9

    Google Scholar 

  • Citakoglu H, Cetin M, Cobaner M, Haktanir T (2017) Modeling of seasonal precipitation with geostatistical techniques and its estimation at un-gauged locations. Teknik Dergi 28(1):7725–7745

    Article  Google Scholar 

  • Conoscenti C, Ciaccio M, Caraballo-Arias NA, Gómez-Gutiérrez Á, Rotigliano E, Agnesi V (2015) Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: a case of the Belice River basin (western Sicily, Italy). Geomorphology 242:49–64

    Article  Google Scholar 

  • Conoscenti C, Rotigliano E, Cama M, Caraballo-Arias NA, Lombardo L, Agnesi V (2016) Exploring the effect of absence selection on landslide susceptibility models: a case study in Sicily, Italy. Geomorphology 261:222–235

    Article  Google Scholar 

  • Costanzo D, Chacón J, Conoscenti C, Irigaray C, Rotigliano E (2014) Forward logistic regression for earth-flow landslide susceptibility assessment in the Platani river basin (southern Sicily, Italy). Landslides 11(4):639–653

    Article  Google Scholar 

  • Dahal RK, Hasegawa S, Nonomura A, Yamanaka M, Masuda T, Nishino K (2008) GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility map**. Environ Geol 54(2):311–324

    Article  Google Scholar 

  • Desgraupes B (2013) Clustering indices. University of Paris Ouest

  • Ercan K, Mehmet C, Osman A (2008) Hydrologic homogeneous regions using monthly streamflow in Turkey. Earth Sci Res J 12(2):181–193

    Google Scholar 

  • Feizizadeh B, Blaschke T (2013) GIS-multicriteria decision analysis for landslide susceptibility map**: comparing three methods for the Urmia lake basin, Iran. Nat Hazards 65(3):2105–2128. doi:10.1007/s11069-012-0463-3

    Article  Google Scholar 

  • Feizizadeh B, Blaschke T (2014) An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility map**. Int J Geogr Inf Sci 28(3):610–638. doi:10.1080/13658816.2013.869821

    Article  Google Scholar 

  • Feizizadeh B, Jankowski P, Blaschke T (2014a) A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis. Comput Geosci 64:81–95. doi:10.1016/j.cageo.2013.11.009

    Article  Google Scholar 

  • Feizizadeh B, Shadman Roodposhti M, Jankowski P, Blaschke T (2014b) A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility map**. Comput Geosci 73:208–221. doi:10.1016/j.cageo.2014.08.001

    Article  Google Scholar 

  • Gökceoglu C, Aksoy H (1996) Landslide susceptibility map** of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques. Eng Geol 44(1–4):147–161

    Article  Google Scholar 

  • Haktanir T, Citakoglu H (2014) Trend, independence, stationarity, and homogeneity tests on maximum rainfall series of standard durations recorded in Turkey. J Hydrol Eng 19(9):05014009

    Article  Google Scholar 

  • Haktanir T, Cobaner M, Kisi O (2010) Frequency analyses of annual extreme rainfall series from 5 min to 24 h. Hydrol Process 24(24):3574–3588

    Article  Google Scholar 

  • Haktanir T, Citakoglu H, Seckin N (2016) Regional frequency analyses of successive-duration annual maximum rainfalls by L-moments method. Hydrol Sci J 61(4):647–668

    Article  Google Scholar 

  • Huth R (2006) The effect of various methodological options on the detection of leading modes of sea level pressure variability. Tellus A 58(1):121–130

    Article  Google Scholar 

  • Jaafari A, Najafi A, Pourghasemi H, Rezaeian J, Sattarian A (2014) GIS-based frequency ratio and index of entropy models for landslide susceptibility assessment in the Caspian forest, northern Iran. Int J Environ Sci Technol 11(4):909–926

    Article  Google Scholar 

  • Lombardo L, Cama M, Conoscenti C, Märker M, Rotigliano E (2015) Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messina (Sicily, southern Italy). Nat Hazards 79(3):1621–1648

    Article  Google Scholar 

  • Luis Md, Gonzalez-Hidalgo J, Brunetti M, Longares L (2011) Precipitation concentration changes in Spain 1946–2005. Nat Hazard Earth Syst 11(5):1259–1265

    Article  Google Scholar 

  • Minder JR, Roe GH, Montgomery DR (2009) Spatial patterns of rainfall and shallow landslide susceptibility. Water Resour Res 45(4):w04419–w04430

    Article  Google Scholar 

  • Muñoz E, Ochoa A (2016) Rainfall seasonality on landslide probability: a modelling approach. In: E3S web of conferences. EDP Sciences, p 15012

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

    Article  Google Scholar 

  • Oliver JE (1980) Monthly precipitation distribution: a comparative index. Prof Geogr 32(3):300–309

    Article  Google Scholar 

  • Paolini L, Villalba R, Grau HR (2005) Precipitation variability and landslide occurrence in a subtropical mountain ecosystem of NW Argentina. Dendrochronologia 22(3):175–180

    Article  Google Scholar 

  • Park HJ, Lee JH, Woo I (2013) Assessment of rainfall-induced shallow landslide susceptibility using a GIS-based probabilistic approach. Eng Geol 161:1–15

    Article  Google Scholar 

  • Pourghasemi H, Pradhan B, Gokceoglu C, Moezzi KD (2012) Landslide susceptibility map** using a spatial multi criteria evaluation model at Haraz Watershed, Iran. In: Pradhan B, Buchroithner M (eds) Terrigenous mass movements. Springer, Berlin, pp 23–49. doi:10.1007/978-3-642-25495-6_2

  • Ramos-Cañón AM, Prada-Sarmiento LF, Trujillo-Vela MG, Macías JP, Santos-R AC (2015) Linear discriminant analysis to describe the relationship between rainfall and landslides in Bogotá, Colombia. Landslides 13(4):671–681

  • Raziei T, Bordi I, Pereira L (2008) A precipitation-based regionalization for Western Iran and regional drought variability. Hydrol Earth Syst Sci 12(6):1309–1321

    Article  Google Scholar 

  • Richman MB (1986) Rotation of principal components. J Climatol 6(3):293–335

    Article  Google Scholar 

  • Salarian T, Zare M, Jouri MH, Miarrostami S, Mahmoudi M (2014) Evaluation of shallow landslides hazard using artificial neural network of Multi-Layer Perceptron method in Subalpine Grassland (Case study: Glandrood watershed-Mazandaran). Int J Agric Crop Sci 7(11):795–804

    Google Scholar 

  • Shahid S (2009) Spatio-temporal variability of rainfall over Bangladesh during the time period 1969–2003. Asia-Pac J Atmos Sci 45(3):375–389

    Google Scholar 

  • Turkes M, Koç T, Saris F (2009) Spatiotemporal variability of precipitation total series over Turkey. Int J Climatol 29(8):1056

    Article  Google Scholar 

  • Vakhshoori V, Zare M (2016) Landslide susceptibility map** by comparing weight of evidence, fuzzy logic, and frequency ratio methods. Geomat Nat Hazards Risk 7(5):1731–1752

    Article  Google Scholar 

  • Vicente-Serrano SM et al (2015) Spatio-temporal variability of droughts in Bolivia: 1955–2012. Int J Climatol 35(10):3024–3040

    Article  Google Scholar 

  • Wu W, Sidle RC (1995) A distributed slope stability model for steep forested basins. Water Resour Res 31(8):2097–2110

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Geographic Information System, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran

    Mohammad Arab Amiri

  2. Department of Earth and Marine Sciences, University of Palermo, Palermo, Italy

    Christian Conoscenti

Authors
  1. Mohammad Arab Amiri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christian Conoscenti
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Arab Amiri.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Arab Amiri, M., Conoscenti, C. Landslide susceptibility map** using precipitation data, Mazandaran Province, north of Iran. Nat Hazards 89, 255–273 (2017). https://doi.org/10.1007/s11069-017-2962-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-017-2962-8

Keywords

Search

Navigation