IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v70y2014i2p995-1017.html
   My bibliography  Save this article

Landslide susceptibility deterministic approach using geographic information systems: application to Breaza town, Romania

Author

Listed:
  • Iuliana Armaş
  • Florin Vartolomei
  • Florica Stroia
  • Livioara Braşoveanu

Abstract

The study is a deterministic-based approach on landslide susceptibility. The purpose of the paper is to create quantitative susceptibility maps by joining the one-dimension infinite slope stability model with a raster-based GIS (ILWIS) and taking into account the spatial distribution of input parameters. A landslide-prone area, with relative homogeneous geology and geomorphology, located in the Subcarpathian sector of the Prahova River, Romania, was selected for the study. There are frequent problems caused by active landslides in the studied area, especially in years with heavy precipitation, often causing destruction of houses and roads situated on the slopes (1992, 1997, and 2005). Detailed surveys covering a 7-year period provided the necessary input data on slope parameters, hydrological components, and the geotechnical background. Two simulations were used: one on dry soil conditions and one on fully saturated soil conditions. A third test was based on the level of the groundwater table mapped in summer 2008. Detailed analyses were particularly focused on landslides to compare predicted results with actual results using field measurements. The model is very suitable for use in raster GIS because it can calculate slope instability on a pixel basis, each raster cell being considered individually. The drawback of the model is the highly detailed data of input parameters. Despite this disadvantage, in conclusion, the usefulness of slope stability models on a large-scale basis was emphasized under infinitely high failure plain conditions and lithological homogeneity. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Iuliana Armaş & Florin Vartolomei & Florica Stroia & Livioara Braşoveanu, 2014. "Landslide susceptibility deterministic approach using geographic information systems: application to Breaza town, Romania," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(2), pages 995-1017, January.
  • Handle: RePEc:spr:nathaz:v:70:y:2014:i:2:p:995-1017
    DOI: 10.1007/s11069-013-0857-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-013-0857-x
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11069-013-0857-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Giacomo D’Amato Avanzi & Francesco Falaschi & Roberto Giannecchini & Alberto Puccinelli, 2009. "Soil slip susceptibility assessment using mechanical–hydrological approach and GIS techniques: an application in the Apuan Alps (Italy)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 50(3), pages 591-603, September.
    2. Chang-Jo Chung & Andrea Fabbri, 2003. "Validation of Spatial Prediction Models for Landslide Hazard Mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 30(3), pages 451-472, November.
    3. A. Carrara & F. Guzzetti & M. Cardinali & P. Reichenbach, 1999. "Use of GIS Technology in the Prediction and Monitoring of Landslide Hazard," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 20(2), pages 117-135, November.
    4. Agus Muntohar & Hung-Jiun Liao, 2010. "Rainfall infiltration: infinite slope model for landslides triggering by rainstorm," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 54(3), pages 967-984, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mehrnoosh Jadda & Helmi Shafri & Shattri Mansor, 2011. "PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 57(2), pages 395-412, May.
    2. L. Lombardo & M. Cama & M. Maerker & E. Rotigliano, 2014. "A test of transferability for landslides susceptibility models under extreme climatic events: application to the Messina 2009 disaster," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(3), pages 1951-1989, December.
    3. Roşca Sanda & Bilaşco Ştefan & Petrea Dănuţ & Fodorean Ioan & Vescan Iuliu & Filip Sorin, 2015. "Application of landslide hazard scenarios at annual scale in the Niraj River basin (Transylvania Depression, Romania)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(3), pages 1573-1592, July.
    4. E. Rotigliano & C. Cappadonia & C. Conoscenti & D. Costanzo & V. Agnesi, 2012. "Slope units-based flow susceptibility model: using validation tests to select controlling factors," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 61(1), pages 143-153, March.
    5. Kourosh Shirani & Mehrdad Pasandi & Alireza Arabameri, 2018. "Landslide susceptibility assessment by Dempster–Shafer and Index of Entropy models, Sarkhoun basin, Southwestern Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(3), pages 1379-1418, September.
    6. Alejandro Gonzalez-Ollauri & Slobodan B. Mickovski, 2021. "A Simple GIS-Based Tool for the Detection of Landslide-Prone Zones on a Coastal Slope in Scotland," Land, MDPI, vol. 10(7), pages 1-15, June.
    7. Marko Sinčić & Sanja Bernat Gazibara & Martin Krkač & Hrvoje Lukačić & Snježana Mihalić Arbanas, 2022. "The Use of High-Resolution Remote Sensing Data in Preparation of Input Data for Large-Scale Landslide Hazard Assessments," Land, MDPI, vol. 11(8), pages 1-37, August.
    8. Paulo Rodolpho Pereira Hader & Fábio Augusto Gomes Vieira Reis & Anna Silvia Palcheco Peixoto, 2022. "Landslide risk assessment considering socionatural factors: methodology and application to Cubatão municipality, São Paulo, Brazil," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(2), pages 1273-1304, January.
    9. Raquel Melo & José Luís Zêzere, 2017. "Modeling debris flow initiation and run-out in recently burned areas using data-driven methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1373-1407, September.
    10. Paul Sestraș & Ștefan Bilașco & Sanda Roșca & Sanda Naș & Mircea V. Bondrea & Raluca Gâlgău & Ioel Vereș & Tudor Sălăgean & Velibor Spalević & Sorin M. Cîmpeanu, 2019. "Landslides Susceptibility Assessment Based on GIS Statistical Bivariate Analysis in the Hills Surrounding a Metropolitan Area," Sustainability, MDPI, vol. 11(5), pages 1-23, March.
    11. L. Lombardo & M. Cama & C. Conoscenti & M. Märker & E. Rotigliano, 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 Messi," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1621-1648, December.
    12. Esteban Bravo-López & Tomás Fernández Del Castillo & Chester Sellers & Jorge Delgado-García, 2023. "Analysis of Conditioning Factors in Cuenca, Ecuador, for Landslide Susceptibility Maps Generation Employing Machine Learning Methods," Land, MDPI, vol. 12(6), pages 1-28, May.
    13. Zhi-hua Yang & Heng-xing Lan & Xing Gao & Lang-ping Li & Yun-shan Meng & Yu-ming Wu, 2015. "Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(3), pages 2467-2487, February.
    14. Chuhan Wang & Qigen Lin & Leibin Wang & Tong Jiang & Buda Su & Yanjun Wang & Sanjit Kumar Mondal & Jinlong Huang & Ying Wang, 2022. "The influences of the spatial extent selection for non-landslide samples on statistical-based landslide susceptibility modelling: a case study of Anhui Province in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 1967-1988, July.
    15. Khabat Khosravi & Ebrahim Nohani & Edris Maroufinia & Hamid Reza Pourghasemi, 2016. "A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making techn," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 947-987, September.
    16. Malcolm Anderson & Liz Holcombe & Rob Flory & Jean-Philippe Renaud, 2008. "Implementing low-cost landslide risk reduction: a pilot study in unplanned housing areas of the Caribbean," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 47(3), pages 297-315, December.
    17. Gerardo Grelle & Antonietta Rossi & Paola Revellino & Luigi Guerriero & Francesco Maria Guadagno & Giuseppe Sappa, 2019. "Assessment of Debris-Flow Erosion and Deposit Areas by Morphometric Analysis and a GIS-Based Simplified Procedure: A Case Study of Paupisi in the Southern Apennines," Sustainability, MDPI, vol. 11(8), pages 1-20, April.
    18. Jaydip Dey & Saurabh Sakhre & Ritesh Vijay & Hemant Bherwani & Rakesh Kumar, 2021. "Geospatial assessment of urban sprawl and landslide susceptibility around the Nainital lake, Uttarakhand, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 3543-3561, March.
    19. Andrzej Gruchot & Tymoteusz Zydroń & Andrzej Wałęga & Jana Pařílková & Jacek Stanisz, 2022. "Influence of Rainfall Events and Surface Inclination on Overland and Subsurface Runoff Formation on Low-Permeable Soil," Sustainability, MDPI, vol. 14(9), pages 1-27, April.
    20. Tanmoy Das & Vansittee Dilli Rao & Deepankar Choudhury, 2022. "Numerical investigation of the stability of landslide-affected slopes in Kerala, India, under extreme rainfall event," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(1), pages 751-785, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:70:y:2014:i:2:p:995-1017. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.