Landslide susceptibility assessment along the National Highway-244 from Batote to Doda, J & K, India: A study based on the Frequency Ratio Method

Authors

  • Yudhbir Singh PG Department of Geology, University of Jammu
  • Muzamil Liaqat Department of Geography, Jamia Millia Islamia, Delhi
  • Shifali Chib PG Department of Geology, University of Jammu
  • Bashir Ahmad Lone PG Department of Geology, University of Jammu
  • Sumit Johar University of Jammu
  • Arvind Bhutiyal PG Department of Geology, University of Jammu

DOI:

https://doi.org/10.51710/jias.v40iII.326

Abstract

The National Highway-244 is highly susceptible to landslide occurrences, frequently resulting in road blockades and causing significant hardships for the local population. These landslides pose a threat to human lives, property and the environment, leading to substantial losses. In this study, an attempt has been made to carry out landslide susceptibility assessment through frequency ratio method along the National Highway-244 utilizing GIS and statistical computations. It considers eight parameters, which include topographical (slope, slope aspect, slope curvature, hill shade, and relief), anthropogenic (distance to road and distance to river) and geological parameters that mostly influence the occurrence of landslides in the area under investigation. The present study focuses only along National Highway-244 and data has been gathered from field visits and secondary sources. The results of the study inferred that the area under investigation falls into different susceptibility zones, namely very high, high, moderate, low, and very low, covering approximately 15%, 31%, 27%, 19%, and 8%, respectively of the total area. This study reveals that a considerable proportion, around 73%, of the study area falls within very high to moderate susceptibility zones. The conclusions drawn from this study hold significant implications for stakeholders and also provide valuable insights for future planning and infrastructure development, enabling them to make informed decisions. By considering the susceptibility zones identified in this study, stakeholders can implement appropriate measures to mitigate the impact of landslides, ensuring the safety and stability of the region.

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References

Alvioli, M., Guzzetti, F., and Rossi, M. (2014). Scaling properties of rainfall induced landslides predicted by a physically based model. Geomorphology, v. 213, pp. 38-47.

Akgun, A., K?ncal, C. and Pradhan, B. (2012). Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey). Environmental monitoring and assessment, v. 184, pp. 5453-5470.

Bhat, G.M., Pandita, S.K., Dhar, B.L., Sahni, A.K. and Haq, I.U. (2002). Preliminary geotechnical investigation of slope failures along Jammu-Srinagar national highway between Batote and Banihal. Reprinted from Aspects of Geology Environment of the Himalaya, v. 2, pp. 275-288.

Chen, W., Pourghasemi, H.R. and Naghibi, S.A. (2018). A comparative study of landslide susceptibility maps produced using support vector machine with different kernel functions and entropy data mining models in China. Bulletin of Engineering Geology and the Environment, v. 77, pp. 647-664.

Chimidi, G., Raghuvanshi, T.K. and Suryabhagavan, K.V. (2017). Landslide hazard evaluation and zonation in and around Gimbi town, western Ethiopia—a GIS-based statistical approach. Applied Geomatics, v. 9, pp. 219-236.

El Abidine, R. Z. and Abdelmansour, N. (2019). Landslide susceptibility mapping using information value and frequency ratio for the Arzew sector (North-Western of Algeria). Bulletin of the Mineral Research and Exploration, v. 160(160), pp. 197-211.

Fayez, L., Pazhman, D., Pham, B.T., Dholakia, M.B., Solanki, H A., Khalid, M. and Prakash, I. (2018). Application of frequency ratio model for the development of landslide susceptibility mapping at part of Uttarakhand State, India. International Journal of Applied Engineering Research, v. 13(9), pp. 6846-6854.

Gabet, E.J., Burbank, D.W., Putkonen, J.K., Pratt-Sitaula, B.A. and Ojha, T. (2004). Rainfall thresholds for landsliding in the Himalayas of Nepal. Geomorphology, v. 63(3-4), pp. 131-143.

Girma, F., Raghuvanshi, T.K., Ayenew, T. and Hailemariam, T. (2015). Landslide hazard zonation in Ada Berga District, Central Ethiopia–a GIS based statistical approach. Journal of Geomorphology, v. 9(i), pp. 25-38.

Guzzetti, F., Peruccacci, S., Rossi, M. and Stark, C.P. (2007). Rainfall thresholds for the initiation of landslides in central and southern Europe. Meteorology and Atmospheric Physics, v. 98, pp. 239-267.

Gyawali, P., Aryal, Y.M., Tiwari, A., Prajwol, K.C. and Ansari, K. (2021). Landslide Susceptibility Assessment Using Bivariate Statistical Methods: A Case Study of Gulmi District, western Nepal. VW Engineering International, v. 3, pp. 29-40.

Hamza, T. and Raghuvanshi, T.K. (2017). GIS based landslide hazard evaluation and zonation–A case from Jeldu District, Central Ethiopia. Journal of King Saud University-Science, 29(2), 151-165.

Hussain, G., Singh, Y. and Bhat, G.M. (2018). Landslide susceptibility mapping along the national highway-1D, between Kargil and Lamayuru, Ladakh Region, Jammu and Kashmir. Journal of the Geological Society of India, v. 91, pp. 457-466.

Hussain, G., Singh, Y., Bhat, G.M., Sharma, S., Sangra, R. and Singh, A. (2019). Geotechnical characterisation and finite element analysis of two landslides along the national highway 1-A (Ladakh Region, Jammu and Kashmir). Journal of the Geological Society of India, v. 94, pp. 93-99.

Kanungo, D. P., Arora, M. K., Sarkar, S. and Gupta, R. P. (2006). A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas. Engineering Geology, v. 85(3-4), pp. 347-366.

Khan, H., Shafique, M., Khan, M.A., Bacha, M.A., Shah, S.U., and Calligaris, C. (2019). Landslide susceptibility assessment using Frequency Ratio, a case study of northern Pakistan. The Egyptian Journal of Remote Sensing and Space Science, v. 22(1), pp. 11-24.

Lee, S. and Min, K. (2001). Statistical analysis of landslide susceptibility at Yongin, Korea. Environmental Geology, v. 40(9), pp. 12-18.

Lee, S.A.R.O. (2005). Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. International Journal of Remote Sensing, v. 26(7), pp. 1477-1491.

Moung-Jin, L., Won-Kyong, S., Joong-Sun, W., Inhye, P. and Saro, L. (2014). Spatial and temporal change in landslide hazard by future climate change scenarios using probabilistic-based frequency ratio model. Geocarto International, v. 29(6), pp. 639-662.

Petley, D.N. (2008). The global occurrence of fatal landslides in 2007. Geophysical Research Abstracts, v. 10, pp. 3.

Pradhan, B. and Lee, S. (2009). Landslide risk analysis using artificial neural network model focusing on different training sites. International Journal of Physical Sciences, v. 3(11), pp. 1-15.

Pradhan, B., Chaudhari, A., Adinarayana, J. and Buchroithner, M.F. (2012). Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia. Environmental Monitoring and Assessment, v. 184, pp. 715-727.

Reichenbach, P., Rossi, M., Malamud, B.D., Mihir, M., and Guzzetti, F. (2018). A review of statistically-based landslide susceptibility models. Earth Science Reviews, v. 180, pp. 60-91.

Sangra, R., Singh, Y., Bhat, G.M., Pandita, S.K. and Hussain, G. (2017). Geotechnical investigation on slopes failures along the Mughal Road from Bafliaz to Shopian, Jammu and Kashmir, India. Journal of the Geological Society of India, v. 90, pp. 616-622.

Shahabi, H., Khezri, S., Ahmad, B.B., and Hashim, M. (2014). RETRACTION: Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models, v. 2, pp. 4-8.

Singh, Y., and Bhat, G.M. (2010). Role of basin morphometric parameters in landslides along the national highway-1A between Udhampur and Batote, Jammu and Kashmir, India: a case Study. Himalayan Geology, v. 31(1), pp. 43-50.

Singh, Y. and Bhat, G.M. (2011). Landslide investigations: morphometric and geotechnical approach-a case study from Northwest Himalaya, India. Lambert Academic Publications, v. 5, p. 113.

Singh, Y., Ul Haq, A., Bhat, G.M., Pandita, S.K., Singh, A., Sangra, R. and Kotwal, S.S. (2018). Rainfall-induced landslide in the active frontal fold–thrust belt of Northwestern Himalaya, Jammu: dynamics inferred by geological evidences and Ground Penetrating Radar. Environmental Earth Sciences, v. 77, pp. 1-17.

Tien Bui, D., Pradhan, B., Lofman, O. and Revhaug, I. (2012). Landslide susceptibility assessment in Vietnam using support vector machines, decision tree, and Naive Bayes Models. Mathematical Problems in Engineering, v. 7, pp. 12-19.

Van Westen, C.J., Castellanos, E. and Kuriakose, S.L. (2008). Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview. Engineering Geology, v. 102(3-4), pp. 112-131.

Yilmaz, I. (2009). Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat-Turkey). Computers & Geosciences, v. 35(6), pp. 1125-1138.

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Published

2023-12-31

How to Cite

Singh, Y., Liaqat, M., Chib, S., Lone, B. A., Johar, S., & Bhutiyal, A. (2023). Landslide susceptibility assessment along the National Highway-244 from Batote to Doda, J & K, India: A study based on the Frequency Ratio Method. Journal of The Indian Association of Sedimentologists (peer Reviewed), 40(II), 40–48. https://doi.org/10.51710/jias.v40iII.326
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