Document Type : Original Research Paper

Authors

1 Department of Civil Engineering, Chitkara University Institute of Engineering & Technology, Chitkara University, Punjab, India

2 Department of Civil Engineering, National Institute of Technology, Hamirpur, Himachal Pradesh, India

Abstract

The GIS-multi-criteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for predicting the future hazards, land use planning, and hazard preparedness. Identification of landslide susceptible regions helps in making a strategic plan for future developmental activities in the landslide-prone areas. It enables the integration of different data layers with varying levels of uncertainty. In this work, GIS-MCDA is applied to landslide hazard zonation for the Kullu district in Himachal Pradesh, India. The current work aims to evaluate the performance of the analytical hierarchy process (AHP) for the development of a landslide hazard map. The geographical information system is used for the preparation of the database, analysis, modelling, and results. The ArcGIS 10.0 software is used to integrate the input layers by assigning appropriate weights. Six landslide causal factors are used, whereby the parameters are extracted from an associated spatial database. These factors are evaluated, and then the respective factor weight and class weight are assigned to each one of the associated factors. The developed landslide hazard map is categorized into three risk zones. The current work may be of great assistance to regional planners and decision-makers in deciding on the most suitable risk mitigation measures at the local level to prevent the potential losses and damages from landslides in the region.

Keywords

[1]. Varnes, D.J. (1978). Slope movement types and processes. Special report, 176: 11-33.
[2]. Kumar, A., Sharma, R.K., and Mehta, B.S. (2020). Slope stability analysis and mitigation measures for selected landslide sites along NH-205 in Himachal Pradesh, India. J Earth Syst Sci 129, 135.
[3]. Kumar, N., Shankar, V., and Poddar, A. (2020). Investigating the effect of limited climatic data on evapotranspiration-based numerical modeling of soil moisture dynamics in the unsaturated root zone: a case study for potato crop. Model. Earth Syst. Environ. 6: 2433–2449.
[4]. Aslam, B., Maqsoom, A., Khalil, U., Ghorbanzadeh, O., Blaschke, T., Farooq, D., and Ghamisi, P. (2022). Evaluation of different landslide susceptibility models for a local scale in the Chitral District, Northern Pakistan. Sensors. 22 (9): 3107.
[5]. Afzal, N., Ahmad, A., Shirazi, S.A., and Younes, I. (2022). GIS-based landslide susceptibility mapping using analytical hierarchy process: a case study of Astore region, Pakistan. EQA-International Journal of Environmental Quality, 48, 27-40.
[6]. Feizizadeh, B. and Blaschke, T. (2013). GIS-multi-criteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran. Natural hazards. 65 (3): 2105-2128.
[7]. Mert, B.A. (2018). A GIS-aided resource estimation of coalfields in Kangal basin, Sivas province, Turkey. Journal of Mining and Environment. 9 (3): 581-591.
[8]. Pazand, K., Hezarkhani, A., Ataei, M., and Ghanbari, Y. (2011). Combining AHP with GIS for predictive Cu porphyry potential mapping: A case study in Ahar Area (NW, Iran). Natural resources research. 20 (4): 251-262.
[9]. Safari, M., Ataei, M., Khalokakaie, R., and KARAMOZIAN, M. (2010). Mineral processing plant location using the analytic hierarchy process—a case study: the Sangan iron ore mine (phase 1). Mining Science and Technology (China). 20 (5): 691-695.
[10]. Safari, M., Kakaei, R., Ataei, M., and Karamoozian, M. (2012). Using fuzzy TOPSIS method for mineral processing plant site selection. Arabian Journal of Geosciences. 5 (5): 1011-1019.
[11]. Singh, K., and Kumar, V. (2018). Hazard assessment of landslide disaster using information value method and analytical hierarchy process in highly tectonic Chamba region in bosom of Himalaya. Journal of Mountain science. 15 (4): 808–824.
[12]. Sharma, R.K. and Mehta, B.S., (2012). Macro-zonation of landslide susceptibility in Garamaura-Swarghat-Gambhar section of national highway 21, Bilaspur District, Himachal Pradesh (India). Nat Hazards 60: 671–688.
[13]. Saaty, T.L. (1994). Homogeneity and clustering in AHP ensures the validity of the scale. European Journal of Operational Research. 72 (3): 598-601.
[14]. Satty, T.L. (1980). The analytic hierarchy process, analytic hierarchy process.
[15]. Sharma, R.K., Mehta, B.S., and Jamwal, C.S. (2013). Cut slope stability evaluation of NH-21 along Nalayan-Gambhrola section, Bilaspur district, Himachal Pradesh, India. Nat Hazards 66: 249–270.
[16]. Singh, K. and Kumar, V. (2017). Landslide hazard mapping along national highway-154A in Himachal Pradesh, India using information value and frequency ratio. Arabian J. Geosci. 10(24): 1-18.
[17]. Kumar A., Sharma R.K., and Bansal V.K. (2018). GIS-Based Landslide Hazard Mapping Along NH-3 in Mountainous Terrain of Himachal Pradesh, India, using Weighted Overlay Analysis. In: Singh H., Garg P., Kaur I. (Eds.) Proceedings of the 1st International Conference on Sustainable Waste Management through Design. ICSWMD 2018. Lecture Notes in Civil Engineering, 21. Springer, Cham.
[18]. Choubey, V.M., Mukherjee, P.K., Bajwa, B.S., and Walia, V. (2007). Geological and tectonic influence on water–soil–radon relationship in Mandi–Manali area, Himachal Himalaya. Environmental geology. 52 (6): 1163-1171.
[19]. Bhargava, O.N. and Bassi, U.K. (1994). The crystalline thrust sheets in the Himachal Himalaya and the age of amphibolite facies metamorphism. Journal of Geological Society of India (Online archive from Vol. 1 to Vol. 78). 43 (4): 343-352.
[20]. Sah, M.P. and Mazari, R.K. (2007). An overview of the geo-environmental status of the Kullu Valley, Himachal Pradesh, India. Journal of Mountain Science. 4 (1): 003-023.
[21]. Shanker R. and Dua, K.S. (1978). On the existence of a Tear fault along upper Beas Valley, district Kulu, Himachal Pradesh, and its bearing on the thermal activity.
[22]. Sharma R.K., Kaur A., and Kumar A. (2019). Slope Stability Analysis by Bishop Analysis using MATLAB Program based on Particle Swarm Optimization Technique. In: Singh H., Garg P., Kaur I. (Eds.) Proceedings of the 1st International Conference on Sustainable Waste Management through Design. ICSWMD 2018. Lecture Notes in Civil Engineering, 21. Springer, Cham.
[23]. Kumar, A., Sharma, R.K., and Bansal, V.K. (2018b). Landslide hazard zonation using analytical hierarchy process along National Highway-3 in mid Himalayas of Himachal Pradesh, India. Environmental Earth Sciences 77, 719.
[24]. SINGH, S. P., and Roy, A.K. (2022). Slope stability analysis and preventive actions for a landslide location along NH-05 in Himachal Pradesh, India. Journal of Mining and Environment.
[25]. Kumar, A., Sharma, R.K., and Bansal, V.K. (2019). GIS-based comparative study of information value and frequency ratio method for landslide hazard zonation in a part of mid-Himalaya in Himachal Pradesh. Innov. Infrastruct. Solut. 4, 28.
[26]. Richards, J.A. (1986). Error correction and registration of image data. In Remote Sensing Digital Image Analysis 33-68. Springer, Berlin, Heidelberg.
[27]. Saha, A.K., Arora, M.K., Csaplovics, E., and Gupta, R.P. (2005). Land cover classification using IRS LISS III image and DEM in a rugged terrain: a case study in Himalayas. Geocarto International. 20 (2): 33-40.
[28]. Kumar, A., Poddar, A., and Nautiyal, A. (2021). Urban Transportation System Problems in Context of the Indian Conditions. In Belt and Road Webinar Series on Geotechnics, Energy and Environment (pp. 300-314). Springer, Singapore.
[29]. Poddar, A., Kumar, A., Kashyap, V., and Thapa, S. (2022) Data-Driven Modelling Approach in Model Rainfall-Runoff for a Mountainous Catchment. In Modelling and Simulation of Environmental Systems. 253-268
[30]. Nautiyal, A., Kumar, A., Poddar, A., and Parajuli, N. (2021). Optimum transportation of relief materials aftermath the disaster. Journal of Achievements in Materials and Manufacturing Engineering. 109 (1).