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Debris flow susceptibility assessment of Leh Valley, Ladakh, based on concepts of connectivity, propagation and evidence-based probability

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  • Choudhurimayum Pankaj Sharma

    (Wadia Institute of Himalayan Geology
    Indian Institute of Science Education and Research Kolkata)

  • Anil Kumar

    (Wadia Institute of Himalayan Geology)

  • Poonam Chahal

    (Hebrew University of Jerusalem)

  • Uma Kant Shukla

    (Banaras Hindu University)

  • Pradeep Srivastava

    (Wadia Institute of Himalayan Geology
    Indian Institute of Technology Roorkee)

  • Manoj K. Jaiswal

    (Indian Institute of Science Education and Research Kolkata)

Abstract

The Leh Valley which lies within the Trans Himalayan state of Ladakh, India, is known to be affected almost annually by debris flows ranging from minor to catastrophic scale events. The effect has been getting magnified due to increased urbanization and rapid growth in tourism industry. Though these flows are triggered by intense and abnormal rainfall events the conditioning factor has always been the topography and sediment availability. A lucid acknowledgement of the terrain condition and the degree of vulnerability of such events is required. For this a detail investigation of sediment availability, topographic conditions and their relation with known events becomes crucial. This study utilizes index of connectivity (IC) model to understand the sediment source-sink relationship and farther applied Flow-R model to simulate the probable scenario of events through predefined algorithms. We then use the Weights of evidence (WOE) method to compute the statistical probability of debris flow occurrence. This paper demonstrates the application of these three independent techniques and their implementation in a highly rugged terrain of Ladakh which is a region of frequent debris flows onslaught. The IC and Flow-R models are found to be counter supportive and effective in delineating areas which could be affected by flows that will solely originate in upstream areas where high angle channels directly connected to sediment sources are present. WOE-based model determines the probability of the rare and extensive flows that results from downward integration of other drainage networks in an open fan area.

Suggested Citation

  • Choudhurimayum Pankaj Sharma & Anil Kumar & Poonam Chahal & Uma Kant Shukla & Pradeep Srivastava & Manoj K. Jaiswal, 2023. "Debris flow susceptibility assessment of Leh Valley, Ladakh, based on concepts of connectivity, propagation and evidence-based probability," 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. 115(2), pages 1833-1859, January.
  • Handle: RePEc:spr:nathaz:v:115:y:2023:i:2:d:10.1007_s11069-022-05619-x
    DOI: 10.1007/s11069-022-05619-x
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    References listed on IDEAS

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    1. Susanne Schmidt & Marcus Nüsser & Ravi Baghel & Juliane Dame, 2020. "Cryosphere hazards in Ladakh: the 2014 Gya glacial lake outburst flood and its implications for risk assessment," 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. 104(3), pages 2071-2095, December.
    2. Motonao Ishikawa & Naomune Yamamoto & Gaku Yamanaka & Kuniaki Suwa & Shun Nakajima & Reiko Hozo & Tsering Norboo & Kiyohito Okumiya & Kozo Matsubayashi & Kuniaki Otsuka, 2013. "Disaster-related psychiatric disorders among survivors of flooding in Ladakh, India," International Journal of Social Psychiatry, , vol. 59(5), pages 468-473, August.
    3. Renoj Thayyen & A. Dimri & Pradeep Kumar & G. Agnihotri, 2013. "Study of cloudburst and flash floods around Leh, India, during August 4–6, 2010," 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. 65(3), pages 2175-2204, February.
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