IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v93y2018i3d10.1007_s11069-018-3343-7.html
   My bibliography  Save this article

Application of Hidden Markov Model for avalanche danger simulations for road sectors in North-West Himalaya

Author

Listed:
  • Jagdish Chandra Joshi

    (Snow and Avalanche Study Establishment)

  • Tankeshwar Kumar

    (Panjab University)

  • Sunita Srivastava

    (Panjab University)

  • Divya Sachdeva

    (Snow and Avalanche Study Establishment)

  • Ashwagosha Ganju

    (Snow and Avalanche Study Establishment)

Abstract

Hidden Markov Model (HMM) has been developed for avalanche warning on 10 different road sectors in Pir-Panjal and Great Himalayan mountain ranges of North-West Himalaya. The model uses a data set of nine snow and meteorological variables—average air temperature, snow temperature index, snow drift index, snowfall in 24 h, snowfall in 48 h, snow water equivalent, snowfall intensity, standing snow and snowpack settlement collected during past 20 winters (1992–2012). The HMM is composed of four observations derived from the model input variables and four state variables. The state variables of the model are four levels of avalanche danger (No, Low, Medium and High). Single HMM has been developed to provide avalanche warning for both direct and delayed/wet avalanches with a lead time of two days. The HMM has been validated with (Case-1) and without (Case-2) incorporating delayed/wet avalanches using data collected during four winters (2012–2016) and compared with official Avalanche Warning Bulletin issued by Snow and Avalanche Study Establishment during these winters. The model has been validated through computation of accuracy measures such as percent correct (PC), bias, false alarm rate, probability of detection and Heidke Skill Score. The PC of the HMM for different stations for Case-1 varies from 80.1 to 98.6% for day-1 and 81.2 to 98.3% for day-2 and that for Case-2 from 82.2 to 98.6% for day-1 and 83.3 to 98.3% for day-2.

Suggested Citation

  • Jagdish Chandra Joshi & Tankeshwar Kumar & Sunita Srivastava & Divya Sachdeva & Ashwagosha Ganju, 2018. "Application of Hidden Markov Model for avalanche danger simulations for road sectors in North-West Himalaya," 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 1127-1143, September.
    • Handle: RePEc:spr:nathaz:v:93:y:2018:i:3:d:10.1007_s11069-018-3343-7
    DOI: 10.1007/s11069-018-3343-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-018-3343-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-018-3343-7?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Prabhjot Kaur & Jagdish Chandra Joshi & Preeti Aggarwal, 2022. "A multi-model decision support system (MM-DSS) for avalanche hazard prediction over North-West Himalaya," 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(1), pages 563-585, January.
    2. Jagdish Chandra Joshi & Prabhjot Kaur & Bhupinder Kumar & Amreek Singh & P. K. Satyawali, 2020. "HIM-STRAT: a neural network-based model for snow cover simulation and avalanche hazard prediction over North-West Himalaya," 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. 103(1), pages 1239-1260, August.

    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:93:y:2018:i:3:d:10.1007_s11069-018-3343-7. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.