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Modeling sediment concentration in debris flow by Tsallis entropy

Author

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  • Singh, Vijay P.
  • Cui, Huijuan

Abstract

Debris flow is a natural hazard that occurs in landscapes having high slopes, such as mountainous areas. It can be so powerful that it destroys whatever comes in its way, that is, it can kill people and animals; decimate roads, bridges, railway tracks, homes and other property; and fill reservoirs. Owing to its frequent occurrence, it is receiving considerable attention these days. Of fundamental importance in debris flow modeling is the determination of concentration of debris (or sediment) in the flow. The usual approach to determining debris flow concentration is either empirical or hydraulic. Both approaches are deterministic and therefore say nothing about the uncertainty associated with the sediment concentration in the flow. This paper proposes to model debris flow concentration using the Tsallis entropy theory. Verification of the entropy-based distribution of debris flow concentration using the data and equations reported in the literature shows that the Tsallis entropy-proposed model is capable of mimicking the field observed concentration and has potential for practical application.

Suggested Citation

  • Singh, Vijay P. & Cui, Huijuan, 2015. "Modeling sediment concentration in debris flow by Tsallis entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 49-58.
    • Handle: RePEc:eee:phsmap:v:420:y:2015:i:c:p:49-58
    DOI: 10.1016/j.physa.2014.10.075
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    Citations

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    Cited by:

    1. Zhang, Gengxi & Su, Xiaoling & Singh, Vijay P., 2020. "Modelling groundwater-dependent vegetation index using Entropy theory," Ecological Modelling, Elsevier, vol. 416(C).
    2. Eck, Daniel J. & McKeague, Ian W., 2016. "Central Limit Theorems under additive deformations," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 156-162.
    3. Ghoshal, Koeli & Kumbhakar, Manotosh & Singh, Vijay P., 2019. "Distribution of sediment concentration in debris flow using Rényi entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 267-281.

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