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Constructing rainfall thresholds for debris flow initiation based on critical discharge and S-hydrograph

journal contribution
posted on 26.01.2021, 11:20 by Yajun Lin, Xingmin Meng, Peng Guo, Tom Dijkstra, Yan Zhao, Guan Chen, Dongxia Yue
© 2020 Elsevier B.V. Debris flows caused by channel bed erosion present major hazards affecting life, livelihoods, and the built environment in mountainous regions. An efficient way to decrease hazard impact is through reliable hazard forecasts and appropriate early-warning strategies. Rainfall thresholds are fundamental in achieving reliable hazard forecasts. However, a lack of rainfall records often impedes the empirical establishment of such thresholds. This paper constructs rainfall intensity-duration thresholds based on process-based critical runoff discharge for the initiation of debris flows and a mathematical approximation among peak discharge, rainfall intensity and duration. Simulations of conditions that triggered debris flow and non-debris flow events allowed determination of the lower and upper limits of critical discharge for debris flow initiation. In turn, these critical discharge limits are compared with four estimates derived from process-based approaches to test which approach best delimit the critical conditions. Hydrological simulations derive S-hydrographs for recorded rainfall events. Further analysis of the S-hydrographs results in a mathematical approximation of peak discharge as a function of rainfall intensity and duration and the establishment of the minimum rainfall required to produce a particular peak discharge. The minimum rainfall threshold to trigger an event can be calculated by setting the process-based critical discharge as the peak dis charge. In turn, this enables the establishment of a conventional rainfall I-D threshold for debris flow initiation. This process-based approach enables the construction of valley-specific I-D thresholds in data-poor areas and provides a promising pathway to improve the reliability of debris flow hazard forecasts and early warnings.

Funding

National Key Research and Development 737 Program of China (Grant No 2017YFC1501005)

National Natural Science Foundation of China (Grant No. 41907224)

Key Technology Research and Development Program 740 of the Ministry of Gansu Province, China (Grant No. 19ZD2FA002)

Fundamental Research Funds for the Central Universities (Grant Nos. lzujbky-2020-pd12; lzujbky-2020-sp03)

Zhouqu, China, disaster - data capture, modelling and preliminary geohazard assessment

Natural Environment Research Council

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History

School

  • Architecture, Building and Civil Engineering

Published in

Engineering Geology

Volume

280

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Engineering Geology and the definitive published version is available at https://doi.org/10.1016/j.enggeo.2020.105962

Acceptance date

07/12/2020

Publication date

2020-12-10

Copyright date

2021

ISSN

0013-7952

Language

en

Depositor

Dr Tom Dijkstra Deposit date: 22 January 2021

Article number

105962

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