Research on early warning of debris flow based on efficacy coefficient method

MENG Fan-qi; LI Guang-jie; WANG Qing-bing; QIN Sheng-wu; ZHAO Hai-qing; JIN Xin

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Research on early warning of debris flow based on efficacy coefficient method

更新时间：2026-06-25

- Research on early warning of debris flow based on efficacy coefficient method
- Vol. 33, Issue 3, (2012)
- 作者机构：
  
  1. 吉林大学建设工程学院,长春,130026
  2. 山东省地质环境监测总站,济南,250014
  3. 沈阳地质矿产研究所,沈阳,110033
  4. 辽宁省地质环境监测总站,沈阳,110033
- 作者简介：
- 基金信息：
- DOI：
  CLC： TV144
- Online First：12 March 2012，
  
  Published：2012
- 稿件说明：
移动端阅览
MENG Fan-qi, LI Guang-jie, WANG Qing-bing, et al. Research on early warning of debris flow based on efficacy coefficient method[J]. 2012, 33(3).
DOI：

MENG Fan-qi, LI Guang-jie, WANG Qing-bing, et al. Research on early warning of debris flow based on efficacy coefficient method[J]. 2012, 33(3). DOI：

摘要

泥石流灾害破坏力巨大，预测预报泥石流发生的可能性是防灾减灾的重要手段，也是国内外学者研究的热点。基于功效系数法原理，在综合分析泥石流灾害发生的气象、地质环境影响因素的基础上，选取了山坡坡度、相对高差、植被覆盖率、沿沟松散物储量、5 d累计降雨量、最大小时雨强和当日雨量为评价因子，采用改进后的层次分析法计算评价因子的权重系数，建立了泥石流预测预警模型。以岫岩地区泥石流为例对预警模型进行检验，预测结果较好地反映了实际情况。表明基于功效系数法的泥石流预测预警模型具备较高的可靠性和实用性，研究结果为泥石流预测预警提供了一种新的思路和方法。

Abstract

For great destructive debris flow

predicting the likelihood of its early warning is an important means of disaster prevention and mitigation

as well as scholars focus on the key issues. Based on the principle of efficacy coefficient method

analyzing the meteorological and geological environmental factors synthetically; evaluation factors such as hill slope

relative height

vegetation cover

along the groove loose material reserves

5 d cumulative rainfall

maximum rainfall intensity per hour

and intraday rainfall are selected. Using the improved analytic hierarchy process to calculate the weight coefficients of evaluation factors

a early warning of debris flow prediction model is established. Taking an early warning of debris flow in Xiuyan for example

the model is tested to predict the results which reflect the actual situation better. The debris flow early warning model has higher reliability and practicability

and it can provide new ideas and methods for early warning of debris flow prediction.

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Related Institution

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