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ZHAI Shuhua, MAO Jian, NAN Yun, LIU Huanhuan, WANG Yuntao, WANG Qiangqiang, XIONG Chunhua, WANG Yanmei. Multi-factors fusion method of debris flow prediction based on genetic programming[J]. The Chinese Journal of Geological Hazard and Control, 2020, 31(6): 111-115. DOI: 10.16031/j.cnki.issn.1003-8035.2020.06.14
Citation: ZHAI Shuhua, MAO Jian, NAN Yun, LIU Huanhuan, WANG Yuntao, WANG Qiangqiang, XIONG Chunhua, WANG Yanmei. Multi-factors fusion method of debris flow prediction based on genetic programming[J]. The Chinese Journal of Geological Hazard and Control, 2020, 31(6): 111-115. DOI: 10.16031/j.cnki.issn.1003-8035.2020.06.14

Multi-factors fusion method of debris flow prediction based on genetic programming

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  • Received Date: July 19, 2020
  • Revised Date: September 26, 2020
  • Available Online: January 21, 2021
  • Debris flow is a frequent geological disaster, which often poses a great threat to the safety of people’s lives and property. Outbreak of debris flow is not only related to rainfall, but also related to many geological and environmental factors. In this paper, the watershed area, ratio of loose materials and the average slope of the gully bed are taken as the geological factors,the maximum hourly rainfall intensity (T) and the total rainfall (R) are taken as the rainfall index, the sample database is established by means of geological factors and rainfall index, genetic programming is used to establish a prediction model for the critical rainfall index of debris flow, which overcomes the shortcomings of the previous warning model that used rainfall as a single indicator, model verification results show that the model has high warning accuracy and strong adaptability, which can realize timely warning.
  • [1]
    崔鹏, 杨坤, 陈杰. 前期降雨对泥石流形成的贡献:以蒋家沟泥石流形成为例[J]. 中国水土保持科学, 2003, 1(1):11-15.

    [CUI P, YANG K, CHEN J. Relationship between occurrence of debris flow and antecedent precipitation:taking the Jiangjia gully as an example[J]. Science of Soil and Water Conservation, 2003, 1(1):11-15.(in Chinese)]
    [2]
    韦方强, 胡凯衡, 陈杰. 泥石流预报中前期有效降水量的确定[J]. 山地学报, 2005, 23(4):453-457.

    [WEI F Q, HU K H, CHEN J. Determination of effective antecedent rainfall for debris flow forecast[J]. Journal of Mountain Science, 2005, 23(4):453-457.(in Chinese)]
    [3]
    丛威青, 潘懋, 李铁锋, 等. 降雨型泥石流临界雨量定量分析[J]. 岩石力学与工程学报, 2006, 25(增刊1):2808-2812.[CONG W Q, PAN M, LI T F, et al. Quantitative analysis of critical rainfall-triggered debris flows[J]. Chinese Journal of Rock Mechanics and Engineering, 2006, 25

    (Sup1):2808-2812.(in Chinese)]
    [4]
    田冰, 王裕宜, 洪勇. 泥石流预报中前期降水量与始发日降水量的权重关系:以云南省蒋家沟为例[J]. 水土保持通报, 2008, 28(2):71-75.

    [TIAN B, WANG Y Y, HONG Y. Weighted relation between antecedent rainfall and process precipitation in debris flow prediction-A case study of Jiangjia gully in Yunnan Province[J]. Bulletin of Soil and Water Conservation, 2008, 28(2):71-75.(in Chinese)]
    [5]
    刘艳辉, 唐灿, 李铁锋, 等. 地质灾害与降雨雨型的关系研究[J]. 工程地质学报, 2009, 17(5):656-661.

    [LIU Y H, TANG C, LI T F, et al. Statistical relations between geo-hazards and rain-type[J]. Journal of Engineering Geology, 2009, 17(5):656-661.(in Chinese)]
    [6]
    倪化勇, 王德伟. 基于雨量(强)条件的泥石流预测预报研究现状、问题与建议[J]. 灾害学, 2010, 25(1):124-128.

    [NI H Y, WANG D W. Present status, problem and advice on the research of prediction and forecasting of debris flow based on rainfall condition[J]. Journal of Catastrophology, 2010, 25(1):124-128.(in Chinese)]
    [7]
    梁光模, 姚令侃. 确定暴雨泥石流临界雨量的研究[J]. 路基工程, 2008(6):3-5.[LIANG G M, YAO L K. Study on determining the critical rainfall of rainstorm mudflow[J]. Subgrade Engineering, 2008

    (6):3-5.(in Chinese)]
    [8]
    白利平, 孙佳丽, 南赟. 北京地区泥石流灾害临界雨量阈值分析[J]. 地质通报, 2008, 27(5):674-680.

    [BAI L P, SUN J L, NAN Y. Analysis of the critical rainfall thresholds for mudflow in Beijing, China[J]. Geological Bulletin of China, 2008, 27(5):674-680.(in Chinese)]
    [9]
    王海芝. 北京山区基于历史资料的泥石流临界雨量研究[J]. 城市地质, 2008, 3(1):18-21.

    [WANG H Z. A study of the critical rainfall volume for mudflows based on his-torical data in the mountainous area of Beijing[J]. Urban Geology, 2008, 3(1):18-21.(in Chinese)]
    [10]
    涂剑, 马超, 杨海龙. 北京山区暴雨泥石流激发雨量条件[J]. 中国水土保持科学, 2017, 15(5):103-110.

    [TU J, MA C, YANG H L. Rainfall condition of triggering debris flows in Beijing mountain regions[J]. Science of Soil and Water Conservation, 2017, 15(5):103-110.(in Chinese)]
    [11]
    贾三满, 路璐, 翟淑花, 等. 北京山区泥石流预警阈值初步研究[J]. 城市地质, 2016, 11(3):1-7.

    [JIA S M, LU L, ZHAI S H, et al. Preliminary study on early warning threshold of debris flow in Beijing mountainous area[J]. Urban Geology, 2016, 11(3):1-7.(in Chinese)]
    [12]
    王军, 李学峰. 基于Logistic回归的泥石流灾害预警模型[J]. 厦门理工学院学报, 2018, 26(3):73-77.

    [WANG J, LI X F. Logistic regression for early warning of debris flow hazards[J]. Journal of Lujiang University, 2018, 26(3):73-77.(in Chinese)]
    [13]
    何朝阳, 许强, 巨能攀, 等. 基于降雨过程自动识别的泥石流实时预警技术[J]. 工程地质学报, 2018, 26(3):703-710.

    [HE C Y, XU Q, JU N P, et al. Real-time early warning technology of debris flow based on automatic identification of rainfall process[J]. Journal of Engineering Geology, 2018, 26(3):703-710.(in Chinese)]
    [14]
    王之君, 李仁年, 拓万全. 基于历史观测数据的泥石流突变起动模式研究——以陇南山区白龙江流域为例[J]. 灾害学, 2019, 34(2):140-144.

    [WANG Z J,LI R N, TUO W Q.Historical field observation data-based study on the catastrophic initiation mode of debris flow:a case of the Bailong river basin in Longnan mountain areas[J]. Journal of Catastrophology, 2019, 34(2):140-144.(in Chinese)]
    [15]
    王进孝.土石流临界降雨线极限状态之研究-基因演算最佳化类神经网路[D].台湾:国立台湾大学,2004.[WANG J X. Study on the critical line of debris flow based on genetic evolutional neural networks[D].Taiwan:National Taiwan University, 2004.(in Chinese)]
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