基于集对分析的岩溶塌陷危险性预测评价
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摘要
为准确、有效地预测评价岩溶塌陷的危险性,运用集对分析原理建立岩溶塌陷危险性预测模型。选择岩性、岩溶发育程度、地形地貌、地质构造、土层厚度、土层岩性、地下水位距基岩面距离、地下水位变幅、地下水径流强度、地表水入渗、人工抽水强度和其他人类工程活动12个指标为岩溶塌陷主要影响因素,并将塌陷危险性划分为5个等级,用定量或定性的方法对指标进行赋值,构建其分级标准。运用集对分析方法,将影响因素实测值分别与5个危险性等级评价标准组成集对,计算其联系度,最后根据联系数的排序结果,判定岩溶塌陷危险性等级。利用该方法对贵州定扒地区岩溶塌陷危险性进行预测,结果表明,该模型评价结果与实际情况相符。
The paper aims at introducing a risk prediction and evaluation model for the karst-strata collapse based on the study of the theory of set pair analysis. We have engaged in and investigated and explored the 12 factors that the collapse may get involved with according to the developmental condition of the karst collapse in Guizhou as well as the currently available research findings to our sampling research target. The said 12 influential factors,may all contribute to the constituent embodiment for establishing the risk prediction and evaluation system for the karst collapse,namely,the lithological character of bedrock,the developmental condition of the karst,the landform,the geophysical structure,the soil thickness,the soil lithology,the distance from the underground water level to the bedrock surface,the amplitude of the variations of the underground water sources,the run-off intensity of the underground water,the infiltration situation of the surface water,the artificial pumping intensity and all the human engineering interference activities. And,in terms of the types of all the indexical factors,the evaluation can also be conducted in a quantitative or qualitative way,for example,the risk liabilities can be divided into 5 grades,that is,the stable grade( 1),the nearly stable( 2),the less stable grade( 3),the vulnerable grade to the collapse one( 4),the extremely vulnerable grade to the grade at the brink to collapse( 5). And,then,it would be possible to adopt the set pair analysis method,that is to say,all the data values of each evaluation index to be calculated can be paired up with one of the corresponding five risk grades,so as to establish the expression formula of its connection degree,with the ultimately determined risk grades of karst collapse serving as the basis of the sequence of connection numbers. And,with the model developed to be used in the risk prediction and evaluation of the karst collapse in Dingpa region,Guizhou,the evaluation results we have gained prove that the region is extremely vulnerable to collapse,which conforms to the earlier prediction of the actual situation of such collapse in the region. Moreover,the research results also indicate that the method we have developed is feasible for the risk prediction of the actual regional karst collapse. Therefore,the method we have developed can be expected to provide a scientific reference for the prevention and control of the local karst collapse.
The paper aims at introducing a risk prediction and evaluation model for the karst-strata collapse based on the study of the theory of set pair analysis. We have engaged in and investigated and explored the 12 factors that the collapse may get involved with according to the developmental condition of the karst collapse in Guizhou as well as the currently available research findings to our sampling research target. The said 12 influential factors,may all contribute to the constituent embodiment for establishing the risk prediction and evaluation system for the karst collapse,namely,the lithological character of bedrock,the developmental condition of the karst,the landform,the geophysical structure,the soil thickness,the soil lithology,the distance from the underground water level to the bedrock surface,the amplitude of the variations of the underground water sources,the run-off intensity of the underground water,the infiltration situation of the surface water,the artificial pumping intensity and all the human engineering interference activities. And,in terms of the types of all the indexical factors,the evaluation can also be conducted in a quantitative or qualitative way,for example,the risk liabilities can be divided into 5 grades,that is,the stable grade( 1),the nearly stable( 2),the less stable grade( 3),the vulnerable grade to the collapse one( 4),the extremely vulnerable grade to the grade at the brink to collapse( 5). And,then,it would be possible to adopt the set pair analysis method,that is to say,all the data values of each evaluation index to be calculated can be paired up with one of the corresponding five risk grades,so as to establish the expression formula of its connection degree,with the ultimately determined risk grades of karst collapse serving as the basis of the sequence of connection numbers. And,with the model developed to be used in the risk prediction and evaluation of the karst collapse in Dingpa region,Guizhou,the evaluation results we have gained prove that the region is extremely vulnerable to collapse,which conforms to the earlier prediction of the actual situation of such collapse in the region. Moreover,the research results also indicate that the method we have developed is feasible for the risk prediction of the actual regional karst collapse. Therefore,the method we have developed can be expected to provide a scientific reference for the prevention and control of the local karst collapse.
引文
[1]KANG Yanren(康彦仁),XIANG Shijun(项式钧),CHEN Jian(陈健),et al.Karst collapse in South China(中国南方岩溶塌陷)[M].Nanning:Guangxi Science and Technology Press,1990:2-38.
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[3]MENG Yan(蒙彦),HUANG Jianmin(黄健民),LEI Mingtang(雷明堂),et al.Quantitative forecast method of karst collapse based on grey verhulst model[J].Carsologica Sinica(中国岩溶),2009,28(1):17-22.
[4]LI Gongyan(李公岩),LI Yuanzhong(李元仲),YANG Ruiying(杨蕊英),et al.Hierarchic-fuzzy prediction and evaluation of karst collapse in Zaozhuang City,Shangdong Province[J].The Chinese Journal of Geological Hazard and Control(中国地质灾害与防治学报),2008,19(2):87-90.
[5]WU Yunbo(武运泊),WANG Yunsheng(王运生),CAO Wenzheng(曹文正).Risk evaluation of karst collapse based on AHP&fuzzy comprehensive evaluation[J].The Chinese Journal of Geological Hazard and Control(中国地质灾害与防治学报),2015,26(1):43-48.
[6]LI Zhong(李忠),ZHANG Yaowen(张耀文),LI Haijun(李海君).Prediction evaluation of karst collapse based on the improved BP-network[J].Journal of Liaoning Technical University:Natural Science(辽宁工程技术大学学报:自然科学版),2013,32(1):1-6.
[7]KOUTEPOV V M,MIRONOV O K,TOLMACHEV V V.Assessment of suffosion-related hazards in karst areasusing GIS technology[J].Environmental Geology,2008,54(5):957-962.
[8]JIN Yanzhu(金艳珠),TAN Shucheng(谈树成),HU Xionggang(虎雄岗),et al.Geo-hazard susceptibility zoning evaluation of karst collapse based on the combination of AHP and GIS:a case study of Shizong,Yunnan[J].Tropical Geography(热带地理),2012,32(2):173-178.
[9]LAI Yongbiao(赖永标),QIAO Chunsheng(乔春生).Intelligent model of karstic collapse prediction based on SVM[J].Journal of Beijing Jiaotong University(北京交通大学学报),2008,32(1):36-39.
[10]HUANG Rendong(黄仁东),HAN Ming(韩明),ZHANG Xiaojun(张小军),et al.Classification prediction of karst collapse tendency level based on Fisher discriminant analysis method[J].China Safety Science Journal(中国安全科学学报),2011,21(9):70-76.
[11]ZHAO Keqin(赵克勤).Set pair analysis and its application(集对分析及其初步应用)[M].Hangzhou:Zhejiang Science and Technology Press,2000:9-113.
[12]ZHANG Bin(张斌).The fuzzy set pair analysis way of multi-objective system decision[J].Systems Engineering—Theory&Practice(系统工程理论与实践),1997(12):108-114.
[13]WANG Zhongzhong(王忠忠).Karst sinkhole hazard evaluation of Zhaoqing city,Pearl river delta[J].Soil Engineering and Foundation(土工基础),2015,29(4):90-93.
[14]LIU Baochen(刘宝臣),TANG Qian(唐黔),QIU Mengyao(邱孟尧).Zhunyi karst terrain sinkhole collapse evaluation and hazard predictions[J].Soil Engineering and Foundation(土工基础),2014,27(4):33-36.
[15]PAN Jian(潘健),ZHOU Sen(周森),LIN Peiyuan(林培源),et al.Preliminary study of risks of karst collapse in Guangzhou Baiyun district[J].Rock and Soil Mechanics(岩土力学),2013,34(9):2589-2600.
[16]XIAO Minggui(肖明贵).The forming mechanism and forecast of fatalness about karst subsidence in Guilin City(桂林市岩溶塌陷形成机制与危险性预测)[D].Changchun:Jilin University,2005.
[17]ZHANG Liang(张梁),ZHANG Yecheng(张业成),LUO Yuanhua(罗元华),et al.Theory and practice of geological disaster assessment(地质灾害灾情评估理论与实践)[M].Beijing:Geological Press,1998:53-56.
[18]CHU Xuewei(褚学伟),DANG Shuang(党爽),DING Jianping(丁坚平).Analysis of karst collapse distribution in Guizhou Province and influential factors[J].Yangtze River(人民长江),2015,46(12):42-44.
[19]LIU Kaidong(刘凯栋).Karst collapse in Guizhou Province[J].Geology of Guizhou(贵州地质),1990,7(3):204-215.
[2]LEI Mingtang(雷明堂),JIANG Xiaozhen(蒋小珍).Research on the present situation and developing tendency of karst collapse and techniques for its supporting[J].The Chinese Journal of Geological Hazard and Control(中国地质灾害与防治学报),1998,9(3):1-6.
[3]MENG Yan(蒙彦),HUANG Jianmin(黄健民),LEI Mingtang(雷明堂),et al.Quantitative forecast method of karst collapse based on grey verhulst model[J].Carsologica Sinica(中国岩溶),2009,28(1):17-22.
[4]LI Gongyan(李公岩),LI Yuanzhong(李元仲),YANG Ruiying(杨蕊英),et al.Hierarchic-fuzzy prediction and evaluation of karst collapse in Zaozhuang City,Shangdong Province[J].The Chinese Journal of Geological Hazard and Control(中国地质灾害与防治学报),2008,19(2):87-90.
[5]WU Yunbo(武运泊),WANG Yunsheng(王运生),CAO Wenzheng(曹文正).Risk evaluation of karst collapse based on AHP&fuzzy comprehensive evaluation[J].The Chinese Journal of Geological Hazard and Control(中国地质灾害与防治学报),2015,26(1):43-48.
[6]LI Zhong(李忠),ZHANG Yaowen(张耀文),LI Haijun(李海君).Prediction evaluation of karst collapse based on the improved BP-network[J].Journal of Liaoning Technical University:Natural Science(辽宁工程技术大学学报:自然科学版),2013,32(1):1-6.
[7]KOUTEPOV V M,MIRONOV O K,TOLMACHEV V V.Assessment of suffosion-related hazards in karst areasusing GIS technology[J].Environmental Geology,2008,54(5):957-962.
[8]JIN Yanzhu(金艳珠),TAN Shucheng(谈树成),HU Xionggang(虎雄岗),et al.Geo-hazard susceptibility zoning evaluation of karst collapse based on the combination of AHP and GIS:a case study of Shizong,Yunnan[J].Tropical Geography(热带地理),2012,32(2):173-178.
[9]LAI Yongbiao(赖永标),QIAO Chunsheng(乔春生).Intelligent model of karstic collapse prediction based on SVM[J].Journal of Beijing Jiaotong University(北京交通大学学报),2008,32(1):36-39.
[10]HUANG Rendong(黄仁东),HAN Ming(韩明),ZHANG Xiaojun(张小军),et al.Classification prediction of karst collapse tendency level based on Fisher discriminant analysis method[J].China Safety Science Journal(中国安全科学学报),2011,21(9):70-76.
[11]ZHAO Keqin(赵克勤).Set pair analysis and its application(集对分析及其初步应用)[M].Hangzhou:Zhejiang Science and Technology Press,2000:9-113.
[12]ZHANG Bin(张斌).The fuzzy set pair analysis way of multi-objective system decision[J].Systems Engineering—Theory&Practice(系统工程理论与实践),1997(12):108-114.
[13]WANG Zhongzhong(王忠忠).Karst sinkhole hazard evaluation of Zhaoqing city,Pearl river delta[J].Soil Engineering and Foundation(土工基础),2015,29(4):90-93.
[14]LIU Baochen(刘宝臣),TANG Qian(唐黔),QIU Mengyao(邱孟尧).Zhunyi karst terrain sinkhole collapse evaluation and hazard predictions[J].Soil Engineering and Foundation(土工基础),2014,27(4):33-36.
[15]PAN Jian(潘健),ZHOU Sen(周森),LIN Peiyuan(林培源),et al.Preliminary study of risks of karst collapse in Guangzhou Baiyun district[J].Rock and Soil Mechanics(岩土力学),2013,34(9):2589-2600.
[16]XIAO Minggui(肖明贵).The forming mechanism and forecast of fatalness about karst subsidence in Guilin City(桂林市岩溶塌陷形成机制与危险性预测)[D].Changchun:Jilin University,2005.
[17]ZHANG Liang(张梁),ZHANG Yecheng(张业成),LUO Yuanhua(罗元华),et al.Theory and practice of geological disaster assessment(地质灾害灾情评估理论与实践)[M].Beijing:Geological Press,1998:53-56.
[18]CHU Xuewei(褚学伟),DANG Shuang(党爽),DING Jianping(丁坚平).Analysis of karst collapse distribution in Guizhou Province and influential factors[J].Yangtze River(人民长江),2015,46(12):42-44.
[19]LIU Kaidong(刘凯栋).Karst collapse in Guizhou Province[J].Geology of Guizhou(贵州地质),1990,7(3):204-215.