基于最小熵的金沙江上游区域泥石流危险度评价
|
摘要
泥石流作为一种突发的地质灾害，其来势凶猛、流量大、破坏力强、发生时间短而复发频率高，灾害分布范围广，数量多，是世界性的地质灾害。山区所具有的地质环境背景使得山区成为泥石流的多发地区，我国国土面积的三分之二为山地，因此我国是泥石流灾害严重的国家之一。泥石流灾害已经危害山区的生活稳定、社会生产及经济发展，要规避上述问题以及保护人民生命财产安全，急需对泥石流进行研究。
本文在对金沙江流域的20条泥石流危险性进行综合评价过程中，运用了下列非线性方法：“最小熵”、“通径分析”、“层次分析法”、“熵值法”、“可拓理论”以及“组合赋权法”，并对各泥石流危险度评价模型的特点及不同之处进行对比分析。有如下主要的研究内容及成果：
1、本文研究对象为金沙江波罗水电站库坝区内的泥石流，经过野外的实地进行调查、资料的精心搜集以及进行室内资料的解译整理，分析了金沙江波罗水电站库坝区泥石流的整体发育条件，并详细介绍20条典型泥石流的地质地貌特征以及发育情况。在前人研究的基础上，结合研究区泥石流的具体情况，初步提取泥石流评价的12个指标。
2、运用最小熵法和通径分析法分别对初步选取的评价指标进行约简优化，两者约简后的指标集分别为{流域切割密度、泥砂补给段长度比、植被覆盖率、流域内人口密度、主沟平均比降、主沟长度、流域面积}、{流域切割密度、流域内人口密度、主沟平均比降、单位面积物源量、主沟长度、流域面积}，两组指标集均能充分反映泥石流危险度的信息。
3、采用层次分析法、熵值法的组合赋权法计算组合权重，结合后的两组指标集，分别建立研究区泥石流危险性评价的最小熵-可拓模型及通径分析-可拓模型，对研究区泥石流危险度进行分级。
4、为了对比验证最小熵和通径分析法结果的客观合理性，本文引入传统的刘希林模型对研究区泥石流危险性进行评价，以作对比。结果表明：最小熵-可拓模型模型判对率更高，且更安全合理。
5、两个模型提取的指标组合均包括流域切割密度、流域内人口密度、主沟平均比降、主沟长度、流域面积，说明这5个指标为泥石流危险度评价的重要影响因素。
Debris flow, which as a sudden natural disasters, the ferocious, largeflow, destructive, shorter time and higher frequency of recurrence,iswidely distributing and often occuring. The mountains often happen debrisflow because their geological circumstances are proned to forming anddeveloping debris flow. China is a country with about two-thirds of thetotal land area is mountain. There, it is one of the countries undergoingsevere debris flows. The debris flow hazard area has stable life, socialproduction and economic development, in order to avoid the above problemsand protect people's lives and property safety, an urgent need for studiesof debris flow.
In this paper,20debris flow risk of Jinsha River basin comprehensiveevaluation process, using the nonlinear methods:"minimum entropy","pathanalysis","analytic hierarchy process","entropy","extension theory"and "the combination weighting method", and the characteristics of thedangerous degree of debris flow the evaluation model and differenceanalysis. There are the main research contents and contributions:
1.The object of study is the Jinsha Jiang Bo Luo hydropower stationreservoir area of debris flow, through field investigation, datacollected and indoor data interpretation of finishing, analyses theconditions the overall development of hydropower station reservoir areaof debris flow Kim Shah Jean Polo, and introduced in detail the geologicalfeatures of the20typical debris flow and development. On the basis ofprevious studies, combined with the specific circumstances of debris flowin the study area, the preliminary extraction of12indices of debris flowevaluation.
2. Applied the minimum entropy and path analysis to preliminary selection of evaluation index reduction optimization. The results of eachothers were {drainage density、loose material supply length ratio、Vegetation coverage、population density of the drainage、average gradientof the main channel、length of the main channel、drainage area}、{drainagedensity、population density of the drainage、average gradient of the mainchannel、average material、 length of the main channel、drainage area}、
3．Applied the analytic hierarchy process and entropy method tocalculate the combination weighting.Respectively to establish debrisflow risk assessment in the study area of minimum entropy-extensiontheory model and path theroy-extension theory model of debris flow riskclassification in the studied area.
4. In order to verifing the rationality and reliability of the twomodel, this paper introduced the traditional Liu Xilin model for debrisflow risk evaluation in the study area.The results showed that the minimumentropy-extension theory model has a higher safety and rationality.
5. The commom evaluation indexs extracted by the two models weredrainage density, population density of the drainage, average gradientof the main channel, length of the main channel and drainage area, whichmaybe indicate thoese five index play important roles in evaluating thedebris flow hazard.
本文在对金沙江流域的20条泥石流危险性进行综合评价过程中，运用了下列非线性方法：“最小熵”、“通径分析”、“层次分析法”、“熵值法”、“可拓理论”以及“组合赋权法”，并对各泥石流危险度评价模型的特点及不同之处进行对比分析。有如下主要的研究内容及成果：
1、本文研究对象为金沙江波罗水电站库坝区内的泥石流，经过野外的实地进行调查、资料的精心搜集以及进行室内资料的解译整理，分析了金沙江波罗水电站库坝区泥石流的整体发育条件，并详细介绍20条典型泥石流的地质地貌特征以及发育情况。在前人研究的基础上，结合研究区泥石流的具体情况，初步提取泥石流评价的12个指标。
2、运用最小熵法和通径分析法分别对初步选取的评价指标进行约简优化，两者约简后的指标集分别为{流域切割密度、泥砂补给段长度比、植被覆盖率、流域内人口密度、主沟平均比降、主沟长度、流域面积}、{流域切割密度、流域内人口密度、主沟平均比降、单位面积物源量、主沟长度、流域面积}，两组指标集均能充分反映泥石流危险度的信息。
3、采用层次分析法、熵值法的组合赋权法计算组合权重，结合后的两组指标集，分别建立研究区泥石流危险性评价的最小熵-可拓模型及通径分析-可拓模型，对研究区泥石流危险度进行分级。
4、为了对比验证最小熵和通径分析法结果的客观合理性，本文引入传统的刘希林模型对研究区泥石流危险性进行评价，以作对比。结果表明：最小熵-可拓模型模型判对率更高，且更安全合理。
5、两个模型提取的指标组合均包括流域切割密度、流域内人口密度、主沟平均比降、主沟长度、流域面积，说明这5个指标为泥石流危险度评价的重要影响因素。
Debris flow, which as a sudden natural disasters, the ferocious, largeflow, destructive, shorter time and higher frequency of recurrence,iswidely distributing and often occuring. The mountains often happen debrisflow because their geological circumstances are proned to forming anddeveloping debris flow. China is a country with about two-thirds of thetotal land area is mountain. There, it is one of the countries undergoingsevere debris flows. The debris flow hazard area has stable life, socialproduction and economic development, in order to avoid the above problemsand protect people's lives and property safety, an urgent need for studiesof debris flow.
In this paper,20debris flow risk of Jinsha River basin comprehensiveevaluation process, using the nonlinear methods:"minimum entropy","pathanalysis","analytic hierarchy process","entropy","extension theory"and "the combination weighting method", and the characteristics of thedangerous degree of debris flow the evaluation model and differenceanalysis. There are the main research contents and contributions:
1.The object of study is the Jinsha Jiang Bo Luo hydropower stationreservoir area of debris flow, through field investigation, datacollected and indoor data interpretation of finishing, analyses theconditions the overall development of hydropower station reservoir areaof debris flow Kim Shah Jean Polo, and introduced in detail the geologicalfeatures of the20typical debris flow and development. On the basis ofprevious studies, combined with the specific circumstances of debris flowin the study area, the preliminary extraction of12indices of debris flowevaluation.
2. Applied the minimum entropy and path analysis to preliminary selection of evaluation index reduction optimization. The results of eachothers were {drainage density、loose material supply length ratio、Vegetation coverage、population density of the drainage、average gradientof the main channel、length of the main channel、drainage area}、{drainagedensity、population density of the drainage、average gradient of the mainchannel、average material、 length of the main channel、drainage area}、
3．Applied the analytic hierarchy process and entropy method tocalculate the combination weighting.Respectively to establish debrisflow risk assessment in the study area of minimum entropy-extensiontheory model and path theroy-extension theory model of debris flow riskclassification in the studied area.
4. In order to verifing the rationality and reliability of the twomodel, this paper introduced the traditional Liu Xilin model for debrisflow risk evaluation in the study area.The results showed that the minimumentropy-extension theory model has a higher safety and rationality.
5. The commom evaluation indexs extracted by the two models weredrainage density, population density of the drainage, average gradientof the main channel, length of the main channel and drainage area, whichmaybe indicate thoese five index play important roles in evaluating thedebris flow hazard.
引文
[1]苏小琴.四川沪定县城区深家沟泥石流特征及风险评价研究[D].成都：成都理工大学,2007.
[2]梅岩.四川省北川县5.12强震区泥石流危险性评价[D].成都：成都理工大学,2011.
[3]铁永波.强震区城镇泥石流灾害风险评价方法与体系研究[D].成都：成都理工大学,2009.
[4]罗宇.四川省盐源县格地罗沟泥石流灾害性分析[D].成都：成都理工大学,2012.
[5]张建石.基于GIS的汶川县城镇泥石流风险性评价研究—以南沟泥石流为例[D].成都：成都理工大学,2012.
[6]柳金峰,欧国强.泥石流危险性评价的新思路[J].地质灾害与环境保护,2004,15(1):5-8
[7]张梁,张业成,罗元华,等.地质灾害灾情评估理论与实践[M].北京:地质出版社,1998.
[8]罗元华.论泥石流灾害风险评估方法[J].中国矿业,2000,9(6):70-72.
[9] C.M.弗莱施曼[苏]著,姚德基译.泥石流[M].北京:科学出版社,1986.29-35.
[10]足立胜治，德山九仁夫，中筋章人，二宫寿男，大八木俊治.土石流发生危险度の判定にフやて[J].新砂防，1977，30(3):7-16.
[11] Wieczork, GF. EvaluatingDangerLandslideCatalogueMaps[J]. Bulletin of theAssociation of Engineering Geologists,1984,1(1):337-342.
[12] Ellen SD, W ieczorek GF. Landslide, floods andmarine effects ofthe stormof January3-51982in the San Francisco Bay Region [R]. California:USGeologicalSurveyProfessionalPaper,1434,310.
[13] Eldeen M T, Predisaster Physical Planning: Inteqration of Disaster RiskAnalysis into Physical Planning: A Case Study in Tunisia[J]. Disasters,1980,4(2):211-222．
[14] Takahashi T, Estimation of potential debris flows and their hazardous zones:Soft countermeasures for a disaster[J]. JOURAL OF NATURAL DISASTER SCIENCE.1981:57-89.
[15] Hollingsworth R. and G. S. Kovacs. Soil slumps and debris flows: Predictionand protection[J]. Bulletin of the Association of Engineering Geologists,1981,18(1):17-28.
[16]高桥保.土石流の堆积危险范围の预测[J].第17回自然灾害科学总合ツヅポテム,1980,133-148
[17]久保田哲也，正务章，板垣昭彦.流域の任意地点における短时间降雨预测手法と土石流发生危险度判定图の开发[J].新砂防，1990，42(6):11-17.
[18] Olivier Lateltin, Example of hazard assessment and land-use planning inSwitzerland for snow avalanches, floods and landslides[J]. Swiss nationalhydrological and geological survey. Bern,1998
[19] Okimura T. A slope stability method for predicting rapid mass movementson granite mountain slopes[J]. Natural Disaster Science.1983,5(1):13-30
[20] Carrara A. GIS techniques and statistical models in evaluatinglandslidehazard[J]. Earth Surface Processes and Landforms, New York,1991,16(1):427-445
[21] Carrara A, Cardinali M, Guzzetti F. Uncertainty in assessing landslidehazard and risk[J]. ITC Journa,l1992(2):172-183.
[22]王礼先.北京山区荒溪分类与危险区制图[J].山地研究.1995,13(3):141-146.
[23]谭炳炎,靳番,荆绍华.泥石流沟的判别方法和数量化综合评判[A]//泥石流防治理论和实践[C].西安:西安交通大学出版社,1991:45-71.
[24]罗云.灾害评价初探[J].灾害学,1987,2(3):10-14.
[25]刘希林.泥石流危险度判定的研究[J].灾害学.1988,3(3):10-15.
[26]唐邦兴、柳絮青、刘世建.中国泥石流灾害分布与危害区划图（1:6,000,000）,成都地图出版社,1991.
[27]唐川,刘希林,朱静.泥石流堆积泛滥区危险度的评价与应用[J].自然灾害学报.1993,2(4):79-84.
[28]张汉雄.人为泥石流灾害严重等级的定量模糊综台评判[J].自然灾害学报,1996,5(3):50~70
[29]汤家法,谢洪.GIS技术支持下的泥石流危险度区划研究[J].四川测绘报,2002,15(2):87~89
[30]韦方强，胡凯衡．泥石流危险性分区及其在泥石流减灾中的应用[J]．中国地质灾害与防治学报，2007，18(1)：23-27．
[31]赵源．风险评价技术在2003年“7.11”泥石流灾害评价中的应用[J]．灾害学，2004，19(1)：35-39．
[32]李新坡,莫多闻.应用GIS和神经网络方法进行泥石流危险度评价的研究[J].水土保持研究.2005,12(8):6-9.
[33]匡乐红,徐林荣,刘宝琛.基于可拓方法的泥石流危险性评价[J].中国铁道科学.2006,27(5):1-5.
[34]陈刚，何政伟，杨斌，杨洋.遗传BP神经网络在泥石流危险性评价中的应用[J].计算机工程与应用.2010,46(3)：228-231.
[35]王学良，李建一.基于层次分析法的泥石流危险性评价体系研究[J].中国矿业.2011，20(10):113-117.
[36]黄孝刚,张家军,甘华阳.滑坡危险性评价预测的新思路[J].中国地质灾害与预防学报,2002,13(3):23-28.
[37]柴贺军,黄润秋,刘汉超.滑坡堵江危险性分析与评价[J].中国地质灾害与防治学报,1997,8(4):1-7.
[38]汪明武.基于神经网络的泥石流危险度区划[J].水文地质工程地质,2000,(2):18-19.
[39]李志斌,郑成德.滑坡、泥石流危险度评判的灰色模式识别理论与模型[J].系统工程理论与实践,2000,(5):128-132.
[40]成都理工大学.金沙江波罗水电站库区综合地质调查报告[R].2008.
[41]四川省地质矿产局区域地质调查大队.中华人民共和国区域地质调查报告（1:200000）德格幅[M].1986.
[42]四川省水利电力局水文总站.四川省水文手册[M].1979.
[43]伍保祥.金沙江上游波罗水电站库区滑坡发育规律及岸坡稳定性风险分析[D].成都理工大学硕士学位论文，2008.
[44]贾留杰，沈军辉，刘维国.波罗水电站库区泥石流发育分布特征研究[J].地质学报，2009，29(1):55-58.
[45]中华人民共和国建设部.建筑抗震设计规范GB50011-2001[S].2001.
[46]刘希林,王全才,孔纪名,等.都(江堰)汶(川)公路泥石流危险性评价及活动趋势[J].防灾减灾工程学报，2004，24(1):41-46.
[47]张成杰，王常明.灰色关联法在泥石流危险性评价中的应用[J].吉林地质，2005，24(4):111-120.
[48]陈治，郑永胜.泥石流危险度的分类评价[J].中国地质灾害与防治学报，1997，8(1):27-31.
[49]刘希林，唐川.泥石流危险性评价[M].
[50] Ohlmacher, G.C., Davis, J.C.,2003. Using multiple logistic regression andGIS technology to predict landslide hazard in northeast Kansas, USA.Engineering Geology69,331-343.
[51] Lan, H.X., Zhou, C.H., Wang, L.J., Zhang, H.Y., Li, R.H.,2004. Landslidehazard spatial analysis and prediction using GIS in the Xiaojiang watershed,Yunnan, China.
[52] Catani, F., Casagli, N., Ermini, L., Righini, G., Menduni, G.,2005.Landslide hazard and risk mapping at catchment scale in the Arno River basin.Landslides2,329-342.
[53] Chang, T.C., Chao, R.J.,2006. Application of back-propagation networksin debris fow prediction. Engineering Geology85,270-280.
[54] Chang, T.C.,2007. Risk degree of debris fow applying neural networks.Nature Hazards42,209-224.
[55] Lu, G.Y., Chiu, L.S., Wong, D.W.,2007. Vulnerability assessment ofrainfall-induced debris fows in Taiwan. Nature Hazards43,223-244.
[56] Lee, S., Pradhan, B.,2007. Landslide hazard mapping at Selangor, Malaysiausing frequency ratio and logistic regression models. Landslides4,33-41.
[57] Chang, T.C., Chien, Y.H.,2007. The application of genetic algorithm indebris fows prediction. Environmental Geology53,339-347.
[58] Tiranti, D., Bonetto, S., Mandrone, G.,2008. Quantitative basincharacterisation to refne debris-fow triggering criteria and processes:an example from the Italian Western Alps. Landslides5,45-57.
[59] Tunusluoglu, M.C., Gokceoglu, C., Nefeslioglu, H.A., Sonmez, H.,2008.Extraction of potential debris source areas by logistic regressiontechnique: a case study from Barla, Besparmak and Kapi mountains (NWTaurids, Turkey). Environmental Geology54,9-22.
[60] Ranjan, K.D., Shuichi, H., Atsuko, N., Minoru, Y., Takuro, M., Katsuhiro,N.,2004. GIS based weights-of-evidence modelling of rainfall-inducedlandslides in small catchments for landslide susceptibility mapping.Environmental Geology54,311-324.
[61] Akgun, A., Dag, S., Bulut, F.,2008. Landslide susceptibility mapping fora landslide-prone area (Findikli, NE of Turkey) by likelihood-frequencyratio and weighted linear combination models. Environmental Geology54,1127-1143.
[62] Chia-Nan Liu, Jia-Jyun Dong, Yih-Ferng Peng.Effects of strong groundmotion on the susceptibility of gully type debris flows, EngineeringGeology,104(2009)241–253
[63]谭炳炎.泥石流沟严重程度的数量化综合评判[J].铁道学报,1986,02:74-82.
[64] Liu CN, Dong JJ, Peng YF, Huang HF (2009) Effects of strong ground motionon the susceptibility of gully type debris flows. Engineering Geology104:241-253.
[65]杨鑫.基于3S技术的汶川强震区潜在突发性泥石流危险性区划及评价研究[D].成都理工大学博士学位论文，2012.
[66]牛岑岑，泥石流危险度评价指标的提取与等级划分[D].吉林大学博士学位论文，2013.
[67]刘希林，张松林，唐川.中国西南山区沟谷暴雨泥石流危险度判定的基本原理和方法[J].云南地理环境研究，1993，5(2):62-70.
[68]匡乐红，徐林荣，刘宝琛.基于可拓方法的泥石流危险性评价[J].中国铁道科学，27(5):1-6.
[69] Kuang YH, Xu LR, Liu BC, Yao JC (2006) A new method for choosing zonationindicators of mudflow danger degrees based on the rough set theory. JGeomech12:236-241.
[70] Liu T, Zhang HJ, Wu JD, Hou XF, Zheng GQ, Ye ZH (2008) Application ofanalytic hierarchy process in debris flow risk degree assessment–a casestudy of Miyun County, Beijing City. Bull Soil Water Conserv28:6-10.
[71] Liu XL, Mo DW (2002) Debris flow risk and site-specific debris flow riskassessment. J Eng Geol10:266-273.
[72] Liu XL, Ni HY, Zhao YS, Peng C (2006) Research on the6.1debris flow hazardsin Meigu county of Liangshan state, Sichuan. J Eng Geol14:152-158.
[73] Benda LE, Cundy TW (1990) Predicting deposition of debris flows in mountainchannels. Can Geotech J27:409-417.
[74]张春山，李国俊，张业成，等.黄河上游地区崩塌滑坡泥石流地质灾害风险评价[J].地质力学学报，2006，12(2):211-218.
[75] Shannon C E. Amathematical theory of communication. Bell SysTech J,1948,27:623~659.
[76] Jaynes ET. Information theory and statistical mechanics. Phys Rev,1957,106(4):620~630.
[77]艾南山.侵蚀流域系统的信息熵[J].水土保持学报,1987,1(2):1-7.
[78]艾南山,岳天祥.再论流域系统的信息熵[J].水土保持学报,1988,2(4):1-7.
[79]李雅辉,杨武年,杨鑫等.基于流域系统的地貌信息熵泥石流敏感性评价[j].中国水土保持,2011.1(1).
[80]王晓朋,潘懋,任群智.基于流域系统地貌信息熵的泥石流危险性定量评价[j].北京大学学报(自然科学版),2007,43(2).
[81]丁继新，周圣华，杨志法等.川藏公路然乌-东久段地质灾害定量评价-“地质灾害熵”概念的提出和应用[j].自然灾害学报,2005,14(4).
[82]张晨，王清，陈剑平等.金沙江流域泥石流的组合赋权法危险度评价[j].岩土力学，2011，32（3）.
[83]杨宗佶,乔建平.基于信息熵的典型滑坡危险度评价研究[j].四川大学学报(工程科学版),2008,40(4).
[84] Chien-chih Chen, Chih-Yuan Tseng, Jia-Jyun Dong. New entropy-based methodfor variables selection and its application to the debris-flow hazardassessment. Engineering Geology,2007,94:19–26.
[85] Weiss, R.E.,1995. The influence of variable selection: aBayesiandiagnostic perspective. J. Am. Stat. Assoc.90,619–625.
[86] Raftery, A.E., Madigan, D., Hoeting, J.A.,1997. Bayesian modelaveragingfor regression models. J. Am. Stat. Assoc.92,179–191.
[87] Forbes, F., Peyrard, N.,2003. Hidden Markov random field modelselectioncriteria based on mean field-like approximations. IEEETrans. Pattern Anal.Mach. Intell.25(9),1089–1101.
[88] Dupuis, J.A., Robert, C.P.,2003. Variable selection in qualitativemodelsvia an entropic explanatory power. J. Stat. Plan. Inference111,77–94.
[89] Tseng, C.Y.,2006. Entropic criterion for model selection. Physica, A370,530–538.
[90] Jaynes, E.T.,1957a. Information theory and statistical mechanics.Phys.Rev.106,620–630.
[91] Jaynes, E.T.,1957b. Information theory and statistical mechanics II.Phys.Rev.108,171–190.
[92] Jaynes, E.T.,2003. Probability Theory: The Logic of Science.CambridgeUniversity Press, Cambridge, UK.
[93] Skilling, J.,1989. Maximum Entropy and Bayesian Methods.Kluwer,Dordrecht.
[94] Caticha, A.,2004. Relative Entropy and Inductive Inference. In:Erickson,G., Zhai, Y.(Eds.), Bayesian Inference and MaximumEntropy Methods inScience and Engineer, vol.707. AIP, New York.
[95] Pareschi MT, Santacroce R, Sulpizio R, Zanchetta G. Volcaniclastic debrisflows in the Clanio Valley(Campania, Italy): in sights for the assessmentof hazard potential[J]. Geomorphology,2002,43:219–231.
[96] Hu¨rlimann M, Rickenmann D, Medina V, Bateman A.Evaluation of approachesto calculate debrisflow parameters for hazard assessment. Eng Geol[J].2008,102:152–163.
[97]杜家菊,陈志伟.使用SPSS线性回归实现通径分析的方法[J].生物学通报,2010,45(2):4-6.
[98]敬艳辉,邢留伟.通径分析及其应用[J].统计教育,2006(2):24-26.
[99]何隆祥,王清,熊辉,等.膨胀土边坡稳定影响因素敏感度的通径分析[J].工程地质学报.2012,20(增):186-191.
[100]刘希林，莫多闻.泥石流风险评价[M].成都:四川科技出版社，2003.
[101]DUKE J M, AULL-HYDE R. Identifying public preferences for land preservationusing the analytic hierarchy process[J]. Ecological Economics,2002,42:131–145.
[102]CHEN C C, TSENG C Y, DONG J J. New entropy-based method for variablesselection and its application to the debris-flow hazard assessment[J].Engineering Geology,2007,94:19–26.
[103]SAATY T L. A Scaling Method for Priorities in Hierarchical Structures[J].Journal of Mathematical Psychology,1977,15:234–281.
[104]TSENG C Y. Entropic criterion for model selection[J].2006, Physica, A,370:530–538.
[105]冯庆高，周传波，傅志峰，章广成.基坑支护方案的灰色模糊可变决策模型[J].岩土力学,2010,31(7):2226–2231.
[106]杨春燕，蔡文.可拓工程方法[M].北京:科学出版社，2007.
[107]朱静，周矩乾.泥石流判释与危险度综合评价研究[A]//云南省滑坡泥石流重点区域预测预报与评价方法研究[C].昆明:云南科技出版社，1995，94-109.
[108]JUN Y. Application of extension theory in misfire fault diagnosis ofgasoline engines[J]. Expert Systems with Applications,2009,36:1217–1221.
[109]WANG M H, TSENG Y F, CHEN H C, CHAO K H. A novel clustering algorithm basedon the extension theory and genetic algorithm[J]. Expert Systems withApplications,2009,36:8269–8276.
[110]杨春燕，蔡文.可拓工程方法[M].北京:科学出版社，2007.
[111]蔡文.可拓逻辑初步[M].北京:科学出版社，2004.
[112]贾超，肖树芳，刘宁.可拓学理论在洞室岩体质量评价中的应用[J].岩石力学与工程学报，2003，22(5):751-756.
[113]Jun Y. Application of extension theory in misfire fault diagnosis ofgasoline engines[J]. Expert Systems with Applications,2009,36:1217-1221.
[114]蔡文，石勇.可拓学的科学意义与未来发展[J].哈尔滨工业大学学报，2006，38(7):1079-1086.
[115]Mahmoud A, Abu-Zeid. Water and Sustainable Development: the Vision forWorld Water Life and the Environment[J]. Water Policy,1998,(1):9-19.
[116]高洁，戴建新，王雪红.可拓决策方法综述[J].系统工程理论方法应用，2004，13(3):264-271.
[117]Rubin L R. Unbounded sets of maps and compactification in extensiontheory[J]. Topology and its applications,2007,155:82-91.
[118]张文，乌东德水电站库区岩体结构评价方法研究[D].吉林大学博士学位论文，2013.
[119]王英杰，王磊，荣起国.基于最小熵分析的泥石流危险度可拓学评价[J].吉林大学学报（工学版），2013，43:547-554.
[120]Liu Q, Button E, Klima K. Investigation for probabilistic prediction ofshear strength properties of clay-rich fault gouge in the Austrian Alps[J].Engineering geology,2007,94:103-121.
[2]梅岩.四川省北川县5.12强震区泥石流危险性评价[D].成都：成都理工大学,2011.
[3]铁永波.强震区城镇泥石流灾害风险评价方法与体系研究[D].成都：成都理工大学,2009.
[4]罗宇.四川省盐源县格地罗沟泥石流灾害性分析[D].成都：成都理工大学,2012.
[5]张建石.基于GIS的汶川县城镇泥石流风险性评价研究—以南沟泥石流为例[D].成都：成都理工大学,2012.
[6]柳金峰,欧国强.泥石流危险性评价的新思路[J].地质灾害与环境保护,2004,15(1):5-8
[7]张梁,张业成,罗元华,等.地质灾害灾情评估理论与实践[M].北京:地质出版社,1998.
[8]罗元华.论泥石流灾害风险评估方法[J].中国矿业,2000,9(6):70-72.
[9] C.M.弗莱施曼[苏]著,姚德基译.泥石流[M].北京:科学出版社,1986.29-35.
[10]足立胜治，德山九仁夫，中筋章人，二宫寿男，大八木俊治.土石流发生危险度の判定にフやて[J].新砂防，1977，30(3):7-16.
[11] Wieczork, GF. EvaluatingDangerLandslideCatalogueMaps[J]. Bulletin of theAssociation of Engineering Geologists,1984,1(1):337-342.
[12] Ellen SD, W ieczorek GF. Landslide, floods andmarine effects ofthe stormof January3-51982in the San Francisco Bay Region [R]. California:USGeologicalSurveyProfessionalPaper,1434,310.
[13] Eldeen M T, Predisaster Physical Planning: Inteqration of Disaster RiskAnalysis into Physical Planning: A Case Study in Tunisia[J]. Disasters,1980,4(2):211-222．
[14] Takahashi T, Estimation of potential debris flows and their hazardous zones:Soft countermeasures for a disaster[J]. JOURAL OF NATURAL DISASTER SCIENCE.1981:57-89.
[15] Hollingsworth R. and G. S. Kovacs. Soil slumps and debris flows: Predictionand protection[J]. Bulletin of the Association of Engineering Geologists,1981,18(1):17-28.
[16]高桥保.土石流の堆积危险范围の预测[J].第17回自然灾害科学总合ツヅポテム,1980,133-148
[17]久保田哲也，正务章，板垣昭彦.流域の任意地点における短时间降雨预测手法と土石流发生危险度判定图の开发[J].新砂防，1990，42(6):11-17.
[18] Olivier Lateltin, Example of hazard assessment and land-use planning inSwitzerland for snow avalanches, floods and landslides[J]. Swiss nationalhydrological and geological survey. Bern,1998
[19] Okimura T. A slope stability method for predicting rapid mass movementson granite mountain slopes[J]. Natural Disaster Science.1983,5(1):13-30
[20] Carrara A. GIS techniques and statistical models in evaluatinglandslidehazard[J]. Earth Surface Processes and Landforms, New York,1991,16(1):427-445
[21] Carrara A, Cardinali M, Guzzetti F. Uncertainty in assessing landslidehazard and risk[J]. ITC Journa,l1992(2):172-183.
[22]王礼先.北京山区荒溪分类与危险区制图[J].山地研究.1995,13(3):141-146.
[23]谭炳炎,靳番,荆绍华.泥石流沟的判别方法和数量化综合评判[A]//泥石流防治理论和实践[C].西安:西安交通大学出版社,1991:45-71.
[24]罗云.灾害评价初探[J].灾害学,1987,2(3):10-14.
[25]刘希林.泥石流危险度判定的研究[J].灾害学.1988,3(3):10-15.
[26]唐邦兴、柳絮青、刘世建.中国泥石流灾害分布与危害区划图（1:6,000,000）,成都地图出版社,1991.
[27]唐川,刘希林,朱静.泥石流堆积泛滥区危险度的评价与应用[J].自然灾害学报.1993,2(4):79-84.
[28]张汉雄.人为泥石流灾害严重等级的定量模糊综台评判[J].自然灾害学报,1996,5(3):50~70
[29]汤家法,谢洪.GIS技术支持下的泥石流危险度区划研究[J].四川测绘报,2002,15(2):87~89
[30]韦方强，胡凯衡．泥石流危险性分区及其在泥石流减灾中的应用[J]．中国地质灾害与防治学报，2007，18(1)：23-27．
[31]赵源．风险评价技术在2003年“7.11”泥石流灾害评价中的应用[J]．灾害学，2004，19(1)：35-39．
[32]李新坡,莫多闻.应用GIS和神经网络方法进行泥石流危险度评价的研究[J].水土保持研究.2005,12(8):6-9.
[33]匡乐红,徐林荣,刘宝琛.基于可拓方法的泥石流危险性评价[J].中国铁道科学.2006,27(5):1-5.
[34]陈刚，何政伟，杨斌，杨洋.遗传BP神经网络在泥石流危险性评价中的应用[J].计算机工程与应用.2010,46(3)：228-231.
[35]王学良，李建一.基于层次分析法的泥石流危险性评价体系研究[J].中国矿业.2011，20(10):113-117.
[36]黄孝刚,张家军,甘华阳.滑坡危险性评价预测的新思路[J].中国地质灾害与预防学报,2002,13(3):23-28.
[37]柴贺军,黄润秋,刘汉超.滑坡堵江危险性分析与评价[J].中国地质灾害与防治学报,1997,8(4):1-7.
[38]汪明武.基于神经网络的泥石流危险度区划[J].水文地质工程地质,2000,(2):18-19.
[39]李志斌,郑成德.滑坡、泥石流危险度评判的灰色模式识别理论与模型[J].系统工程理论与实践,2000,(5):128-132.
[40]成都理工大学.金沙江波罗水电站库区综合地质调查报告[R].2008.
[41]四川省地质矿产局区域地质调查大队.中华人民共和国区域地质调查报告（1:200000）德格幅[M].1986.
[42]四川省水利电力局水文总站.四川省水文手册[M].1979.
[43]伍保祥.金沙江上游波罗水电站库区滑坡发育规律及岸坡稳定性风险分析[D].成都理工大学硕士学位论文，2008.
[44]贾留杰，沈军辉，刘维国.波罗水电站库区泥石流发育分布特征研究[J].地质学报，2009，29(1):55-58.
[45]中华人民共和国建设部.建筑抗震设计规范GB50011-2001[S].2001.
[46]刘希林,王全才,孔纪名,等.都(江堰)汶(川)公路泥石流危险性评价及活动趋势[J].防灾减灾工程学报，2004，24(1):41-46.
[47]张成杰，王常明.灰色关联法在泥石流危险性评价中的应用[J].吉林地质，2005，24(4):111-120.
[48]陈治，郑永胜.泥石流危险度的分类评价[J].中国地质灾害与防治学报，1997，8(1):27-31.
[49]刘希林，唐川.泥石流危险性评价[M].
[50] Ohlmacher, G.C., Davis, J.C.,2003. Using multiple logistic regression andGIS technology to predict landslide hazard in northeast Kansas, USA.Engineering Geology69,331-343.
[51] Lan, H.X., Zhou, C.H., Wang, L.J., Zhang, H.Y., Li, R.H.,2004. Landslidehazard spatial analysis and prediction using GIS in the Xiaojiang watershed,Yunnan, China.
[52] Catani, F., Casagli, N., Ermini, L., Righini, G., Menduni, G.,2005.Landslide hazard and risk mapping at catchment scale in the Arno River basin.Landslides2,329-342.
[53] Chang, T.C., Chao, R.J.,2006. Application of back-propagation networksin debris fow prediction. Engineering Geology85,270-280.
[54] Chang, T.C.,2007. Risk degree of debris fow applying neural networks.Nature Hazards42,209-224.
[55] Lu, G.Y., Chiu, L.S., Wong, D.W.,2007. Vulnerability assessment ofrainfall-induced debris fows in Taiwan. Nature Hazards43,223-244.
[56] Lee, S., Pradhan, B.,2007. Landslide hazard mapping at Selangor, Malaysiausing frequency ratio and logistic regression models. Landslides4,33-41.
[57] Chang, T.C., Chien, Y.H.,2007. The application of genetic algorithm indebris fows prediction. Environmental Geology53,339-347.
[58] Tiranti, D., Bonetto, S., Mandrone, G.,2008. Quantitative basincharacterisation to refne debris-fow triggering criteria and processes:an example from the Italian Western Alps. Landslides5,45-57.
[59] Tunusluoglu, M.C., Gokceoglu, C., Nefeslioglu, H.A., Sonmez, H.,2008.Extraction of potential debris source areas by logistic regressiontechnique: a case study from Barla, Besparmak and Kapi mountains (NWTaurids, Turkey). Environmental Geology54,9-22.
[60] Ranjan, K.D., Shuichi, H., Atsuko, N., Minoru, Y., Takuro, M., Katsuhiro,N.,2004. GIS based weights-of-evidence modelling of rainfall-inducedlandslides in small catchments for landslide susceptibility mapping.Environmental Geology54,311-324.
[61] Akgun, A., Dag, S., Bulut, F.,2008. Landslide susceptibility mapping fora landslide-prone area (Findikli, NE of Turkey) by likelihood-frequencyratio and weighted linear combination models. Environmental Geology54,1127-1143.
[62] Chia-Nan Liu, Jia-Jyun Dong, Yih-Ferng Peng.Effects of strong groundmotion on the susceptibility of gully type debris flows, EngineeringGeology,104(2009)241–253
[63]谭炳炎.泥石流沟严重程度的数量化综合评判[J].铁道学报,1986,02:74-82.
[64] Liu CN, Dong JJ, Peng YF, Huang HF (2009) Effects of strong ground motionon the susceptibility of gully type debris flows. Engineering Geology104:241-253.
[65]杨鑫.基于3S技术的汶川强震区潜在突发性泥石流危险性区划及评价研究[D].成都理工大学博士学位论文，2012.
[66]牛岑岑，泥石流危险度评价指标的提取与等级划分[D].吉林大学博士学位论文，2013.
[67]刘希林，张松林，唐川.中国西南山区沟谷暴雨泥石流危险度判定的基本原理和方法[J].云南地理环境研究，1993，5(2):62-70.
[68]匡乐红，徐林荣，刘宝琛.基于可拓方法的泥石流危险性评价[J].中国铁道科学，27(5):1-6.
[69] Kuang YH, Xu LR, Liu BC, Yao JC (2006) A new method for choosing zonationindicators of mudflow danger degrees based on the rough set theory. JGeomech12:236-241.
[70] Liu T, Zhang HJ, Wu JD, Hou XF, Zheng GQ, Ye ZH (2008) Application ofanalytic hierarchy process in debris flow risk degree assessment–a casestudy of Miyun County, Beijing City. Bull Soil Water Conserv28:6-10.
[71] Liu XL, Mo DW (2002) Debris flow risk and site-specific debris flow riskassessment. J Eng Geol10:266-273.
[72] Liu XL, Ni HY, Zhao YS, Peng C (2006) Research on the6.1debris flow hazardsin Meigu county of Liangshan state, Sichuan. J Eng Geol14:152-158.
[73] Benda LE, Cundy TW (1990) Predicting deposition of debris flows in mountainchannels. Can Geotech J27:409-417.
[74]张春山，李国俊，张业成，等.黄河上游地区崩塌滑坡泥石流地质灾害风险评价[J].地质力学学报，2006，12(2):211-218.
[75] Shannon C E. Amathematical theory of communication. Bell SysTech J,1948,27:623~659.
[76] Jaynes ET. Information theory and statistical mechanics. Phys Rev,1957,106(4):620~630.
[77]艾南山.侵蚀流域系统的信息熵[J].水土保持学报,1987,1(2):1-7.
[78]艾南山,岳天祥.再论流域系统的信息熵[J].水土保持学报,1988,2(4):1-7.
[79]李雅辉,杨武年,杨鑫等.基于流域系统的地貌信息熵泥石流敏感性评价[j].中国水土保持,2011.1(1).
[80]王晓朋,潘懋,任群智.基于流域系统地貌信息熵的泥石流危险性定量评价[j].北京大学学报(自然科学版),2007,43(2).
[81]丁继新，周圣华，杨志法等.川藏公路然乌-东久段地质灾害定量评价-“地质灾害熵”概念的提出和应用[j].自然灾害学报,2005,14(4).
[82]张晨，王清，陈剑平等.金沙江流域泥石流的组合赋权法危险度评价[j].岩土力学，2011，32（3）.
[83]杨宗佶,乔建平.基于信息熵的典型滑坡危险度评价研究[j].四川大学学报(工程科学版),2008,40(4).
[84] Chien-chih Chen, Chih-Yuan Tseng, Jia-Jyun Dong. New entropy-based methodfor variables selection and its application to the debris-flow hazardassessment. Engineering Geology,2007,94:19–26.
[85] Weiss, R.E.,1995. The influence of variable selection: aBayesiandiagnostic perspective. J. Am. Stat. Assoc.90,619–625.
[86] Raftery, A.E., Madigan, D., Hoeting, J.A.,1997. Bayesian modelaveragingfor regression models. J. Am. Stat. Assoc.92,179–191.
[87] Forbes, F., Peyrard, N.,2003. Hidden Markov random field modelselectioncriteria based on mean field-like approximations. IEEETrans. Pattern Anal.Mach. Intell.25(9),1089–1101.
[88] Dupuis, J.A., Robert, C.P.,2003. Variable selection in qualitativemodelsvia an entropic explanatory power. J. Stat. Plan. Inference111,77–94.
[89] Tseng, C.Y.,2006. Entropic criterion for model selection. Physica, A370,530–538.
[90] Jaynes, E.T.,1957a. Information theory and statistical mechanics.Phys.Rev.106,620–630.
[91] Jaynes, E.T.,1957b. Information theory and statistical mechanics II.Phys.Rev.108,171–190.
[92] Jaynes, E.T.,2003. Probability Theory: The Logic of Science.CambridgeUniversity Press, Cambridge, UK.
[93] Skilling, J.,1989. Maximum Entropy and Bayesian Methods.Kluwer,Dordrecht.
[94] Caticha, A.,2004. Relative Entropy and Inductive Inference. In:Erickson,G., Zhai, Y.(Eds.), Bayesian Inference and MaximumEntropy Methods inScience and Engineer, vol.707. AIP, New York.
[95] Pareschi MT, Santacroce R, Sulpizio R, Zanchetta G. Volcaniclastic debrisflows in the Clanio Valley(Campania, Italy): in sights for the assessmentof hazard potential[J]. Geomorphology,2002,43:219–231.
[96] Hu¨rlimann M, Rickenmann D, Medina V, Bateman A.Evaluation of approachesto calculate debrisflow parameters for hazard assessment. Eng Geol[J].2008,102:152–163.
[97]杜家菊,陈志伟.使用SPSS线性回归实现通径分析的方法[J].生物学通报,2010,45(2):4-6.
[98]敬艳辉,邢留伟.通径分析及其应用[J].统计教育,2006(2):24-26.
[99]何隆祥,王清,熊辉,等.膨胀土边坡稳定影响因素敏感度的通径分析[J].工程地质学报.2012,20(增):186-191.
[100]刘希林，莫多闻.泥石流风险评价[M].成都:四川科技出版社，2003.
[101]DUKE J M, AULL-HYDE R. Identifying public preferences for land preservationusing the analytic hierarchy process[J]. Ecological Economics,2002,42:131–145.
[102]CHEN C C, TSENG C Y, DONG J J. New entropy-based method for variablesselection and its application to the debris-flow hazard assessment[J].Engineering Geology,2007,94:19–26.
[103]SAATY T L. A Scaling Method for Priorities in Hierarchical Structures[J].Journal of Mathematical Psychology,1977,15:234–281.
[104]TSENG C Y. Entropic criterion for model selection[J].2006, Physica, A,370:530–538.
[105]冯庆高，周传波，傅志峰，章广成.基坑支护方案的灰色模糊可变决策模型[J].岩土力学,2010,31(7):2226–2231.
[106]杨春燕，蔡文.可拓工程方法[M].北京:科学出版社，2007.
[107]朱静，周矩乾.泥石流判释与危险度综合评价研究[A]//云南省滑坡泥石流重点区域预测预报与评价方法研究[C].昆明:云南科技出版社，1995，94-109.
[108]JUN Y. Application of extension theory in misfire fault diagnosis ofgasoline engines[J]. Expert Systems with Applications,2009,36:1217–1221.
[109]WANG M H, TSENG Y F, CHEN H C, CHAO K H. A novel clustering algorithm basedon the extension theory and genetic algorithm[J]. Expert Systems withApplications,2009,36:8269–8276.
[110]杨春燕，蔡文.可拓工程方法[M].北京:科学出版社，2007.
[111]蔡文.可拓逻辑初步[M].北京:科学出版社，2004.
[112]贾超，肖树芳，刘宁.可拓学理论在洞室岩体质量评价中的应用[J].岩石力学与工程学报，2003，22(5):751-756.
[113]Jun Y. Application of extension theory in misfire fault diagnosis ofgasoline engines[J]. Expert Systems with Applications,2009,36:1217-1221.
[114]蔡文，石勇.可拓学的科学意义与未来发展[J].哈尔滨工业大学学报，2006，38(7):1079-1086.
[115]Mahmoud A, Abu-Zeid. Water and Sustainable Development: the Vision forWorld Water Life and the Environment[J]. Water Policy,1998,(1):9-19.
[116]高洁，戴建新，王雪红.可拓决策方法综述[J].系统工程理论方法应用，2004，13(3):264-271.
[117]Rubin L R. Unbounded sets of maps and compactification in extensiontheory[J]. Topology and its applications,2007,155:82-91.
[118]张文，乌东德水电站库区岩体结构评价方法研究[D].吉林大学博士学位论文，2013.
[119]王英杰，王磊，荣起国.基于最小熵分析的泥石流危险度可拓学评价[J].吉林大学学报（工学版），2013，43:547-554.
[120]Liu Q, Button E, Klima K. Investigation for probabilistic prediction ofshear strength properties of clay-rich fault gouge in the Austrian Alps[J].Engineering geology,2007,94:103-121.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |