基于GIS与信息量模型的地质灾害危险性评价——以云南省丘北县为例
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摘要
以云南省丘北县县域内的地质灾害作为研究对象,基于地质灾害的空间分布特征、发育现状和形成条件,选取坡度、断裂构造、工程地质岩组、降雨量、道路、河流水系和土地利用/覆被7个评价指标,运用GIS技术和信息量模型相结合的方法开展了丘北县地质灾害危险性评价,根据综合信息量值将丘北县划分为极低度、低度、中度、高度、极高度5级危险区.结果表明,研究区地质灾害主要分布在西部和北部地区;地质灾害集中发育在软硬间夹岩类和软质岩类分布区,并且与地形坡度、交通干线和河流水系的展布具有相一致的特点,且现有灾害点的分布与危险度分区具有很好的相关性;通过野外实地验证,危险性分区和实际情况较为吻合.信息量模型与GIS相结合能够较为客观、快速地对地质灾害的空间分布和危险性做出评价,研究成果可为丘北县开展地质灾害防范和治理提供数据支撑.
This paper takes the geological disasters in Qiubei County,Yunnan Province as the research object,and selects slope,fault structure,engineering geological rock group,rainfall,road,river system and land based on the combination of GIS and information model,the risk assessment of geological disasters in Qiubei County was carried out by using/indexing the seven indexes.According to the comprehensive information,Qiubei County was divided into extremely low,low,medium degree,height and very high 5 level dangerous area.The results show that the geological disasters in the study area are mainly distributed in the western and northern regions.The geological disasters are concentrated in the soft and hard interbedded and soft rock distributions,and are consistent with the distribution of terrain slope,traffic trunk and river system,and the distribution of the current disaster points has a good correlation with the risk zoning.Through field verification,the dangerous zoning and the actual situation are more consistent.The research results are consistent with the actual situation,it shows that information model combined with GIS has advantages in studying the spatial distribution and the risk assessment of geological disasters,and the research results can provide data support for Qiubei County to carry out geological disaster prevention and management.
This paper takes the geological disasters in Qiubei County,Yunnan Province as the research object,and selects slope,fault structure,engineering geological rock group,rainfall,road,river system and land based on the combination of GIS and information model,the risk assessment of geological disasters in Qiubei County was carried out by using/indexing the seven indexes.According to the comprehensive information,Qiubei County was divided into extremely low,low,medium degree,height and very high 5 level dangerous area.The results show that the geological disasters in the study area are mainly distributed in the western and northern regions.The geological disasters are concentrated in the soft and hard interbedded and soft rock distributions,and are consistent with the distribution of terrain slope,traffic trunk and river system,and the distribution of the current disaster points has a good correlation with the risk zoning.Through field verification,the dangerous zoning and the actual situation are more consistent.The research results are consistent with the actual situation,it shows that information model combined with GIS has advantages in studying the spatial distribution and the risk assessment of geological disasters,and the research results can provide data support for Qiubei County to carry out geological disaster prevention and management.
引文
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[20]张晓东,刘湘南,赵志鹏,等.盐池县地质灾害遥感调查及空间分布特征[J].水文地质工程地质,2017,44(1):164.
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[23]黄润秋,许向宁,唐川,等.地质环境评价与地质灾害管理[M].北京:科学出版社,2008.
[24]李忠生.国内外地震滑坡灾害研究综述[J].灾害学,2003,18(4):64.
[25]陈晓利,冉洪流,祁生文.1976年龙陵地震诱发滑坡的影响因子敏感性分析[J].北京大学学报(自然科学版),2009,45(1):104.
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[27]高克昌,崔鹏,赵纯勇,等.基于地理信息系统和信息量模型的滑坡危险性评价——以重庆万州为例[J].岩石力学与工程学报,2006,25(5):991.
[28]ALDO C,SUSANNA P,CLAUDIO T,et al.A procedure for landslide susceptibility zonation by the conditional analysis method[J].Geomorphology,2002,48(4):349.
[2]易明华,吴辉,叶柯.地理国情的地质灾害危险性评价[J].测绘科学,2017,42(8):40.
[3]姚玉增,任群智,李仁峰,等.层次分析法在山地地质灾害危险性评价中应用——以辽宁凌源地区为例[J].水文地质工程地质,2010,37(2):130.
[4]张丽,李广杰,周志广,等.基于灰色聚类的区域地质灾害危险性分区评价[J].自然灾害学报,2009,18(1):164.
[5]金菊良,魏一鸣,丁晶.基于改进层次分析法的模糊综合评价模型[J].水利学报,2004,3(11):65.
[6]吕远强,杜林军,罗伟强.基于人工神经网络的区域地质灾害危险性预测评价[J].中国地质灾害与防治学报,2007,18(1):95.
[7]KANUNGO D P,SARKAR S,SHARMA S.Combining neural network with fuzzy,certainty factor and likelihood ratio concepts for spatial prediction of landslides[J].Nat Hazards,2011,59(3):1491.
[8]柳依莎,杨华.基于信息量模型的地质灾害危险性评价研究——以重庆市涪陵区为例[J].重庆师范大学学报(自然科学版),2012,29(4):34.
[9]吴柏清,何政伟,刘严松.基于GIS的信息量法在九龙县地质灾害危险性评价中的应用[J].测绘科学,2008,33(4):146.
[10]杜军,杨青华,严嘉,等.基于GIS与信息量模型的汶川次生地质灾害危险性评价[J].地球科学:中国地质大学学报,2010,35(2):324.
[11]邓辉,何政伟,陈晔,等.信息量模型在山地环境地质灾害危险性评价中的应用——以四川泸定县为例[J].自然灾害学报,2014,23(2):67.
[12]王云龙,文宝萍.兰州市滑坡地质灾害危险性研究[J].中国地质,2011,38(6):1593.
[13]薛东剑,何政伟,陶舒,等.“5.12”震后区域地质灾害危险性评价研究——以青川、平武县为例[J].地球科学进展,2011,26(3):311.
[14]贾贵义,全永庆,黎志恒,等.基于组合赋权法的白龙江流域甘肃段地质灾害危险性评价[J].冰川冻土,2014,36(5):1227.
[15]阮沈勇,黄润秋.基于GIS的信息量法模型在地质灾害危险性区划中的应用[J].成都理工学院学报,2001,28(1):89.
[16]DUMAN T Y,CAN T,GOKCEOGLU C,et al.Application of logistic regression for landslide susceptibility zoning of Cekmece Area,Istanbul,Turkey[J].Environmental Geology,2006,51(2):241.
[17]CHE V B,KERVYN M,SUH C E,et al.Landslide susceptibility assessment in Limbe(SW Cameroon):a field calibrated seed and information value method[J].Catena,2012,92(1):83.
[18]BHANDARY N P,DAHAL R K,TIMILSINA M,et al.Rainfall event-based landslide susceptibility zonation mapping[J].Nat Hazards,2013,69(1):365.
[19]刘彦花,叶国华.基于粗糙集与GIS的滑坡地质灾害风险评估——以广西梧州为例[J].灾害学,2015,30(2):108.
[20]张晓东,刘湘南,赵志鹏,等.盐池县地质灾害遥感调查及空间分布特征[J].水文地质工程地质,2017,44(1):164.
[21]FEIZIZADEH B,BLASCHKE T.GIS-multicriteria decision analysis for landslide susceptibility mapping:comparing three methods for the Urmialake basin,Iran[J].Nat Hazards,2013,65(3):2105.
[22]袁湘秦,赵法锁,陈新建,等.陕西省绥德县地质灾害易发性区划[J].灾害学,2017,32(1):117.
[23]黄润秋,许向宁,唐川,等.地质环境评价与地质灾害管理[M].北京:科学出版社,2008.
[24]李忠生.国内外地震滑坡灾害研究综述[J].灾害学,2003,18(4):64.
[25]陈晓利,冉洪流,祁生文.1976年龙陵地震诱发滑坡的影响因子敏感性分析[J].北京大学学报(自然科学版),2009,45(1):104.
[26]刘传正,刘艳辉,温铭生,等.长江三峡库区地质灾害成因与评价研究[M].北京:地质出版社,2007.
[27]高克昌,崔鹏,赵纯勇,等.基于地理信息系统和信息量模型的滑坡危险性评价——以重庆万州为例[J].岩石力学与工程学报,2006,25(5):991.
[28]ALDO C,SUSANNA P,CLAUDIO T,et al.A procedure for landslide susceptibility zonation by the conditional analysis method[J].Geomorphology,2002,48(4):349.