GIS支持下的黄土高原地震滑坡区划研究
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摘要
分析了影响黄土滑坡的各项影响因子,利用层次分析法(AHP)确定各影响因子的权重。在GIS支持下,建立包括各因子图的空间数据库,对各因子进行分级赋值,然后进行因子加权叠加分析,完成三种超越概率下(50年超越概率2%、10%和63.5%)黄土高原地震滑坡区划图。黄土地震滑坡灾害最严重地区一个是宁夏南部及与其相邻的甘肃白银地区,另一个是甘肃天水地区。
The Loess Plateau, the region with most extensive and thickest loess deposition in China, is located at middle reaches of the Yellow River and its area reaches 275 600 km~2. And it is the region with severe seismic disaster because of loess characteristics of loosen, big hole and weak cementation and frequent strong earthquake occurring. Landslides are one of the most damaging collateral hazards associated with earthquakes. In fact, damage from triggered landslides has sometimes exceeded damage directly related to strong shaking and fault rupture. Seismic landslide zonation maps representing the susceptibility of slopes to failure during and earthquake could therefore be useful tools for preventing disasters and to help land-use planners to make decisions. Six factors impacting loess landslide are analyzed: seismic acceleration, stratum, morphology type, precipitation, slope angle and natural density, and the relative importance of each determined factor of slope instability was quantitatively determined by pair-wise comparison using the analytical hierarchy process (AHP) method. The result shows that seismic acceleration is the most important factor with weight value 0.3834. The following factors are morphology type and slope angle with weight value 0.2734 and 0.1543, respectively. Stratum, precipitation and natural density are not the major factors with weight value 0.0599, 0.0878 and 0.0416, respectively. Through digitizing, the spatial database including the factor′s mapsof the factors and their attribute data is built in AcrView GIS software. Each factor map is converted into grid format with size 200m×200m. Then each factor is classified into several classes with regard to their changing in the nature and each class is valued from 1 to 6 according to their impacting degree on landslide. Subsequently the values of six factors classes are multiplied by derived weights for each factor and then are summed together. So the total value so-called landslide index for each pixel and whole region are achieved. With regard to landslide index, the Loess Plateau is divided to four susceptibility classes: very low, low, moderate and high. Finally the landslide zonation maps of the Loess Plateau with three probabilities of exceedance (2%, 10% and 63.5% probability of exceedance in 50 years) are accomplished. Comparing past landslides distribution with zonation map of 2% probability of exceedance in 50 years shows the most landslides are located in high and moderate susceptibility areas, and the group landslides are located in high susceptibility areas. There are two regions with severest landslide hazard: one is south of Ningxia Province with adjacent Baiyin Prefecture of Gansu Province; the other is Tianshui Prefecture of Gansu Province. The moderate landslide hazard areas include: the areas around the above areas from east Pingliang Prefecture to Lanzhou City; Fen-Wei graben and its around areas. The other areas have low landslide susceptibility, especially Erdos block is the stablest area.
The Loess Plateau, the region with most extensive and thickest loess deposition in China, is located at middle reaches of the Yellow River and its area reaches 275 600 km~2. And it is the region with severe seismic disaster because of loess characteristics of loosen, big hole and weak cementation and frequent strong earthquake occurring. Landslides are one of the most damaging collateral hazards associated with earthquakes. In fact, damage from triggered landslides has sometimes exceeded damage directly related to strong shaking and fault rupture. Seismic landslide zonation maps representing the susceptibility of slopes to failure during and earthquake could therefore be useful tools for preventing disasters and to help land-use planners to make decisions. Six factors impacting loess landslide are analyzed: seismic acceleration, stratum, morphology type, precipitation, slope angle and natural density, and the relative importance of each determined factor of slope instability was quantitatively determined by pair-wise comparison using the analytical hierarchy process (AHP) method. The result shows that seismic acceleration is the most important factor with weight value 0.3834. The following factors are morphology type and slope angle with weight value 0.2734 and 0.1543, respectively. Stratum, precipitation and natural density are not the major factors with weight value 0.0599, 0.0878 and 0.0416, respectively. Through digitizing, the spatial database including the factor′s mapsof the factors and their attribute data is built in AcrView GIS software. Each factor map is converted into grid format with size 200m×200m. Then each factor is classified into several classes with regard to their changing in the nature and each class is valued from 1 to 6 according to their impacting degree on landslide. Subsequently the values of six factors classes are multiplied by derived weights for each factor and then are summed together. So the total value so-called landslide index for each pixel and whole region are achieved. With regard to landslide index, the Loess Plateau is divided to four susceptibility classes: very low, low, moderate and high. Finally the landslide zonation maps of the Loess Plateau with three probabilities of exceedance (2%, 10% and 63.5% probability of exceedance in 50 years) are accomplished. Comparing past landslides distribution with zonation map of 2% probability of exceedance in 50 years shows the most landslides are located in high and moderate susceptibility areas, and the group landslides are located in high susceptibility areas. There are two regions with severest landslide hazard: one is south of Ningxia Province with adjacent Baiyin Prefecture of Gansu Province; the other is Tianshui Prefecture of Gansu Province. The moderate landslide hazard areas include: the areas around the above areas from east Pingliang Prefecture to Lanzhou City; Fen-Wei graben and its around areas. The other areas have low landslide susceptibility, especially Erdos block is the stablest area.
引文
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[2] TaylorDW.FundamentalsofSoilMechanics[M].NewYork:Wiley,1948.
[3] KoppulaSD.Pseudo staticanalysisofclayslopessubjectedtoearthquakes[J].Geotechnique,1984,34(1),71-79.
[4] WilsonR,EieczorekG,HarpE.Developmentofcriteriaforregionalmappingofseismicslopestability[J].GeologicalSocietyofAmerica,AbstractswithPrograms,1979,11(3):37～38.
[5] JibsonRW,ELHarp,JAMichael.Amethodforproducingdigitalprobabilisticseismiclandslidehazardmaps[J].EngineeringGeology,2000,58(3-4):271-289.
[6] LuziL,FPergalani.ApplicationsofstatisticalandGIStechniquestoslopeinstabilityzonation(1∶50000Fabrianogeologicalmapsheet)[J].SoilDynamicsandEarthquakeEngineering,1996,15(2):83-94.
[7] ReficeA,DCapolongo.Probabilisticmodelingofuncertaintiesinearthquake inducedlandslidehazardassessment[J].Computers＆Geosciences,2002,28(6):735-749.
[8] MilesSB,CLHo.RigorouslandslidehazardzonationusingNewmark′smethodandstochasticgroundmotionsimulation[J].SoilDynamicsandEarthquakeEngineering,1999,18(4):305-323.
[9] TechnicalCommitteeforEarthquakeGeotechnicalEngineering,ISSMGE.ManualforZonationonSeismicGeotechnicalHazards[M].Tokyo:TheJapaneseGeotechnicalSociety,1999.
[10]GuptaRP,BCJoshi.LandslidehazardzoningusingtheGISapproach—acasestudyfromtheRamgangaCatchment,Himalayas[J].EngineeringGeology,1990,28(2):119-131.
[11]DaiFC,CFLee.LandslidecharacteristicsandslopeinstabilitymodelingusingGIS,LantauIsland,HongKong[J].Geomorphology,2002,42(3-4):213-228.
[12]ClericiA,SPerego,CTellini.Aprocedureforlandslidesusceptibilityzonationbytheconditionalanalysismethod[J].Geomorphology,2002,48(4):349-364.
[13]BarredoJI,ABenavides.ComparingheuristiclandslidehazardassessmenttechniquesusingGISintheTirajanabasin,GranCanariaIsland,Spain[J].InternationalJournalofAppliedEarthobservationandGeoinformation,2000,2(1):9-23.
[14]Esmali,HAhmadi.UsingGIS＆RSinmassmovementshazardzonation—acasestudyinGermichayWatershed,Ardebil,Iran[A].MapIndiaConference2003[C].2003.(http://www.gisdevelopment.net/application/natural＿hazards/landslides/mi03128.htm).
[15]中华人民共和国国家标准.中国地震动参数区划图(GB18306-2001)[S].北京:国家质量技术监督局,2001.
[16]SaatyT.Theanalyticalhierarchyprocess[M].NewYork:McGrawHill,1980.
[17]王兰民,袁中夏,石玉成,等.黄土地震灾害区划指标与方法研究[J].自然灾害学报,1999,8(3),87～92.
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