As a prerequisite for groundwater protection and contamination control, evaluation of groundwater con- tamination risk was the extension of groundwater vulnerability assessment. Based on disaster theory and using shallow groundwater of the lower reaches of Liaohe River Plain as the study area, we built an evaluation index system and a contamination index model for groundwater contamination risks from the perspectives of intrinsic vulnerability, external stresses, and functional value. We used data acquisition technology （remote sensing） and spatial analysis technology （GIS） to calculate the value of groundwater contamination risks. The spatial distribution of hotspots was obtained by calculating G index. Results show that groundwater contamination is above a mid-level risk in most of the study area. Areas with extreme high risk account for 37.86%, areas with high risk 32.47%, areas with moderate risk 12.07%, areas with light risk 3.17%, and areas with slight risk 14.43%. Hotspots areas are mainly located in central Shenyang City, northwest of Xinmin City, Beizhen City and Liaozhong County. Coldspots are mainly in Panjin City, Yingkou City, Dashiqiao City, Dawa County and Panshan County. The results reflect the spatial distribution and mechanism of groundwater contamination risk in the study area and provide relative references for land use planning and groundwater resource protection in the lower reaches of the Liaohe River Plain.
以下辽河平原为研究对象,在DRASTIC模型基础上,结合RS技术建立了DRASTICL(DRASTIC land use type)模型。利用Arc GIS的水文分析工具对DEM影像进行子流域划分与数据提取。通过对参数进行不确定性表征,对三角模糊参数设定不同α截集,在此基础上将随机参数和模糊参数进行蒙特卡罗模拟。将不同α截集下模拟结果代入模糊模式识别模型,根据累积分布规律,选取不同百分位,从而得出不同α截集与不同百分位地下水脆弱性取值。结合Arc GIS数据可视化表达,得出不同α截集下下辽河平原浅层地下水脆弱性分布图,以此辨析下辽河平原浅层地下水不确定性与脆弱性程度。最后运用灵敏度分析辨别各参数对模拟结果的实际贡献程度。结果表明:(1)模糊模式识别模型用非线性的形式充分反映参数连续性变化对模拟结果产生的影响。(2)加入土地利用类型参数,结果更能反映人类活动影响下地下水脆弱程度。(3)不同α水平、不同百分位、与不同灵敏度系数3个层次的分析有效处理了参数不确定性问题,为制定相关政策提供更加准确的参考依据,对今后本地区的地下水环境开发利用和保护具有重要意义。
