地球信息科学学报 ›› 2016, Vol. 18 ›› Issue (2): 238-247.doi: 10.3724/SP.J.1047.2016.00238

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下辽河平原浅层地下水脆弱性评价

孙才志(), 陈雪姣, 陈相涛   

  1. 辽宁师范大学城市与环境学院,大连 116029
  • 收稿日期:2015-07-09 修回日期:2015-09-29 出版日期:2016-02-10 发布日期:2016-02-04
  • 作者简介:

    作者简介:孙才志(1970-),男,博士后,教授,博士生导师,主要从事地下水资源评价与管理研究。E-mail: suncaizhi@lnnu.edu.cn

  • 基金资助:
    教育部高等学校学科点专项科研基金项目(20122136110003)

The Assessment of Shallow Groundwater Vulnerability in the Lower Reaches of Liaohe River Plain

SUN Caizhi*(), CHEN Xuejiao, CHEN Xiangtao   

  1. College of Urban and Environmental science, Liaoning Normal University, Dalian 116029, China
  • Received:2015-07-09 Revised:2015-09-29 Online:2016-02-10 Published:2016-02-04
  • Contact: SUN Caizhi E-mail:suncaizhi@lnnu.edu.cn

摘要:

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ArcGIS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ArcGIS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。

关键词: 下辽河平原, 地下水脆弱性, 不确定性, 灵敏度系数

Abstract:

Considering the limitations of DRASTIC model and the effect of uncertainties on the groundwater resource evaluation, combining with RS technology, a DRASTICL model based on fuzzy pattern recognition was established. The model was applied to assess the groundwater vulnerability in the lower reaches of Liaohe River Plain. The sub-watershed information was extracted by DEM using the hydrologic analysis tool of ArcGIS. According to the uncertainty characterization of the parameters, the stochastic and fuzzy parameters were simulated under different α-cuts of the triangular fuzzy parameters by Monte Carlo. According to the simulation under different α-cuts by the DRASTICL model based on the fuzzy pattern recognition and the cumulative distribution, the different groundwater vulnerable values under different α-cuts and percentiles were obtained. In order to analyze the groundwater uncertainty and vulnerability, the groundwater vulnerability distribution map under different α-cuts of the lower reaches of Liao River Plain was visualized by ArcGIS. Finally, the sensitivity analysis was used to identify the actual contribution of each parameter making to the simulation results. The results show that: (1) the fuzzy pattern recognition model generates a continuous vulnerability index and describes the groundwater vulnerability of contamination transit continuously from the easiest to the most difficult by the nonlinear form. (2) Adding the parameter of land use type could better reflect the groundwater vulnerability degree, which is higher in the paddy field area than in the dry land. (3) This study deals with the uncertainty issues of parameters effectively from three categories: different alpha levels, different percentiles, and different sensitivity coefficients. This article reflects the vulnerability degree of groundwater in different regions and under different possibilities and combines the subjectivity of decision makers with the objectivity of the actual hydrogeological condition for the research region, which has great significance to local groundwater development and protection.

Key words: the lower reaches of Liaohe River Plain, groundwater vulnerability, uncertainty, sensitivity coefficient