地下水污染物浓度与电阻率映射关系的构建

doi:10.7523/j.issn.2095-6134.2018.06.013

中国科学院大学学报 ›› 2018, Vol. 35 ›› Issue (6): 814-821.DOI: 10.7523/j.issn.2095-6134.2018.06.013

地下水污染物浓度与电阻率映射关系的构建

赵少桦^1,2,3, 董艳辉^1,2,3, 李学兰⁴, 王礼恒^1,2

1 中国科学院地质与地球物理研究所中国科学院页岩气与地质工程重点实验室, 北京 100029;
2 中国科学院地球科学研究院, 北京 100029;
3 中国科学院大学, 北京 100049;
4 中南大学地球科学与信息物理学院, 长沙 410083

收稿日期:2017-08-12 修回日期:2018-01-05 发布日期:2018-11-15
通讯作者: 董艳辉
基金资助:
中国科学院青年创新促进会（2016063）和北京市自然科学基金（8174077）资助

Establishment of the relationship between contamination concentration and electrical resistivity in shallow aquifer based on groundwater numerical modeling

ZHAO Shaohua^1,2,3, DONG Yanhui^1,2,3, LI Xuelan⁴, WANG Liheng^1,2

1 Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China;
2 Institutions of Earth Science, Chinese Academy of Sciences, Beijing 100029, China;
3 University of Chinese Academy of Sciences, Beijing 100049, China;
4 School of Geoscience and Info-Physics, Central South University, Changsha 410083, China

Received:2017-08-12 Revised:2018-01-05 Published:2018-11-15

摘要/Abstract

摘要： 地球物理方法中的地电方法所获取的地下含水层视电阻率如何转换为地下水中污染物的浓度分布是有待解决的问题。本研究探索基于地下水流动与溶质运移数值模型构建映射关系的方法。从构建的多个已知污染物浓度场出发，通过Archie定律建立地电模型并对其进行地球物理正演模拟来代表野外观测到的电阻率数据，而后通过反演获得视电阻率反演数据分布，最后通过分析污染物浓度与视电阻率反演数据的统计特征来建立映射关系。结果显示地下水浓度场和电阻率之间的映射关系可通过不同的统计方法如线性拟合、多项式拟合来建立，但在不同的模型区域映射关系有所差异，表现出空间差异性。相比于直接采用Archie公式将视电阻率转化为浓度场的方法，线性拟合或多项式拟合所建立的映射关系在映射精度方面都具有明显优势。两者在多数情况中的应用效果类似，但在部分区域渗透系数较小（例如：渗透系数k=28m/d）的情况下，多项式拟合的映射关系应用效果优于线性拟合的映射关系。总体而言，本研究所构建的基于地下水模型的映射方式比直接采用Archie公式的方法更为精确，并且能获取更多的场域整体信息，可配合钻孔取样监测在地下水污染调查方面发挥作用。

关键词: 地下水污染, 溶质浓度, 电阻率, 地下水数值模拟

Abstract: Geophysical method is an important technique in groundwater contamination investigation. The geoelectrical method is capable of mapping both low and high resistivity and has been commonly used to explore concentration of contamination in groundwater. How to convert apparent resistivity of groundwater into concentration distribution of contamination in groundwater should be first considered carefully. Therefore, it is necessary to establish a relationship between electrical resistivity and contamination concentration for concentration estimation using geoelectrical information. We present a method for establishing this relationship based on groundwater numerical model. In this method, the relationship of electrical information and concentration information is obtained by comparing the contamination data from solute transport model with the electrical resistivity data from geophysical forward and inverse modeling. The results show that there is a clear relationship between the electrical resistivity and contamination concentration, which also has a spatial heterogeneity. The applications of the relationships established using linear fitting and polynomial fitting both are better than that by converting electrical resistivity data to concentration directly using Archie's law. In addition, the relationship established using polynomial fitting is better than that using linear fitting in some cases. The method proposed in this work has great potential for estimating the concentration of groundwater concentration based on geoeletrical data.

Key words: groundwater contamination, concentration, electrical resistivity, groundwater numerical simulation

中图分类号:

P631.325

赵少桦, 董艳辉, 李学兰, 王礼恒. 地下水污染物浓度与电阻率映射关系的构建[J]. 中国科学院大学学报, 2018, 35(6): 814-821.

ZHAO Shaohua, DONG Yanhui, LI Xuelan, WANG Liheng. Establishment of the relationship between contamination concentration and electrical resistivity in shallow aquifer based on groundwater numerical modeling[J]. , 2018, 35(6): 814-821.

参考文献

[1] 熊玲,鄢贵权. 浅谈我国地下水的污染现状及防治措施[J]. 贵州科学,2009,27(4):86-90.
[2] 郭永海, 王志明, 刘淑芬,等. 石家庄市地下水污染特征及其与超量开采的关系[J]. 铀矿地质, 2005, 21(2):123-127.
[3] 王爱平, 杨建青, 杨桂莲,等. 我国地下水监测现状分析与展望[J]. 水文, 2010, 30(6):53-56.
[4] 钟秋. 地下水污染调查中的地球物理方法[J]. 地下水, 2014, 36(2):57-58.
[5] 喻永祥, 吴吉春. 利用ERT数据推求非均质多孔介质渗透系数初探[J]. 水文地质工程地质, 2006, 33(2):41-44.
[6] 闫永利, 马晓冰, 袁国平,等. 大地电磁法在阿苏卫填埋场地下水污染检测的应用研究[J]. 地球物理学报, 2007, 50(6):1863-1868.
[7] 杨学明, 苏永军, 杜东,等. 音频大地电磁法在海水入侵动态监测中的应用[J]. 物探与化探, 2013, 37(2):301-305.
[8] Singha K, Moysey S. Accounting for spatially variable resolution in electrical resistivity tomography through field-scale rock-physics relations[J]. Geophysics, 2006, 71(4):A25.
[9] Singha K, Gorelick S M. Hydrogeophysical tracking of three-dimensional tracer migration:the concept and application of apparent petrophysical relations[J]. Water Resources Research, 2006, 42(6):253-263.
[10] Koestel J, Kemna A, Javaux M, et al. Quantitative imaging of solute transport in an unsaturated and undisturbed soil monolith with 3-D ERT and TDR[J]. Water Resources Research, 2008, 44(12):1-17.
[11] Pollock D, Cirpka O A. Temporal moments in geoelectrical monitoring of salt tracer experiments[J]. Water Resources Research, 2008, 44(12):723-729.
[12] Wehrer M, Slater L D. Characterization of water content dynamics and tracer breakthrough by 3-D electrical resistivity tomography (ERT) under transient unsaturated conditions[J]. Water Resources Research, 2015, 51(1):97-124.
[13] 李国山, 周启友, 刘汉乐,等. 高密度电阻率成像法监测静水中溶质运移过程[J]. 工程勘察, 2008(10):72-75.
[14] 张嘉, 王明玉. 非均质渗透介质纵向弥散度数值模拟估算法适宜性探析[J]. 中国科学院研究生院学报, 2011, 28(1):35-42.
[15] 薛禹群. 地下水数值模拟[M]. 北京:科学出版社, 2007.
[16] Harbaugh A W. MODFLOW-2005, the US Geological survey modular ground-water model:the ground-water flow process[M]. Reston:US Department of the Interior, US Geological Survey, 2005.
[17] Ma R, Zheng C M. Effects of density and viscosity in modeling heat as a groundwater tracer[J]. Groundwater, 2010, 48(3):380-389.
[18] 施庆国. 高密度电阻率法二维和三维有限差分正演计算[D]. 长春:吉林大学, 2012.

地下水污染物浓度与电阻率映射关系的构建

Establishment of the relationship between contamination concentration and electrical resistivity in shallow aquifer based on groundwater numerical modeling

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