DNAPL场地污染通量升尺度预测的敏感性分析

宋美钰; 施小清; 康学远; 吴吉春

doi:10.19509/j.cnki.dzkq.tb20220262

DNAPL场地污染通量升尺度预测的敏感性分析

doi: 10.19509/j.cnki.dzkq.tb20220262

宋美钰^{a, b,},
施小清^{a, b, ,},
康学远^{a, b},
吴吉春^{a, b}

a.
南京大学地球科学与工程学院, 南京 210023
b.
南京大学表生地球化学教育部重点实验室, 南京 210023

基金项目:

国家重点研发计划项目 2018YFC1800604

国家自然科学基金项目 41977157

详细信息

作者简介:
宋美钰(1998—)，女，现正攻读水文学与水资源专业硕士学位，主要从事地下水数值模拟研究工作。E-mail: songmeiyu@smail.nju.edu.cn

通讯作者:
施小清(1979—)，男，教授，主要从事地下水流数值模拟研究工作。E-mail: shixq@nju.edu.cn

中图分类号: X141
计量
- 文章访问数: 861
- PDF下载量: 28
- 被引次数: 0
出版历程
- 收稿日期: 2022-06-07

Sensitivity analysis of upscaling prediction of the mass flux at DNAPL contaminated sites

Song Meiyu^{a, b
,},
Shi Xiaoqing^{a, b
, ,},
Kang Xueyuan^{a, b},
Wu Jichun^{a, b}

a.
School of Earth Science and Engineering, Nanjing University, Nanjing 210023, China
b.
Key Laboratory of Surficial Geochemistry of Ministry of Education, Nanjing University, Nanjing 210023, China

摘要

摘要:
重非水相液体(DNAPL)污染问题日益严重。为评估DNAPL污染场地的环境风险, 常采用升尺度模型推估DNAPL污染源区溶解相的质量通量(溶解通量)。由于升尺度模型中的参数较多, 调查成本较高, 因此需筛选模型中的关键参数, 指导实际污染场地设计合理的观测数据采集方案。首先对升尺度模型中6个参数(地下水平均流速q、标准化浓度C₀/C^eq、离散状DNAPL质量比例GF₀、初始时刻离散状DNAPL贡献的通量比例f_g、拟合参数β₁及β₂)开展全局敏感性分析, 识别其中关键参数, 进而采用局部敏感性分析定量化关键参数的变化对通量预测的影响。研究结果表明, 参数q、C₀/C^eq、GF₀和f_g对通量预测有较大影响。q和C₀/C^eq在整个衰减过程中敏感性均相对较高, GF₀和f_g随着衰减过程的进行, 敏感性不断增高, 分别在衰减中后期和后期达到峰值; 对于不同结构的污染源区, q或C₀/C^eq增大时, 通量的增幅基本不变。随着污染源区中离散状DNAPL和池状DNAPL间的质量比例(GTP)增大, GF₀或f_g增大时, 其对通量预测的影响不断增大或减小。因此在预测溶解通量时需将调查成本重点应用于q和C₀/C^eq; 在合理设计污染源区修复方案时, 应重点调查GF₀; 在预测污染源区寿命时, f_g为重要调查对象; 对于所有结构的污染源区, q和C₀/C^eq均为重要调查对象, 对于GTP较大的污染源区, 应将调查成本重点应用于GF₀, 对于GTP较小的污染源区, 应重点调查f_g。
- 重非水相液体 /
- 溶解通量 /
- 升尺度模型 /
- 全局敏感性分析 /
- 局部敏感性分析
Abstract:
Dense nonaqueous phase liquid (DNAPL) contamination is a growing problem. To assess the environmental risk of DNAPL-contaminated sites, the mass flux of the dissolved phase (mass flux) in the source zone of DNAPL contamination is often extrapolated using upscaling models. Due to the large number of parameters in the upscaling model and the high cost of investigation, the key parameters in the model need to be screened to guide the design of a reasonable observation data collection scheme for actual contaminated sites. In this paper, a global sensitivity analysis was first conducted on six parameters (mean groundwater velocity q, standardized concentration C₀/C^eq, the mass ratio of ganglia GF₀, the fraction of the mass flux attributable to the ganglia dissolution f_g, and fitting parameters β₁ and β₂) in the upscaling model to identify the key parameters, and then a local sensitivity analysis was used to quantify the impact of changes in the key parameters on mass flux prediction. The results showed that the parameters q, C₀/C^eq, GF₀ and f_g had a large impact on the mass flux prediction. The sensitivities of q and C₀/C^eq were relatively high throughout the depletion process, while those of GF₀ and f_g increased continuously with the depletion process, reaching peaks in the middle and late stages of depletion, respectively. For source zones with different structures, the increase in mass flux was essentially constant when q or C₀/C^eq increased. As the ganglia-to-pool (GTP) mass ratio increased in source zones, its effect on the mass flux prediction continued to increase or decrease when GF₀ or f_g increased. Therefore, the investigation needs to focus on q and C₀/C^eq when predicting the mass flux, on GF₀ when reasonably designing the remediation plan of the source zone, and on f_g when predicting the lifetime of the source zone. For all structural source zones, q and C₀/C^eq are the most important to investigate, and the investigation cost should be focused on GF₀ for source zones with large GTP and f_g for source zones with small GTP.
- DNAPL /
- mass flux /
- upscaled model /
- global sensitivity analysis /
- local sensitivity analysis

HTML全文

图 1 污染通量的升尺度预测^[12]

Figure 1. Upscaling prediction of the mass flux

下载: 全尺寸图片幻灯片

图 2 算例渗透场(a)、饱和度(b)及污染羽(c)分布

Figure 2. Examples of infiltration field (a), saturation (b) and contamination plume (c) distribution

下载: 全尺寸图片幻灯片

图 3 Morris法敏感性分析平均结果

Figure 3. Average results of Morris method sensitivity analysis

下载: 全尺寸图片幻灯片

图 4 Morris法敏感性分析结果时变曲线

Figure 4. Time-varying curves of the results obtained from the Morris method sensitivity analysis

下载: 全尺寸图片幻灯片

图 5 Sobol法敏感性分析结果

Figure 5. Results of Sobol method sensitivity analysis

下载: 全尺寸图片幻灯片

图 6 参数q变化时(a)以及参数C₀/C^eq变化时(b)通量的95%置信区间

Figure 6. 95% confidence interval of the mass flux with changes in q (a), and with changes in C₀/C^eq (b)

下载: 全尺寸图片幻灯片

图 7 参数GF₀变化时(a)以及参数f_g变化时(b)通量的95%置信区间

Figure 7. 95% confidence interval of the mass fluxwith changes in GF₀ (a), and with changes in f_g (b)

下载: 全尺寸图片幻灯片

图 8 参数增加5%时通量的平均增幅

Figure 8. Average increase in flux for a 5% increase in parameters

下载: 全尺寸图片幻灯片

表 1 模型参数设置

Table 1. Setting of the model input parameters

参数	取值
研究区范围/m	50×25×15
网格尺寸/m	1×1×1
观测断面位置/m	x=50
生成参考场的地质参数
lnK_i的协方差函数	q(x, x′)=σ_{K_i}²exp(－\|x－x′\|/I²)
lnK_i的相关长度/m	I_x, I_y, I_z=18, 6.25, 1
lnK_i的方差	σ_{lnK_i}²=2.0
lnK_i的均值/ln(m·s^-1)	μ_{lnK_i}=－8.0
平均粒径/μm	295
流体性质	水	DNAPL
密度/(kg·m^-3)	1 000	1 496
黏滞性/(Pa·s)	0.001	0.000 89
DNAPL污染源区
泄露位置/m	(25, 12.5, 0.5)
DNAPL类型	三氯乙烯
DNAPL的残余饱和度	0.20
Brooks-Corey模型参数λ	2
DNAPL的总质量/kg	2 000
泄露速率/(m³·s^-1)	5×10^-20~5×10^-4
GTP	1.1~36.5
运移参数
水力梯度	0.01
孔隙度/%	30
纵向弥散度/m	0.5
横向弥散度/m	0.05
分子扩散系数/(cm²·s^-1)	1.6×10^-5

下载: 导出CSV

表 2 模型参数范围设置

Table 2. Setting of the range of model parameters

参数	参数范围	概率分布	参数选取依据
lg(C₀/C^eq)	-3.70~0	均匀分布	《地下水质量标准》Ⅳ类水标准^[35]、三氯乙烯在水中的溶解度
f_g	0.01~0.99	均匀分布	参数的物理意义^[15]
GF₀	0.01~0.99	均匀分布	参数的物理意义^[15]
lg(q)/(m·d^-1)	-2~1	均匀分布	常见的场地地下水流速范围^[36]
lg(β₁)	-1~0.48	均匀分布	Parker等的相关研究^{[15, 18, 37]}
β₂	0.1~0.5	均匀分布	Parker等的相关研究^{[15, 18, 37]}

下载: 导出CSV

参考文献(37)

[1]	邓亚平, 郑菲, 施小清, 等. 多孔介质中DNAPLs运移行为研究进展[J]. 南京大学学报: 自然科学版, 2016, 52(3): 409-420. https://www.cnki.com.cn/Article/CJFDTOTAL-NJDZ201603001.htm Deng Y P, Zheng F, Shi X Q, et al. Review on the transport of dense non-aqueous phase liquids in porous media[J]. Journal of Nanjing University : Natural Science Edition, 2016, 52(3): 409-420(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-NJDZ201603001.htm
[2]	郑菲, 高燕维, 孙媛媛, 等. 污染源区结构特征对Tween 80去除DNAPL效果的影响[J]. 中国环境科学, 2016, 36(7): 2035-2042. doi: 10.3969/j.issn.1000-6923.2016.07.019 Zheng F, Gao Y W, Sun Y Y, et al. The influence of source-zone architecture on DNAPL removal by Tween 80 flushing[J]. China Environmental Science, 2016, 36(7): 2035-2042(in Chinese with English abstract). doi: 10.3969/j.issn.1000-6923.2016.07.019
[3]	郭琼泽, 张烨, 姜蓓蕾, 等. 表面活性剂增强修复地下水中PCE的砂箱实验及模拟[J]. 中国环境科学, 2018, 38(9): 3398-3405. doi: 10.3969/j.issn.1000-6923.2018.09.025 Guo Q Z, Zhang Y, Jiang B L, et al. Experiment and numerical simulation of surfactant-enhanced aquifer remediation in PCE contaminated laboratory sandbox[J]. China Environmental Science, 2018, 38(9): 3398-3405(in Chinese with English abstract). doi: 10.3969/j.issn.1000-6923.2018.09.025
[4]	Stewart L D, Chambon J C, Widdowson M A, et al. Upscaled modeling of complex DNAPL dissolution[J]. Journal of Contaminant Hydrology, 2022, 244: 103920. doi: 10.1016/j.jconhyd.2021.103920
[5]	Koch J, Nowak W. Predicting DNAPL mass discharge and contaminated site longevity probabilities: Conceptual model and high-resolution stochastic simulation[J]. Water Resources Research, 2015, 51(2): 806-831. doi: 10.1002/2014WR015478
[6]	Zhang S, Mao G, Crittenden J, et al. Groundwater remediation from the past to the future: A bibliometric analysis[J]. WaterResearch, 2017, 119: 114-125.
[7]	Zhu J, Sykes J F. Simple screening models of NAPL dissolution in the subsurface[J]. Journal of Contaminant Hydrology, 2004, 72(1/4): 245-258.
[8]	Parker J C, Park E. Modeling field-scale dense nonaqueous phase liquid dissolution kinetics in heterogeneous aquifers[J]. Water Resources Research, 2004, 40(5): 147-158.
[9]	Falta R W, Rao P S, Basu N. Assessing the impacts of partial mass depletion in DNAPL source zones: I. Analytical modeling of source strength functions and plume response[J]. Journal of Contaminant Hydrology, 2005, 78(4): 259-280. doi: 10.1016/j.jconhyd.2005.05.010
[10]	Zhang Z, Brusseau M L. Nonideal transport of reactive solutes in heterogeneous porous media: 5. Simulating regional-scale behavior of a trichloroethene plume during pump-and-treat remediation[J]. Water Resources Research, 1999, 35(10): 2921-2935. doi: 10.1029/1999WR900162
[11]	Karaoglu A G, Copty N K, Akyol N H, et al. Experiments and sensitivity coefficients analysis for multiphase flow model calibration of enhanced DNAPL dissolution[J]. Journal of Contaminant Hydrology, 2019, 225: 103515. doi: 10.1016/j.jconhyd.2019.103515
[12]	Kueper B H, Frind E O. Two-phase flow in heterogeneous porous media: 1. Model development[J]. Water Resources Research, 1991, 27(6): 1049-1057. doi: 10.1029/91WR00266
[13]	郭芷琳, 马瑞, 张勇, 等. 地下水污染物在高度非均质介质中的迁移过程: 机理与数值模拟综述[J]. 中国科学: 地球科学, 2021, 51(11): 1817-1836. https://www.cnki.com.cn/Article/CJFDTOTAL-JDXK202111001.htm Guo Z L, Ma R, Zhang Y, et al. Contaminant transport in heterogeneous aquifers: A critical review of mechanisms and numerical methods of non-Fickian dispersion[J]. Science China: Earth Sciences, 2021, 51(11): 1817-1836(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-JDXK202111001.htm
[14]	薛佩佩, 文章, 梁杏. 地质统计学在含水层参数空间变异研究中的应用进展与发展趋势[J]. 地质科技通报, 2022, 41(1): 209-222. doi: 10.19509/j.cnki.dzkq.2022.0015 Xue P P, Wen Z, Liang X. Application and development trend of geostatistics in the research of spatial variation of aquifer parameters[J]. Bulletin of Geological Science and Technology, 2022, 41(1): 209-222(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2022.0015
[15]	Christ J A, Ramsburg C A, Pennell K D, et al. Predicting DNAPL mass discharge from pool-dominated source zones[J]. Journal of contaminant hydrology, 2010, 114(1/4): 18-34.
[16]	Kokkinaki A, Werth C J, Sleep B E. Comparison of upscaled models for multistage mass discharge from DNAPL source zones[J]. Water Resources Research, 2014, 50(4): 3187-3205. doi: 10.1002/2013WR014663
[17]	Guo Z, Russo A E, DiFilippo E L, et al. Mathematical modeling of organic liquid dissolution in heterogeneous source zones[J]. Journal of Contaminant Hydrology, 2020, 235: 103716. doi: 10.1016/j.jconhyd.2020.103716
[18]	宋美钰, 施小清, 马春龙, 等. 复杂DNAPL污染源区溶解相污染通量的升尺度计算[J]. 中国环境科学, 2022, 42(5): 2095-2104. doi: 10.3969/j.issn.1000-6923.2022.05.013 Song M Y, Shi X Q, Ma C L, et al. Upscaling dissolved phase mass flux for complex DNAPL source zones[J]. China Environmental Science, 2022, 42(5): 2095-2104(in Chinese with English abstract). doi: 10.3969/j.issn.1000-6923.2022.05.013
[19]	Li K B, Abriola L M. A multistage multicriteria spatial sampling strategy for estimating contaminant mass discharge and its uncertainty[J]. Water Resources Research, 2009, 45: W06407.
[20]	Kang X, Shi X, Deng Y, et al. Coupled hydrogeophysical inversion of DNAPL source zone architecture and permeability fieldin a 3D heterogeneous sandbox by assimilation time-lapse cross-borehole electrical resistivity data via ensemble Kalman filtering[J]. Journal of Hydrology, 2018, 567: 149-164. doi: 10.1016/j.jhydrol.2018.10.019
[21]	Kang X, Kokkinaki A, Kitanidis P K, et al. Improved characterization of DNAPL source zones via sequential hydrogeophysical inversion of hydraulic-head, self-potential and partitioning tracer data[J]. Water Resources Research, 2020, 56(8): e2020WR027627.
[22]	束龙仓, 王茂枚, 刘瑞国, 等. 地下水数值模拟中的参数灵敏度分析[J]. 河海大学学报: 自然科学版, 2007, 35(5): 491-494. https://www.cnki.com.cn/Article/CJFDTOTAL-HHDX200705002.htm Shu L C, Wang M M, Liu R G, et al. Sensitivity analysis of parameters in numerical simulation of groundwater[J]. Journal of Hohai University: Natural Science Edition, 2007, 35(5): 491-494(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-HHDX200705002.htm
[23]	郑菲, 施小清, 吴吉春, 等. 苏北盆地盐城组咸水层CO₂地质封存泄漏风险的全局敏感性分析[J]. 高校地质学报, 2012, 18(2): 232-238. doi: 10.3969/j.issn.1006-7493.2012.02.005 Zheng F, Shi X Q, Wu J C, et al. Global sensitivity analysis of leakage risk for CO₂ geological sequestration in the saline aquifer of Yancheng Formation in Subei Basin[J]. Geological Journal of China Universities, 2012, 18(2): 232-238(in Chinese with English abstract). doi: 10.3969/j.issn.1006-7493.2012.02.005
[24]	Welter D E, White J T, Hunt R J, et al. Approaches in highly parameterized inversion: PEST++ Version 3, a Parameter ESTimation and uncertainty analysis software suite optimized for large environmental models[R]. : US Geological Survey, 2015.
[25]	Bea S A, Wainwright H, Spycher N, et al. Identifying key controls on the behavior of an acidic-U (Ⅵ) plume in the Savannah River Site using reactive transport modeling[J]. Journal of Contaminant Hydrology, 2013, 151: 34-54. doi: 10.1016/j.jconhyd.2013.04.005
[26]	Wainwright H M, Finsterlr S. Global sensitivity and data-worth analyses in iTOUGH2: User's guide[R]. : Office of Scientific and Technical Information (OSTI), 2016.
[27]	杜建雯, 施小清, 徐红霞, 等. 基于iTOUGH2的生物降解模型全局敏感性时变分析[J]. 水文地质工程地质, 2020, 47(2): 35-42. https://www.cnki.com.cn/Article/CJFDTOTAL-SWDG202002006.htm Du J W, Shi X Q, Xu H X, et al. Temporal variation of global sensitivity analysis for biodegradation model using iTOUGH2[J]. Hydrogeology & Engineering Geology, 2020, 47(2): 35-42(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SWDG202002006.htm
[28]	Saltelli A, Ratto M, Tarantola S, et al. Sensitivity analysis for chemical models[J]. Chemical Reviews, 2005, 105(7): 2811-2828. doi: 10.1021/cr040659d
[29]	Valsala R, Govindarajan S K. Co-colloidal BTEX and microbial transport in a saturated porous system: Numerical modeling and sensitivity analysis[J]. Transport in Porous Media, 2019, 127(2): 269-294. doi: 10.1007/s11242-018-1191-2
[30]	孙飞飞, 许钦, 任立良, 等. 水文模型参数敏感性分析概述[J]. 中国农村水利水电, 2014(3): 92-95. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNSD201403027.htm Sun F F, Xu Q, Ren L L, et al. An analysis of the parameters sensitivity of hydrological model[J]. China Academic Journal Electronic Publishing House, 2014(3): 92-95(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-ZNSD201403027.htm
[31]	王上上, 陈富, 李东贤, 等. 锚杆不确定性对加固边坡失稳概率的影响[J]. 地质科技通报, 2022, 41(2): 282-289. doi: 10.19509/j.cnki.dzkq.2022.0055 Wang S S, Chen F, Li D X, et al. Influence of anchor uncertainty on the failure probability of reinforced slope[J]. Bulletin of Geological Science and Technology, 2022, 41(2): 282-289(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2022.0055
[32]	Hill M C, Tiedeman C R. Effective groundwater model calibration: With analysis of data, sensitivities, predictions, and uncertainty[M]. New York: John Wiley & Sons, 2006.
[33]	McKay M D. Evaluating prediction uncertainty[R]. : Nuclear Regulatory Commission, 1995.
[34]	Rajabi M M, Ataie-Ashtiani B, Janssen H. Efficiency enhancement of optimized Latin hypercube sampling strategies: Application to Monte Carlo uncertainty analysis and meta-modeling[J]. Advances in Water Resources, 2015, 76: 127-139. doi: 10.1016/j.advwatres.2014.12.008
[35]	地下水质量标准: GB14848-2017[S]. 北京: 中国标准出版社, 2017. Quality standard in groundwater: GB14848-2017[S]. Beijing: Standards Press of China, 2017.
[36]	于青春, 万力, 靳孟贵, 等. 水文地质学基础[M]. 北京: 地质出版社, 2011. Yu Q C, Wan L, Jin M G, et al. Foundation of hydrogeology[M]. Beijing: Geological Publishing House, 2011(in Chinese).
[37]	Park E, Parker J C. Evaluation of an upscaled model for DNAPL dissolution kinetics in heterogeneous aquifers[J]. Advances in Water Resources, 2005, 28(12): 1280-1291.

施引文献

资源附件(0)

访问统计

点击查看大图

图(8) / 表(2)

计量

文章访问数: 861
PDF下载量: 28
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

DNAPL场地污染通量升尺度预测的敏感性分析

doi: 10.19509/j.cnki.dzkq.tb20220262

作者简介:
宋美钰(1998—)，女，现正攻读水文学与水资源专业硕士学位，主要从事地下水数值模拟研究工作。E-mail: songmeiyu@smail.nju.edu.cn

通讯作者:
施小清(1979—)，男，教授，主要从事地下水流数值模拟研究工作。E-mail: shixq@nju.edu.cn

计量

Sensitivity analysis of upscaling prediction of the mass flux at DNAPL contaminated sites

计量

目录

留言板

DNAPL场地污染通量升尺度预测的敏感性分析

doi: 10.19509/j.cnki.dzkq.tb20220262

作者简介: 宋美钰(1998—)，女，现正攻读水文学与水资源专业硕士学位，主要从事地下水数值模拟研究工作。E-mail: songmeiyu@smail.nju.edu.cn

通讯作者: 施小清(1979—)，男，教授，主要从事地下水流数值模拟研究工作。E-mail: shixq@nju.edu.cn

计量

出版历程

Sensitivity analysis of upscaling prediction of the mass flux at DNAPL contaminated sites

计量

出版历程

目录

作者简介:
宋美钰(1998—)，女，现正攻读水文学与水资源专业硕士学位，主要从事地下水数值模拟研究工作。E-mail: songmeiyu@smail.nju.edu.cn

通讯作者:
施小清(1979—)，男，教授，主要从事地下水流数值模拟研究工作。E-mail: shixq@nju.edu.cn