长白山源头区地下水质评价及监测指标优化

谷志琪; 卞建民; 王宇; 马丽欣; 孙晓庆; 阮冬梅

PDF(1057 KB)

中国环境科学 ›› 2023, Vol. 43 ›› Issue (10) : 5257-5264.

水污染与控制

长白山源头区地下水质评价及监测指标优化

谷志琪¹, 卞建民¹, 王宇¹, 马丽欣², 孙晓庆¹, 阮冬梅¹

作者信息 +

Groundwater quality assessment and index optimization of water quality monitoring in the water source area of Changbai Mountain

GU Zhi-qi¹, BIAN Jian-min¹, WANG Yu¹, MA Li-xin², SUN Xiao-qing¹, RUAN Dong-mei¹

Author information +

文章历史 +

摘要

以长白山源头区-安图县作为研究区，分析地下水化学特征及其形成过程，基于组合熵权的云模型评估地下水质量，并利用随机森林联合多元线性回归构建水质指标优化模型，确定地下水源保障监测的关键指标.结果表明，研究区地下水水化学类型主要为HCO₃-Mg·Na·Ca型，主要受岩石风化作用影响；地下水质量评价等级为Ⅰ~Ⅲ类的样品数达到74%；最佳指标优化模型的R²和RMSE值分别为0.6333和0.726，优化指标为F^-、Na⁺、TDS、Cl^-，作为该区地下水监测的关键指标，能够有效减少监测费用，并为强化水源地安全保障提供科学依据.

Abstract

This study chose Antu County, the water source area of Changbai Mountain as the study area. the hydrochemical characteristics and formation mechanism of groundwater in the study area was analyzed. The cloud model based on entropy weight was used to evaluate the groundwater quality. Furthermore, an optimization model of water quality index was constructed by coupling random forest and stepwise multiple linear regression analysis to determine the key indicators of groundwater source security monitoring. The results showed that the primary water chemistry type of groundwater in the study area was HCO₃-Mg·Na·Ca type, which was mainly controlled by the rock weathering and dissolution effects. About 74% of groundwater samples were classified as Class Ⅰ-Ⅲ. The R² and RMSE values of the best index optimization model were 0.6333 and 0.726, respectively. F^-, Na⁺, TDS and Cl^- were identified as the key indicators of groundwater quality monitoring in the study area. This optimized water quality index can effectively reduce monitoring costs and provide scientific basis for guaranteeing the safety of water sources.

导出引用

谷志琪, 卞建民, 王宇, 马丽欣, 孙晓庆, 阮冬梅. 长白山源头区地下水质评价及监测指标优化[J]. 中国环境科学. 2023, 43(10): 5257-5264

GU Zhi-qi, BIAN Jian-min, WANG Yu, MA Li-xin, SUN Xiao-qing, RUAN Dong-mei. Groundwater quality assessment and index optimization of water quality monitoring in the water source area of Changbai Mountain[J]. China Environmental Science. 2023, 43(10): 5257-5264

中图分类号： X824

参考文献

[1] 吕琳.吉林省矿泉水区域与非矿泉水区域环境中矿物质元素含量分析[D]. 长春:吉林大学, 2015. Lu L. Research on the environmental mineral elements contents of the mineral water area and the non-mineral water area in Jilin Provinoe[D]. Changchun:Jilin University, 2015.
[2] 汪明武,周天龙,叶晖,等.基于联系云的地下水水质可拓评价模型[J]. 中国环境科学, 2018,38(8):3035-3041. Wang M W, Zhou T L, Ye H, et al. A novel extension evaluation model of groundwater quality based on connection cloud model[J]. China Environmental Science, 2018,38(8):3035-3041.
[3] 朱琴,左丽明,彭锦添,等.河北省近岸海域海水淡化取水水质适宜性分析[J]. 海洋开发与管理, 2017,34(7):60-66. Zhu Q, Zuo L M, Peng J T, et al. Analysis on optimal water quality sources for seawater desalination in Hebei Coastal Waters[J]. Ocean Development and Management, 2017,34(7):60-66.
[4] 沈强,胡俊,胡菊香.浙江省绿色水源地评价体系研究[J]. 环境工程, 2014,32(1):847-851,859. Shen Q, Hu J, Hu J X. Study on assessment system for green water-source in Zhejiang province[J]. Environmental Engineering, 2014,32(1):847-851,859.
[5] 于冰,梁国华,何斌,等.城市供水系统多水源联合调度模型及应用[J]. 水科学进展, 2015,26(6):874-884. Yu B, Liang G H, He B, et al. Modeling of joint operation for urban water-supply system with multi-water sources and its application[J]. Advances in Water Science, 2015,26(6):874-884.
[6] Yang Q, Zhang J, Hou Z, et al. Shallow groundwater quality assessment:Use of the improved Nemerow pollution index, wavelet transform and neural networks[J]. Journal of Hydroinformatics, 2017, 19(5):784-794.
[7] Wang A F, Yang X T, Gu X B. The risk assessment of rockburst intensity in the highway tunnel based on the variable fuzzy sets theory[J]. Scientific reports, 2023,13(1):4755.
[8] Gu Z Q, Bian J M, Wu J J, et al. Effects of anthropogenic activities on hydrochemical characteristics of ground water of Da'an irrigation area in Western of Jilin Province[J]. Environ Sci Pollut Res Int, 2021, 29(14):20479-20495.
[9] 刘潇,薛莹,纪毓鹏,等.基于主成分分析法的黄河口及其邻近水域水质评价[J]. 中国环境科学, 2015,35(10):3187-3192. Liu X, Xue Y, Ji Y P, et al. An assessment of water quality in the Yellow River estuary and its adjacent waters based on principal component analysis[J]. China Environmental Science, 2015,35(10):3187-3192.
[10] Jia Z, Bian J M, Wang Y, et al. Assessment and validation of groundwater vulnerability to nitrate in porous aquifers based on a DRASTIC method modified by projection pursuit dynamic clustering model[J]. Journal of Contaminant Hydrology, 2019,226:103522.
[11] 高玉琴,赖丽娟,姚敏,等.基于正态云-模糊可变耦合模型的水环境质量评价[J]. 水资源与水工程学报, 2018,29(5):1-7. Gao Y Q, Lai L J, Yao M, et al. Water environment quality assessment based on normal cloud-fuzzy variable coupling model[J]. Journal of Water Resources and Water Engineering, 2018,29(5):1-7.
[12] 李德毅,孟海军,史雪梅.隶属云和隶属云发生器[J]. 计算机研究与发展, 1995:15-20. Li D Y, Meng H J, Shi X M. Membership clouds and membership cloud generators[J]. Journal of Computer Research and Development, 1995:15-20.
[13] 姜厚竹.松花江流域省界缓冲区水质监测指标与断面优化[D]. 哈尔滨:东北林业大学, 2017. Jiang H Z. Water quality monitoring index and section optimization of provincial buffer zone in Songhua River basin[D]. Harbin:Northeast Forestry University, 2017.
[14] 曲茉莉.黑龙江水系干流监测水质指标与断面优化研究[D]. 哈尔滨:哈尔滨工业大学, 2012. Qu M L. Study on monitoring indexes and monitoring sections optimization of the main stream of Heilongjiang River[D]. Harbin:Harbin Institute of Technology, 2012.
[15] 侯佳均.北京市平谷区地下水污染监控指标优化研究[D]. 成都:成都理工大学, 2020. Hou J J. Study on optimization of groundwater pollution monitoring index in Pinggu District of Beijing[D]. Chengdu:Chengdu University of Technolog, 2020.
[16] Naghibi Seyed A K, Daneshi Alireza. Application of support vector machine, random forest, and genetic algorithm optimized random forest models in groundwater potential mapping[J]. Water Resources Management, 2017,31(9):2761-2775.
[17] Naghibi Seyed A K, Daneshi Alireza. Application of support vector machine, random forest, and genetic algorithm optimized random forest models in groundwater potential mapping[J]. Water Resources Management, 2017,31(9):2761-2775.
[18] 许力文,卞建民,孙晓庆,等.灌区退水对区域地下水质影响与健康风险评估[J/OL]. 中国环境科学:1-10[2023-02-22].DOI:10.19674/j.cnki.issn1000-6923.20221117.017. Xu L W, Bian J M, Sun X Q, et al. The influence and health risk assessment of groundwater quality in irrigated area[J/OL]. China Environmental Science:1-10[2023-02-22].DOI:10.19674/j.cnki. issn1000-6923.20221117.017.
[19] He S, W J H, Wang D, et al. Predictive modeling of groundwater nitrate pollution and evaluating its main impact factors using random forest[J]. Chemosphere, 2022,290.
[20] 杜尚海,古成科,张文静.随机森林理论及其在水文地质领域的研究进展[J]. 中国环境科学, 2022,42(9):4285-4295. Du S H, Gu C K, Zhang W J. A review on the progresses in random forests theory and its applications in hydrogeology[J]. China Environmental Science, 2022,42(9):4285-4295.
[21] Xu T T, Zheng J Q, Han S J, et al. Responses of soil nitrogen transformation to long-term nitrogen fertilization and precipitation changes in a broad-leaved Korean pine forest in Changbai Mountains, China[J]. The journal of applied ecology, 2018,29(9):2797-2807.
[22] 张文卿,王文凤,刘淑芹,等.长白山矿泉水补给径流与排泄关系[J]. 河海大学学报(自然科学版), 2019,47(2):108-113. Zhang W Q, Wang W F, Liu S Q, et al. Relationship of recharge runoff and drainage for the mineral water in the Changbai Mountain[J] Journal of Hohai University (Natural Sciences), 2019,47(2):108-113.
[23] 马于曦.安图县矿泉水水源涵养能力评估与生态红线划定[D]. 长春:吉林大学, 2021. Ma Y X. Assessment of water conservation capacity and delineation of ecological red line of mineral water in Antu County[D]. Changchun:Jilin University, 2021.
[24] Liu, Q Y, Wang M W, Zhou T L, et al. A connection cloud model coupled with extenics for water eutrophication evaluation[J]. Earth Science Informatics, 2019,12(4):659-669.
[25] 雷丽萍.基于云模型的水质评价方法优化研究[D]. 成都:南交通大学, 2019. Lei L P. Research on optimization of water quality assessment method based on cloud model[D]. Chengdu:Southwest Jiaotong University, 2019.
[26] 杨明悦,毛献忠.基于变量重要性评分-随机森林的溶解氧预测模型——以深圳湾为例[J]. 中国环境科学, 2022,42(8):3876-3881. Yang M Y, Mao X Z. Dissolved oxygen prediction model based on variable importance measures and random forest:A case study of Shenzhen Bay[J]. China Environmental Science, 2022,42(8):3876-3381.
[27] Cutler D R, Edwards Jr T C, Beard K H, et al. Random forests for classification in ecology[J]. Ecology, 2007,88(11):2783-2792.
[28] GB/T 14848-2017地下水质量标准[S]. GB/T 14848-2017 Groundwater quality standard[S].
[29] 曹玉和,齐佳伟,熊绍礼.吉林省氟中毒病区水文质地特征及防氟改水对策[J]. 中国地质, 2010:690-695. Cao Y H, Qi J W, Xiong S L. Hydrogeological characteristics of endemic fluorine disease areas of Jilin Province and water source project countermeasures for fluorine prevention[J] Geology in China, 2010:690-695.
[30] 侯炳江.基于组合赋权的水质综合评价云模型及其应用[J]. 水电能源科学, 2016,34(8):24-27. Hou B J. Water quality evaluation based on combination weight-normal cloud model and its application[J]. Water Resources and Power, 2016,34(8):24-27.
[31] 赵梦婷,黄显峰,金国裕,等. 基于改进云模型的区域水质评价研究[J]. 安徽农业大学学报, 2020,47(5):778-783. Zhao M T, Huang X F, Jin G Y, et al. Study on regional water quality evaluation based on improved cloud model[J]. Journal of Anhui Agricultural University, 2020,47(5):778-783.