2013-2019年陕北矿区饮用水源地水质特征及驱动因素
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X824

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国家自然科学基金项目“陕北窟野河流域煤炭开采对河流生态健康的影响机理研究”(51969031);陕西省重点研发计划项目(2020SF-412,2020SF-409);西北旱区生态水利国家重点实验室开放基金项目(2019KFKT-13);榆林市科技局项目(2019-101-2)


Water Quality Characteristics and Driving Factors of Drinking Water Source in Northern Shaanxi Mining Area During 2013-2019
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    摘要:

    [目的] 分析陕北矿区饮用水源地尤家峁水库的水质变化特征和驱动因素,为中国同类地区饮用水的保护和处理提供技术依据。[方法] 于2013-2019年对榆林市饮用水源地尤家峁水库水质进行连续监测,获取了20项水质指标数据,并采用主成分分析法(PCA)和PCA-熵值结合法对监测数据进行分析。[结果] ①浑浊度、色度、锰含量是影响尤家峁水库水质的主要驱动因子,高锰酸盐指数、氨氮次之。水质净化的首要任务是除锰。②尤家峁水库2014年水质最差,2015,2016年水质较好;年内冬季水质最好,夏季最差,与降水量、气温变化有明显的相关性。③ PCA是一种切实可行的水质主要驱动因子识别方法,与PCA-熵值结合法的计算结果基本一致。[结论] 锰污染是尤家峁水库水质恶化的主导因素,夏季锰浓度明显升高,应相应调整水处理工艺或增大药剂投加量,以满足民生饮水安全。

    Abstract:

    [Objective] The water quality change characteristics and driving factors of Youjiamao reservoir, which is a drinking water source of mining area in Northern Shaanxi Province were analyzed to provide a technical support for the protection and treatment of drinking water in similar areas.[Methods] The water quality of Youjiamao reservoir was continuously monitored from 2013 to 2019, and 20 water quality indicators were obtained. The principal component analysis (PCA) and PCA-entropy method were used to analyze the monitoring data.[Results] ① Turbidity, chroma, manganese were the main driving factors of water quality in Youjiamao reservoir, followed by permanganate index and ammonia nitrogen. The primary task of water purification was to remove manganese. ② The water quality of Youjiamao reservoir was the worst in 2014, and was better in 2015 and 2016. Water quality was the best in winter and the worst in summer, which had obvious correlation with the precipitation and temperature. ③ PCA was a feasible method to identify the main driving factors of water quality, which was basically consistent with the calculation result of PCA-entropy method.[Conclusion] Manganese pollution is the key factor for the deterioration of water quality in Youjiamao reservoir, and the manganese concentration is significantly higher in summer. Therefore, water treatment technology should be adjusted or chemicals dosage should be increased to meet the drinking water safety.

    参考文献
    [1] 吴喜军,李怀恩,董颖,等.陕北地区煤炭开采等人类活动对河道径流影响的定量识别[J].环境科学学报,2014,34(3):772-780.
    [2] 王小军,贺瑞敏,宋晓猛,等.榆林能源化工基地供水水源问题分析[J].地下水,2014,36(6):139-142.
    [3] Wu Xijun, Dong Ying. River runoff influence factors recognition using the stepwise regression analysis:A case of Northern China coal mining area[J]. Polish Journal of Environmental Studies, 2020,29(1):893-900.
    [4] Liu Jing, LiuYongjun, Zhang Aining, et al. Spatial distribution, source identification, and potential risk assessment of toxic contaminants in surface waters from Yulin, China[J]. Environmental Monitoring and Assessment, 2019,191(5):191-293.
    [5] 张涵,李奇翎,郭珊珊,等.成都平原典型区地下水污染时空异质性及污染源分析[J].环境科学学报,2019,39(10):3516-3527.
    [6] 孙悦,李再兴,张艺冉,等.雄安新区-白洋淀冰封期水体污染特征及水质评价[J].湖泊科学,2020,32(4):952-963.
    [7] 项颂,庞燕,侯泽英,等.基于熵值法的云南高原浅水湖泊水生态健康评价[J].环境科学研究,2020,33(10):2272-2282.
    [8] 张继宇,王国重,李中原,等.熵值密切值法在陆浑水库营养状况评估中的应用[J].水资源与水工程学报,2019,30(4):119-123.
    [9] 龚清莲,刘颖,汤冰冰.长江宜宾段水质时空分布特性分析[J].环境科学与技术,2016,39(3):111-116.
    [10] 李国华,李畅游,史小红,等.基于主成分分析及水质标识指数法的黄河托克托段水质评价[J].水土保持通报,2018,38(6):310-314.
    [11] 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.
    [12] Zhang Bing, Song Xianfang, Zhang Yinghua, et al. Hydrochemical characteristics and water quality assessment of surface water and groundwater in Songnen Plain, Northeast China[J]. Water Research, 2012,46(8):2737-2748.
    [13] Liu Jing, Hang Xiaoshuai, Liang Bin, et al. Characteristics of spatial and temporal variation of water quality of sensitive waters in Taihu Lake[J]. Journal of Ecology and Rural Environment, 2012, 28(6):628-632.
    [14] 樊庆锌,杨先兴,邱微.松花江哈尔滨段城市水环境质量评价[J].中国环境科学,2014,34(9):2292-2298.
    [15] 杨学福,王蕾,关建玲,等.基于多元统计分析的渭河西咸段水质评价[J].环境工程学报,2016,10(3):1560-1565.
    [16] Heller D, Ter Veen R, Hagenhoff B, et al. Hidden information in principal component analysis of ToF-SIMS data:On the use of correlation loadings for the identification of significant signals and structure elucidation[J]. Surface and Interface Analysis, 2017,49(10):1028-1038.
    [17] 朱文侠,姜在炳,赵格兰,等.基于主成分分析法和熵值法的煤层气开采剩余资源量评价[J].煤矿安全,2019,50(5):162-167.
    [18] Ou Weijian, Fang Xinyan. Assessment of black-start modes based on entropy value method and principal component analysis[J]. Power System Protection & Control, 2014,42(8):22-27.
    [19] 张清华,韦永著,曹建华,等.柳江流域饮用水源地重金属污染与健康风险评价[J].环境科学,2018,39(4):1598-1607.
    [20] 董颖,李乐,武宏梅,等.基于水源地水质变化的KMnO4预氧化技术应用研究[J].给水排水,2020,46(9):60-64.
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董颖,吴喜军,李怀恩,张亚宁,武宏梅,刘静,张范平.2013-2019年陕北矿区饮用水源地水质特征及驱动因素[J].水土保持通报,2021,41(1):284-289

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  • 收稿日期:2020-10-18
  • 最后修改日期:2020-12-21
  • 在线发布日期: 2021-03-16