基于主成分分析的喀斯特山区河流水质评价及水质时空特征分析:以贵州省张维河为例
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摘要
为了探求喀斯特山区河流水质状况及水质时空特征,选取贵州省平寨水库的支流张维河上的8个监测点,于2017年8月—2018年5月,对13项水质指标进行分季节监测。通过SPSS软件,利用主成分分析法,从13项指标中降维得出影响张维河水质的4个主成分,根据各主成分的方差贡献率及主成分的得分进行分析。结果表明:张维河上游主成分综合得分为-4. 158,下游得分为4. 221,上游水质总体上优于下游;全流域冬季主成分得分为2. 327,夏季得分为-0. 787,枯水期污染情况比丰水期严重;点源污染与非点源污染并存,并且以点源污染为主。
In order to explore the water quality status and spatio-temporal characteristics of rivers in Karst Mountainous areas,eight monitoring points on Zhangwei River,a tributary of Pingzhai Reservoir( a Guizhou Central Water Conservancy Project),were selected for seasonal monitoring of 13 water quality indicators,from August 2017 to May 2018. Through SPSS software and principal component analysis method,four principal components affecting the water quality of Zhangwei River were selected from 13 indexes,and the variance contribution rate of each principal component and the score of principal component were analyzed. The results showed that the comprehensive score of the principal components in the upper reaches of Zhangwei River was-4. 158,and that in the lower reaches was 4. 221. The water quality in the upper reaches was better than that in the lower reaches generally; the score of the principal components in winter was 2. 327,and that in summer was-0. 787,thus the pollution situation in dry season was more serious than that in flood season; the point source pollution was the main contributor,coexisting with non-point source pollution.
In order to explore the water quality status and spatio-temporal characteristics of rivers in Karst Mountainous areas,eight monitoring points on Zhangwei River,a tributary of Pingzhai Reservoir( a Guizhou Central Water Conservancy Project),were selected for seasonal monitoring of 13 water quality indicators,from August 2017 to May 2018. Through SPSS software and principal component analysis method,four principal components affecting the water quality of Zhangwei River were selected from 13 indexes,and the variance contribution rate of each principal component and the score of principal component were analyzed. The results showed that the comprehensive score of the principal components in the upper reaches of Zhangwei River was-4. 158,and that in the lower reaches was 4. 221. The water quality in the upper reaches was better than that in the lower reaches generally; the score of the principal components in winter was 2. 327,and that in summer was-0. 787,thus the pollution situation in dry season was more serious than that in flood season; the point source pollution was the main contributor,coexisting with non-point source pollution.
引文
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[2]杜泽兵，阳文静，向丽雄，等．湖泊水质影响因素研究综述[J]．环境污染与防治，2017,39(3):120.
[3]魏乐，裴国霞，郭琦，等．不同水质评价方法在金海水库的应用[J]．湖北农业科学，2016,55(8):1974-1978.
[4] Hilary S Green,Xueqi Li,Mauro De Pra,et al. A rapid method for the detection of extra virgin olive oil adulteration using UHPLCCAD profiling of triacylglycerols and PCA[J]. Food Control,2020,107.
[5]徐光宇，柴国平，徐明德，等．主成分分析法在汾河太原城区段水质评价中的应用[J]．环境工程，2014,32(6):122-124.
[6]陆文，李北涛，郭治远，等．基于主成分分析的生活垃圾组分模型研究[J]．环境工程，2013,31(6):100-103.
[7]周忠发．基于GIS的喀斯特地区农村土地适宜性评价:以贵州省仁怀市为例[J]．贵州师范大学学报(自然科学版)，2006,24(3):17-19.
[8] Mohammad Jafarzadegan,Faramarz Safi-Esfahani,Zahra Beheshti.Combining hierarchical clustering approaches using the PCA method[J]. Expert Systems With Applications,2019,137.
[9] David Rebollo Monedero,Ahmad Mohamad Mezher,Xavier Casanova Colomé，et al. Efficient k-anonymous microaggregation of multivariate numerical data via principal component analysis[J].Information Sciences,2019,503.
[10]曹明达，周忠发，潘艳喜，等．喀斯特洞穴滴水水文化学过程的时空变化及其环境指示:以贵州织金洞为例[J]．水土保持研究，2017,24(3):339-346.
[11] Zheng Fan,Ling Yalan,Tang Yuqing,et al. A fidelity-restricted distributed principal component analysis compression algorithm for non-cable seismographs[J]. Journal of Applied Geophysics,2019,169.
[12] Zhang Zhenhua,Hu Chuangye,Zhang Yifei,et al. The combined application of principal component analysis and decision tree in nuclear pulse shape discrimination[J]. Nuclear Inst. and Methods in Physics Research,A,2019,943.
[13] Stefano Ferrari Interlenghi,JoséLuiz de Medeiros,Ofélia de Queiroz Fernandes Araújo. A lifecycle sustainability assessment of CO2emissions,energy consumption and social aspects of methylic and ethylic biodiesel using principal component analysis[J]. Materials Science Forum,2019,4919.
[14]张宜松，曹国良，张萌．基于主成分分析法的陕北地区可持续发展对比研究[J]．环境工程，2017,35(5):136-140.
[15]汪天祥，许士国，韩成伟．改进主成分分析法在南淝河水质评价中的应用[J]．水电能源科学，2012,30(10):33-36.
[16]李静，沈梦兰，王彦伟，等．基于主成分分析法的巴彦浩特镇饮用水水源地水质评价[J]．环境与发展，2018(10):125-134.
[17]葛丽颖，王海鹤，傅成诚，等．基于主成分分析的红枫湖水质分析评价[J]．环保科技，2018,24(3):21-26.
[18]冉桂花，葛继稳，苗文杰，等．三峡库区古夫河水质时空分异特征[J]．生态学报，2013,33(17):5385-5396.
[19]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.
[20]李秋娟，李仰征，王芳，等．七星关区倒天河不同河段冬季水质污染状况及原因分析[J]．贵州师范大学学报(自然科学版)，2014,32(5):38-41.
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