基于Python的因子分析在水质自动监测数据评价中的应用

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中图分类号 X824 文献标识码 A 文章编号 1007-7731（2025）14-0074-06

DOI号 10.16377/j.cnki.issn1007-7731.2025.14.016

Application of factor analysisbased on Python in the evaluationof automatic waterqualitymonitoringdata

NIE Huijun 1，2，3. KONG Yu1，2.3 CAI Ying1，2，3 ZHU Xiaoxiao1，2，3 ZHANG Miao1，2.3 ZHANG Xuejiao 1，2，3 WU Tianqi 1，2，3

Jiangsu Environmental Engineering Technology Co.，Ltd.，Nanjing 21Oo19，China; ²Jiangsu Environmental Protection Group Co.，Ltd.， Nanjing 21OO36， China; 3Jiangsu Province Engineering Research Centerof Synergistic Control ofPolution and Carbon Emissions in Key Industries，Nanjing 210019，China）

AbstractTo enhance the utilization efficiency of automatic water quality monitoring data，accurate identify key factorsof waterpolution，thePythonand factoranalysis were employed toconductanin-depthanalysis ofcontinuous monitoring data from2O21 to 2O23 ataprovincial monitoring station in Jiangsu Province.Theresearch results indicate that the three extracted principal factors retainandexplain the original evaluation indicators with a cumulative variance contribution rate of 64.29% . Total phosphorus （TP）， permanganate index （COD ）， turbidity （Tur），and ammonia nitrogen Mn （NH 3 -N） are theassociated indicatorsof the firstprincipal factor （F1），playinga crucial rolein explaining the characteristicsof water qualityvariationsinthestudiedarea.The waterqualityatthestudiedsectionexhibited significant fluctuations，with exceedance periods mainlyconcentrated inFebruary to March（winter-spring）and around July （flood season），showing clear seasonal characteristics of exceedance.Factor analysiscan cover indicators that may be limited bysingle-factor evaluation methods，such asconductivity （EC），Tur，andtotal nitrogen （TN），demonstrating significant advantages in comprehensively assessing water quality，describing water quality fluctuation pattrns， polution levels，and polution duration.This research provides areference for precise water qualitymonitoring and water ecological environment protection.

KeywordsPython;factor analysis; automatic monitoringdata; water quality evaluation; factor scores

近年来，生态环境监测领域取得了显著进展，特别是地表水环境质量监测网得到了全面升级，已建成1837座水质自动监测国控站[1，同时各省市及地方配备了相应数量的省控站和地方站，形成了覆盖广泛、功能完善的监测网络。（剩余8472字）