利用主成分分析和多元线性回归建立阿比亚州阿巴地下水质量模型

Ogbonnaya Paul Kanu, E. Ugwoha, N. Udeh, Victor Amah
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引用次数: 0

摘要

本研究旨在建立阿比亚州阿巴市地下水质量模型。为了实现这一目标,研究人员在雨季和旱季从 16 个井眼中采集了 32 份水样,并在实验室中对 pH 值、电导率、总硬度、生化需氧量 5、化学需氧量、铅、镉、铬、NH3、TDS、SO4、NO3 和 PO4 进行了分析。采用主成分分析法(PCA)和多元线性回归法(MLR)提取主因子,并建立了预测阿比亚州阿巴市水质指数的模型。在旱季,水质指数可通过水质指数(WQI)模型与 pH 值、PO4、COD、SO4 和 Pb 值进行估算,调整 R2 = 0.9999999938,标准误差为 0.043868872。同时,在雨季,可使用含浊度、PO4、NO3、COD、SO4 和 Pb 的 WQI 模型估算水质指数,调整 R2 = 0.9999997469,标准误差为 0.066697494。旱季参数的单因子方差分析结果(p = 0.000 < 0.05)表明,渗滤液对地下水水质的影响很大。在雨季,单因素方差分析结果 p = 0.000 < 0.05 表明渗滤液对地下水水质有很大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling Groundwater Quality of Aba in Abia State Using Principal Component Analysis and Multiple Linear Regression
The aim of this study was to model the groundwater quality of Aba in Abia state. To achieve the aim, thirty-two water samples were taken from sixteen boreholes during the rainy and dry seasons and analysed in the laboratory for pH, Electrical Conductivity, Total Hardness, BOD5, COD, Pb, Cd, Cr, NH3, TDS, SO4, NO3 and PO4. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) were employed to extract the principal factors and develop a model for predicting water quality index for Aba, Abia State. In the dry season, water quality index could be estimated using the Water Quality Index (WQI) model with pH, PO4, COD, SO4 and Pb with Adjusted R2 = 0.999999999938 and standard error of 0.043868872. Meanwhile, in the rainy season, WQI could be estimated using the WQI model with Turbidity, PO4, NO3, COD, SO4 and Pb with Adjusted R2 = 0.999999997469 and standard error of 0.066697494. The one-way ANOVA for the parameters in the dry season with p = 0.000 < 0.05 indicated that leachate had a large effect on groundwater quality. During the rainy season, one-way ANOVA result with p = 0.000 < 0.05 asserted that leachate had a large effect on groundwater quality.
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