首页> 外文期刊>Journal of King Saud University >Predicting hydraulic conductivity around septic tank systems using soil physico-chemical properties and determination of principal soil factors by multivariate analysis
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Predicting hydraulic conductivity around septic tank systems using soil physico-chemical properties and determination of principal soil factors by multivariate analysis

机译:利用土壤理化性质并通过多变量分析确定主要土壤因子来预测化粪池系统周围的水力传导率

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The knowledge of soil hydraulic conductivity is essential for the study of waste water infiltration rate into the soil subsurface. This study assesses selected soil hydraulic properties of soil around septic tank systems. Twelve soil samples were collected from four different locations within Ido Local Government Area, Oyo State, Nigeria. The analyzed parameters were done based on standard procedures. The measured values of soil physico-chemical properties were used to predict Ksatusing multiple linear regression analysis. The soil water content, porosity, Organic Carbon, Soil pH, bulk density, soil resistivity and saturated hydraulic conductivity (Ksat) ranged from 20.6 to 26.2%, 34.3 to 47.2%, 0.11 to 0.37%, 5.8 to 6.2, 1.40 to 1.74?g/cm3, 4.55 to 5.80?O?cm and 1.34 to 10.52?mm/hr respectively. The relationship obtained from regression analysis on data (R2?=?86.8) is a new model with empirical linear equationKsat=82.08-5.93BD-10.98RES-2.69wc-16.12O.C+9.38pHwhich allows a new relation to estimateKsatfrom the selected parameters. Principal component analysis (PCA) identified 3 major factors accounting for 92.7% of the total variation in the soil hydraulic variables. The result of Cluster Analysis (CA) shows groups based on correlation between hydraulic parameters and topographic settings.
机译:对于研究废水渗入土壤地下的速率,土壤水力传导率的知识至关重要。这项研究评估化粪池系统周围土壤的选定土壤水力特性。从尼日利亚奥约州伊多地方政府区域内的四个不同地点收集了十二个土壤样品。分析的参数是根据标准程序完成的。使用多元线性回归分析法将土壤理化性质的测量值用于预测Ksat。土壤含水量,孔隙率,有机碳,土壤pH,堆积密度,土壤电阻率和饱和水力传导率(Ksat)分别为20.6至26.2%,34.3至47.2%,0.11至0.37%,5.8至6.2、1.40至1.74? g / cm 3,分别为4.55至5.80Ω·cm 3和1.34至10.52Ω·mm / hr。通过对数据进行回归分析获得的关系(R2?=?86.8)是一个具有经验线性方程Ksat = 82.08-5.93BD-10.98RES-2.69wc-16.12O.C + 9.38pH的新模型,该模型允许通过选定的关系来估计Ksat参数。主成分分析(PCA)确定了3个主要因素,占土壤水力变量总变化的92.7%。聚类分析(CA)的结果显示了基于水力参数和地形设置之间的相关性的组。

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