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Using Multivariate Analysis to Predict the Behaviour of Soils Under Effluent Irrigation

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Abstract

Onsite wastewater treatment systems aim to assimilate domestic effluent into the environment. Unfortunately failure of such systems is common and inadequate effluent treatment can have serious environmental implications. The capacity of a particular soil to treat wastewater will change over time. The physical properties influence the rate of effluent movement through the soil and its chemical properties dictate the ability to renovate effluent. A research project was undertaken to determine the role that physical and chemical soil properties play in predicting the long-term behaviour of soil under effluent irrigation and to determine if they have a potential function as early indicators of adverse effects of effluent irrigation on treatment sustainability. Principal Component Analysis (PCA) and Cluster Analysis grouped the soils independently of their soil classifications and allowed us to distinguish the most suitable soils for sustainable long term effluent irrigation and determine the most influential soil parameters to characterise them. Multivariate analysis allowed a clear distinction between soils based on the cation exchange capacities. This in turn correlated well with the soil mineralogy. Mixed mineralogy soils in particular sodium or magnesium dominant soils are the most susceptible to dispersion under effluent irrigation. The soil Exchangeable Sodium Percentage (ESP) was identified as a crucial parameter and was highly correlated with percentage clay, electrical conductivity, exchangeable sodium, exchangeable magnesium and low Ca:Mg ratios (less than 0.5).

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Abbreviations

AS/NZS:

australian standard/new zealand standard

CCR:

clay activity ratio

CEC:

cation exchange capacity

EC:

electrical conductivity

ECEC:

effective cation exchange capacity

ESC exchangeable sodium content; ESI:

electrochemical stability index

ESP:

exchangeable sodium percentage

FCA:

fuzzy cluster analysis

PCA:

principal component analysis

SAR:

sodium adsorption ratio

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  1. School of Urban Development, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, Australia, 4001

    Les Dawes & Ashantha Goonetilleke

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  1. Les Dawes
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  2. Ashantha Goonetilleke
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Correspondence to Les Dawes.

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Dawes, L., Goonetilleke, A. Using Multivariate Analysis to Predict the Behaviour of Soils Under Effluent Irrigation. Water Air Soil Pollut 172, 109–127 (2006). https://doi.org/10.1007/s11270-005-9064-z

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