Indicators of Soil Quality in a Waste Water Amended Semi-Arid Soil.

Forty-two surface soil samples (0-0.15 m) were collected from of a field that had been cleared of native vegetation, sowed with a pasture mix and irrigated with reverse osmosis (RO) reject waste water (electrical conductivity (EC) of  2.73 dS/m) for two consecutive years and analyzed for multiple soil quality indicators (SQI). This is a preliminary study with the objective to investigate the relationships among the measured SQI through multivariate statistics, in order to reduce the number of measurements needed for soil quality evaluation. Potential SQI that were assessed included mean weight diameter of the dry aggregates (MWD), dry aggregates > 2 mm (D > 2 mm), dry aggregates < 0.25 mm (D < 0.25 mm), wet aggregate stability, permanganate oxidizable carbon (POXC), soil organic carbon (SOC), (EC), pH, sand, silt and clay contents, and chemical parameters (NO₃-N, P, Ca, Mg, Na, Zn, Fe, Mn and Cu). Statistical significant correlations were found among several SQI. The data was further subjected to exploratory factor analysis (EFA) using varimax rotation for principal component extractions. Variables that were not correlated with other variables and those that had too high correlations (>0.8) were excluded from the EFA analysis. The sampling adequacy based on Kaiser-Meyer-Olkin Measure was 0.6 and the average communality was 0.71. Results showed that a total of 71% of the variance in the data was extracted into three components. These components showed distinct structure which can be defined by the SQI measurements. The first component related mostly to soil aggregation with MWD having the highest loading of 0.95, while the second component was related to soil fertility with K having the highest loading of 0.89. The third component was mixed, comprising of soil reaction, salinity and soil biological activity, with pH having the highest loading of -0.75. This preliminary study shows that directional changes in soil quality of a waste water irrigated field can be captured by smaller sets of measurements. Further studies are needed that will include more sites and a larger number of data points.