INTERPRETATION OF GROUNDWATER CHEMISTRY DATA USING MULTIVARIATE STATISTICAL TECHNIQUES

Hydrogeologists in general and hydrogeochemists in particular are commonly asked to collect and interpret groundwater chemistry data for determining the groundwater quality at a particular site. More often, this involves graphical representation of data and a comparison with the drinking water quality standards. However, public laws and regulations require rigorous and a comprehensive quantitative approach, including statistical analysis to interpret the groundwater chemistry data. The analysis might be helpful in identifying the contaminated sites. A total of 19 groundwater samples were collected from Wadi Bani Malik located 40 km to the east of Jeddah, Saudi Arabia. The area once known to be a dumping ground for untreated waste has now been partially remediated. To establish that the higher concentration of salts found in the Wadi is due to the sewage dumping, the data were compared with an adjacent Wadi Madsus that was not known to have any history of dumping. A distribution-free method of multivariate data analysis was employed to compare the variation in species abundance and composition among sampling sites. Principal Coordinate Analysis indicates that some of the wells in both the wadis have same compositional trend and also some samples overlap within the same area. Analysis of similarity (ANOSIM) using R package vegan software indicates a strong correlation (R = 0.82) between Wadi Bani Malik and Wadi Madsus. The P factor calculated while performing the analysis suggests that sewage dumping significantly contaminated (P = 0.001) the groundwater quality of the Bani Malik area.