Factor Analysis (Multivariate) of Ground Water Quality of Makhmor Plain/ North Iraq

INTRODUCTION

Classification of wells according to their water quality can provide useful information for the users. Complex processes control the distribution of water quality parameters in groundwater, which typically has a large range of chemical composition. The ground water quality depends not only on natural factors such as the litho logy of the aquifer, the quality of recharge water and the type of interaction between water and aquifer, but also on human activities, which can alter these groundwater systems either by polluting them or by changing the hydrological cycle.

Sophisticated data analysis techniques are required to interpret groundwater quality effectively. The univariate statistical analysis has been generally used to treat ground water quality. The simplicity of the univariate statistical analysis is obvious and likewise the fallacy of reductionism could be apparent. In order to avoid this problem, multivariate analysis was used to explain the correlation amongst a large number of variables in terms of small number of factors without losing much information. The intention underlying the use of multivariate analysis is to achieve great efficiency of data compression from the original data, and to gain some information useful in the interpretation of the environmental geochemical origin. This method can also help to indicate natural association between variables. Multivariate treatment of environmental data is widely successfully used to interpret the relationship among the variables, so that the environmental systems could be better.

Makhmor plain is an important area in Northern Iraq, well-known with agricultural activities. Irrigation with ground water in the plain had got more attention in the last years. This plain lies in south east Erbil city. It is surrounded by the upper Zab river from the north, lower Zab river from the south, Tigris river from the west and Qara Chauq Mountain from the east. It has an area of 2700 km. Many studies were conducted on the water quality of Makhmor plain. Ground water of the plain has bad quality. Sulfate is a principal component in the groundwater of Makhmor area due to high concentration in the soil and the rocks.

OBJECTIVE

This research aimed to apply multivariate statistical analysis on groundwater quality of Makhmor plain by using factor analysis to indicate natural association between variables. Also the research tries to classify the wells of the plain using cluster analysis into groups according to their water quality.

METHODOLOGY

Thirty five deep wells and 28 shallow wells lying in an area of 2700 km in Makhmor plain were included in the study. Ground water quality parameters were represented by pH, Ca^2+, Mg^2+, Na⁺, Boron, K⁺, Cl^-, SO₄^2-, CO₃^- + HCO₃^-, NO₃^-.

Factor analysis extracted two factors from the water quality parameters of the deep wells. Factor I accounted for more than 50% of the variance among water quality. Cations including Boron, Na, Mg and K with anions including Cl^-, SO₄^2- and NO₃^- were loaded significantly on it. It represented the variation in the geological formation of study area, inconsistent distribution of agricultural activities and wastewater. For shallow wells, factor analysis extracted three factors. Factor I accounted for more than the 50% of the variance in the water quality. Six of water quality parameters were loaded on factor I. These parameters included pH and cations represented by boron, Na⁺ and Mg²⁺ in addition to Cl^- and SO₄^2- as anions. Cluster analysis had divided the deep wells into three groups with 50% similarity. Cluster I included two wells with the worst water quality, while cluster II had the lowest concentrations of cations and anions in the area and includes 8 wells. Cluster III showed mid concentrations between I and II clusters. For shallow wells, three clusters were obtained with 37.5% similarity. Cluster I included 7 wells with worst water quality, while cluster II exhibited the lowest concentrations of ions. These results obtained from the multivariate analysis can be very useful for the farmers and the users of ground water in this area.

SOURCE

http://en.wikipedia.org/wiki/Factor_analysis

http://www.damascusuniversity.gov.sy/mag/eng/images/stories/19-26.pdf

SUBMITTED BY

Madhumita Das
12089
Finance Batch of 2009-11
SIBM Bangalore