Spatio-Temporal Water Quality Assessment and Pollution Source Apportionment of Lake Chamo using Water Quality Index and Multivariate Statistical Techniques

Abstract

Despite the current management effort to reduce pollution of water bodies, lakes are far more vulnerable to pollution than the ocean and rivers. Point and non-point pollution are ending on the lake bodies and concerned bodies should trigger interventions. This study aims to assess the effect of pollution on the water quality of Chamo lake using the weighted arithmetic water quality index (WQI) and multivariate statistical methods. Fifteen monitoring points are used to collect water samples from the lake for dry and rainy periods. Twenty-three physical-chemical parameters were analyzed in the water quality laboratory of Arba Minch University, out of which five parameters were analyzed using a multi-meter at the field. The physicochemical water quality analysis result of Lake Chamo revealed that the constituent’s concentration did not show significant variation spatially. The factor analysis result in the Lake Chamo revealed that it had extracted seven principal components that can be explained with a total variance of 86.3%. More than 65% of the monitoring stations in Lake Chamo have an acceptable water quality for irrigation. Moreover, some of the monitoring stations, closer to high human activities, are relatively more polluted than others. Besides, some sensitive parameters such as turbidity have clearly shown that the WQI value can be changed with the parameters changing. Based on clustering analysis, most (47%) of the monitoring are characterized by the recipients of uncontrolled public and state farm and agricultural wastes. The study recommends integrated watershed management and source-based pollution control, which could significantly decrease the pollution level in Lake Chamo after identifying the pollution hotspot areas. Continuous Lake water quality monitoring is necessary for deciding lake pollution.