We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Spatio-Temporal Water Quality Assessment and Pollution Source Apportionment of Lake Chamo using Water Quality Index and Multivariate Statistical Techniques
Summary
This study assessed water quality and pollution sources in Lake Chamo in Ethiopia using a water quality index and multivariate statistics, finding deteriorating conditions linked to agricultural runoff, urban wastewater, and other anthropogenic inputs, and identifying spatial hotspots for targeted pollution management.
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.
Sign in to start a discussion.
More Papers Like This
Assessing water quality in North-East Algeria: a comprehensive study using water quality index (WQI) and PCA
Researchers assessed water quality across multiple drinking water sources in North-East Algeria using a water quality index and principal component analysis. The study provides a comprehensive evaluation of contamination levels in the Cheffia Dam, Oued El Aneb, and Treat boreholes, identifying key pollutant sources affecting these important water supplies.
Spatiotemporal Assessment of Water Quality in the Yamuna River (Delhi-NCR Stretch) Using Water Quality Index and Multivariate Statistical Analysis: A Seasonal Perspective
Researchers conducted a seasonal water quality assessment of the Yamuna River's most polluted stretch in Delhi, finding critically degraded conditions at all eight monitoring stations year-round, with peak pollution during pre-monsoon season marked by very high BOD, COD, and near-zero dissolved oxygen levels.
Impacts of anthropogenic activities on the ecology and ecosystem service delivery of Lake Ziway, Ethiopia
Researchers investigated how agricultural intensification, including heavy pesticide and fertilizer use, has degraded the ecology and ecosystem services of Lake Ziway in Ethiopia, finding that runoff-driven eutrophication and contamination are threatening fisheries, water quality, and biodiversity in this critical freshwater system.
Multivariate Analysis of Water Quality Measurements on the Danube River
This study applied multivariate statistical analysis to evaluate water quality data collected across multiple depths and cross-sections of the Danube River, identifying patterns in physical, chemical, and biological parameters. Better tools for interpreting complex environmental monitoring data support early detection of pollution including chemical contaminants that interact with microplastics.
Water Quality Assessment of Inland Waters in Cartagena de Indias – Colombia, Using Multivariate Statistics
Researchers assessed water quality in four inland water bodies in Cartagena de Indias, Colombia over the period 2008-2022, analyzing parameters including dissolved oxygen, BOD, COD, total coliforms, chlorophyll, and total phosphorus using descriptive and multivariate statistical methods to characterize long-term pollution trends in urban coastal waters.