Assessing surface water quality in the Birim North district of Ghana using spatial modelling

Abstract

Surface water quality considerations are becoming increasingly important in Ghana due to anthropogenic activities which affect their benefits to humans and aquatic life but studies on spatial modelling to assess surface water quality in Ghana are nascent. This study explores surface water quality in the Birim North District of Ghana using spatial modelling. Using a cross-sectional study design, 540 surface water samples were collected from 15 rivers and streams in 2018. Surface water quality was studied through 31 indicators. Landsat satellite images (2019) of the study area was analysed for environmental and NDVI data. The data was fitted to Pearson’s product moment correlation, principal component analysis (PCA) and linear regression. The correlation coefficient (r) among selected water properties showed a number of strong associations. PCA output showed the data is a six-component system that explains 78.2% of the total variance in the data. The major indicators of water quality in the study area are DO, calcium, manganese, magnesium, phosphate, iron, arsenic, copper and BOD and account for 25.7% variance. The major sources of pollutants emanated from agriculture, mining, soluble rocks/soil and sewage. The quality of the water was better during the dry season compared to the wet season. The magnitude of independent variables in increasing order of predicting WQI was: Buffer, Cultivated area, Built-up, Forest, Rivers and streams cluster, Elevation, Season. The results inform that management interventions for surface water ecosystems should be targeted temporally and spatially to the key areas which are necessary from both practical and economic perspectives.