Spatial and Temporal Variations in Water Quality Along the Bua River, Malawi

Water quality in freshwaters are declining worldwide owing to increases in human populations, expansion of agricultural activities, and climate change. There are regions of the world that are understudied and little to no baseline information exists related to water quality, such as in Africa. We focused our work on the Bua River, Malawi which supports sustenance fishing and basic needs for local communities. A portion of the river has elevated levels of protection because it is found within the Nkhotakota Wildlife Reserve. We evaluated the water quality at five sites in the Bua River monthly from May 2018 to June 2020 capturing the three main seasons (warm wet, cool dry, and hot dry) to a provide baseline understanding of its water quality both longitudinally and over time and to identify possible pollution sources. Soluble reactive phosphorus (SRP) varied longitudinally with the highest values at the mouth and the lowest upstream in the Bua River, although other water quality parameters did not vary spatially. However, there were greater differences across seasons for water temperature, pH, and chlorophyll a. For example, chlorophyll a was higher during the hot dry season (3.28µgL-1) compared to the cool dry season (2.10µgL-1) and warm wet season (1.91µgL-1). Water transparency, as measured by secchi depth was lowest during the warm wet season, which coincides with higher concentrations in SRP. All measurements of salt content, Electrical Conductivity (EC), Total Dissolved Solids (TDS), and salinity) were higher during the hot dry season and correlated negatively with SRP. Similarly, bicarbonate and alkalinity were also higher during the hot dry season. Principle Component Analysis indicated that the parameters responsible for variations of Bua River water quality are mainly related to soluble minerals, water temperature, and surface runoff associated with agricultural activities and domestic waste accounting for 78.49% of the total variance in the data set