Integral Application of Chemical Mass Balance and Watershed Model to Estimate Point and Nonpoint Source Pollutant Loads in Data-Scarce Little Akaki River, Ethiopia

The quality of Little Akaki River in Addis Ababa (Ethiopia) is deteriorating significantly due to uncontrolled waste released from point and diffuse sources. In this study, pollution load from these sources was quantified by integrating chemical mass balance analysis (CMB) and the watershed model of pollution load (PLOAD) for chemical oxygen demand, biochemical oxygen demand, total dissolved solid, total nitrogen, nitrate, and phosphate. Water samples monitored bimonthly at 15 main channel monitoring stations and 11-point sources were used for estimation of pollutant load using FLUX32 software in which the flow from the soil and water assessment tool (SWAT) model calibration, measured instantaneous flow, and constituent concentration were used as input. The SWAT simulated the flow quite well with a coefficient of determination (R2) of 0.78 and 0.82 and Nash-Sutcliff (NSE) of 0.76 and 0.80 during calibration and validation, respectively. The uncharacterized nonpoint source load calculated by integrating CMB and PLOAD showed that the contribution of nonpoint source prevails at the middle and downstream segments of the river. Maximum chemical oxygen demand (COD) load from uncharacterized nonpoint sources was calculated at the monitoring station located below the confluence of two rivers (near German Square). On the other hand, high organic pollution load, biochemical oxygen demand (BOD) load, was calculated at a station upstream of Aba Samuel Lake, whereas annual maximum total dissolved solid (TDS), total nitrogen (TN), and phosphate load (PO4-P) from the nonpoint source in Little Akaki River (LAR) were found at a river section near Kality Bridge and maximum NOX load was calculated at station near German Square. The integration of the CMB and PLOAD model in this study revealed that the use of area-specific pollutant export coefficients would give relatively accurate results than the use of mean and median ECf values of each land use.