Fertilizers increase agricultural productivity and farmers' income. However, intensive agriculture frequently overuses fertilizers, which in turn can contaminate surface and groundwater. In this study, hydrochemical and multi-isotope (δ15NNO3, δ18ONO3 and δ18OH2O) data have been combined to identify nitrate pollution sources in Ghana's Densu River Basin, trace the Nitrogen (N) biogeochemical processes in the basin and apportion the contribution of each pollution source. Surface water NO3- ranged from 0.3 to 10.6 mg/L (as N), while groundwater NO3- ranged from 0.9 to 34 mg/L. Hierarchical cluster analysis classified the water samples into three spatial categories: upstream, midstream, and downstream, reflecting river and land use patterns. The multi-isotope model considered five primary NO3- sources: atmospheric deposition, manure/sewage, NH4+ in fertilizers, other NO3- based fertilizers and soil N. Nitrification was identified as the major biogeochemical process upstream, whereas mixing of sources and denitrification dominate the midstream to downstream sections of the basin. Nitrate source apportioning using a MixSIAR model reveal that N fertilizers (40 %) and soil N (34 %) contribute the most to nitrate pollution upstream of the river. From the midstream to downstream sections, manure/sewage (43 %) become the dominant nitrate source, reflecting the transition from agriculture to peri-urban and urban land use. This study has shown that soil erosion and runoff contribute to nitrate pollution in the Densu River, at levels comparable to N fertilizers, and groundwater across the basin is impacted mainly by manure/sewage. The multi-isotope analyses allowed the partitioning of N sources in other ways not possible using only classical hydrochemical methods.
Keywords: Bayesian mixing model; Hierarchical cluster analysis; Nitrate pollution; Nitrogen isotopes; Southern Ghana.
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