Tracing sulfate sources in a tropical agricultural catchment with a stable isotope Bayesian mixing model

Abstract

Sulfate (SO 4 2− ) is an essential anion in drinking water and a vital macronutrient for plant growth. However, elevated sulfate levels can impact ecosystem or human health and could be an important indicator of acid rock drainage or pollution. Therefore, monitoring SO 4 2− sources and transport is important for water quality assessments. This study focused on exploring the sources and transformations of SO 4 2− as well as estimating the proportional contribution of the potential SO 4 2− pollutant sources to groundwater and surface water in a tropical river basin, the Densu River Basin. The study used major ions combined with stable sulfur and oxygen isotope compositions and a Bayesian isotope mixing model, MixSIAR. The major ion characteristics indicate that SO 4 2− concentrations remain stable throughout the rainy and dry seasons but originate from diverse sources. The multi-isotope model ( δ 34 S SO4 , δ 18 O SO4 ) identified four potential SO 4 2− sources: detergent, precipitation, sewage, and sulfate fertilizer. However, the δ 34 S SO4 and δ 18 O SO4 values of the fertilizer source signatures overlapped with those of precipitation and sewage. Nevertheless, the contributions from each source were disentangled using the MixSIAR model, which revealed sewage as the most dominant SO 4 2− pollutant in the Densu Basin, accounting for ~47 % of sulfate in groundwater and ~ 56 % of sulfate in surface water. Sulfate fertilizer (~33 %) was the second most important source after sewage for groundwater, while detergent (~23 %) was the second most important source for surface water. The redox processes of bacterial sulfate reduction and sulfide oxidation were determined to have a minimal impact on the sulfur isotope fractionation within the basin. This study highlights the benefits of combining major ions, sulfur isotopes and the MixSIAR model for identifying sources of sulfate. This approach accounts for uncertainties in source contributions which allows for more robust and reliable apportionment of sulfate sources. The study emphasizes the need for effective waste management and pollution control measures to protect water quality and provides vital guidelines on how to partition sulfate sources on a large catchment scale and evidence for making pollution management decisions on water resources. • Assessed stable isotope MixSIAR model to trace sulfate sources in a tropical agricultural catchment • Disentangled overlapping δ 34 S SO4 signatures from fertilizer, rain, and sewage • Sulfate levels remained consistent year-round, indicating stable pollution source proportions. • Highlighted the impacts of sulfate pollution on water quality in tropical agricultural regions • Sulfate reduction and sulfide oxidation were not significant redox processes in the catchment.

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