Effects of change in streamflow patterns on water quality. (15th January 2022) - Patil, Rupesh; Wei, Yongping; Pullar, David; Shulmeister, James
Abstract: Streamflow patterns are closely linked with the quality of stream water, but they are often dealt separately. Due to this, the effects of change in streamflow patterns resulting from river regulation and flow diversion on stream water quality remain under-investigated. This study models change in water quality indicators including pollutants (total suspended solids and turbidity), nutrients (total nitrogen and phosphorus), dissolved oxygen, nitrogen (kjeldahl), pH, and salinity caused by the change in streamflow patterns under different scenarios of river regulation, flow diversion, and rainfall. The generalized additive model was used and the Goulburn-Broken catchment, Australia was chosen as the case study. It was found that concentrations of pollutants and nutrients increased by 38% while dissolved oxygen and nitrogen (kjeldahl) decreased by 35% during the period 1990–2018. These changes were associated with an average increase of 20% in low and medium flows, an average decline of 22% in high and overbank flows and a 15% decline in rainfall. Under the scenario of climate change, river regulation and flow diversion, the overbank flow patterns would mimic the effects of low and medium flows on the water quality indicators that would raise the concentration of pollutants, nutrients, and salinity by 19%. Restoration of high flows would decrease these concentrations by 28% relative to current concentrations, however, it would also reduce dissolved oxygen, nitrogen (kjeldahl), and pH. Effects of streamflow patterns on water quality have implications for environmental flow management, thus, this study recommends critical adjustments in low, medium, and high flows for improving water quality. Highlights: An approach to link change in stream water quality with change in streamflow pattern. Overbank flow patterns mimic the effects of low and medium flows on water quality. Revise current water quality management strategies with minimum computational efforts. The approach is best suited for rivers with strong streamflow variation.