Use of Agricultural Best-Management Practices for Watershed Management

Conrad Stang and Bahram Gharabaghi

ABSTRACT

The water quality in the group of bays and rivers located in southeastern Georgian Bay is influenced by the agricultural activities within the series of subwatersheds that make up Severn Sound. This area experienced eutrophic conditions and excessive algae production causing it to be listed as an Area of Concern on the Great Lakes. In 2002, Severn Sound became delisted by meeting the requirements specified in the Remedial Action Plan. This involved the successful implementation of numerous agricultural Best Management Practices (BMPs) aimed at reducing non-point source watershed loadings of sediment and sediment-bound phosphorus. The aim of this study was to evaluate if the applied agricultural BMPs were successful in reducing sediment and nutrients loads.

Instantaneous grab samples analyzed for Total Suspended Solids (TSS) and Total Phosphorus (TP) were taken at the watershed outlets of Hog Creek and Sturgeon River. Daily sediment-transport (or rating) curves were generated for periods before and after the implementation of BMPs by relating TSS concentrations and streamflow in the form of a power equation. The power equation was then used to predict unknown sediment loads between sampling intervals and aggregated to estimate monthly and annual loads. It was observed that after BMPs were applied the intercept of the daily and monthly sediment-transport curves were reduced and reflected previous literature. Thus the applied agricultural BMPs were successful in reducing watershed yields of sediment and sediment-bound phosphorus.

The BMP reduction factors were further evaluated by simulating watershed-based loadings of nutrients, sediment and streamflow with the CAnadian Nutrient and Water Evaluation Tool (CANWET). The model, with further enhancements by the author, was able reflect the temporal variability of sediment transport and effectiveness of BMPs in Southern Ontario. The calibrated CANWET model was utilized to provide further cost-effective insight into future remedial action scenarios involving agricultural BMPs.


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