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An ensemble of Bayesian SPARROW models for the Precambrian Shield in the eastern Georgian Bay drainage basin, Ontario, Canada

Authors :
Alexey Neumann
E. Agnes Blukacz-Richards
Huaxia Yao
George B. Arhonditsis
April L. James
Source :
Journal of Great Lakes Research. 47:1671-1688
Publication Year :
2021
Publisher :
Elsevier BV, 2021.

Abstract

The present study applied an ensemble of Bayesian SPARROW models in the eastern Georgian Bay drainage basin informed by multi-agency tributary water quality monitoring data collected in the area. Consistent with our current understanding of the role of wetlands in the Precambrian Shield, our analysis showed that they could be responsible for nearly 30% of the total phosphorus (TP) loading from forested areas and 23% of the delivered TP from the eastern Georgian Bay drainage basin. Agricultural areas contribute over 40% of the TP loading associated with anthropogenic activities, which was two times higher than the predicted nutrient losses per unit area in southern Georgian Bay. This finding raises concerns regarding the likelihood of elevated eutrophication risks from future expansion of agriculture in central and northern Ontario. Considering the uncertainty pertaining to their broader influence, cottage septic fields were estimated to be the second anthropogenic P source after agriculture, accounting for 9% of the delivered TP loading to the downstream outlets into Georgian Bay. Research on eutrophication of coastal embayments in Georgian Bay has historically focused on factors, such as basin morphometry, internal P loading, and dreissenid-mediated nearshore shunt. In this context, our SPARROW model offered an additional perspective by estimating that a significant fraction (≈90%) of the TP loading delivered to the Georgian Bay embayments could be originating from upstream sites, even though our predictions suggested that nearly half (49%) of P loading reaching the stream network deposits on the sediments of inland lakes in central Ontario.

Details

ISSN :
03801330
Volume :
47
Database :
OpenAIRE
Journal :
Journal of Great Lakes Research
Accession number :
edsair.doi...........9ad35bd8b727510b68950af541120f36