AbstractsGeography &GIS

Quantifying Urban and Agricultural Nonpoint Source Total Phosphorus Fluxes Using Distributed Watershed Models and Bayesian Inference

by Christopher Charles Wellen




Institution: University of Toronto
Department:
Year: 2014
Keywords: Bayesian; Hydrology; Modelling; Watershed
Record ID: 2024873
Full text PDF: http://hdl.handle.net/1807/43759


Abstract

Despite decades of research, the water quality of many lakes is impaired by excess total phosphorus loading. Four studies were undertaken using watershed models to understand the temporal and spatial variability of diffuse urban and agricultural total phosphorus pollution to Hamilton Harbour, Ontario, Canada. In the first study, a novel Bayesian framework was introduced to apply Spatially Referenced Regressions on Watershed Attributes (SPARROW) to catchments with few long term load monitoring sites but many sporadic monitoring sites. The results included reasonable estimates of whole-basin total phosphorus load and recommendations to optimize future monitoring. In the second study, the static SPARROW model was extended to allow annual time series estimates of watershed loads and the attendant source-sink processes. Results suggest that total phosphorus loads and source areas vary significantly at annual timescales. Further, the total phosphorus export rate of agricultural areas was estimated to be nearly twice that of urban areas. The third study presents a novel Bayesian framework that postulates that the watershed response to precipitation occurs in distinct states, which in turn are characterized by different model parameterizations. This framework is applied to Soil-Water Assessment Tool (SWAT) models of an urban creek (Redhill Creek) and an agricultural creek (Grindstone Creek) near Hamilton. The results suggest that during the limnological growing season (May – September), urban areas are responsible for the bulk of overland flow in both Creeks: In Redhill Creek, between 90% and 98% of all surface runoff, and in Grindstone Creek, between 95% and 99% of all surface runoff. In the fourth chapter, suspended sediment is used as a surrogate for total phosphorus. Despite disagreements regarding sediment source apportionment between three model applications, Bayesian model averaging allows an unambiguous identification of urban land uses as the main source of suspended sediments during the growing season. Taken together, these results suggest that multiple models must be used to arrive at a comprehensive understanding of total phosphorus loading. Further, while urban land uses may not be the primary source of sediment (and total phosphorus) loading annually, their source strength is increased relative to agricultural land uses during the growing season.