Using GIS and SWAT to Model Stream Modification, Sediment and Carbon Transfer within the Grand River Drainage Network, Ontario

English Abstract:

The Grand River watershed (~7000 km²) is an important agricultural area in Southern Ontario, with several large and growing municipalities. As in many watersheds, there have been historical modifications to the drainage network related to various human endeavors. ArcMap has been used to model how a natural drainage network would appear, based on digital elevation maps (DEM) to predict flow paths. Channel lengths and locations of the predicted network were compared with a ground-truthed channel inventory (Grand River Conservation Authority and Ontario Ministry of Natural Resources) to determine efficacy of the model. Channels not anticipated by topography were mostly first-order, with low sinuosity, and were most common in areas with high agricultural land use, and are likely excavated extensions to headwater streams to facilitate drainage. Land use, in particular agricultural activity, has significantly increased the total drainage density, sediment erosion and nutrient export in the Grand. The Soil and Water Assessment Tool (SWAT) was used to evaluate sub-basin hydrology, and the transfer of sediments, organic carbon, and other nutrients (N&P) from terrestrial to aquatic systems based on land use, management practices, historical flow and meteorological data for a 10-year period (January 2000 – December 2010) from the Grand River Basin. The SWAT model predicted well the stream discharge and sediment load, along with nutrient export when compared to observed data. A modified drainage network, based on introducing natural sinuosity to excavated headwater channels, was simulated using GIS, and SWAT was applied to estimate the retention of carbon, sediment and nutrients under this new “restoration” scenario. Model results suggest that remediation efforts could target these excavated channels in the head-water catchment areas in order to improve carbon and nutrient retention.