Utilization of bathymetry data to examine lead sediment contamination distributions in Lake Ontario

Bathymetry data offer interesting opportunities for the analysis of contaminant distribution patterns. This research utilized lead surficial sediment sample data from Lake Ontario that were collected by the Canada Centre for Inland Waters in 1968 and 1998. Traditionally, two-dimensional analyses such as dot maps or proportional circle representation have been utilized to examine pollutant levels. Generating area estimates allows for expanded spatial analysis of contaminant distribution patterns. Lake-wide surfaces were derived using the ordinary kriging technique. These were then layered on bathymetry data to examine three-dimensional relationships between observed pollution patterns and lake-bottom features. Spatial variability was observed in both the 1968 and 1998 datasets. Contamination levels in 1998 dropped substantially, especially in areas that were previously the most heavily polluted and above the Probable Effect Level (4660.23 km2 or 26.72% of the common analysis area lake-bottom in 1998 versus 6189.07 km2 or 62.00% in 1968). Conversely, areas below the Threshold Effect Level increased from 922.09 km2 (5.29%) in 1968 to 3484.22 km2 (19.98%) in 1998. In both years, shallow and sill/ridge areas tended to have lower levels of contamination than deeper lake basins or contaminant inflow areas. The 1968 dataset likely provides a more detailed estimation surface as there were more points available for interpolation procedures. The kriging surfaces when combined with bathymetry, sedimentology information, and knowledge of physical processes provide a comprehensive illustration of the contaminant distributions whether they are high (1968) or when loadings are significantly reduced (1998). The results have implications for future sediment assessment programs and survey design on a lake-wide basis. The bathymetry data allowed for enhanced interpretation and an improved understanding of observed lead pollution patterns.