|Agricultural pollutants are a serious threat to water
resources in Canada’s farming regions. Surface runoff can carry
sediment, nutrients, pesticides, and bacteria from agricultural fields
to nearby surface waters degrading ecosystems and introducing threats
to human health (Draper & Reed 2009; Royer, et al. 2004).
Additionally, rainwater and snowmelt frequently carry harmful
agrochemicals to sensitive aquifers below, which once there
indefinitely jeopardize the health of groundwater resources (Draper
& Reed 2009). Determining the potential of agricultural lands to
contaminate both surface and groundwater would allow land managers to
effectively mitigate the negative corollaries of farming to precious
Soil erosion is the main method by which agricultural contaminants enter surface waters. As rain falls on bare soil the force of the raindrops causes soil aggregates to break apart thus detaching individual soil particles. If the rate of rainfall exceeds the rate of infiltration, water will flow down-slope carrying soil particles, as well as surface contaminants with it (Brady & Weil 2010). Besides precipitation, the rate of soil erosion is dependent on a number of other factors. The slope of the surface directly influences the rate of erosion; the steeper and longer the slope the higher the risk of soil loss (Renard et al. 1997). The permeability of a soil is related to its texture, structure, and organic matter content which all play a role in influencing the rate of soil erosion. A soil with low permeability and organic matter content or a poor structure will be much more susceptible to detachment and transport by rainfall than a well-drained soil with high organic matter content (Stone & Hilborn 2000). Lastly, the land use as well as the management practices utilised by farmers and land managers can have a profound impact on rates of soil loss. The effectiveness of agricultural practices at reducing soil loss is dependent on the type of crops grown as well as the tillage methods used. Furthermore, management practices such as up and down slope tillage increase the risk of soil loss compared to contour or cross-slope ploughing (Brady & Weil 2010). Sediment transported during an erosion event is commonly carried to nearby water bodies where soil and other particles may be carried further downstream or settle out in lacustrine environments. The rate of soil loss due to fluvial erosion on agricultural lands has been modelled extensively using the Universal Soil Loss Equation (USLE) although this model does not account for the spatial pathways taken by sediment during an erosion event.
Percolation, or leaching, is the process by which water, and potential contaminants, travel downward through the soil profile eventually reaching the water table. Much like surface erosion, a variety of factors interact to influence the rate of percolation and thus groundwater vulnerability. Factors including topography, depth to water table, recharge rate, soil media, vadose zone media, aquifer media, and hydraulic conductivity all influence the susceptibility of groundwater to surface contaminants (Aller et al. 1987). Topography specifically affects groundwater vulnerability as areas with low or no slopes encourage the pooling of water, as water begins to pool the chance of that water percolating downward through the soil profile increases. Conversely, on steep slopes or hillsides water has a greater chance of flowing downhill and entering nearby surface waters, thus eliminating much of the risk to aquifers associated with agrochemicals located on steep slopes. Furthermore, the closer the water table is to the ground surface the higher the risk of contamination. The greater the distance between the ground surface and the water table, the less likely it becomes that contaminants will enter groundwater as they must travel further through any underlying materials (Lampman 1995). The composition of the materials located beneath the ground surface will also affect aquifer vulnerability. Water and any accompanying soluble pollutants travel slower in tightly packed clays or bedrock compared to sands or gravels. The longer a contaminant takes to travel through the soil profile the less likely it becomes that said contaminant will reach the water table.
Modelling of both soil erosion and groundwater vulnerability has been the focus of research for decades (Aller, et al. 1987; Ciesiolka, et al. 2006). Recent research has focused on the improvement of current soil erosion and groundwater vulnerability models. The USLE has undergone numerous improvements since its inception during the 1940s, including the release of the revised universal soil loss equation (RUSLE) (Renard, et al. 1994). Current trends in research focus on applying the USLE or RUSLE models in a GIS based environment to aid land managers in determining the spatial distribution of erosion intensity on a variety of landscapes. Numerous studies exist outlining the benefits of such an approach (Fistikoglu & Harmancioglu 2002, Olsen & Kristensen 1998, Jain & Kothyari 2000). Similarly, researchers have been attempting to model the complex interactions between surface and subsurface environments (Al-Zabet 2002; Prasad, et al. 2011). One such model, DRASTIC (Aller et al. 1987), has been extensively utilised by researchers coupled with GIS to investigate the spatial distribution of groundwater vulnerability at location across the globe (Ahmed 2009; Chitsazan & Akhtari 2009; Rahman 2008).
While there have been a number of studies on nutrient losses due to soil erosion in agricultural settings (Royer, et al. 2004; Elrashidi, et al. 2004) there is a lack of consensus regarding the modelling of the temporal and spatial pathways taken by these particles to reach nearby surface and groundwater. Furthermore, a limited number of studies have specifically looked at the modelling of both surface and groundwater contamination by agricultural operations (Garratt & Kennedy 2006) and fewer still that utilize the benefits of GIS. In attempting to close these research gaps it is paramount to utilise an integrated approach to the analysis and modeling of surface and groundwater vulnerability as a way to obtain a better understanding of the vulnerability of freshwater resources. While the lack of consensus on contaminant transport modelling may hinder this study’s ability to effectively account for the transport of agrochemicals into surface waters it is believed that the lack of direct knowledge can be overcome by sufficient knowledge of the study area as well as the assumption that particles eroded farther away from a stream will have less of a chance of entering that stream.
Because erosion and leaching are complex processes, the ability to apply the USLE and DRASTIC models over a large geographic area is greatly aided by the utilisation of a GIS. GIS allows for quick identification of areas prone to high rates of erosion and percolation in relation to surface water and aquifers. One of the major benefits of a GIS is the ability to quickly determine the factor, or combination of factors, which contribute to a high potential to contaminate freshwater resources in any one area. Once the major contributing factor, or factors, have been identified it is easy to determine the most pragmatic approach to reduce surface and groundwater vulnerability. GIS not only facilitates the visualisation of areas prone to mobilisation and percolation, but with the utilisation of a MCE one can analyse the potential to contaminate surface water and groundwater, creating a single unified spatial distribution of the risk of contamination from all agricultural sources in a watershed. GIS can not only provide land managers with the latest information on current environmental conditions, but it also provides policy makers with the ability to conduct scenario analysis to determine the most environmentally, economically, and socially acceptable solution to water contamination should harmful levels of agrochemicals be detected in water bodies (Yang, et al. 2009). For example, if high levels of agricultural pollutants were detected in a sensitive aquifer a scenario analysis could be done to determine the effect of a buffer layer of clay or similar impermeable material on the rate of infiltration and thus overall groundwater vulnerability. Thus, the value of GIS is immense and without the ability to manipulate large amounts of spatial data, integrated modelling would not be feasible.
The purpose of this study is to assess the potential
vulnerability of both surface and ground water to agricultural
contaminants in the Fairchild Creek Watershed utilising an integrated
model, consisting of the USLE, a transport component, and DRASTIC, in a
1. Identify the factors relating to soil erosion
2. Identify the factors relating to groundwater contamination
3. Develop an integrated GIS-based MCE model, unifying the
USLE and DRASTIC models to determine the potential of an area to
4. Apply the GIS-based MCE model to examine the overall
contamination potential in the Fairchild Creek Watershed