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Well-designed rapid sampling strategies can fill this gap by assessing water quality at multiple spatially-defined locations across a landscape over time. Such strategy will allow a complete description of the spatial variability of water quality across a sampling unit and will inform whether or not water quality controls over time. The key to understanding temporal variability is, therefore, the time period over which sampling is conducted. The time-frame of the data collection can be reduced, for example, to de-couple the effects of changes in land-use or climate from those of time. Longer time periods can increase the power to detect localised changes in trends or to identify sites with unusually strong or weak trends (Maurer et al., 2007). This is because the length of the monitoring period becomes a proxy for the mean residence time of environmental contaminants and habitats.
Water quality sampling requires coordination between the sampling process and the analyses and data reporting. The time consumed for sampling and analysis has the potential to influence the timeliness of the results and the interpretive product. Strategies that minimise the time for sampling are therefore important to maximise the use of sampling resources. To illustrate this scenario, I present a water quality rapid sampling strategy in which I sampled the River St. Lawrence below the dam at the La Grande Generating Station during 2009, 2010 and 2011. Using correlations between water quality samples over three years and selected years with additional sampling data, I estimated the spatial variability of the water quality results from five water quality parameters: nitrate, nitrite, phosphate, silica and phosphate. My findings suggest that rapid sampling strategies are relevant whenever regular monitoring is too costly to perform, when the seasonal variability or temporal variability of water quality needs to be assessed, or when the results would otherwise be difficult to interpret.
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