Assessing the Spatio-Temporal Variability of Soil Moisture Within the Brightwater Creek Watershed in Saskatchewan, Canada

English Abstract:

Understanding spatio-temporal variability of soil moisture has implications for climate and weather forecasting, drought monitoring, agricultural management, and environmental modelling. Soil moisture data from a joint University of Guelph and Environment Canada in-situ network in the Brightwater Creek watershed located in Saskatchewan, Canada was used to evaluate the spatio-temporal variability of soil moisture in a northern Prairie environment. At the 5 cm measurement depth, standard deviation of the soil moisture anomaly values increase with increasing soil water content. At the 20 & 50 cm measurement depths, an upward convex relationship and downward convex relationship, respectively, are established between the standard deviation and soil moisture. The highest standard deviation values at the 20 cm depth and lowest standard deviation values at the 50 cm depth were centered over the average spatial network soil moisture. A correlation matrix presenting relationships between measurement depths throughout the field season demonstrates the strongest correlation (r = 0.908; p<0.001) between the 20-50 cm depth. Autocorrelation was utilized to calculate an e-folding frequency which evaluates the temporal variability of soil moisture at all measurement depths for each network site. The average e-folding frequency for the 5, 20 & 50 cm measurement depths was 6.35, 12.97 and 12.29 days respectively. Variogram analysis was utilized to evaluate the spatial variability of soil moisture. The nugget and sill evolved coincidently on most sampling days across all depths. Range values were typically higher during wet periods for all depths, with pure nugget effect occurring at very wet (after large rain event) or after prolonged periods without precipitation. The results of this study will be important for water resource management as better understanding of soil moisture variability will ultimately improve the applications that make use of these measurements and improve our understand of hydrological processes.