Regional scale spatial and temporal variability of soil moisture in a prairie region. Issue 20 (16th August 2016)

• Record Type: Journal Article
• Authors: Burns, Travis T.; Berg, Aaron A.; Cockburn, Jaclyn; Tetlock, Erica
• Is Part Of: Hydrological processes. Volume 30:Issue 20(2016)
• Page Start: 3639
• Page End: 3649
• Publication Date: 2016-08-16
• Subjects: soil moisture -- spatial and temporal variability -- in‐situ monitoring network -- regional scale -- vertical moisture profile; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.10954
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: Understanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e ‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd.