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Temporally stable patterns but seasonal dependent controls of soil water content: Evidence from wavelet analyses
Authors:Wei Hu  Bing Cheng Si  Asim Biswas  Henry Wai Chau
Institution:1. New Zealand Institute for Plant & Food Research Ltd, Christchurch, New Zealand;2. Department of Soil Science, University of Saskatchewan, Saskatoon, SK, Canada;3. College of Hydraulic and Architectural Engineering, Northwest A&F University, Yangling, China;4. School of Environmental Sciences, University of Guelph, Guelph, ON, Canada;5. Department of Soil and Physical Sciences, Faculty of Agriculture and Life Sciences, Lincoln University, Lincoln, New Zealand
Abstract:Scale‐ and location‐dependent relationships between soil water content (SWC) and individual environmental factors have been widely explored. SWC is controlled by multiple factors concurrently; however, the multivariate relationship is rarely explored at different scales and locations. Multivariate controls of SWC at different scales and locations in two seasons within a hummocky landscape of North America were identified using bivariate wavelet coherency and multiple wavelet coherence. Results showed that depth to CaCO3 layer, which was correlated with elevation over all locations at scales of 36–144 m and cos(aspect), provided the best individual factor for explaining SWC variations in spring (May 2) and summer (August 23), respectively. Although spatial patterns of SWC were temporally stable, different topographic indices affected spatial distribution of SWC in different seasons (elevation in spring and aspect in summer) due to different dominating hydrological processes. These varying hydrological processes also resulted in the distinct role of soil organic carbon (SOC) content in different seasons: a positive correlation in spring and a negative correlation in summer. Multiple wavelet coherence identified a combination of depth to CaCO3 layer and SOC in spring and a combination of cos(aspect) and SOC in summer that controlled SWC at different scales and locations, respectively. This indicated a combined effect of soil and topographic properties on SWC distribution and a clear need for these two factors in developing scale‐dependent prediction of SWC in the hummocky landscape of North America.
Keywords:bivariate wavelet coherency  influencing factor  multiple scales  multiple wavelet coherence  soil moisture  spatial variability
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