Temporal stability of field-scale patterns in soil water content across topographically diverse agricultural landscapes

Temporal stability (TS) of soil water content (SWC) is commonly used to identify representative locations for SWC monitoring, to recover missing monitoring data, to design agronomic experiments, and to validate remote-sensing methods. Even though the factors affecting TS SWC, i.e. scale, sampling methods and frequency, weather conditions, soil properties, vegetation, surface topography, and surface/subsurface hydrology, are well known, their interaction and combined effect on TS SWC is poorly understood. To fill this knowledge gap, we monitored SWC during three growing and two winter seasons at four topo-hydrological positions (THP): summit, slope, dry depression, and flooded depression of an agricultural field under corn-soybean rotation with and without cover crop (rye). Twenty 10 m x 10 m experimental plots were located at the four THP in Mason, MI, USA. SWC was monitored at depths of 20, 40 and 60 cm from June 2014 through Oct 2016. We used the Vachaud et al. (1985) approach to quantify TS SWC, and ANOVA/ANCOVA and a regression tree exploratory tool to evaluate the effects of weather conditions, soil properties, vegetation, and surface topography/hydrology on TS SWC. Our results showed that the latter factor plays an important role in TS SWC patterns at the scale of an agricultural field. TS SWC patterns were more frequently observed in locations where the effect of local (soil properties, vegetation) controls interfered with the non-local (surface and subsurface water fluxes) controls of SWC dynamics. The presence of TS SWC was clearly associated with the temporal variability of SWC in individual locations, suggesting that TS SWC depends on representation of locations with different temporal variability of SWC in the examined dataset.