Determining hot moments/spots of hillslope soil moisture variations based on high-resolution spatiotemporal soil moisture data

Abstract

Characterizing soil moisture variation has critical implications for various ecosystem processes and the hydrological cycle. In this study, we identified the hot moments (times with high temporal variation rates) and hot spots (areas with high temporal variation rates) of the soil moisture variation and investigated their controlling factors on a tea garden hillslope in Taihu Lake Basin, China. Daily soil moisture data were calculated for 39 sites, and then, daily soil moisture maps were generated from March 1, 2014 to February 28, 2015. The soil moisture temporal variation rates (VR) at different locations and during different time periods were calculated based on these maps. We found that because soil water content at the subsurface was more spatially varied than that at the surface on this hillslope, spatial heterogeneity of VR was also greater at 0.3-m depth than that at 0.1-m depth. Elevation, sand content and rock fragment content were positively correlated (p < 0.05) with this spatial heterogeneity, while slope and clay content were negatively correlated (p < 0.05) with it. June and July 2014 were the hot moments with high VR at both depths of 0.1- and 0.3-m, while December 2014 was the cold moment with the lowest VR at both depths on this study hillslope. Meteorological factors (precipitation and temperature) explained 59.9% and 56.9% of the total variance in the time series of spatial mean VR at the depths of 0.1- and 0.3-m, respectively. Stronger variations in spatial mean VR were found during representative medium and large rainfall events than during representative small rainfall events. In addition, the response of spatial mean VR to rainfall at 0.3-m depth was delayed compared to that at 0.1-m depth. The findings and methodologies of this study can be useful in determining the hot spots and hot moments of soil moisture variations, which could be potentially useful for investigating various hydrological, ecological, environmental, and agronomic processes.