Seasonal and event dynamics of spatial soil moisture patterns at the small catchment scale

Abstract

Our understanding of short‐ and long‐term dynamics of spatial soil moisture patterns is limited due to measurement constraints. Using new highly detailed data, this research aims to examine seasonal and event‐scale spatial soil moisture dynamics in the topsoil and subsoil of the small spruce‐covered Wüstebach catchment, Germany. To accomplish this, univariate and geo‐statistical analyses were performed for a 1 year long 4‐D data set obtained with the wireless sensor network SoilNet. We found large variations in spatial soil moisture patterns in the topsoil, mostly related to meteorological forcing. In the subsoil, temporal dynamics were diminished due to soil water redistribution processes and root water uptake. Topsoil range generally increased with decreasing soil moisture. The relationship between the spatial standard deviation of the topsoil soil moisture (SDθ) and mean water content ( ) showed a convex shape, as has often been found in humid temperate climate conditions. Observed scatter in topsoil SDθ( ) was explained by seasonal and event‐scale SDθ( ) dynamics, possibly involving hysteresis at both time scales. Clockwise hysteretic SDθ( ) dynamics at the event scale were generated under moderate soil moisture conditions only for intense precipitation that rapidly wetted the topsoil and increased soil moisture variability controlled by spruce throughfall patterns. This hysteretic effect increased with increasing precipitation, reduced root water uptake, and high groundwater level. Intense precipitation on dry topsoil abruptly increased SDθ but only marginally increased mean soil moisture. This was due to different soil rewetting behavior in drier upslope areas (hydrophobicity and preferential flow caused minor topsoil recharge) compared with the moderately wet valley bottom (topsoil water storage), which led to a more spatially organized pattern. This study showed that spatial soil moisture patterns monitored by a wireless sensor network varied with depth, soil moisture content, seasonally, and within single wetting and drying episodes. This was controlled by multiple factors including soil properties, topography, meteorological forcing, vegetation, and groundwater.