Spatial and temporal characteristics of soil moisture in an intensively monitored agricultural field (OPE3)

A four-dimensional dataset of soil moisture from the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field has been analyzed for temporal and spatial characteristics. Knowledge of soil moisture patterns improves the understanding of processes in the land surface system and helps to identify these processes for use in modeling research. Statistics describing the soil moisture distribution in time showed a lower temporal variability at points in deeper soil layers, except for the deep sensors which were influenced by subsurface flow, where a high temporal variability could be found. The temporal autocorrelation increased with depth in the soil profile. The cross correlation between time series of soil moisture at different points in space decreased with depth and was more variable in deeper soil layers. For the spatial pattern of soil moisture, geostatistical information was extracted from variograms. The evolution of the spatial patterns was dependent on the soil moisture state. In the upper layer, the spatial variability and range increased with increasing soil moisture, while the opposite was found for deeper layers. For deeper layers, the range was mostly limited due to the complex hydrogeology. In this paper, all analyses were related to the needs in modeling and assimilation practices.