Comparison of the estimated water and energy budgets of a large winter wheat field during AgriSAR 2006 by multiple sensors and models

SummaryAn accurate understanding of the behavior of the water and energy balance terms in agricultural areas is of interest for a number of different disciplines. The objective of this paper is to use a multi-sensor and multi-model approach to study the water and energy budget of a winter wheat field in North-Eastern Germany. The study has been performed as part of the AgriSAR 2006 campaign. A Large Aperture Scintillometer (LAS) and a Bowen-Ratio Energy Balance (BREB) installation have been used to analyze the energy balance. Soil moisture profiles were continuously monitored at a number of depths. It has been found that the LAS and BREB estimates of the sensible heat flux are consistent during daytime, but that during nighttime the LAS estimates are approximately 100 Wm−2 lower than the BREB estimates. This may be explained by the effect of the uncertainty in the stability functions for stable conditions on the LAS results. Further, generally low Bowen ratio values, in the order of 0.5, were obtained, even during very hot, dry days. This implies that the evapotranspiration rates are determined by the moisture content of the deeper soil layers. The soil moisture values of the upper and lower soil layers become decoupled under dry conditions. Two commonly used hydrologic models, PROMET and TOPLATS, were applied during the study period. PROMET reproduces the soil moisture profile slightly better than TOPLATS, while the latter model simulates the partitioning of the energy balance slightly better. This can be explained by the manner in which the energy and water balances are solved by both models. Overall, the results suggest that the evapotranspiration rates of the winter wheat field are not correlated with the surface soil moisture values, that these surface soil moisture values are not correlated with the lower soil moisture values under dry conditions, and that commonly used hydrologic models can reproduce these observations.