Moisture in the topsoil

The boundary that separates the earth from the atmosphere is a crucial zone of study for meteorology and hydrology. Here, solar energy is partitioned into sensible heat which drives atmospheric circulation, latent heat needed for evaporation from the soil and transpiration of vegetation, and soil heat which warms the subsurface. Precipitation is partitioned into interception that evaporates directly into the atmosphere, surface runoff that discharges quickly into water courses and infiltration which resides longer in the subsurface. Soil moisture influences all these processes and is therefore considered a key variable in land-atmosphere interaction. In order to obtain a better understanding of the heat and water balance of topsoil, observations are key, but challenging with in situ point sensors. Recent rapid developments in remote sensing have tremendously increased our ability to observe the boundary between soil and atmosphere. Retrieving state variables such as soil temperature and moisture from remote sensing is far from trivial: detected signals originate not only from the soil, but also from the atmosphere and vegetation, the depth of the detection is a function of the soil moisture itself, and pixels are large and heterogeneous. Field validation is difficult, because of scale disparity between in situ point sensors and remote sensing pixels. Still, given the limitations, remote sensing provides an opportunity to improve understanding of heat and moisture transfer in the topsoil. The central question of this research is: What can be learnt from (remote sensing) observations about the heat and moisture balance of the topsoil? First a cross validation of different soil moisture products based on remote sensing was performed to investigate similarities and differences between these products. The differences were significant and could be attributed to differences in land use and vegetation, but not fully explained. This illustrated that retrieval algorithms for soil moisture are far from converged. One prerequisite for improving retrieval algorithms is ground truth, ground observations at scales relevant for remote sensing. Second, a field technique was developed that can potentially be used for bridging the observation gap between point sensors and remote sensing pixels. This technique uses Distributed Temperature Sensing (DTS) over horizontal extents up to kilometers to infer soil moisture at this intermediate scale. Propagation of variations in atmospheric temperature and radiation with depth is a function of soil moisture. By using DTS observations at three depths, it is possible to infer soil moisture, assuming that heat conduction is the dominant …