High-resolution investigation of soil moisture dynamics at the hillslope scale
PhD thesis
Soil moisture is a key state variable that controls hydrological and energy fluxes at various spatial and temporal scales. Understanding and characterizing this variability is one of the major challenges within hydrological sciences. Furthermore, understanding soil moisture dynamics at the hillslope scale is important to link point- and catchment-scale studies, and for up- and down-scaling of hydrological processes. Nonetheless, deriving generalizable process understanding is not trivial, because of the non-linearity of hillslope response to rainfall.
Recent developments of wireless sensor technology allow for the long-term monitoring of soil water content with high spatial and temporal resolution, hence facilitate a better understanding of soil moisture dynamics and the related hydrological processes. Geophysical techniques such as electromagnetic induction (EMI) methods have been widely used during the last decades to map soil properties at the field scale, because of their suitability for fast and precise mapping of soil apparent electrical conductivity (ECa) over large areas.
The overall aim of the PhD thesis is to describe the soil moisture dynamics at different spatial and temporal scales within a hillslope area with varying topography and soil types but homogeneous land use. In addition to this, the work is aimed on the definition of an efficient monitoring strategy for the investigation of soil moisture, combining the high resolution information from a wireless sensor network with time-lapse EMI measurements carried out over a 1-year period.
Within the Schäfertal catchment, a 2.5 ha hillslope area was permanently instrumented with a wireless soil moisture and soil temperature monitoring network (SoilNet). It comprises 240 sensors distributed at three depths (5, 25 and 50 cm), measuring hourly soil water content and soil temperature. Their spatial distribution was defined according to a geostatistical sampling strategy based on ancillary information. Time-lapse EMI measurements were carried out to map spatial patterns of ECa over several depths.