1. To measure moisture content in the unsaturated zone under different land use classes using different techniques representing different spatial and temporal scales.
2. To indirectly estimate groundwater recharge for different land use classes based on measurement of moisture content, tracer concentrations, temperature, geophysical data and water table fluctuations.
3. To measure and estimate hydraulic properties for a range of spatial scales.
Task 1: Instrumentation of soil profiles
At the HOBE agriculture field site (Voulund), automated profile soil moisture measurements at an hourly time step are collected from the soil surface to 4m depth with a TDR system similar to the one described in WP1 Task 3. Also, 5TE Decagon sensors have been placed from 0-50 cm and from 1 to 4 m depths to measure profile soil moisture and temperature. Suction cups from 1-4 m were installed to sample soil water and infer recharge rates from a field tracer experiment. At the forest and wetland HOBE field sites (Gludsted and Skjern Enge), equivalent TDR and temperature sensors have been installed near the surface. Additionally, profile soil moisture and soil temperature data is acquired from 30 distributed permanent stations with Decagon 5TE sensors installed at three depths in the top 0.5 m of the soil.
Task 2: Geophysical arrays
Geophysical arrays are installed for cross-borehole monitoring of the spatio-temporal variations of water content and a saline tracer. The setup consists of five ERT and four GPR boreholes drilled to the water table. Eight boreholes form a cross consisting of two lines with the last ERT borehole in the centre. Along each line, the outer two boreholes are equipped with ERT instrumented PVC-tubes while the inner two boreholes have access tubes for GPR antennae. An array of piezometers will be installed for automatic recordings of water table fluctuations.
Task 3: Soil physical parameters
Soil cores samples were used for laboratory analysis of soil hydraulic characteristics. Soil texture, water retention and saturated soil hydraulic conductivity were measured. The laboratory analysis was further expanded to include near-saturated hydraulic conductivity on 20 by 20 cm soil cores. Large scale effective hydraulic properties will be estimated using both inverse approaches based on the collected data on water content and tracer concentrations and various upscaling techniques including the stochastic approaches.
Task 4: Airborne remote sensing of soil moisture
During a selected time window, airborne brightness temperature measurements of the EMIRAD-2 microwave L-band radiometer (Technical University of Denmark) and concurrent ground observations of soil moisture and auxiliary parameters are acquired in the Skjern River Catchment, Denmark. Using the ground data as input to a radiative transfer model, L-band brightness temperatures are modeled. The data is aggregated for comparison at both, the airborne spatial scale (few kilometers) and the SMOS footprint scale (~44 km).
Task 5: Satellite borne remote sensing of soil moisture
Brightness temperature and soil moisture products of the Soil Moisture and Ocean Salinity (SMOS) satellite as well as auxiliary data used in the soil moisture retrieval algorithm are validated in the Skjern River Catchment, Denmark using the data obtained through Tasks 4 and 6. The advantage of the airborne campaign data set of high spatial coverage and density is the possibility to bridge the spatial scales stepwise, from ground via airborne to space-borne measurements. Meanwhile soil moisture networks provide long-term series at high temporal resolution, facilitating the assessment of temporal dynamics.
Task 6: Regionalization of soil moisture
Data of different spatial and temporal resolutions is acquired in the Skjern River Catchment by means of two complementary approaches: (1) a short-term field campaign including airborne radiometer observations as well as concurrently measured in situ data from selected ground patches, and (2) the measurements from a long-term distributed soil moisture and soil temperature network. These data are used for the calibration and validation of the SMOS radiometer as well as distributed hydrological models. Once confidence in these two data sources is established, solid spatially discretized soil moisture estimates for the entire catchment can be generated by combining them.