Evaluating the Uncertainty of Long-Term Soil Moisture Datasets.

oil moisture information is important for various purposes including planning and budgeting for irrigation and input information for hydrological climate models. Evaluating the uncertainty of current data from soil moisture monitoring networks can improve the quality of such soil datasets and its applied use. Long term soil moisture monitoring in Texas is primarily supported by the Soil Climate Analysis Network (SCAN) implemented by NRCS, and U.S. Climate Reference Network (CRN) implemented by the NCDC. Both networks use Stevens Water Hydra Probe for measuring soil moisture, and they also use the manufacturer provided default calibration curves.

Texas, contains Vertisols and Vertic integrades as well as Alfisols with significant texture discontinuities with depth, which create distinct sources of uncertainties in measuring soil moisture. The objectives of this study were to 1) evaluate different methods of Hydra Probe calibration and 2) apply this knowledge to the long term soil moisture data at the SCAN sites and address the spatial and temporal accuracy of soil moisture data from these sites in Texas. Twenty two Hydra probes were calibrated using three methods: manufacturer provided calibration equations, soil specific calibration equations developed in the lab, and field calibration equations that used neutron probe for two different soil orders. Both the manufacturer provided and lab calibrations were compared with the field calibration at different depths and over time. We will present the results from our calibration comparisons and discuss the improvements of SCAN sites as a result of onsite calibration.