Field validation of a cosmic-ray neutron sensor using a distributed sensor network

With continued refinement in land surface model resolution the need for accurate and continuous soil moisture datasets at intermediate spatial scales has become critical for improved meteorological and hydrological prediction. The current availability of such data is inadequate. Here, we present a comparison of two datasets that provide average soil moisture over an area hundreds of meters squared in a dryland ecosystem in southern Arizona. One dataset is from a high-resolution soil moisture network of 180 time-domain transmission probes; the other is from a cosmic-ray neutron sensor placed at the center of the study area. We find the cosmic-ray neutron counts correlate well with spatially averaged point measurements of soil moisture over a 6-mo period with an RMSE of 0.0165 m3 m-3 and percent error of less than 20%. Neutron transport simulations suggest our understanding of the effective sensor depth in the presence of vertical variations in water content is adequate. We find that daily evapotranspiration water fluxes inferred from cosmic-ray measurements agree with previously published eddy-covariance measured values at the study site, suggesting that the cosmic-ray neutron sensor may be able to provide flux measurements of the near surface at intermediate spatial scales.