Improving the Operability of the Cosmic-ray Neutron Soil Moisture Method: An Estimation of Lattice Water using Global Datasets

Abstract:

Currently, global trends in consumptive water-use indicate an increasing and unsustainable reliance on groundwater resources. Each year approximately 60% of water used for agriculture is wasted through inadequate water conservation, losses in distribution, and inappropriate times and rates of irrigation. Therefore, in order to coordinate a strategy to accomplish the agricultural demands of our global community we must maintain a stable global food and water trade while increasing crop yield and efficiency. This research aims to improve the operability of the recently developed and promising cosmic-ray neutron method for estimating field scale soil moisture. The sensor works by passively counting above ground low-energy neutrons which correlate to the total water in the sensor measurement volume (a sphere with radius of ~300 m and vertical soil depth of ~30 cm). Because the sensor responds to different forms of water (sources of hydrogen), estimates of background water in the mineral soil need to be accounted for in order to minimize measurement error. Here we compared field-scale estimates of soil mineral water with readily available global datasets. Using the newly compiled 1km resolution Global Soil Dataset (GSDE), we were able to investigate the correlation between soil mineral water and clay content for various soil taxonomic orders. Preliminary results suggest statistically significant linear relationships for Aridisol, Mollisol and Ultisol soil orders. Incorporation of this dataset will allow for real-time soil moisture mapping of hundreds of center-pivots using the mobile cosmic-ray probe without the need for time-consuming in-situ soil sampling. Integrating this technique into soil moisture management has the potential to increase the efficiency of irrigation water used in agriculture.