Improving the Operability of the Cosmic-ray Neutron Soil Moisture Method: Remote Sensing of Fresh Biomass in Crops

Abstract:

Projected increases in global population will put enormous pressure on fresh water resources in the coming decades. Approximately 70 percent of human water use is allocated to agriculture with 40 percent of global food production originating from irrigated lands. Growing demand for food will only worsen the strain placed on many irrigated agricultural systems resulting in an unsustainable reliance on groundwater. This work represents an effort to improve the operability of the recently developed and promising cosmic-ray neutron method for estimating field-scale soil moisture. The cosmic-ray sensor passively measures above ground low-energy neutrons, which correlate to the amount of water within the measurement area (a circle with radius of ~300 m and a depth of ~30 cm). The sensor sees all forms of water (hydrogen), therefore time-varying water in growing biomass should be accounted for to reduce systematic measurement error and bias. Two vegetation indices were used to estimate fresh biomass within study agricultural fields near York, NE. The wide dynamic range vegetation index (WDRVI) and the green normalized difference vegetation index (GRNDVI) were both calculated from MODIS 500 m resolution satellite reflectance data for the summer of 2014. Additionally, in-situ biomass samples were collected from study fields to compare to biomass estimates obtained from MODIS reflectance data. Preliminary results suggest that remotely sensed fresh biomass estimates collected over the course of a growing season were sufficient and accurate enough (~ within 1 kg/m²) to eliminate the systematic error in the cosmic-ray calibration method for both soybean and maize crops. The incorporation of this novel technique for soil moisture management in producer operations has the potential to increase the efficiency of irrigation water use.