Towards disentangling heterogeneous soil moisture patterns in cosmic-ray neutron sensor footprints

Abstract. Cosmic-ray neutron sensing (CRNS) allows for non-invasive soil moisture estimations at the field scale. The derivation of generally relies on secondary cosmic-ray neutrons in epithermal to fast energy ranges. Most approaches and processing techniques observed intensities are based assumption homogeneous site conditions or patterns with correlation lengths shorter than measurement footprint detector. However, view non-linear relationship between moisture, it is questionable whether these assumptions applicable. In this study, we investigated how a non-uniform distribution within impacts CRNS estimation combined use thermal can be advantageous case. Thermal have lower energies substantially smaller around sensor neutrons. Analyses using URANOS (Ultra RApid Neutron-Only Simulation) Monte Carlo simulations investigate dynamics study northeastern Germany revealed that mainly covers mineral soils near-field while also large areas organic soils. We found either combining by rescaling method developed adjusting all parameters transfer function leads an improved calibration against reference measurements compared standard approach alone. provided indicator heterogeneity. We, therefore, suggest offers potential spatial disaggregation terms near- far-field dynamics.