Abstract
AbstractCosmic‐Ray Neutron Probes (CRNP) have found application in soil moisture (SM) estimation due to their conveniently large (>100 m) footprints. Here, we explore the possibility of using high‐density polyethylene (HDPE) moderator to limit the field of view, and hence, the footprint of a SM sensor formed of 12 CRNP mounted on to a mobile robotic platform (Thorvald) for better in‐field localization of moisture variation. Ultra Rapid Adaptable Neutron‐Only Simulation neutron scattering simulations are used to show that 5 cm of additional HDPE moderator (used to shield the upper surface and sides of the detector) is sufficient to (a) reduce the footprint of the detector considerably, (b) approximately double the percentage of neutrons detected from within 5 m of the detector, and (c) does not affect the shape of the curve used to convert neutron counts into SM. Simulation and rover measurements for a transect crossing between grass and concrete additionally suggest that (d) SM changes can be sensed over a length scales of tens of meters or less (roughly an order of magnitude smaller than commonly used footprint distances), and (e) the additional moderator does not reduce the detected neutron count rate (and hence increase noise) as much as might be expected given the extent of the additional moderator. The detector with additional HDPE moderator was also used to conduct measurements on a stubble field over three weeks to test the rover system in measuring spatial and temporal SM variation.
Highlights
Soil Moisture (SM) is a crucial variable in hydrological cycles and affects weather prediction, climate studies, greenhouse gas control, hydrological modeling, weather prediction, climate forecasts, modeling of greenhouse gas exchanges, and ecosystem monitoring
We explore the possibility of using high-density polyethylene (HDPE) moderator to limit the field of view, and the footprint of a soil moisture (SM) sensor formed of 12 Cosmic-Ray Neutron Probes (CRNP) mounted on to a mobile robotic platform (Thorvald) for better in-field localization of moisture variation
This study demonstrates a novel mobile CRNP mounted on a robotic platform for easier in-field relocation of the sensors
Summary
Soil Moisture (SM) is a crucial variable in hydrological cycles and affects weather prediction, climate studies, greenhouse gas control, hydrological modeling, weather prediction, climate forecasts, modeling of greenhouse gas exchanges, and ecosystem monitoring. Due to the spatial heterogeneity of SM, point-based techniques lack representativeness (Entin et al, 2000; Famiglietti et al, 1999; Western & Blöschl, 1999). More recently radar-based techniques, typically using satellite data, have been explored for estimating SM at the landscape scale. This method is limited by shallow penetration depths (Entekhabi et al, 2004; Njoku & Entekhabi, 1996), challenging signal analysis not least due to local variances in vegetation and surface roughness (Robinson et al, 2008), discontinuous temporal coverage, high cost and relative short life spans of satellite missions (Al-Yaari et al, 2014)
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