Investigating temporal field sampling strategies for site-specific calibration of three soil moisture–neutron intensity parameterisation methods

Abstract

Abstract. The Cosmic-Ray Neutron Sensor (CRNS) can provide soil moisture information at scales relevant to hydrometeorological modelling applications. Site-specific calibration is needed to translate CRNS neutron intensities into sensor footprint average soil moisture contents. We investigated temporal sampling strategies for calibration of three CRNS parameterisations (modified N 0 , HMF, and COSMIC) by assessing the effects of the number of sampling days and soil wetness conditions on the performance of the calibration results while investigating actual neutron intensity measurements, for three sites with distinct climate and land use: a semi-arid site, a temperate grassland, and a temperate forest. When calibrated with 1 year of data, both COSMIC and the modified N 0 method performed better than HMF. The performance of COSMIC was remarkably good at the semiarid site in the USA, while the N 0mod performed best at the two temperate sites in Germany. The successful performance of COSMIC at all three sites can be attributed to the benefits of explicitly resolving individual soil layers (which is not accounted for in the other two parameterisations). To better calibrate these parameterisations, we recommend in situ soil sampled to be collected on more than a single day. However, little improvement is observed for sampling on more than 6 days. At the semi-arid site, the N 0mod method was calibrated better under site-specific average wetness conditions, whereas HMF and COSMIC were calibrated better under drier conditions. Average soil wetness condition gave better calibration results at the two humid sites. The calibration results for the HMF method were better when calibrated with combinations of days with similar soil wetness conditions, opposed to N 0mod and COSMIC, which profited from using days with distinct wetness conditions. Errors in actual neutron intensities were translated to average errors specifically to each site. At the semi-arid site, these errors were below the typical measurement uncertainties from in situ point-scale sensors and satellite remote sensing products. Nevertheless, at the two humid sites, reduction in uncertainty with increasing sampling days only reached typical errors associated with satellite remote sensing products. The outcomes of this study can be used by researchers as a CRNS calibration strategy guideline.

Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity

“…Thus they support the original hypothesis by Desilets et al (2010) of a single calibration campaign to capture the local soil moisture dynamics. The approach can thus substantially reduce the calibration efforts for CRNS probes, in contrast to recent findings from Iwema et al (2015) and Heidbüchel et al (2016).…”

“…However, outstanding features were also reported in the CRNS data which did not fit well to the accepted theory described by Desilets et al (2010). Authors suggested that additional hydrological processes and hydrogen pools could influence the signal (e.g., Franz et al, 2013a;Baatz et al, 2014;Baroni and Oswald, 2015), while others applied recalibration of semiphysical parameters to better fit individual site conditions (e.g., Rivera Villarreyes et al, 2011;Lv et al, 2014;Iwema et al, 2015;Heidbüchel et al, 2016). Despite the unambiguous improvements obtained by corrections and recalibration approaches, some features in many datasets could still not be explained using current knowledge and consequently seemed to be unrelated to hydrological processes.…”

Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

“…Moreover, given the small changes of 0 values for the 3 different calibration dates (±26 cph or 1.8% difference), we found the effects of vegetation on neutron count were likely small for this environment given the accuracy of the gravimetric calibration datasets themselves (standard error of mean ±0.02 m 3 /m 3 ). Finally, the recommendation of using a minimum of 3 calibration sampling dates at different water contents to estimate 0 was reported elsewhere [42] and is based on neutron particle transport modeling and an error propagation analysis. For best practices, we recommend a minimum of 3 gravimetric calibration periods to estimate 0 in agricultural environments.…”

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

“…Soil bulk density, soil moisture, lattice water and 12 h averaged measured neutron intensity were used to determine calibration parameters specific to each CRNS and the COSMIC operator. This represents a compromise between the measurement noise (which follows a Poisson distribution) and the assumed variation of environmental variables over the averaging time window (Iwema et al, 2015).…”