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 N0, 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 N0 method performed better than HMF. The performance of COSMIC was remarkably good at the semi-arid site in the USA, while the N0mod 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 N0mod 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 N0mod 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.
Highlights
Soil moisture is an important state variable in land– atmosphere interaction processes (Robinson et al, 2008), ecosystem structure, function, and diversity, and a key factor in agriculture (Siebert et al, 2005; Robinson et al, 2008; Seneviratne et al, 2010)
The simulated neutron intensities closely matched the observed neutron intensities with relative errors (MAEval divided by mean neutron intensity) between 1 and 2 %
At RB, N0 method (N0mod) seemed to have yielded the best calibration result, while hydrogen molar fraction method (HMF) and COsmic-ray Soil Moisture Interaction Code (COSMIC) showed some periods of both overand underestimation with absolute errors up to 28 cph
Summary
Soil moisture is an important state variable in land– atmosphere interaction processes (Robinson et al, 2008), ecosystem structure, function, and diversity (especially in drylands, Rodriguez-Iturbe and Porporato, 2004), and a key factor in agriculture (Siebert et al, 2005; Robinson et al, 2008; Seneviratne et al, 2010). Soil moisture content has been measured mainly with point-scale sensors (∼ 2 dm) (Topp and Ferré, 2002) or satellite sensors (e.g. Soil Moisture and Ocean Salinity (SMOS), Kerr et al, 2001) (2500–25 000 km). Soil moisture content has been measured mainly with point-scale sensors (∼ 2 dm) (Topp and Ferré, 2002) or satellite sensors (e.g. Soil Moisture and Ocean Salinity (SMOS), Kerr et al, 2001) (2500–25 000 km2) This leaves a gap at intermediate scales (∼ 1 km), relevant to hydrometeorological modelling and applications, and small watershed-scale studies (0.1–80 km). Because of the high attenuation power of hydrogen for these cosmic-ray neutrons, fast neutron intensity decreases with increasing hydrogen content within the sensor footprint (Zreda et al, 2008). The measurement depth varies between about 12 (wet conditions) and 76 cm (dry conditions) (Zreda et al, 2008)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
