Review article: Performance assessment of electromagnetic wave-based field sensors for SWE monitoring   

Abstract

Abstract. Continuous and spatially distributed data of snow mass (snow water equivalent, SWE) from automatic ground-based measurements are increasingly required for climate change studies and for hydrological applications (snow hydrological model improvement and data assimilation). We present and compare four new-generation non-invasive sensors that are based on electromagnetic waves for direct measurements of SWE: Cosmic Ray Neutron Probe (CNRP); Gamma Ray Monitoring (GMON) scintillator; frequency-modulated continuous-wave radar (FMCW-Radar) at 24 GHz; and Global Navigation Satellite System (GNSS) receivers for SWE retrieval. All four techniques are relatively low cost, have low power requirements, provide continuous and autonomous measurements, and can be installed in remote areas. Their operating principles are briefly summarized before examples of comparative measurements are provided. A performance review comparing their advantages, drawbacks and accuracies is discussed. Overall instrument accuracy is estimated to range between 9 and 15 %.

Snow water equivalent measurement in the Arctic based on cosmic ray neutron attenuation

“…Snow core results were averaged to represent a single value for that date. Results from Turcan and Loijens (1975), Peterson and Brown (1975), Goodison et al (1981), Sturm et al (2010), andRoyer et al (2021) state that the standard measurement error associated with using this type of snow corer ranges from 1 %-10 %.…”

“…This means the CRNSs' baselines between the two seasons are likely to be different. To consider if this explanation is reasonable, we followed the approach of Sigouin and Si (2016), also noted by Royer et al (2021), in which the authors applied a correction based on soil water storage in the top 10 cm of the soil profile and adjusted their SWE values accordingly. To follow this approach, we used an estimated water capacity of the top 10 cm soil layer to be up to 2 mm cm −1 (Blencowe et al, 1960;Ball, 2001) and assumed a 50 % soil moisture.…”

“…In practice, this further indicates that a linear regression function is well transferable in time at sites with similar soil water storage capacity -such as Elora. In a broader approach, this allows researchers and operators to set up the CRNS, even after the initial snowfall and subsequent soil freeze-up, and capture accurate SWE data so long as it is corrected for soil moisture conditions afterwards (Royer et al, 2021). Additionally, another significant advantage of utilizing a linear regression approach is that it is considerably more time efficient than fitting the full N 0 -calibration function.…”