Abstract
Common snow monitoring instruments based on hydrostatic pressure such as snow pillows are often influenced by various disturbing effects, which result in a reduced quality of the snow cover and snow water equivalent estimates. Such disturbing effects include energy transport into the snowpack, wind fields, and variations of snow properties within the snowpack (e.g. ice layers). Recently, it has been shown that Cosmic-Ray Neutron Probes (CRNP) are a promising technique to monitor snow pack development. CRNP can provide larger support and need lower maintenance compared to conventional sensors. These instruments are sensitive to the intensity of epithermal neutrons that are produced in the soil by cosmic radiation and are widely used to determine soil moisture in the upper decimetres of the ground. The application of CRNP for snow monitoring is based on the principle that snow water moderates the epithermal neutron intensity, which can be directly related to the snow water equivalent (SWE) of the snow pack. In this study, long-term CRNP measurements in the Pinios Hydrologic Observatory (PHO), Greece, were used to test different methods for converting neutron count rates to snow pack characteristics: i) linear regression, ii) standard N0-calibration function, iii) a physically-based calibration approach, and iv) thermal to epithermal neutron ratio. For this, a sonic sensor located near the CRNP was used to compare CRNP-derived snow pack dynamics with snow depth measurements. We found that the above-ground CRNP is well suited for measurement of field scale SWE, which is in agreement with findings of other studies. The analysis of the accuracy of the four conversion methods showed that all methods were able to determine the mass of the snow pack during the snow events reasonably well. The N0-calibration function and the physically-based calibration function performed best and the thermal to epithermal neutron ratio performed worst. Furthermore, we found that SWE determination with above-ground CRNP can be affected by other influences (e.g. heavy rainfall). Nevertheless, CRNP-based SWE determination is a potential alternative to established method like snow depth-based SWE methods, as it provides SWE estimate for a much larger scales (12-18 ha).
Highlights
Snow accumulation dynamics are an important indicator of climate change development as it can be used to investigate modifications in precipitation patterns as well as the occurrence of increasingly strong snowmelt events that are caused by rising global temperatures (Kripalani and Kulkarni, 1999; Earman et al, 2006)
The aim of this paper is to evaluate the accuracy of the Cosmic-Ray Neutron Probes (CRNP) method for measuring snow water equivalent (SWE) dynamics at a test site situated in the Pinios Hydrologic Observatory (PHO)—central Greece
We found that the above-ground CRNP is well-suited for measurement of field scale SWE, which is in agreement with findings of other studies (e.g., Desilets et al, 2010; FIGURE 10 | Comparison of two parameterizations of (B) the epithermal regression function, (C) the neutron ratio regression function, (D) the N0 function, and (E) the physically based model for a snow event in winter 2018/19
Summary
Snow accumulation dynamics are an important indicator of climate change development as it can be used to investigate modifications in precipitation patterns as well as the occurrence of increasingly strong snowmelt events that are caused by rising global temperatures (Kripalani and Kulkarni, 1999; Earman et al, 2006). Various devices measuring temporal dynamics of SWE are available, all of which have their strengths and limitations (Pirazzini et al, 2018). These devices are based on the measurement of the mass or of the pressure of the overlying snow (e.g., snow cushions and snow scales). In the case of GPR, upward-facing systems are placed below the snowpack to obtain information about snow stratigraphy (Heilig et al, 2009) and snow depth (Schmid et al, 2014) With this technique, the penetration depth strongly depends on the measurement frequency of the GPR system. A detailed list of instruments for measuring snow properties and their strengths and limitations can be found in Pirazzini et al (2018)
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