Cosmic-ray neutron sensing based monitoring of snowpack dynamics: A comparison of four conversion methods

2020 ◽  
Author(s):  
Heye Reemt Bogena ◽  
Frank Herrmann ◽  
Jannis Jakobi ◽  
Vassilios Pisinaras ◽  
Cosimo Brogi ◽  
...  
Keyword(s):  
Snow Cover ◽  
Energy Transport ◽  
Snow Water Equivalent ◽  
Ground Surface ◽  
Cosmic Ray ◽  
Snow Pack ◽  
Wind Fields ◽  
Neutron Intensity ◽  
Epithermal Neutrons ◽  
Snow Water

<p>Snow monitoring instruments like snow pillows are influenced by disturbances such as energy transport into the snowpack, influences from wind fields or varying snow properties within the snowpack (e.g. ice layers). The intensity of epithermal neutrons that are produced in the soil by cosmic radiation and measured above the ground surface is sensitive to soil moisture in the upper decimetres of the ground within a radius of hectometres. Recently, it has been shown that aboveground cosmic ray neutron sensors (CRNS) are also a promising technique to monitor snow pack development thanks to the larger support that they provide and to the lower need for maintenance compared to conventional sensor systems. The basic principle is that snow water moderates neutron intensity in the footprint of the CRNS probe. The epithermal neutrons originating from the soil become increasingly attenuated with increasing depth of the snow cover, so that the neutron intensity measured by the CRN probe above the snow cover is directly related to the snow water equivalent.</p><p>In this paper, we use long-term CRNS measurements in the Pinios Hydrologic Observatory, Greece, to test different methods for the conversion from neutron count rates to snow pack characteristics, namely: i) linear regression, ii) the standard N<sub>0</sub>-calibration function, iii) a physically-based calibration approach and iv) the thermal to epithermal neutron ratio. The latter was also tested for its reliability in determining the start and end of snowpack development, respectively. The CRNS-derived snow pack dynamics are compared with snow depth measurements by a sonic sensor located near the CRNS probe. In the presentation, we will discuss the accuracy of the four conversion methods and provide recommendations for the application of CRNS-based snow pack measurements.</p>

scholarly journals Sensing Area‐Average Snow Water Equivalent with Cosmic‐Ray Neutrons: The Influence of Fractional Snow Cover

2019 ◽  
Vol 55 (12) ◽  
pp. 10796-10812 ◽  
Author(s):  
P. Schattan ◽  
M. Köhli ◽  
M. Schrön ◽  
G. Baroni ◽  
S. E. Oswald
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Cosmic Ray ◽  
Fractional Snow Cover ◽  
Snow Water

scholarly journals Spatial and temporal variability of snow depth and ablation rates in a small mountain catchment

2010 ◽  
Vol 4 (2) ◽  
pp. 215-225 ◽  
Author(s):  
T. Grünewald ◽  
M. Schirmer ◽  
R. Mott ◽  
M. Lehning
Keyword(s):  
Snow Cover ◽  
Temporal Variability ◽  
Snow Depth ◽  
Energy Transport ◽  
Snow Water Equivalent ◽  
Laser Scanner ◽  
Ablation Rate ◽  
Spatial And Temporal Variability ◽  
M Cell ◽  
Snow Water

Abstract. The spatio-temporal variability of the mountain snow cover determines the avalanche danger, snow water storage, permafrost distribution and the local distribution of fauna and flora. Using a new type of terrestrial laser scanner, which is particularly suited for measurements of snow covered surfaces, snow depth was monitored in a high alpine catchment during an ablation period. From these measurements snow water equivalents and ablation rates were calculated. This allowed us for the first time to obtain a high resolution (2.5 m cell size) picture of spatial variability of the snow cover and its temporal development. A very high variability of the snow cover with snow depths between 0–9 m at the end of the accumulation season was observed. This variability decreased during the ablation phase, while the dominant snow deposition features remained intact. The average daily ablation rate was between 15 mm/d snow water equivalent at the beginning of the ablation period and 30 mm/d at the end. The spatial variation of ablation rates increased during the ablation season and could not be explained in a simple manner by geographical or meteorological parameters, which suggests significant lateral energy fluxes contributing to observed melt. It is qualitatively shown that the effect of the lateral energy transport must increase as the fraction of snow free surfaces increases during the ablation period.

scholarly journals Calibration of a non-invasive cosmic-ray probe for wide area snow water equivalent measurement

2016 ◽  
Vol 10 (3) ◽  
pp. 1181-1190 ◽  
Author(s):  
Mark J. P. Sigouin ◽  
Bing C. Si
Keyword(s):  
Remote Sensing ◽  
Linear Regression ◽  
Soil Water ◽  
Snow Water Equivalent ◽  
Pearson Correlation ◽  
Water Storage ◽  
Cosmic Ray ◽  
Soil Water Storage ◽  
Neutron Intensity ◽  
Snow Water

Abstract. Measuring snow water equivalent (SWE) is important for many hydrological purposes such as modelling and flood forecasting. Measurements of SWE are also crucial for agricultural production in areas where snowmelt runoff dominates spring soil water recharge. Typical methods for measuring SWE include point measurements (snow tubes) and large-scale measurements (remote sensing). We explored the potential of using the cosmic-ray soil moisture probe (CRP) to measure average SWE at a spatial scale between those provided by snow tubes and remote sensing. The CRP measures above-ground moderated neutron intensity within a radius of approximately 300 m. Using snow tubes, surveys were performed over two winters (2013/2014 and 2014/2015) in an area surrounding a CRP in an agricultural field in Saskatoon, Saskatchewan, Canada. The raw moderated neutron intensity counts were corrected for atmospheric pressure, water vapour, and temporal variability of incoming cosmic-ray flux. The mean SWE from manually measured snow surveys was adjusted for differences in soil water storage before snowfall between both winters because the CRP reading appeared to be affected by soil water below the snowpack. The SWE from the snow surveys was negatively correlated with the CRP-measured moderated neutron intensity, giving Pearson correlation coefficients of −0.90 (2013/2014) and −0.87 (2014/2015). A linear regression performed on the manually measured SWE and moderated neutron intensity counts for 2013/2014 yielded an r2 of 0.81. Linear regression lines from the 2013/2014 and 2014/2015 manually measured SWE and moderated neutron counts were similar; thus differences in antecedent soil water storage did not appear to affect the slope of the SWE vs. neutron relationship. The regression equation obtained from 2013/2014 was used to model SWE using the moderated neutron intensity data for 2014/2015. The CRP-estimated SWE for 2014/2015 was similar to that of the snow survey, with an root-mean-square error of 8.8 mm. The CRP-estimated SWE also compared well to estimates made using snow depths at meteorological sites near (< 10 km) the CRP. Overall, the empirical equation presented provides acceptable estimates of average SWE using moderated neutron intensity measurements. Using a CRP to monitor SWE is attractive because it delivers a continuous reading, can be installed in remote locations, requires minimal labour, and provides a landscape-scale measurement footprint.

scholarly journals The Effect of Snow Distribution on Gamma-Ray Survey of Snow Cover

1985 ◽  
Vol 6 ◽  
pp. 211-214
Author(s):  
Morten Johnsrud
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Gamma Ray ◽  
Snow Water Equivalent ◽  
Ground Surface ◽  
Snow Water ◽  
Snow Distribution ◽  
One Year ◽  
Source Of Error ◽  
Small Elements

Topography and snowdrifts may cause large variations in the snow cover as well as in snow depth from one year to another. A simple model is developed to study the influence of different snow distributions and the importance of this as a source of error. The ground surface “seen” from the detector will appear as a disc that can be divided into a number of small elements where it is possible to place the wanted snow distribution. Calculations of the gamma radiation field with different snow distributions show how small changes in the snow cover and distribution will influence the measurements as a function of the average snow water equivalent.

scholarly journals Calibration of a non-invasive cosmic-ray probe for wide area snow water equivalent measurement

2016 ◽  
Author(s):  
M. J. P. Sigouin ◽  
B. C. Si
Keyword(s):  
Remote Sensing ◽  
Linear Regression ◽  
Soil Water ◽  
Snow Water Equivalent ◽  
Water Storage ◽  
Cosmic Ray ◽  
Measurement Scale ◽  
Soil Water Storage ◽  
Neutron Intensity ◽  
Snow Water

Abstract. Measuring snow water equivalent (SWE) is important for many hydrological purposes such as modeling and flood forecasting. Measurements of SWE are also crucial for agricultural production in areas where snowmelt runoff dominates spring soil water recharge. Typical methods for measuring SWE include point measurements (snow tubes) and large-scale measurements (remote sensing). We explored the potential of using the cosmic-ray soil moisture probe (CRP) to measure average SWE at a measurement scale between those provided by snow tubes and remote sensing. The CRP measures above ground moderated neutron intensity within a radius of approximately 300 m. Using snow tubes, surveys were performed over two winters (2013/2014 and 2014/2015) in an area surrounding a CRP in an agricultural field in Saskatoon, Saskatchewan, CAN. The raw moderated neutron intensity counts were corrected for atmospheric pressure, water vapor, and temporal variability of incoming cosmic ray flux. The mean SWE from manually measured snow surveys was adjusted for differences in soil water storage before snowfall between both winters because the CRP reading appeared to be affected by soil water below the snowpack. The SWE from the snow surveys was negatively correlated with the CRP-measured moderated neutron intensity, giving Pearson correlation coefficients of −0.92 (2013/2014) and −0.94 (2014/2015). A linear regression performed on the manually measured SWE and moderated neutron intensity counts for 2013/2014 yielded an r2 of 0.84. Linear regression lines from the 2013/2014 and 2014/2015 manually measured SWE and moderated neutron counts were very similar, thus differences in antecedent soil water storage did not appear to affect the slope of the SWE vs. neutron relationship. The regression equation obtained from 2013/2014 was used to model SWE using the moderated neutron intensity data for 2014/2015. The CRP-estimated SWE for 2014/2015 was similar to that of the snow survey, with a RMSE of 7.7 mm. The CRP-estimated SWE also compared well to estimates made using snow depths at meteorological sites near (< 10 km) the CRP. Overall, the empirical equation presented provides acceptable estimates of average SWE using moderated neutron intensity measurements. Using a CRP to monitor SWE is attractive because it delivers a continuous reading, can be installed in remote locations, requires minimal labour, and provides a landscape-scale measurement footprint.

scholarly journals The Effect of Snow Distribution on Gamma-Ray Survey of Snow Cover

1985 ◽  
Vol 6 ◽  
pp. 211-214
Author(s):  
Morten Johnsrud
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Gamma Ray ◽  
Snow Water Equivalent ◽  
Ground Surface ◽  
Snow Water ◽  
Snow Distribution ◽  
One Year ◽  
Source Of Error ◽  
Small Elements

Topography and snowdrifts may cause large variations in the snow cover as well as in snow depth from one year to another. A simple model is developed to study the influence of different snow distributions and the importance of this as a source of error. The ground surface “seen” from the detector will appear as a disc that can be divided into a number of small elements where it is possible to place the wanted snow distribution. Calculations of the gamma radiation field with different snow distributions show how small changes in the snow cover and distribution will influence the measurements as a function of the average snow water equivalent.

scholarly journals Snow mass decrease in the Northern Hemisphere (1979/80–2010/11)

2014 ◽  
Vol 8 (6) ◽  
pp. 5623-5644 ◽  
Author(s):  
Z. Li ◽  
J. Liu ◽  
L. Huang ◽  
N. Wang ◽  
B. Tian ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Supply ◽  
Snow Cover ◽  
Northern Hemisphere ◽  
Total Mass ◽  
Snow Water Equivalent ◽  
Reliable Data ◽  
Snow Pack ◽  
Snow Water ◽  
Snow Mass

Abstract. Snow cover has a key effect on climate change and hydrological cycling, as well as water supply to a sixth of the world's population across the Northern Hemisphere. However, reliable data on trends in snow cover in the Northern Hemisphere is lacking. Snow water equivalent (SWE) is a common measure of the amount of equivalent water of the snow pack. Here we verify the accuracy of three existing global SWE products and merge the most accurate aspects of them to generate a new SWE product covering the last 32 years (1979/80–2010/11). Using this new SWE product, we show that there has been a significant decreasing trend in the total mass of snow in the Northern Hemisphere. The most notable changes in total snow mass are −16.45 ± 6.68 and −13.55 ± 7.80 Gt year−1 in January and February, respectively. These are followed by March and December, which have trends of −12.58 ± 6.88 and −10.70 ± 5.62 Gt year−1, respectively, from 1979/80 to 2010/11. During the same period, the temperature in the study area raised 0.17 °C decade−1, which is thought to be the main reason of SWE decline.

scholarly journals Analysis of the Snow Water Equivalent at the AEMet-Formigal Field Laboratory (Spanish Pyrenees) During the 2019/2020 Winter Season Using a Stepped-Frequency Continuous Wave Radar (SFCW)

2021 ◽  
Vol 13 (4) ◽  
pp. 616
Author(s):  
Rafael Alonso ◽  
José María García del Pozo ◽  
Samuel T. Buisán ◽  
José Adolfo Álvarez
Keyword(s):  
Software Defined Radio ◽  
Continuous Wave ◽  
Snow Water Equivalent ◽  
Cosmic Ray ◽  
Relative Dielectric Permittivity ◽  
Near Surface ◽  
Wave Radar ◽  
Spanish Pyrenees ◽  
Snow Water ◽  
Stepped Frequency

Snow makes a great contribution to the hydrological cycle in cold regions. The parameter to characterize available the water from the snow cover is the well-known snow water equivalent (SWE). This paper presents a near-surface-based radar for determining the SWE from the measured complex spectral reflectance of the snowpack. The method is based in a stepped-frequency continuous wave radar (SFCW), implemented in a coherent software defined radio (SDR), in the range from 150 MHz to 6 GHz. An electromagnetic model to solve the electromagnetic reflectance of a snowpack, including the frequency and wetness dependence of the complex relative dielectric permittivity of snow layers, is shown. Using the previous model, an approximated method to calculate the SWE is proposed. The results are presented and compared with those provided by a cosmic-ray neutron SWE gauge over the 2019–2020 winter in the experimental AEMet Formigal-Sarrios test site. This experimental field is located in the Spanish Pyrenees at an elevation of 1800 m a.s.l. The results suggest the viability of the approximate method. Finally, the feasibility of an auxiliary snow height measurement sensor based on a 120 GHz frequency modulated continuous wave (FMCW) radar sensor, is shown.

scholarly journals The Spatiotemporal Patterns and Interrelationships of Snow Cover and Climate Change in Tianshan Mountains

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 404
Author(s):  
Tong Heng ◽  
Xinlin He ◽  
Lili Yang ◽  
Jiawen Yu ◽  
Yulin Yang ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Warming Trend ◽  
Tianshan Mountains ◽  
Spatiotemporal Patterns ◽  
Tianshan Mountain ◽  
Mountainous Areas ◽  
The Future ◽  
Snow Water ◽  
Nighttime Warming

To reveal the spatiotemporal patterns of the asymmetry in the Tianshan mountains’ climatic warming, in this study, we analyzed climate and MODIS snow cover data (2001–2019). The change trends of asymmetrical warming, snow depth (SD), snow coverage percentage (SCP), snow cover days (SCD) and snow water equivalent (SWE) in the Tianshan mountains were quantitatively determined, and the influence of asymmetrical warming on the snow cover activity of the Tianshan mountains were discussed. The results showed that the nighttime warming rate (0.10 °C per decade) was greater than the daytime, and that the asymmetrical warming trend may accelerate in the future. The SCP of Tianshan mountain has reduced by 0.9%. This means that for each 0.1 °C increase in temperature, the area of snow cover will reduce by 5.9 km2. About 60% of the region’s daytime warming was positively related to SD and SWE, and about 48% of the region’s nighttime warming was negatively related to SD and SWE. Temperature increases were concentrated mainly in the Pamir Plateau southwest of Tianshan at high altitudes and in the Turpan and Hami basins in the east. In the future, the western and eastern mountainous areas of the Tianshan will continue to show a warming trend, while the central mountainous areas of the Tianshan mountains will mainly show a cooling trend.

scholarly journals Estimating snow water equivalent using cosmic‐ray neutron sensors from the COSMOS‐UK network

2021 ◽  
Author(s):  
J. R. Wallbank ◽  
S. J. Cole ◽  
R. J. Moore ◽  
S. R. Anderson ◽  
E. J. Mellor
Keyword(s):  
Snow Water Equivalent ◽  
Cosmic Ray ◽  
Snow Water ◽  
Neutron Sensors
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