Assessment of operational monitoring of snow water equivalent measurements with low-cost GNSS sensors

2020 ◽  
Author(s):  
Achille Capelli ◽  
Franziska Koch ◽  
Patrik Henkel ◽  
Markus Lamm ◽  
Christoph Marty ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Low Cost ◽  
Elevation Gradient ◽  
Swiss Alps ◽  
Mountain Areas ◽  
Promising Alternative ◽  
Wet Snow ◽  
Snow Water

<p>The water stored in the snowpack is a crucial contribution to the hydrological cycle in mountain areas. Estimating the spatial distribution and temporal evolution of snow water equivalent (SWE) in mountain regions is, therefore, a key question in snow hydrology research. For this reason, direct measurements of SWE are still essential, but they are often scarce, not easy to install and maintain, mostly non-continuous or rather expensive. A promising alternative to conventional SWE in-situ measurement methods is a newly developed method based on signals of the freely available Global Navigation Satellite System (GNSS), which can be received with standard low-cost sensors. In general, this measurement technique is based on signal differences between one GNSS antenna buried below the snowpack and one reference antenna above the snow cover. The signal differences reflect the GNSS carrier phase time delay and the GNSS signals strength attenuation within the snowpack, which can be translated into SWE and the snow liquid water content (LWC). So far, this method showed excellent results over several years at the high-alpine test and validation site Weissfluhjoch (Eastern Swiss Alps, 2540 m asl.). Currently, our aim is to assess whether this method is suitable for deriving SWE continuously with reasonable accuracy also at other locations with different characteristics. Therefore, we set up further GNSS sensors at different elevations, where the snow characteristics can vary considerably. At lower elevations the snow cover is normally shallower and is more frequently subject to melt-freeze cycles leading to faster snow aging and different snow densities. Moreover, rapid transition from dry- to wet-snow conditions as well as steep valley sites can be seen as a challenge. In total, we were operating for two season four GNSS stations along a steep elevation gradient (820 m, 1185 m, 1510 m, and 2540 m asl.) within only a few kilometres in the Eastern Swiss Alps. For validation purposes, we monitored SWE and snow height manually and with additional automatic sensors at all locations. We analysed the GNSS SWE derivation accuracy in general and in detail for different meteorological conditions as snowfall, snow settlement, rain on snow and dry or wet snow periods. Eventually, we compared the GNSS results with results from numerical snow cover models.</p>

scholarly journals GNSS signal-based snow water equivalent determination for different snowpack conditions along a steep elevation gradient

2021 ◽  
Author(s):  
Achille Capelli ◽  
Franziska Koch ◽  
Patrick Henkel ◽  
Markus Lamm ◽  
Florian Appel ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Low Cost ◽  
Elevation Gradient ◽  
Liquid Water Content ◽  
Climatic Conditions ◽  
Swiss Alps ◽  
Snow Density ◽  
Validation Data ◽  
Snow Water ◽  
Snow Conditions

Abstract. Snow water equivalent (SWE) can be measured using low-cost Global Navigation Satellite System (GNSS) sensors with one antenna placed below the snowpack and another one serving as a reference above the snow. The underlying GNSS signal-based algorithm for SWE determination for dry- and wet-snow conditions processes the carrier phases and signal strengths and derives additionally liquid water content (LWC) and snow depth (HS). So far, the algorithm was tested intensively for high-alpine conditions with distinct seasonal accumulation and ablation phases. In general, snow occurrence, snow amount, snow density and LWC can vary considerably with climatic conditions and elevation. Regarding alpine regions, lower elevations mean generally earlier and faster melting, more rain-on-snow events and shallower snowpack. Therefore, we assessed the applicability of the GNSS-based SWE measurement at four stations along a steep elevation gradient (820, 1185, 1510 and 2540 m a.s.l.) in the eastern Swiss Alps during two winter seasons (2018–2020). Reference data of SWE, LWC and HS were collected manually and with additional automated sensors at all locations. The GNSS-derived SWE estimates agreed very well with manual reference measurements along the elevation gradient and the accuracy (RMSE = 34 mm, RMSRE = 11 %) was similar under wet- and dry-snow conditions, although significant differences in snow density and meteorological conditions existed between the locations. The GNSS-derived SWE was more accurate than measured with other automated SWE sensors. However, with the current version of the GNSS algorithm, the determination of daily changes of SWE was found to be less suitable compared to manual measurements or pluviometer recordings and needs further refinement. The values of the GNSS-derived LWC were robust and within the precision of the manual and radar measurements. The additionally derived HS correlated well with the validation data. We conclude that SWE can reliably be determined using low-cost GNSS-sensors under a broad range of climatic conditions and LWC and HS are valuable add-ons.

scholarly journals Long-Term Records of Snow Cover Water Equivalent in the Swiss Alps

1994 ◽  
Vol 25 (1-2) ◽  
pp. 53-64 ◽  
Author(s):  
M. B. Rohrer ◽  
L. N. Braun ◽  
H. Lang
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Water Cycle ◽  
Swiss Alps ◽  
Special Investigation ◽  
Quality Aspects ◽  
Snow Water ◽  
Ranking Order ◽  
Seasonal Discharge

The snow-water equivalent (SWE) of the seasonal snow cover is an important component of the water cycle in the Swiss Alps. It is used for predicting seasonal discharge, for short-range discharge forecasts and also for assessing water quality aspects. The SWE has been measured every two weeks at about 50 stations located between 860 and 2,540 m a.s.l. for more than 30 years. In addition there are special investigation areas with stations located between 600 m and 2,900 m a.s.l. where SWE is measured once per winter. The main characteristics of temporal and spatial SWE distributions are analyzed. The variations of SWE values depend in ranking order on elevation, on the year-to-year variations, on the region and on the exposition. The standardized SWE-values depend mostly on the year-to-year variations and on the region.

scholarly journals Effect of Forest Ecosystems on the Snow Water Equivalent in Relation to Aspect And Elevation in the Hučava River Watershed, Poľana Biosphere Reserve (Slovakia)

2017 ◽  
Vol 36 (3) ◽  
pp. 268-280 ◽  
Author(s):  
Michal Mikloš ◽  
Ilja Vyskot ◽  
Tomáš Šatala ◽  
Katarína Korísteková ◽  
Martin Jančo ◽  
...  
Keyword(s):  
Snow Cover ◽  
Forest Ecosystem ◽  
Forest Ecosystems ◽  
Snow Water Equivalent ◽  
Elevation Gradient ◽  
Biosphere Reserve ◽  
European Beech ◽  
Beech Forests ◽  
Spruce Forests ◽  
Snow Water

AbstractThe aim of this work was to assess how forest ecosystems dominated by Norway spruce (Picea abies (L.) or European beech (Fagus sylvatica L.) affect snow water equivalent (SWE) in relation to aspect and elevation. The research plots were established in a small headwater watershed of the Hučava flow belonging to the Poľana Biosphere Reserve (Central Europe, Inner Western Carpathians). The SWE values in this watershed (approximately 580–1270 m a.s.l.) were monitored during the three winter seasons starting from 2012–2013 to 2014–2015. The results revealed high variability in SWE and in snow cover duration between the studied seasons. The spatial variability was significantly affected by the forest ecosystem, aspect and elevation. The seasonal mean SWE value was lower by about 50–60% in the spruce forests and by about 21–30% in the beech forests compared to the open areas (100%). Over the whole seasons, the whole watershed mean SWE value on the slopes with the northern aspect was mostly higher compared to the slopes with the southern aspect. The effect of aspect was significant mainly in the open areas and in the forests dominated by European beech during the ablation periods of every season. In the case of the sufficient snow cover, the mean SWE value always increased with elevation. The elevation gradient of SWE was steepest at the open areas of the watershed in the peaks of the winter seasons. The three-season mean value of SWE elevation gradient (per 100 m) at the time of snow accumulation peak was equal to 16 mm in the spruce forests, 20 mm in the beech forests and 26 mm in the open areas. The research revealed that SWE is significantly affected by the forest ecosystem whilst its effect is dependent on the occurrence of dominant deciduous or coniferous tree species. However, the effect of forests is closely related to topographic characteristics (aspect and elevation) of a locality.

scholarly journals Discrimination of a wet snow cover using passive microwave satellite data

1993 ◽  
Vol 17 ◽  
pp. 307-311 ◽  
Author(s):  
A.E. Walker ◽  
B.E. Goodison
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Western Canada ◽  
Polarization Data ◽  
Wet Snow ◽  
Snow Water ◽  
Remote Sensing Methods

Snow-cover monitoring using passive microwave remote sensing methods has been shown to be seriously limited under melt conditions when the snowpack becomes wet. A wet snow indicator has been developed using DMSP SSM/I 37 GHz dual-polarization data for the open prairie region of western Canada. The indicator is used to identify areas of wet snow and discriminate them from areas of snow-free land. Validation and testing efforts have illustrated that the addition of the indicator to the current SSM/I snow water equivalent algorithm provides a more accurate representation of spatial snow coverage throughout the winter season for the open prairie region. The improved spatial and temporal information resulting from the use of the indicator enhances both climatological and hydrological analyses of snow-cover conditions using passive microwave data. Although the wet snow indicator has only been validated for the open prairie region of western Canada, it may also be applicable to other regions of similar terrain and vegetative characteristics. However, in areas of dense vegetation, such as the boreal forest, the performance of the indicator is poor due to the generally low 37 GHz polarization differences of the vegetation cover.

Seasonal snow accumulation in the mid-latitude forested catchment

Biologia ◽  
2014 ◽  
Vol 69 (11) ◽  
Author(s):  
Václav Šípek ◽  
Miroslav Tesař
Keyword(s):  
Snow Cover ◽  
Forest Canopy ◽  
Forest Cover ◽  
Snow Water Equivalent ◽  
Elevation Gradient ◽  
Snow Accumulation ◽  
Forested Catchment ◽  
Seasonal Snow ◽  
Snow Water ◽  
Fagus Sylvatica L

AbstractThe study deals with the snow cover characteristics (snow depth — SD and snow water equivalent — SWE) concerning the mid-latitude forested catchment. Namely, the influence of the forest canopy (Picea abies (L.) Karst. and Fagus sylvatica L.) and altitude (ranging from 835 m a.s.l. to 1118 m a.s.l.) was investigated. Forest cover was proved to have a significant influence on the snow cover accumulation, reducing SWE by 50 % on average, compared to open sites. The elevation gradient concerning SWE ranged from 30 to 40 mm and from 5 to 20 mm per 100 m in open and forested sites, respectively. Its magnitude was found to be temporarily variable and positively related to the total seasonal snowfall amount. The SWE/SD variability among measurement sites (with different altitude) was higher in open sites compared to forested ones. The catchment SWE/SD variability increases significantly in the snowmelt period (March–April) both in open and forested locations. The differences among snow interception losses, concerning various elevations and the forest canopy, were not statistically significant.

scholarly journals Discrimination of a wet snow cover using passive microwave satellite data

1993 ◽  
Vol 17 ◽  
pp. 307-311 ◽  
Author(s):  
A.E. Walker ◽  
B.E. Goodison
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Western Canada ◽  
Polarization Data ◽  
Wet Snow ◽  
Snow Water ◽  
Remote Sensing Methods

Snow-cover monitoring using passive microwave remote sensing methods has been shown to be seriously limited under melt conditions when the snowpack becomes wet. A wet snow indicator has been developed using DMSP SSM/I 37 GHz dual-polarization data for the open prairie region of western Canada. The indicator is used to identify areas of wet snow and discriminate them from areas of snow-free land. Validation and testing efforts have illustrated that the addition of the indicator to the current SSM/I snow water equivalent algorithm provides a more accurate representation of spatial snow coverage throughout the winter season for the open prairie region. The improved spatial and temporal information resulting from the use of the indicator enhances both climatological and hydrological analyses of snow-cover conditions using passive microwave data. Although the wet snow indicator has only been validated for the open prairie region of western Canada, it may also be applicable to other regions of similar terrain and vegetative characteristics. However, in areas of dense vegetation, such as the boreal forest, the performance of the indicator is poor due to the generally low 37 GHz polarization differences of the vegetation cover.

scholarly journals Variations of the Snow Water Equivalent in the Ourika Catchment (Morocco) over 2000–2018 Using Downscaled MERRA-2 Data

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1120 ◽  
Author(s):  
Mohamed Baba ◽  
Simon Gascoin ◽  
Lionel Jarlan ◽  
Vincent Simonneaux ◽  
Lahoucine Hanich
Keyword(s):  
Snow Cover ◽  
River Flow ◽  
Snow Water Equivalent ◽  
Temporal Variations ◽  
In Situ Measurements ◽  
High Mountain ◽  
Snow Cover Area ◽  
Mountain Areas ◽  
Snow Water

The Ourika River is an important tributary of the Tensift River in the water-stressed region of Marrakesh (Morocco). The Ourika river flow is dominated by the snow melt contribution from the High Atlas mountains. Despite its importance in terms of water resources, the snow water equivalent (SWE) is poorly monitored in the Ourika catchment. Here, we used MERRA-2 data to run a distributed energy-balance snowpack model (SnowModel) over 2000–2018. MERRA-2 data were downscaled to 250-m spatial resolution using a digital elevation model. The model outputs were compared to in situ measurements of snow depth, precipitation, river flow and remote sensing observations of the snow cover area from MODIS. The results indicate that the model provides an overall acceptable representation of the snow cover dynamics given the coarse resolution of the MERRA-2 forcing. Then, we used the model output to analyze the spatio-temporal variations of the SWE in the Ourika catchment for the first time. We suggest that MERRA-2 data, which are routinely available with a delay of a few weeks, can provide valuable information to monitor the snow resource in high mountain areas without in situ measurements.

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.

Catchment-scale evaluation of pollution potential of urban snow at two residential catchments in southern Finland

2013 ◽  
Vol 68 (10) ◽  
pp. 2164-2170 ◽  
Author(s):  
Nora Sillanpää ◽  
Harri Koivusalo
Keyword(s):  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Cold Climate ◽  
Road Maintenance ◽  
Catchment Scale ◽  
Small Surface ◽  
Climate Conditions ◽  
Snow Water ◽  
High Level ◽  
Mass Loads

Despite the crucial role of snow in the hydrological cycle in cold climate conditions, monitoring studies of urban snow quality often lack discussions about the relevance of snow in the catchment-scale runoff management. In this study, measurements of snow quality were conducted at two residential catchments in Espoo, Finland, simultaneously with continuous runoff measurements. The results of the snow quality were used to produce catchment-scale estimates of areal snow mass loads (SML). Based on the results, urbanization reduced areal snow water equivalent but increased pollutant accumulation in snow: SMLs in a medium-density residential catchment were two- to four-fold higher in comparison with a low-density residential catchment. The main sources of pollutants were related to vehicular traffic and road maintenance, but also pet excrement increased concentrations to a high level. Ploughed snow can contain 50% of the areal pollutant mass stored in snow despite its small surface area within a catchment.

scholarly journals Nimbus-7 SMMR Derived Global Snow Cover Parameters

1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Theoretical Calculations ◽  
Winter Season ◽  
Western China ◽  
High Plains ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Snow covers about 40 million km2of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

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