Snowpack energy balance and changes in the frequency and extremity of rain-on-snow events in the warming climate

2021 ◽  
Author(s):  
Ondrej Hotovy ◽  
Michal Jenicek
Keyword(s):  
Energy Balance ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Winter Season ◽  
Catchment Scale ◽  
The Future ◽  
Snow Water ◽  
The Impact ◽  
Catchment Runoff

<p>Seasonal snowpack significantly influences the catchment runoff and thus represents an important input for the hydrological cycle. Changes in the precipitation distribution and intensity, as well as a shift from snowfall to rain is expected in the future due to climate changes. As a result, rain-on-snow events, which are considered to be one of the main causes of floods in winter and spring, may occur more frequently. Heat from liquid precipitation constitutes one of the snowpack energy balance components. Consequently, snowmelt and runoff may be strongly affected by these temperature and precipitation changes.</p><p>The objective of this study is 1) to evaluate the frequency, inter-annual variability and extremity of rain-on-snow events in the past based on existing measurements together with an analysis of changes in the snowpack energy balance, and 2) to simulate the effect of predicted increase in air temperature on the occurrence of rain-on-snow events in the future. We selected 40 near-natural mountain catchments in Czechia with significant snow influence on runoff and with available long-time series (>35 years) of daily hydrological and meteorological variables. A semi-distributed conceptual model, HBV-light, was used to simulate the individual components of the water cycle at a catchment scale. The model was calibrated for each of study catchments by using 100 calibration trials which resulted in respective number of optimized parameter sets. The model performance was evaluated against observed runoff and snow water equivalent. Rain-on-snow events definition by threshold values for air temperature, snow depth, rain intensity and snow water equivalent decrease allowed us to analyze inter-annual variations and trends in rain-on-snow events during the study period 1965-2019 and to explain the role of different catchment attributes.</p><p>The preliminary results show that a significant change of rain-on-snow events related to increasing air temperature is not clearly evident. Since both air temperature and elevation seem to be an important rain-on-snow drivers, there is an increasing rain-on-snow events occurrence during winter season due to a decrease in snowfall fraction. In contrast, a decrease in total number of events was observed due to the shortening of the period with existing snow cover on the ground. Modelling approach also opened further questions related to model structure and parameterization, specifically how individual model procedures and parameters represent the real natural processes. To understand potential model artefacts might be important when using HBV or similar bucket-type models for impact studies, such as modelling the impact of climate change on catchment runoff.</p>

Changes in snow storages and their impact on occurrence and extremity of runoff caused by rain-on-snow events

2020 ◽  
Author(s):  
Ondrej Hotovy ◽  
Michal Jenicek
Keyword(s):  
Air Temperature ◽  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Winter Season ◽  
Model Performance ◽  
Catchment Scale ◽  
The Future ◽  
Snow Water ◽  
The Impact ◽  
Catchment Runoff

<p>Seasonal snowpack significantly influences the catchment runoff and thus represents an important input for the hydrological cycle. Changes in the precipitation distribution and intensity, as well as a shift from snowfall to rain is expected in the future due to climate changes. As a result, rain-on-snow events, which are considered to be one of the main causes of floods in winter and spring, may occur more frequently.</p><p>The objective of this study is 1) to evaluate the frequency, inter-annual variability and extremity of rain-on-snow events in the past based on existing measurements and 2) to simulate the effect of predicted increase in air temperature on the occurrence of rain-on-snow events in the future. We selected 59 near-natural mountain catchments in Czechia with significant snow influence on runoff and with available long-time series (>35 years) of daily hydrological and meteorological variables. A semi-distributed conceptual model, HBV-light, was used to simulate the individual components of the water cycle at a catchment scale. The model was calibrated for each of study catchments by using 100 calibration trials which resulted in respective number of optimized parameter sets. The model performance was evaluated against observed runoff and snow water equivalent. Rain-on-snow events definition by threshold values for air temperature, snow depth, rain intensity and snow water equivalent decrease allowed us to analyze inter-annual variations and trends in rain-on-snow events during the study period 1980-2014 and to explain the role of different catchment attributes.</p><p>The preliminary results show that a significant change of rain-on-snow events related to increasing air temperature is not clearly evident. Since both air temperature and elevation seem to be an important rain-on-snow drivers, there is an increasing rain-on-snow events occurrence during winter season due to a decrease in snowfall fraction. In contrast, a decrease in total number of events was observed due to the shortening of the period with existing snow cover on the ground. Modelling approach also opened further questions related to model structure and parameterization, specifically how individual model procedures and parameters represent the real natural processes. To understand potential model artefacts might be important when using HBV or similar bucket-type models for impact studies, such as modelling the impact of climate change on catchment runoff.</p>

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.

ASSESSMENT OF CHANGES IN THE CHARACTERISTICS OF THE WATER, SNOW AND ICE REGIMES IN THE BASINS OF THE SMALL NORTHERN DVINA RIVER UNDER MODERN CONDITIONS AND THEIR POSSIBLE CHANGES IN THE FUTURE

2021 ◽  
pp. 117-127
Author(s):  
M. V. GEORGIEVSKY ◽  
◽  
N. I. GOROSHKOVA ◽  
V. A. KHOMYAKOVA ◽  
A. V. STRIZHENOK
Keyword(s):  
Snow Cover ◽  
Climate Warming ◽  
Snow Water Equivalent ◽  
Winter Precipitation ◽  
Spring Runoff ◽  
The Future ◽  
Snow Water ◽  
Project Data ◽  
The Impact ◽  
Slight Downward Trend

The article presents an analysis of the impact of climate change on the main characteristics of ice phenomena, snow cover and the water regime in the Small Northern Dvina River basin occurring in recent decades. Recently, a significant climate warming has been observed in the basin. As a result, winters are getting warmer and shorter. There is also an increase in winter precipitation and the number of thaws. Climate warming directly affects the duration of snow cover, which decreases both due to the later formation and to the earlier destruction of snow. There is also a slight downward trend in the annual values of the maximum snow water equivalent, which may be the result of an increase in the number of thaws in winter, when a part of the snow cover melts contributing to the winter river runoff. The analysis of the main characteristics of the ice cover on the rivers of the studied basin shows that their changes are similarly to changes in the snow cover: there is a reduction in the freeze-up period due to its later formation and earlier complete destruction. The maximum ice thickness on the rivers of the basin also tends to decrease. There is an increase in winter and a decrease in spring runoff. Predictive estimates of changes in the observed trends in the future are presented in the fi nal part of the article based on the CMIP5 project data.

Simulating the impact of future climate change on runoff processes in selected catchments of Slovakia

2021 ◽  
Author(s):  
Roman Výleta ◽  
Milica Aleksić ◽  
Patrik Sleziak ◽  
Kamila Hlavcova
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Future Climate Change ◽  
Time Horizons ◽  
The Future ◽  
The Impact ◽  
Impacts Of Climate Change

<p>The future development of the runoff conditions, as a consequence of climate change, is of great interest for water managers. Information about the potential impacts of climate change on the hydrological regime is needed for long-term planning of water resources and flood protection.</p><p>The aim of this study is to evaluate the possible impacts of climate change on the runoff regime in five selected catchments located in the territory of Slovakia. Changes in climatic characteristics (i.e., precipitation and air temperature) for future time horizons were prepared by a regional climate model KNMI using the A1B emission scenario. The selected climatic scenario predicts a general increase in air temperature and precipitation (higher in winter than in summer). For simulations of runoff under changed conditions, a lumped rainfall-runoff model (the TUW model) was used. This model belongs to a group of conceptual models and follows a structure of a widely used Swedish HBV model. The TUW model was calibrated for the period of 2011 – 2019. We assumed that this period would be similar (to recent/warmer climate) in terms of the average daily air temperatures and daily precipitation totals. The future changes in runoff due to climate change were evaluated by comparing the simulated long-term mean monthly runoff for the current state (1981-2010) and modelled scenarios in three time periods (2011-2040, 2041-2070, and 2071-2100). The results indicate that changes in the long-term runoff seasonality and extremality of hydrological cycle could be expected in the future. The runoff should increase in winter months compared to the reference period. This increase is probably related to a rise in temperature and anticipated snowmelt. Conversely, during the summer periods, a decrease in the long-term runoff could be assumed. According to modelling, these changes will be more pronounced in the later time horizons.</p><p>It should be noted that the results of the simulation are dependent on the availability of the inputs, the hydrological/climate model used, the schematization of the simulated processes, etc. Therefore, they need to be interpreted with a sufficient degree of caution</p>

Snowmelt contribution to seasonal runoff: Lessons learned from using a bucket-type model on a large set of catchments

2020 ◽  
Author(s):  
Michal Jenicek ◽  
Ondrej Ledvinka
Keyword(s):  
Groundwater Recharge ◽  
Snow Water Equivalent ◽  
Large Set ◽  
Annual Variations ◽  
Low Flows ◽  
Snow Storage ◽  
The Future ◽  
Seasonal Runoff ◽  
The Impact ◽  
Catchment Runoff

<p>The streamflow seasonality in mountain catchments is largely influenced by snow. However, a shift from snowfall to rain is expected in the future. Consequently, a decrease in snow storage and earlier snowmelt is predicted, which will cause changes in spring and summer runoff. The objectives of this study were to quantify 1) how inter-annual variations in snow storages affect spring and summer runoff, including summer low flows and 2) the importance of snowmelt in generating runoff compared to rainfall. The snow storage, groundwater recharge and streamflow were simulated for 59 mountain catchments in Czechia in the period 1980–2014 using a bucket-type catchment model. The model performance was evaluated against observed daily runoff and snow water equivalent. Hypothetical simulations were performed, which allowed us to analyse the effect of inter-annual variations in snow storage on seasonal runoff separately from other components of the water balance. This was done in the HBV snow routine using the threshold temperature T<sub>T</sub> that differentiates between snow and rain and sets the air temperature of snowmelt onset. By changing the T<sub>T</sub>, we can control the amount of accumulated snow and snowmelt timing, while other variables remain unaffected.</p><p>The results showed that 17-42% (26% on average) of the total runoff in study catchments originates as snowmelt, despite the fact that only 12-37% (20% on average) of the precipitation falls as snow. This means that snow is more effective in generating catchment runoff compared to liquid precipitation. This was documented by modelling experiments which showed that total annual runoff and groundwater recharge decreases in the case of a precipitation shift from snow to rain. In general, snow-poor years are clearly characterized by a lower snowmelt runoff contribution compared to snow-rich years in the analysed period. Additionally, snowmelt started earlier in these snow-poor years and caused lower groundwater recharge. This also affected summer baseflow. For most of the catchments, the lowest summer baseflow was reached in years with both relatively low summer precipitation and snow storage. This showed that summer low flows (directly related to baseflow) in our study catchments are not only a function of low precipitation and high evapotranspiration, but they are significantly affected by previous winter snowpack. This effect might intensify the summer low flows in the future when generally less snow is expected.</p><p>Modelling experiments also opened further questions related to model structure and parameterization, specifically how individual model procedures and parameters represent the real natural processes. To understand potential model artefacts might be important when using HBV or similar bucket-type models for impact studies, such as modelling the impact of climate change on catchment runoff.</p>

scholarly journals <i>ESCIMO.spread</i> – a spreadsheet-based point snow surface energy balance model to calculate hourly snow water equivalent and melt rates for historical and changing climate conditions

2010 ◽  
Vol 3 (2) ◽  
pp. 627-649 ◽  
Author(s):  
U. Strasser ◽  
T. Marke
Keyword(s):  
Energy Balance ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Longwave Radiation ◽  
Energy Balance Model ◽  
Balance Model ◽  
Snow Surface ◽  
Point Energy ◽  
Climate Conditions ◽  
Snow Water

Abstract. This paper describes the spreadsheet-based point energy balance model ESCIMO.spread which simulates the energy and mass balance as well as melt rates of a snow surface. The model makes use of hourly recordings of temperature, precipitation, wind speed, relative humidity, global and longwave radiation. The effect of potential climate change on the seasonal evolution of the snow cover can be estimated by modifying the time series of observed temperature and precipitation by means of adjustable parameters. Model output is graphically visualized in hourly and daily diagrams. The results compare well with weekly measured snow water equivalent (SWE). The model is easily portable and adjustable, and runs particularly fast: hourly calculation of a one winter season is instantaneous on a standard computer. ESICMO.spread can be obtained from the authors on request (contact: [email protected]).

scholarly journals <i>ESCIMO.spread</i> – a spreadsheet-based point snow surface energy balance model to calculate hourly snow water equivalent and melt rates for historical and changing climate conditions

2010 ◽  
Vol 3 (2) ◽  
pp. 643-652 ◽  
Author(s):  
U. Strasser ◽  
T. Marke
Keyword(s):  
Energy Balance ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Longwave Radiation ◽  
Energy Balance Model ◽  
Balance Model ◽  
Snow Surface ◽  
Point Energy ◽  
Climate Conditions ◽  
Snow Water

Abstract. This paper describes the spreadsheet-based point energy balance model ESCIMO.spread which simulates the energy and mass balance as well as melt rates at the snow surface. The model makes use of hourly recordings of temperature, precipitation, wind speed, relative humidity, and incoming global and longwave radiation. The effect of potential climate change on the seasonal evolution of the snow cover can be estimated by modifying the time series of observed temperature and precipitation by means of adjustable parameters. Model output is graphically visualized in hourly and daily diagrams. The results compare well with weekly measured snow water equivalent (SWE). The model is easily portable and adjustable, and runs particularly fast: an hourly calculation of a one winter season is instantaneous on a standard computer. ESCIMO.spread can be obtained from the authors on request.

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 Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

2019 ◽  
Vol 13 (11) ◽  
pp. 3045-3059 ◽  
Author(s):  
Nick Rutter ◽  
Melody J. Sandells ◽  
Chris Derksen ◽  
Joshua King ◽  
Peter Toose ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Layer Thickness ◽  
Snow Water Equivalent ◽  
Estimation Accuracy ◽  
Snow Layer ◽  
Data Set ◽  
Snow Water ◽  
Retrieval Errors ◽  
Snow Microstructure ◽  
The Impact

Abstract. Spatial variability in snowpack properties negatively impacts our capacity to make direct measurements of snow water equivalent (SWE) using satellites. A comprehensive data set of snow microstructure (94 profiles at 36 sites) and snow layer thickness (9000 vertical profiles across nine trenches) collected over two winters at Trail Valley Creek, NWT, Canada, was applied in synthetic radiative transfer experiments. This allowed for robust assessment of the impact of estimation accuracy of unknown snow microstructural characteristics on the viability of SWE retrievals. Depth hoar layer thickness varied over the shortest horizontal distances, controlled by subnivean vegetation and topography, while variability in total snowpack thickness approximated that of wind slab layers. Mean horizontal correlation lengths of layer thickness were less than a metre for all layers. Depth hoar was consistently ∼30 % of total depth, and with increasing total depth the proportion of wind slab increased at the expense of the decreasing surface snow layer. Distinct differences were evident between distributions of layer properties; a single median value represented density and specific surface area (SSA) of each layer well. Spatial variability in microstructure of depth hoar layers dominated SWE retrieval errors. A depth hoar SSA estimate of around 7 % under the median value was needed to accurately retrieve SWE. In shallow snowpacks <0.6 m, depth hoar SSA estimates of ±5 %–10 % around the optimal retrieval SSA allowed SWE retrievals within a tolerance of ±30 mm. Where snowpacks were deeper than ∼30 cm, accurate values of representative SSA for depth hoar became critical as retrieval errors were exceeded if the median depth hoar SSA was applied.

Exploring the use of gpr and satellite-based snow data for snowmelt runoff predictions

2021 ◽  
Author(s):  
Ilaria Clemenzi ◽  
David Gustafsson ◽  
Jie Zhang ◽  
Björn Norell ◽  
Wolf Marchand ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Data Assimilation ◽  
Snow Water Equivalent ◽  
Distribution Model ◽  
Accurate Estimation ◽  
Snowmelt Runoff ◽  
Snow Water ◽  
Snow Distribution ◽  
The Impact

&lt;p&gt;Snow in the mountains is the result of the interplay between meteorological conditions, e.g., precipitation, wind and solar radiation, and landscape features, e.g., vegetation and topography. For this reason, it is highly variable in time and space. It represents an important water storage for several sectors of the society including tourism, ecology and hydropower. The estimation of the amount of snow stored in winter and available in the form of snowmelt runoff can be strategic for their sustainability. In the hydropower sector, for example, the occurrence of higher snow and snowmelt runoff volumes at the end of the spring and in the early summer compared to the estimated one can substantially impact reservoir regulation with energy and economical losses. An accurate estimation of the snow volumes and their spatial and temporal distribution is thus essential for spring flood runoff prediction. Despite the increasing effort in the development of new acquisition techniques, the availability of extensive and representative snow and density measurements for snow water equivalent estimations is still limited. Hydrological models in combination with data assimilation of ground or remote sensing observations is a way to overcome these limitations. However, the impact of using different types of snow observations on snowmelt runoff predictions is, little understood. In this study we investigated the potential of assimilating in situ and remote sensing snow observations to improve snow water equivalent estimates and snowmelt runoff predictions. We modelled the seasonal snow water equivalent distribution in the Lake &amp;#214;veruman catchment, Northern Sweden, which is used for hydropower production. Simulations were performed using the semi-distributed hydrological model HYPE for the snow seasons 2017-2020. For this purpose, a snowfall distribution model based on wind-shelter factors was included to represent snow spatial distribution within model units. The units consist of 2.5x2.5 km&lt;sup&gt;2&lt;/sup&gt; grid cells, which were further divided into hydrological response units based on elevation, vegetation and aspect. The impact on the estimation of the total catchment mean snow water equivalent and snowmelt runoff volume were evaluated using for data assimilation, gpr-based snow water equivalent data acquired along survey lines in the catchment in the early spring of the four years, snow water equivalent data obtained by a machine learning algorithm and satellite-based fractional snow cover data. Results show that the wind-shelter based snow distribution model was able to represent a similar spatial distribution as the gpr survey lines, when assessed on the catchment level. Deviations in the model performance within and between specific gpr survey lines indicate issues with the spatial distribution of input precipitation, and/or need to include explicit representation of snow drift between model units. The explicit snow distribution model also improved runoff simulations, and the ability of the model to improve forecast through data assimilation.&lt;/p&gt;

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