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.

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>

scholarly journals Constraining the HBV model for robust water balance assessments in a cold climate

2021 ◽  
Author(s):  
Helene Birkelund Erlandsen ◽  
Stein Beldring ◽  
Stephanie Eisner ◽  
Hege Hisdal ◽  
Shaochun Huang ◽  
...  
Keyword(s):  
Water Balance ◽  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Snow Accumulation ◽  
Cold Climate ◽  
Snow Melt ◽  
Physically Based Model ◽  
Physically Based ◽  
Snow Water ◽  
Hbv Model

Abstract Robust projections of changes in the hydrological cycle in a non-stationary climate rely on trustworthy estimates of the water balance elements. Additional drivers than precipitation and temperature, namely wind, radiation, and humidity are known to have a significant influence on processes such as evaporation, snow accumulation, and snow-melt. A gridded version of the rainfall-runoff HBV model is run at a 1 × 1 km scale for mainland Norway for the period 1980–2014, with the following alterations: (i) the implementation of a physically based evaporation scheme; (ii) a net radiation-restricted degree-day factor for snow-melt, and (iii) a diagnostic precipitation phase threshold based on temperature and humidity. The combination of improved forcing data and model alterations allowed for a regional calibration with fewer calibrated parameters. Concurrently, modeled discharge showed equally good or better validation results than previous gridded model versions constructed for the same domain; and discharge trend patterns, snow water equivalent, and potential evaporation compared fairly to observations. Compared with previous studies, lower precipitation and evaporation values for mainland Norway were found. The results suggest that a more robust and more physically based model for climate change studies has been obtained, although additional studies will be needed to further constrain evaporation estimates.

scholarly journals Future snow? A spatial-probabilistic assessment of the extraordinarily low snowpacks of 2014 and 2015 in the Oregon Cascades

2017 ◽  
Vol 11 (1) ◽  
pp. 331-341 ◽  
Author(s):  
Eric A. Sproles ◽  
Travis R. Roth ◽  
Anne W. Nolin
Keyword(s):  
Water Resources ◽  
Pacific Northwest ◽  
Snow Water Equivalent ◽  
Probabilistic Approach ◽  
Water Storage ◽  
Climate Change Impacts ◽  
Willamette River ◽  
Climate Conditions ◽  
Snow Water ◽  
Social Environmental

Abstract. In the Pacific Northwest, USA, the extraordinarily low snowpacks of winters 2013–2014 and 2014–2015 stressed regional water resources and the social-environmental system. We introduce two new approaches to better understand how seasonal snow water storage during these two winters would compare to snow water storage under warmer climate conditions. The first approach calculates a spatial-probabilistic metric representing the likelihood that the snow water storage of 2013–2014 and 2014–2015 would occur under +2 °C perturbed climate conditions. We computed snow water storage (basin-wide and across elevations) and the ratio of snow water equivalent to cumulative precipitation (across elevations) for the McKenzie River basin (3041 km2), a major tributary to the Willamette River in Oregon, USA. We applied these computations to calculate the occurrence probability for similarly low snow water storage under climate warming. Results suggest that, relative to +2 °C conditions, basin-wide snow water storage during winter 2013–2014 would be above average, while that of winter 2014–2015 would be far below average. Snow water storage on 1 April corresponds to a 42 % (2013–2014) and 92 % (2014–2015) probability of being met or exceeded in any given year. The second approach introduces the concept of snow analogs to improve the anticipatory capacity of climate change impacts on snow-derived water resources. The use of a spatial-probabilistic approach and snow analogs provide new methods of assessing basin-wide snow water storage in a non-stationary climate and are readily applicable in other snow-dominated watersheds.

scholarly journals Future Snow? A Spatial-Probabilistic Assessment of the Extraordinarily Low Snowpacks of 2014 and 2015 in the Oregon Cascades

2016 ◽  
Author(s):  
Eric A. Sproles ◽  
Travis R. Roth ◽  
Anne W. Nolin
Keyword(s):  
Water Resources ◽  
Pacific Northwest ◽  
Snow Water Equivalent ◽  
Probabilistic Approach ◽  
Water Storage ◽  
Climate Change Impacts ◽  
Climate Conditions ◽  
The Pacific ◽  
Snow Water ◽  
Social Environmental

Abstract. In the Pacific Northwest, USA, the extraordinarily low snowpacks of winters 2013–2014 and 2014–2015 stressed regional water resources and the social-environmental system. We introduce two new approaches to better understand how seasonal snowpack during these two winters would compare to snowpacks under warmer climate conditions. The first approach calculates a spatial-probabilistic metric representing the likelihood that the snowpacks of 2013–2014 and 2014–2015 would occur under +2 °C perturbed climate conditions. We computed snow water storage (basin-wide and across elevations), and the ratio of snow water equivalent to cumulative precipitation (across elevations). We applied these computations to calculate the occurrence probability for similarly low snowpacks under climate warming. Results suggest that, relative to +2 °C conditions, basin-wide snow water storage during winter 2013–2014 would be above average while that of winter 2014–2015 would be far below average. April 1 snow water storage corresponds to a 40 % (2013–2014) and 90 % (2014–2015) probability of being met or exceeded in any given year. The second approach introduces the concept of snow analogs to improve the anticipatory capacity of climate change impacts on snow derived water resources. The use of a spatial-probabilistic approach and snow analogs provide new methods of assessing basin-wide snowpack in a non-stationary climate, and are readily applicable in other snow dominated watersheds.

scholarly journals Modelling the water budget and the riverflows of the Maritsa basin in Bulgaria

2007 ◽  
Vol 4 (2) ◽  
pp. 475-521 ◽  
Author(s):  
E. Artinyan ◽  
F. Habets ◽  
J. Noilhan ◽  
E. Ledoux ◽  
D. Dimitrov ◽  
...  
Keyword(s):  
Water Budget ◽  
Snow Water Equivalent ◽  
Water Cycle ◽  
Slow Component ◽  
First Year ◽  
Transfer Model ◽  
Distributed Hydrological Model ◽  
Snow Water ◽  
High Level ◽  
The Impact

Abstract. A soil-vegetation-atmosphere transfer model coupled with a macroscale distributed hydrological model was used in order to simulate the water cycle for a large region in Bulgaria. To do so, an atmospheric forcing was built for two hydrological years (1 October 1995 to 30 September 1997), at an eight km resolution. It was based on the data available at the National Institute of Meteorology and Hydrology (NIMH) of Bulgaria. Atmospheric parameters were carefully checked and interpolated with a high level of detail in space and time (3-h step). Comparing computed Penman evapotranspiration versus observed pan evaporation validated the quality of the implemented forcing. The impact of the human activities on the rivers (especially hydropower or irrigation) was taken into account. Some improvements of the hydrometeorological model were made: for better simulation of summer riverflow, two additional reservoirs were added to simulate the slow component of the runoff. Those reservoirs were calibrated using the observed data of the 1st year, while the 2nd year was used for validation. 56 hydrologic stations and 12 dams were used for the model calibration while 41 rivergages were used for the validation of the model. The results compare well with the daily-observed discharges, with good results obtained over more than 25% of the rivergages. The simulated snow depth was compared to daily measurements at 174 stations and the evolution of the snow water equivalent was validated at 5 sites. The process of melting and refreezing of snow was found to be important on this region. The comparison of the normalized values of simulated versus measured soil moisture showed good correlation. The surface water budget shows large spatial variations due to the elevation influence on the precipitations, soil properties and vegetation variability. An inter annual difference was observed in the water cycle as the first year was more influenced by Mediterranean climate, while the second year was characterised by continental influence. Energy budget shows a dominating sensible heat component in summer, due to the fact that the water stress limits the evaporation. This study is a first step for the implementation of an operational hydrometeorological model that could be used for real time monitoring and forecast the water budget and the riverflow of Bulgaria.

scholarly journals Hemispheric-scale comparison and evaluation of passive-microwave snow algorithms

2002 ◽  
Vol 34 ◽  
pp. 38-44 ◽  
Author(s):  
Richard L. Armstrong ◽  
Mary J. Brodzik
Keyword(s):  
Satellite Data ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Full Range ◽  
Passive Microwave ◽  
General Tendency ◽  
Climate Conditions ◽  
Preliminary Results ◽  
Snow Water ◽  
Microwave Data

AbstractPassive-microwave satellite remote sensing can greatly enhance large-scale snow measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. This study provides preliminary results from the comparison and evaluation of several different passive-microwave algorithms. These algorithms represent examples which include both mid- and high-frequency channels, vertical and horizontal polarizations and polarization-difference approaches. In our comparisons we utilize larger, more comprehensive, validation datasets which can be expected to provide a full range of snow/climate conditions rather than limited data which may only represent a snapshot in time and space. Evaluation of snow extent derived from passive-microwave data is undertaken through comparison with the U.S. National Oceanic and Atmospheric Administration (NOAA) Northern Hemisphere snow charts which are based on visible-band satellite data. Results clearly indicate those time periods and geographic regions where the two techniques agree and where they tend to consistently disagree. Validation of snow water equivalent derived from passive-microwave data is undertaken using measurements from snow-course transects in the former Soviet Union. Preliminary results indicate a general tendency for nearly all of the algorithms to underestimate snow water equivalent.

scholarly journals Modelling the spatial variability of snow water equivalent at the catchment scale

2007 ◽  
Vol 11 (5) ◽  
pp. 1543-1550 ◽  
Author(s):  
T. Skaugen
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Gamma Distribution ◽  
Snow Water Equivalent ◽  
Temporal Correlation ◽  
Catchment Scale ◽  
Snow Season ◽  
Dynamical Parameters ◽  
Snow Water ◽  
Alpine Catchments

Abstract. The spatial distribution of snow water equivalent (SWE) is modelled as a two parameter gamma distribution. The parameters of the distribution are dynamical in that they are functions of the number of accumulation and melting events and the temporal correlation of accumulation and melting events. The estimated spatial variability is compared to snow course observations from the alpine catchments Norefjell and Aursunden in Southern Norway. A fixed snow course at Norefjell was measured 26 times during the snow season and showed that the spatial coefficient of variation change during the snow season with a decreasing trend from the start of the accumulation period and a sharp increase in the melting period. The gamma distribution with dynamical parameters reproduced the observed spatial statistical features of SWE well both at Norefjell and Aursunden. Also the shape of simulated spatial distribution of SWE agreed well with the observed at Norefjell. The temporal correlation tends to be positive for both accumulation and melting events. However, at the start of melting, a better fit between modelled and observed spatial standard deviation of SWE is obtained by using negative correlation between SWE and melt.

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 Investigating the development of shallow snowpacks on arable land, using comprehensive field observations and spatially distributed snow modelling

2017 ◽  
Vol 49 (1) ◽  
pp. 41-59
Author(s):  
Torsten Starkloff ◽  
Jannes Stolte ◽  
Rudi Hessel ◽  
Coen Ritsema
Keyword(s):  
Overland Flow ◽  
Snow Water Equivalent ◽  
Arable Land ◽  
Model Performance ◽  
Field Observations ◽  
Catchment Scale ◽  
Spatially Distributed ◽  
Snow Water ◽  
Southern Norway ◽  
Agricultural Areas

Abstract Shallow (&lt;1 m deep) snowpacks on agricultural areas are an important hydrological component in many countries, which determines how much meltwater is potentially available for overland flow, causing soil erosion and flooding at the end of winter. Therefore, it is important to understand the development of shallow snowpacks in a spatially distributed manner. This study combined field observations with spatially distributed snow modelling using the UEBGrid model, for three consecutive winters (2013–2015) in southern Norway. Model performance was evaluated by comparing the spatially distributed snow water equivalent (SWE) measurements over time with the simulated SWE. UEBGrid replicated SWE development at catchment scale with satisfactory accuracy for the three winters. The different calibration approaches which were necessary for winters 2013 and 2015 showed the delicacy of modelling the change in shallow snowpacks. Especially the refreezing of meltwater and prevention of runoff and infiltration of meltwater by frozen soils and ice layers can make simulations of shallow snowpacks challenging.

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