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 (<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.

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.

scholarly journals An 18-yr long (1993–2011) snow and meteorological dataset from a mid-altitude mountain site (Col de Porte, France, 1325 m alt.) for driving and evaluating snowpack models

2012 ◽  
Vol 4 (1) ◽  
pp. 13-21 ◽  
Author(s):  
S. Morin ◽  
Y. Lejeune ◽  
B. Lesaffre ◽  
J.-M. Panel ◽  
D. Poncet ◽  
...  
Keyword(s):  
Snow Depth ◽  
Snow Water Equivalent ◽  
Meteorological Data ◽  
Model Performance ◽  
Short Wave ◽  
Wave Radiation ◽  
Density Profiles ◽  
The Public ◽  
Snow Water ◽  
Snowpack Properties

Abstract. A quality-controlled snow and meteorological dataset spanning the period 1 August 1993–31 July 2011 is presented, originating from the experimental station Col de Porte (1325 m altitude, Chartreuse range, France). Emphasis is placed on meteorological data relevant to the observation and modelling of the seasonal snowpack. In-situ driving data, at the hourly resolution, consist of measurements of air temperature, relative humidity, windspeed, incoming short-wave and long-wave radiation, precipitation rate partitioned between snow- and rainfall, with a focus on the snow-dominated season. Meteorological data for the three summer months (generally from 10 June to 20 September), when the continuity of the field record is not warranted, are taken from a local meteorological reanalysis (SAFRAN), in order to provide a continuous and consistent gap-free record. Data relevant to snowpack properties are provided at the daily (snow depth, snow water equivalent, runoff and albedo) and hourly (snow depth, albedo, runoff, surface temperature, soil temperature) time resolution. Internal snowpack information is provided from weekly manual snowpit observations (mostly consisting in penetration resistance, snow type, snow temperature and density profiles) and from a hourly record of temperature and height of vertically free ''settling'' disks. This dataset has been partially used in the past to assist in developing snowpack models and is presented here comprehensively for the purpose of multi-year model performance assessment. The data is placed on the PANGAEA repository (http://dx.doi.org/10.1594/PANGAEA.774249) as well as on the public ftp server ftp://ftp-cnrm.meteo.fr/pub-cencdp/.

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>

scholarly journals Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding

2017 ◽  
Vol 21 (7) ◽  
pp. 3325-3352 ◽  
Author(s):  
Christa Kelleher ◽  
Brian McGlynn ◽  
Thorsten Wagener
Keyword(s):  
Goodness Of Fit ◽  
Snow Water Equivalent ◽  
Expert Knowledge ◽  
Model Performance ◽  
Hierarchical Approach ◽  
Catchment Scale ◽  
Distributed Modeling ◽  
Distributed Models ◽  
Knowledge Based ◽  
Behavioral Parameter

Abstract. Distributed catchment models are widely used tools for predicting hydrologic behavior. While distributed models require many parameters to describe a system, they are expected to simulate behavior that is more consistent with observed processes. However, obtaining a single set of acceptable parameters can be problematic, as parameter equifinality often results in several behavioral sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modeling application. We outline a hierarchical approach to reduce the number of behavioral sets based on regional, observation-driven, and expert-knowledge-based constraints. For our application, we explore how each of these constraint classes reduced the number of behavioral parameter sets and altered distributions of spatiotemporal simulations, simulating a well-studied headwater catchment, Stringer Creek, Montana, using the distributed hydrology–soil–vegetation model (DHSVM). As a demonstrative exercise, we investigated model performance across 10 000 parameter sets. Constraints on regional signatures, the hydrograph, and two internal measurements of snow water equivalent time series reduced the number of behavioral parameter sets but still left a small number with similar goodness of fit. This subset was ultimately further reduced by incorporating pattern expectations of groundwater table depth across the catchment. Our results suggest that utilizing a hierarchical approach based on regional datasets, observations, and expert knowledge to identify behavioral parameter sets can reduce equifinality and bolster more careful application and simulation of spatiotemporal processes via distributed modeling at the catchment scale.

scholarly journals Utility of late summer transient snowline migration rate on Taku Glacier, Alaska

2011 ◽  
Vol 5 (4) ◽  
pp. 1127-1133 ◽  
Author(s):  
M. Pelto
Keyword(s):  
Mass Balance ◽  
Migration Rate ◽  
Satellite Images ◽  
Snow Water Equivalent ◽  
Late Summer ◽  
Ablation Rate ◽  
Field Observations ◽  
Balance Assessment ◽  
Snow Water ◽  
The Mean

Abstract. On Taku Glacier, Alaska a combination of field observations of snow water equivalent (SWE) from snowpits and probing in the vicinity of the transient snowline (TSL) are used to quantify the mass balance gradient. The balance gradient derived from the TSL and SWE measured in snowpits at 1000 m from 1998–2010 ranges from 2.6–3.8 mm m−1. Probing transects from 950 m–1100 m directly measure SWE and yield a slightly higher balance gradient of 3.3–3.8 mm m−1. The TSL on Taku Glacier is identified in MODIS and Landsat 4 and 7 Thematic Mapper images for 31 dates during the 2004–2010 period to assess the consistency of its rate of rise and reliability in assessing ablation for mass balance assessment. For example, in 2010, the TSL was 750 m on 28 July, 800 m on 5 August, 875 m on 14 August, 925 m on 30 August, and 975 m on 20 September. The mean observed probing balance gradient was 3.3 mm m−1, combined with the TSL rise of 3.7 m day−1 yields an ablation rate of 12.2 mm day−1 from mid-July to mid-Sept, 2010. The TSL rise in the region from 750–1100 m on Taku Glacier during eleven periods each covering more than 14 days during the ablation season indicates a mean TSL rise of 3.7 m day−1, the rate of rise is relatively consistent ranging from 3.1 to 4.4 m day−1. This rate is useful for ascertaining the final ELA if images or observations are not available near the end of the ablation season. The mean ablation from 750–1100 m during the July–September period determined from the TSL rise and the observed balance gradient is 11–13 mm day−1 on Taku Glacier during the 2004–2010 period. The potential for providing an estimate of bn from TSL observations late in the melt season from satellite images combined with the frequent availability of such images provides a means for efficient mass balance assessment in many years and on many glaciers.

scholarly journals Investigating the Variability of High-Elevation Seasonal Orographic Snowfall Enhancement and Its Drivers across Sierra Nevada, California

2018 ◽  
Vol 19 (1) ◽  
pp. 47-67 ◽  
Author(s):  
Laurie S. Huning ◽  
Steven A. Margulis
Keyword(s):  
Sierra Nevada ◽  
Snow Water Equivalent ◽  
High Elevation ◽  
Mountain Range ◽  
Distributed Data ◽  
Mountainous Regions ◽  
Average Maximum ◽  
Spatially Distributed ◽  
Orographic Enhancement ◽  
Snow Water

Abstract While orographically driven snowfall is known to be important in mountainous regions, a complete understanding of orographic enhancement from the basin to the mountain range scale is often inhibited by limited distributed data and spatial and/or temporal resolutions. A novel, 90-m spatially distributed snow water equivalent (SWE) reanalysis was used to overcome these limitations. Leveraging this SWE information, the interannual variability of orographic gradients in cumulative snowfall (CS) was investigated over 14 windward (western) basins in the Sierra Nevada in California from water years 1985 to 2015. Previous studies have not provided a detailed multidecadal climatology of orographic CS gradients or compared wet-year and dry-year orographic CS patterns, distributions, and gradients across an entire mountain range. The magnitude of seasonal CS gradients range from over 15 cm SWE per 100-m elevation to under 1 cm per 100 m with a 31-yr average of 6.1 cm per 100 m below ~2500 m in the western basins. The 31-yr average CS gradients generally decrease in higher elevation zones across the western basins and become negative at the highest elevations. On average, integrated vapor transport and zonal winds at 700 hPa are larger during wet years, leading to higher orographically driven CS gradients across the Sierra Nevada than in dry years. Below ~2500 m, wet years yield greater enhancement (relative to dry years) by factors of approximately 2 and 3 in the northwestern and southwestern basins, respectively. Overall, the western Sierra Nevada experiences about twice as much orographic enhancement during wet years as in dry years below the elevation corresponding to the 31-yr average maximum CS.

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