Effects of Averaging and Separating Soil Moisture and Temperature in the Presence of Snow Cover in a SVAT and Hydrological Model for a Southern Ontario, Canada, Watershed (original) (raw)
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westernsnowconference.org
Three snowmelt models of different degrees of model complexity and data requirement were used to simulate snow accumulation and ablation processes for a watershed in the Canadian Prairies. Results show that modifying the popular temperature index method by incorporating near-surface soil temperature as an additional predictor to air temperature could considerably improve the model performance. In addition, the modified method could achieve hourly simulation results that are comparable to a physically based energy balance method. Majority of the improvement in the modified temperature index method occurs when the melt rate is varied as a function of near-surface soil temperature.
Simulations of energy balance components at snow-dominated montane watershed by land surface models
Environmental Earth Sciences, 2017
The quantification of energy interactions among land surface, atmosphere, and surface vegetation is significant to comprehend the hydrological cycle in montane watersheds. Moreover, elevation change is an essential in causing variations in energy fluxes. Thus, estimating the major components of energy interactions is essential for better understanding of the hydrological process. The advanced land surface models (LSMs); the common land model (CLM) and variables infiltration capacity (VIC) are used to estimate accurate hydrometeorological variables. These hydrometeorological variables such as net radiation and sensible, latent, and ground heat fluxes were estimated using CLM and VIC at upper and lower meteorological stations in Sierra Nevada Mountain, California, USA. The estimated fluxes were compared with observations at each site. The estimated daily and monthly net radiation and sensible heat flux from both models showed good agreement with the observations (R C 0.84). The CLM-modeled estimates showed lower trends during the rainfall periods, which occurred mainly during winter at both sites. In comparison, the estimated daily and monthly latent heat flux from CLM at both sites showed better results with lower RMSE and bias than that from VIC, which underestimated latent heat flux. Both models overestimated ground heat flux, and the variation trend was similar to observation. For sensitivity analysis, according to elevation change, all the estimated energy fluxes had slightly different values at the upper and lower met stations. In future studies, parameterization for the LSMs will be conducted for more robust estimations of hydrometeorological variables in montane watersheds.
Journal of Hydrometeorology, 2008
Small-scale topography and snow redistribution have important effects on snow-cover heterogeneity and the timing, rate, and duration of spring snowmelt in mountain tundra environments. However, land surface schemes (LSSs) are usually applied as a means to provide large-scale surface states and vertical fluxes to atmospheric models and do not normally incorporate topographic effects or horizontal fluxes in their calculations A study was conducted in Granger Creek, an 8-km2 catchment within Wolf Creek Research Basin in the Yukon Territory, Canada, to examine whether inclusion of the effects of wind redistribution of snow between landscape units, and slope and aspect in snowmelt calculations for tiles, could improve the simulation of snowmelt by an LSS. Measured snow accumulation, reflecting overwinter wind redistribution of snow, was used to provide initial conditions for the melt simulation, and physically based algorithms from a small-scale hydrological model were used to calculate ...
One-dimensional snow water and energy balance model for vegetated surfaces
Hydrological Processes, 1999
We developed and evaluated a three-layer snow model for application in general circulation models. This onedimensional snow model has many features of the detailed physically based model SNTHERM, yet is computationally much simpler. We have also extended the point model to vegetated areas using the parameterization concepts of the Biosphere-Atmosphere Transfer Scheme (BATS). Results of model applications for two types of vegetated ®elds Ð a short grassland in the French Alps and an old aspen forest in the southern study area of BOREAS Ð were presented. The results, on one hand, indicate the suitability of the model structure and parameter setting; on the other hand, the results explore the limitation of using`point' ®eld observations to evaluate an area model.
An improved snow scheme for the ECMWF land surface model: description and offline validation
Journal of Hydrometeorology, 2010
A new snow scheme for the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface model has been tested and validated. The scheme includes a new parameterization of snow density, incorporating a liquid water reservoir, and revised formulations for the sub-grid snow cover fraction and snow albedo. Offline validation (covering a wide range of spatial and temporal scales) includes simulations for several observation sites from the Snow Models Intercomparison Project-2 (SnowMIP2), global simulations driven by the meteorological forcing from the Global Soil Wetness Project-2 (GSWP2), and by ECMWF ERA-Interim re-analysis. This snow scheme was introduced in the ECMWF operational forecast system in September 2009 (CY35R3). SnowMIP2 simulations revealed that the original snow scheme had a systematic early and late prediction of the final ablation in forest and open sites, respectively. The NEW scheme reduces the negative timing bias in forest plots from 15 to 1 day and the positive bias in open plots from 11 to 2 days. The new snow density parameterization has a good agreement with observations, resulting in an augmented insulation effect of the snowpack. The increased insulation and the new exposed and shaded albedo change the surface energy fluxes. There is a reduction of the basal heat flux that reduces the cooling of the underlying soil, which is warmer in NEW than in CTR (old scheme) during the cold season. Thus, reduced soil freezing decreased the surface runoff and increased soil water storage. The mean annual cycles of runoff and TSWV (terrestrial water storage) analyzed for the Ob and Mackenzie basins are closer to the observations in NEW. In ten Northern hemisphere basins, there is an average reduction of the monthly runoff RMSE from 0.75 to 0.51 mm day-1 when comparing CTR and NEW, respectively. These results illustrate the importance of the snow insulation on the hydrological cycle, even at regional scales. On a hemispheric scale, the new snow scheme reduces the negative bias of snow-covered area, especially during spring. On a daily scale, using NOAA/NESDIS snow cover data, the early ablation in CTR is reduced by a factor of two in some identified regions over the Northern Hemisphere. The changes in snow-covered area are closely related with the changes in surface albedo. The original snow scheme had a systematic negative bias in surface albedo, when compared against MODIS remote sensing data. The new scheme reduced the albedo bias, consequently reducing the spatial (only over snow covered area) and time (October to November) averaged surface net shortwave radiation bias from +7.1 W m-2 in CTR to -1.8 W m-2 in NEW. For each validation dataset, sensitivity experiments were performed to assess the impact of the new components of the presented snow scheme. Prognostic and diagnostic SLW (snow liquid water) representations display similar skill in SnowMIP2 (RMSE of SWE) and GSWP2 (RMSE of basin runoff) simulations. Simulated improvements of SWE in SnowMIP2 locations were mainly due to SLW representation on forest sites and due to the new exposed albedo on open sites. The increased snow insulation effect, due to the new snow density parameterization, had an important role on the basins water balance. Impacts of the new snow cover fraction and exposed and shaded albedo parameterizations were evident when validating against remotely sensed data. Sensitivity tests highlight the role of the different components of the snow scheme with the behavior conditioned by the climate and vegetation conditions of each site. Thus, a robust verification of a LSM model should include a variety of different (and independent) validation datasets.
British Journal of Environment and Climate Change, 2012
To modify two empirical models of snowpack and snowmelt, and compare eight such models. Study Design: Test and modify the models by using five years of snow measurements from Harp Lake. Place and Duration of Study: Methodology: The old daily-run WINTER model was the first model. It was modified to create a second model. The enhanced-temperature-index (ETI) model was slightly modified to be the third model. Modified WINTER and ETI were combined into the fourth model. Hydrology model BROOK90 and SWAT were used as the fifth and sixth model, also daily-run. Operating the WINTER and ETI in hourly steps created the seventh and
Water Resources Research, 2011
1] This paper evaluates the use of field data on the spatial variability of snow water equivalent (SWE) to guide the design of distributed snow models. An extensive reanalysis of results from previous field studies in different snow environments around the world is presented, followed by an analysis of field data on spatial variability of snow collected in the headwaters of the Jollie River basin, a rugged mountain catchment in the Southern Alps of New Zealand. In addition, area-averaged simulations of SWE based on different types of spatial discretization are evaluated. Spatial variability of SWE is shaped by a range of different processes that occur across a hierarchy of spatial scales. Spatial variability at the watershed-scale is shaped by variability in near-surface meteorological fields (e.g., elevation gradients in temperature) and, provided suitable meteorological data is available, can be explicitly resolved by spatial interpolation/extrapolation. On the other hand, spatial variability of SWE at the hillslope-scale is governed by processes such as drifting, sloughing of snow off steep slopes, trapping of snow by shrubs, and the nonuniform unloading of snow by the forest canopy, which are more difficult to resolve explicitly. Subgrid probability distributions are often capable of representing the aggregate-impact of unresolved processes at the hillslope-scale, though they may not adequately capture the effects of elevation gradients. While the best modeling strategy is case-specific, the analysis in this paper provides guidance on both the suitability of several common snow modeling approaches and on the choice of parameter values in subgrid probability distributions. (2011), Representing spatial variability of snow water equivalent in hydrologic and land-surface models: A review, Water Resour. Res., 47, W07539,
Sensitivity of the Snowmelt Runoff Model to snow covered area and temperature inputs
Applied Geography, 2014
Snowpack is an important source of freshwater. Snowmelt runoff models provide a means to predict the timing and magnitude of spring snowmelt. This study assessed the sensitivity of the conceptual, degreeday Snowmelt Runoff Model (SRM) to snow covered area and temperature inputs in a small mountainous catchment in Utah, USA. It was found that snow cover products from the Moderate Resolution Imaging Spectroradiometer (MODIS) underestimate snow covered area during the second half of the melt season, leading to inadequate modeling of spring snowmelt with SRM (Nash-Sutcliffe Efficiency ¼ 0.59; bias of À26.9%). Incorporation of ancillary snow covered area information provided by Landsat ETMþ imagery greatly improved streamflow simulations (Nash-Sutcliffe Efficiency ¼ 0.92; bias of À0.01%). For the temperature input, SRM appeared more sensitive to the elevation and location of the temperature reference station than to the lapse rate scenario used to extrapolate temperatures throughout the watershed. These findings will be useful for snowmelt runoff research and water resource management.
The influence of the spatial distribution of snow on basin-averaged snowmelt
Hydrological Processes, 1998
Spatial variability in snow accumulation and melt owing to topographic eects on solar radiation, snow drifting, air temperature and precipitation is important in determining the timing of snowmelt releases. Precipitation and temperature eects related to topography aect snowpack variability at large scales and are generally included in models of hydrology in mountainous terrain. The eects of spatial variability in drifting and solar input are generally included only in distributed models at small scales. Previous research has demonstrated that snowpack patterns are not well reproduced when topography and drifting are ignored, implying that larger scale representations that ignore drifting could be in error. Detailed measurements of the spatial distribution of snow water equivalence within a small, intensively studied, 26-ha watershed were used to validate a spatially distributed snowmelt model. These observations and model output were then compared to basin-averaged snowmelt rates from a single-point representation of the basin, a two-region representation that captures some of the variability in drifting and aspect and a model with distributed terrain but uniform drift. The model comparisons demonstrate that the lumped, single-point representation and distributed terrain with uniform drift both yielded poor simulations of the basin-averaged surface water input rate. The two-point representation was a slight improvement, but the late season melt required for the observed stream-¯ow was not simulated because the deepest drifts were not represented. These results imply that representing the eects of subgrid variability of snow drifting is equally or more important than representing subgrid variability in solar radiation.