A spatially distributed energy balance snowmelt model for application in mountain basins

Marks, Danny; Domingo, James B.; Susong, Dave; Link, Tim; Garen, David C.

doi:10.1002/(sici)1099-1085(199909)13:12/13<1935::aid-hyp868>3.0.co;2-c

Cited by 303 publications

(290 citation statements)

References 18 publications

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“…SNOBAL (Marks et al, 1998(Marks et al, , 1999 calculates the amount of snowmelt using the energy equation and was developed for deep mountain snowcover. SNOBAL represents the snowcover as two layers: a surface active layer of fixed depth and a lower layer that represents the remaining snowpack.…”

Section: Snobalmentioning

confidence: 99%

On the importance of sublimation to an alpine snow mass balance in the Canadian Rocky Mountains

MacDonald

Pomeroy

Pietroniro

2010

Hydrol. Earth Syst. Sci.

124

130

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Abstract.A modelling study was undertaken to evaluate the contribution of sublimation to an alpine snow mass balance in the Canadian Rocky Mountains. Snow redistribution and sublimation by wind, snowpack sublimation and snowmelt were simulated for two winters over an alpine ridge transect located in the Canada Rocky Mountains. The resulting snowcover regimes were compared to those from manual snow surveys. Simulations were performed using physically based blowing snow (PBSM) and snowpack ablation (SNOBAL) models. A hydrological response unit (HRU)-based spatial discretization was used rather than a more computationally expensive fully-distributed one. The HRUs were set up to follow an aerodynamic sequence, whereby eroded snow was transported from windswept, upwind HRUs to drift accumulating, downwind HRUs. That snow redistribution by wind can be adequately simulated in computationally efficient HRUs over this ridge has important implications for representing snow transport in large-scale hydrology models and land surface schemes. Alpine snow sublimation losses, in particular blowing snow sublimation losses, were significant. Snow mass losses to sublimation as a percentage of cumulative snowfall were estimated to be 20-32% with the blowing snow sublimation loss amounting to 17-19% of cumulative snowfall. This estimate is considered to be a conservative estimate of the blowing snow sublimation loss in the Canadian Rocky Mountains because the study transect is located in the low alpine zone where the topography is Correspondence to: J. W. Pomeroy (john.pomeroy@usask.ca) more moderate than the high alpine zone and windflow separation was not observed. An examination of the suitability of PBSM's sublimation estimates in this environment and of the importance of estimating blowing snow sublimation on the simulated snow accumulation regime was conducted by omitting sublimation calculations. Snow accumulation in HRUs was overestimated by 30% when neglecting blowing snow sublimation calculations.

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Section: Snobalmentioning

confidence: 99%

On the importance of sublimation to an alpine snow mass balance in the Canadian Rocky Mountains

MacDonald

Pomeroy

Pietroniro

2010

Hydrol. Earth Syst. Sci.

124

130

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“…Internal snowpack temperature and melt rates were computed using Snobal (snowmelt energy balance model; Marks et al, 1998Marks et al, , 1999Marks et al, , 2008, which was incorporated as a module within CRHM. This module approximates the snowcover as being composed of 2 layers: a surface active layer of fixed maximum thickness, and a lower layer representing the remaining snowpack.…”

Section: Snowmelt Modelling and Validationmentioning

confidence: 99%

“…Melt is computed in either layer when the accumulated energy exceeds that required to bring the snowpack to 0 • C, at which point positive values of Q m result in snowmelt. A comprehensive description of the Snobal model is given by Marks et al (1998Marks et al ( , 1999Marks et al ( , 2008. The model was run at the point scale at 15 min time intervals in CRHM using meteorological observations from the various stations as the external forcing variables.…”

Section: Snowmelt Modelling and Validationmentioning

confidence: 99%

Simulation of the snowmelt runoff contributing area in a small alpine basin

DeBeer

Pomeroy

2010

Hydrol. Earth Syst. Sci.

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Abstract. Simulation of areal snowmelt and snowcover depletion over time can be carried out by applying point-scale melt rate computations to distributions of snow water equivalent (SWE). In alpine basins, this can be done by considering these processes separately on individual slope units. However, differences in melt timing and rates arise at smaller spatial scales due to the variability in SWE and snowpack cold content, which affects the timing of melt initiation, depletion of the snowcover and spatial extent of the snowmelt runoff contributing area (SRCA). This study examined the effects of variability in SWE, internal energy and applied melt energy on melt rates and timing, and snowcover depletion in a small cold regions alpine basin over various scales ranging from point to basin. Melt rate computations were performed using a physically based energy balance snowmelt routine (Snobal) in the Cold Regions Hydrological Model (CRHM) and compared with measurements at 3 meteorological stations over a ridge within the basin. At the point scale, a negative association between daily melt rates and SWE was observed in the early melt period, with deeper snow requiring greater energy inputs to initiate melt. SWE distributions over the basin (stratified by slope) were measured using snow surveys and repeat LiDAR depth estimates, and used together with computed melt rates to simulate the areal snowcover depletion. Comparison with observations from georeferenced oblique photographs showed an improvement in simulated areal snowcover depletion curves when accounting for the variability in melt rate with depth of SWE in the early melt period. Finally, the SRCA was characterized as the product of the snowcovered area and the fraction of the SWE distribution undergoing active melt and producing an appreciable runoff quantity on each slope unit. Results for each slopeCorrespondence to: C. M. DeBeer (cmd225@mail.usask.ca) were then aggregated to give the basin scale SRCA. The SRCA is controlled by the variability of melt amongst slope units and over individual SWE distributions, the variability of SWE, and the resulting snowcover depletion patterns over the basin.

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“…In fact, the numerical upscaling corresponds to spatially distributed modeling, utilizing a geographical information system (GIS). This approach recently became popular with the advances in computing power ( [1,28,35,46] and many others). However, this study focuses on snow physics and the effect of spatial distribution of solar (short-wave) radiation.…”

Section: Distributed Snow Model With Linear Temperature Profile Appromentioning

confidence: 99%

“…Abbott et al [1] introduced distributed isothermal energy balance model as a snow component in the European Hydrological System (SHE) model. Marks et al [28] developed another spatially distributed snowmelt model, called ISNOBAL, based on the GIS and satellite information. They approximated the snow pack in two layers: active (top) and inactive (bottom) layer.…”

Section: Introductionmentioning

confidence: 99%

Field observations and numerical model experiments for the snowmelt process at a field site

Ohara¹,

Kavvas²

2006

Advances in Water Resources

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There are several levels of models for the snowmelt process in terms of the snow thermal structure: isothermal, bi-layered and multi-layered models. However, it is difficult to choose the appropriate level of complexity for application because the number of unknown variables is crucial in model handling. One of the major issues in energy balance snow models is the shape of the snow temperature vertical profile. This profile, if taken as a specified function, would simplify a snowmelt model calibration and computation significantly. In this study, in order to determine the appropriate representative snow vertical thermal profile, snow temperature measurements have been performed using five snow thermocouples placed vertically along an observation tower with insulating arms. Also, as a field experimental study of an energy balance snow model, the net radiation, air temperature, relative humidity and wind speed along with the vertical one dimensional snow temperature profile have been observed at a field site in Lake Tahoe Basin. The computational results correspond with the measured snow temperature profile and snow water equivalent reasonably well. It is illustrated that the temperature in the snow near surface (called the ''active layer'') varies daily, and the lower snow layer (called the ''inactive layer'') is barely affected by the atmosphere. The results of field observations and the numerical experiments show that the vertical temperature distributions in the active layer, which is the upper layer affected by energy exchange with the atmosphere, generally have an exponential shape during night time under cold weather, while snow pack stays around 0°C during daytime. Both of the results indicate that not only the snow temperature in the top active layer, but also the thickness of snow active layer fluctuates during the snowmelt process. The observation results show that the thickness of the active layer may reach about 60 cm in Sierra Nevada, California. These results provide significant information for the development of appropriate approximations in physically based snowmelt modeling.

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A spatially distributed energy balance snowmelt model for application in mountain basins

Cited by 303 publications

References 18 publications

On the importance of sublimation to an alpine snow mass balance in the Canadian Rocky Mountains

On the importance of sublimation to an alpine snow mass balance in the Canadian Rocky Mountains

Simulation of the snowmelt runoff contributing area in a small alpine basin

Field observations and numerical model experiments for the snowmelt process at a field site

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