1. Please write down the name (and abbreviation) of your snow model or land-surface model with snow component?
Distributed Hydrology Soil Vegetation model (DHSVM)
2. Name and address of model developer;
Mark Wigmosta (Pacific Northwest Research Labs, Battelle)
Bart Nijssen and Pascal Storck (University of Washington, Seattle)
3. Name and address of model user;
Mark Wigmosta, Bart Nijssen, Pascal Storck
Laura Bowling (University of Washington)
Paul Wetherbee (HDR consultants, Anchorage, Alaska)
4. Please indicate whether your model is developed for application
in understanding snow processes, X
in a runoff forecasting model, X
in a weather forecasting model,
in a global climate model (GCM),
or other (please specify)?
5. The first year when the model was used;
approximately 1993 (base version), 1995 (new version)
6. One paragraph description of your model (e.g. abstract from report or paper);
In each model pixel, the land surface may be composed of overstory vegetation, understory vegetation, and soil. The overstory may cover all or a prescribed fraction of the land surface. The understory, if present, covers the entire ground surface. The model allows land surface representations ranging from a closed two-story forest, to sparse low-lying natural vegetation or crops, to bare soil. Meteorological conditions (precipitation, air temperature, solar radiation, wind speed, vapor pressure) are prescribed at a specified reference height well above the overstory.
Solar radiation and wind speed are attenuated through the two canopies. If snow is present, it is assumed to cover the understory and thus affects radiation transfer and the wind profiles via increased albedo and decreased surface roughness. Temperature and relative humidity are not adjusted through the canopy.
An independent one-dimensional (vertical) water balance is calculated for each pixel (Wigmosta et al., 1994). Evaporation of intercepted water from the surfaces of wet vegetation is assumed to occur at the potential rate. Transpiration from dry vegetative surfaces is calculated using a Penman-Monteith approach. The model follows Entekhabi and Eagleson (1989) in using a soil physics-based approach to calculate soil evaporation.
Precipitation occurring below a threshold temperature is assumed to be snow. Snow interception by the overstory is calculated as a function of Leaf Area Index and is adjusted downward for windy or cold conditions (Schmidt and Troendle, 1992). Intercepted snow can be removed from the canopy through snow melt, sublimation, and mass release. Melt of intercepted snow is calculated based on a single layer energy balance approach. Mass release occurs if sufficient melt water is generated during an individual time step such that the snow slides off the canopy (Bunnell et al., 1985; Calder, 1990). Drip from the canopy is added to the ground snowpack (if present) as rain while the cold content of any mass release or unintercepted snow is added directly to the ground snowpack.
Ground snow accumulation and melt are simulated using a two-layer energy-balance model at the snow surface, similar to that described by Anderson (1968). The model accounts for the energy advected by rain, throughfall or drip, as well as net radiation and sensible and latent heat. Bulk transfer coefficients for turbulent exchange are calculated based on the aerodynamic resistance from the snow surface to the calculated two-meter wind and adjusted for atmospheric stability.
7. Please specify any known application range or restrictions;
The model has been applied to all of the following
Interior Mountain regions (dry climate, snowmelt dominated)
Pacific Northwest basins (both ROS and spring melt dominated)
Boreal forest
8. What are the development data needs;
9. What are the operational data needs?
The snow submodel requires an representation of the canopy including height, LAI, roughness, and radiation and windspeed decay coefficients. Snow roughness and the rain/snow threshold are also required.
10. Please indicate with an "x" for those meteorological variables used to
DRIVE your snow model?
precipitation : X
air temperature : X
wind speed : X
wind direction :
humidity : x
downwelling shortwave radiation : X
downwelling longwave radiation : X
cloud cover :
surface pressure :
11. List the state variables (e.g., snow temperature, snow water equivalent, etc) your snow model uses?
snow temperature, SWE (ice and liquid phases are separate)
12. List the measurable/adjustable parameters (e.g., snow surface aerodynamic roughness, maximum albedo at visible wavelength, etc, excluding initial conditions) your snow model uses?
snow albedo is fixed using USACE, 1956 data. snow surface roughness, and vegetation parameters can be adjusted as well as the rain/snow threshold.
13. What are the output data?
The snow submodel will output data on SWE in the canopy and on the ground as well as both temperatures. Drip and mass release from the canopy is output. Snow melt and snowpack outflow are output along with the liquied water content of the ground/intercepted snowpack.
14. What computer language does your model use?
The model uses C
15. How many subroutines (or functions) does your snow model have?
One subroutine for canopy interception, drip and mass release. One subroutine for aerodynamic resistance formulation One subroutine for stability correction One subroutine for the radation balance One subroutine for iteration on snow surface temperature.
16. Number of lines of the snow code?
main code has 412 lines snow interception code has 390 lines radiation routines have 251 lines aerodynamic routines have 260 lines stability routine has 87 lines iteration routine has 150 lines
17. What is the recommended hardware?
Model has been used on Unix workstations (SUN, HP) and Pentium class PC's
18. How does your model determine the form of precipitation (i.e., snowfall and rainfall)? Please give the formulation.
below threshold (all snow) above threshold (all rain) linear interpolation between the two thresholds are user specified
19. Is your snow model one dimensional or multi-dimensional? Please specify.
one dimensional
20. If one dimensional, how many layers are there in your snow model? Please specify layering structure.
it has two layers. A thin surface layer approximately (100 mm thick, again can be adjusted by the user) and the remainder is a pack layer. All energy exchange with the atmosphere occurs with the surface layer.
21. What is your snow model time step?
It is user specified based on the available data. Time steps used to data range from 24 min to 1 hour
22. Does your model snow albedo allow its
spectral differences (visible vs. near-IR)?
directional differences (direct vs. diffuse)?
No distinctions are made
23. Is your model snow albedo a function of
snow age X(with different formualtions for melt or accumulation)
grain size
solar zenith angle
pollution
snow depth?
24. Does your snow model explicitly treat liquid water retention and percolation within the snowpack?
liquid water retention is modeled as a simple reservoir. Until the liquid water storage capacity is met, no percoloation to the pack layer or the soil surface is allowed.
25. Does your snow model account for changes in the hydraulic and thermal properties of snow due to meltwater refreezing?
No.
26. Is snow density in your snow model changing with time or fixed?
Snow density is not calculated, depth of snow is not a state variable, only the SWE is.
27. Is heat capacity and conductivity in your snow model changing with time or fixed?
fixed
28. Does your snow model simulate vapor transfer in the snowpack?
yes
29. Does your snow model account for the heat transfer between the bottom of the snowpack and the underlying soil?
No.
30. In snow energy balance, does your model consider heat convected by rain or falling snow?
yes
31. Does your snow model include snow drifting and redistribution by wind (or avalanche)? If so, how?
no
32. How is areal snow distribution treated?
A given basin or area is modeled as a series of pixel elements at the scale of the DEM. Each pixel is modeled separately therefore accounting for the effect of changing elevation, slope, aspect, and vegetation cover.
33. Does your snow model account for sub-grid (or sub-watershed) effects of topography? If so, how is temperature distributed?
Sub grid variability is limited to the influence of the canopy on a grid cell. If 50% of the grid cell is canopy covered then the model assumes that 50% of the pixel is covered by a full canopy and 50% is bare. Aerodynamic consideration must be explicity given for a partial canopy, i.e. new displacement height and exponential decay coefficient for the windspeed. Temperature is linearly interpolated between available stations or assumed to follow a pseudoadiabation lapse rate (if no explicit info is available).
how is precipitation (spatial, elevation and corrections) distributed?
--based on station interpolation
how is solar radiation distributed?
--based on the local terrain reflectance and shading
how is wind distributed?
--wind is assumed constant over the basin but is adjusted for
vegetation
how are other meteorological variables distributed?
34. Does your snow model consider snow-vegetation interaction?
Yes, see description above
35. Does the snow-vegetation interaction account for
different vegetation types (grass vs. forest),
-- yes, can have both an overstory and understory. Understory
vegetation is assumed to be fully covered after the first snowfall.
Again, the specification of over and understory is left to the user.
different vegetation heights (short vs. tall),
-- yes
different vegetation densities (small vs. large LAI),
-- yes
different vegetation coverages (sparse vs. dense vegetation)?
-- yes, based on canopy coverage fraction
36. Are snow interception, drip and melt on canopy surface allowed in your model?
Yes, they are modeled explicitly.
37. How is the upper limit of the canopy interception determined?
As a function of LAI, adjusted for temperature
38. In the presence of vegetation, how is snow surface albedo altered?
It is unaffected by vegetation
39. In the presence of vegetation, how is snow surface roughness altered?
It is unaffected by vegetation
40. In the presence of forest, does your snow model allow spatial variability of snow depth and water equivalent on forest floor?
only between pixels
41(a). How does your model deliver snowmelt to the soil system (e.g. affecting soil moisture)?
Once the liquid water holding capacity of the pack layer is reached, all excess snowmelt is routed directly to the soil.
(b). Once snowmelt is generated, how does your model relate it to runoff?
Runoff is generated via a saturated excess mechanism. Based on user defined soil properties and a given number of soil layers.
42. How is frozen soil treated in your model?
It is not treated in the base version, the version with VIC-3l includes frozen soils.
43. Has your snow model been tested with the field data?
Yes.
If so, what data? (areas)
what are their temporal and spatial scales?
Temporal scales of multiyear, full season data at a half hour time interval.
Spatial scales include mulitple sites in clearings and under a forest canopy, as well as a large number of weather stations around the world.
44. Has your snow model been used together with remote sensing data as input?
That is currently a work in progress
If so, how?
45. If your snow model is coupled with a numerical weather forecasting model or climate model, has the model snow product been compared with satellite data? If so, what satellite data were used?
46. Please list any other previous applications.
see references below
47. Please specify verification criteria, if any?
verification criteria are limited to correct estimation of SWE and snowmelt over seasonal and event time scales.
48. What are the model fitting procedures, if any?
User may adjust snow surface roughness and vegetation parameters within reasonable values.
49. What are future plans for using/improving the model?
We are currently collecting additional field data for verification of the canopy interception, drip and mass release algorithms.
50. Please provide references relevant to the model description and use.
Wigmosta, M. S., D. P. Lettenmaier, and L. W. Vail, 1994, A distributed hydrology-vegetation model for complex terrain, Water Resources Research, 30(6), 1665-1679.
Storck, P., D. P. Lettenmaier, B. A. Connelly, T. W. Cundy, 1995, Implications of forest practices on downstream flooding: Phase II Final Report, Washington Forest Protection Association, TFW-SH20-96-001, 100p.
Storck, P., Laura Bowling, Paul Wetherbee, Dennis Lettenmaier, 1997: APPLICATION OF A GIS-BASED DISTRIBUTED HYDROLOGY MODEL FOR PREDICTION OF FOREST HARVEST EFFECTS ON PEAK STREAMFLOW IN THE PACIFIC NORTHWEST Accepted for publication in a special issue of Hydrological Processes.