1. Please write down the name (and abbreviation) of your snow model or land-surface model with snow component?


2. Name and address of model developer;

Dr. Geoff W. Kite
National Hydrology Research Institute
11 Innovation Blvd
Canada S7N 3H5

phone (306) 975-5687
fax (306) 975-5143

3. Name and address of model user;

many different

4. Please indicate whether your model is developed for application

   in understanding snow processes,   
   in a runoff forecasting model,	 
   in a weather forecasting model,      X
   in a global climate model (GCM),     X    
   or other (please specify)?           X (regional climate model)

5. The first year when the model was used;


6. One paragraph description of your model (e.g. abstract from report or paper);

SLURP [Kite, 1996] is a continuous simulation distributed hydrological model in which the parameters are related to land cover (vegetation type). The most important parameters used in the model include interception coefficients, depression storage, surface roughness, infiltration coefficient, groundwater conductivity and snowmelt rates. The model can take into account changes in the distribution and type of land cover over time and is therefore suitable for climatic change impact studies [Kite, 1993].

The SLURP model divides the watershed into hydrologically-consistent sub-units known as aggregated simulation areas (ASA). An ASA is not a homogeneous area but is a grouping of smaller areas with known properties. For example, land cover may be measured from satellite for pixels as small as 10-m; it would be impracticable for a hydrological model to operate at such a dimension for a macro-scale basin. Instead, the pixels are aggregated into areas which are more convenient for modeling. The number of ASAs used in modeling a watershed will depend on the size of the watershed and the scales of data available.

At each time increment, the model is applied sequentially to each element of the matrix of ASAs and land covers. Each element of the matrix is simulated by four nonlinear reservoirs representing canopy interception, snowpack, rapid runoff (may be considered as a combined surface storage and top soil layer storage) and slow runoff (may be considered as groundwater). The model routes precipitation through the appropriate processes and generates outputs (evaporation, transpiration and runoff) and changes in storage (canopy interception, snowpack and soil moisture). Runoffs are accumulated from each land cover within an ASA using a time/contributing area relationship for each land cover and the combined runoff is converted to streamflow and routed between each ASA.

7. Please specify any known application range or restrictions;

Has been applied for prairie sloughs (1-2ha area) and for macroscale watersheds such as the Mackenzie (1.8 million square km)

8. What are the development data needs;

Needs topographic data, land cover data, climate and hydrometric data.

9. What are the operational data needs?

climate data

10. Please indicate with an "x" for those meteorological variables used to DRIVE your snow model?

   precipitation                   : X
   air temperature                 : X
   wind speed                      :  
   wind direction                  :   
   humidity                        :  
   downwelling shortwave radiation : X 
   downwelling longwave  radiation : X
   cloud cover                     : 
   surface pressure                : X 

11. List the state variables (e.g., snow temperature, snow water equivalent, etc) your snow model uses?

snow water equivalent, 
soil heat flux

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?


13. What are the output data?

Snow water equivalent, 

14. What computer language does your model use?


15. How many subroutines (or functions) does your snow model have?

integrated in larger model

16. Number of lines of the snow code?


17. What is the recommended hardware?


18. How does your model determine the form of precipitation (i.e., snowfall and rainfall)? Please give the formulation.

above or below specified air temperature

19. Is your snow model one dimensional or multi-dimensional? Please specify.

one dimensional applied to areas of common land cover

20. If one dimensional, how many layers are there in your snow model? Please specify layering structure.

one layer

21. What is your snow model time step?


22. Does your model snow albedo allow its

    spectral differences    (visible vs. near-IR)? 
    directional differences (direct  vs. diffuse)? 

23. Is your model snow albedo a function of

      snow age                 X
      grain size               
      solar zenith angle        
      snow depth?               

24. Does your snow model explicitly treat liquid water retention and percolation within the snowpack?


25. Does your snow model account for changes in the hydraulic and thermal properties of snow due to meltwater refreezing?


26. Is snow density in your snow model changing with time or fixed?

model uses only snow water equivalent

27. Is heat capacity and conductivity in your snow model changing with time or fixed?

heat content not tracked

28. Does your snow model simulate vapor transfer in the snowpack?


29. Does your snow model account for the heat transfer between the bottom of the snowpack and the underlying soil?


30. In snow energy balance, does your model consider heat convected by rain or falling snow?


31. Does your snow model include snow drifting and redistribution by wind (or avalanche)? If so, how?

not now, PBSM is being included.

32. How is areal snow distribution treated?

by land cover

33. Does your snow model account for sub-grid (or sub-watershed) effects of topography? If so, how is temperature distributed?

yes, lapse rate

how is precipitation (spatial, elevation and corrections) distributed?

geostatistical interpolation, lapse rate

how is solar radiation distributed?

geostatistical interpolation

how is wind distributed?

how are other meteorological variables distributed?

34. Does your snow model consider snow-vegetation interaction?

only in terms of interception of precipitation

35. Does the snow-vegetation interaction account for

 different vegetation types     (grass vs. forest),            X
 different vegetation heights   (short vs. tall),           
 different vegetation densities (small vs. large LAI),         X  
 different vegetation coverages (sparse vs. dense vegetation)?

36. Are snow interception, drip and melt on canopy surface allowed in your model?

Interception only evaporates or spills

37. How is the upper limit of the canopy interception determined?

depends on vegetation and current LAI

38. In the presence of vegetation, how is snow surface albedo altered?

initial snow albedo depends on vegetation type

39. In the presence of vegetation, how is snow surface roughness altered?


40. In the presence of forest, does your snow model allow spatial variability of snow depth and water equivalent on forest floor?

not within a land cover type

41(a). How does your model deliver snowmelt to the soil system (e.g. affecting soil moisture)?

snowmelt is infiltrated or runs off

(b). Once snowmelt is generated, how does your model relate it to runoff?

snowmelt either runs off directly (rare) or infiltrates a top soil layer and percolates lower and becomes groundwater runoff

42. How is frozen soil treated in your model?

not at the moment, in progress this year

43. Has your snow model been tested with the field data?


If so, what data? (areas)

what are their temporal and spatial scales?

has been verified with snow course data and with output from atmospheric = models

44. Has your snow model been used together with remote sensing data as input?


If so, how? The model can use snow extent from NOAA AVHRR or Landsat, etc to distribute snow water equivalent and can update the computed snow water equivalent using data from DMSP SSM/I.

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.

47. Please specify verification criteria, if any?

Previous Day

all based on recorded and simulated streamflow

48. What are the model fitting procedures, if any?

parameters estimated then calibrated

49. What are future plans for using/improving the model?

Prairie Blowing Snow Model and frozen-soil infiltration models to be added this year (i.e., 1997)

50. Please provide references relevant to the model description and use.

Kite, G.W., 1995: The SLURP model. Chapter 15 in: Computer models of watershed hydrology by V.P. Singh (ed.), Water Resources Publications, Colorado, USA, 521-562.

Kite, G.W., 1994: Hydrological modelling using remotely sensed data and geographic information systems. In: Trends in Hydrology by J. Menon (ed.), 191-208, CSRI, Trivandrum, India.

Kite, G.W., A. Pietroniro and T.J. Pultz, 1995. Remote Sensing in Hydrology, Proceedings of NHRI Symposium No. 14, NHRI, Saskatoon, 322pp.

Kite G.W, 1995: Scaling of input data for macroscale hydrologic modeling. Water Resources Research, 31(11),2769-2781.

Kite, G.W. and A. Pietroniro, 1996. Remote sensing applications in hydrological modelling, Hydrol. Sci. J., 41(4), 563-591.

Kite, G.W., 1996. Use of remotely sensed data in hydrological modelling of the Upper Columbia Watershed, Can. J. Rem. Sens., 22(1), 14-23.

Kite G.W, A. Dalton & K. Dion, 1994: Simulation of streamflow in macro-scale watersheds using GCM data. Water Resources Research, 30(5), 1547-1559.

Kite, G.W., A. Pietroniro and T.J. Pultz, 1997. Remote Sensing in Hydrology, Proceedings of NHRI Symposium No. 17, Goddard Space Flight Center, 1996, NHRI, Saskatoon, 350pp.

-- Last updated Fri Oct 8 12:47:54 MST 1999 by Zong-Liang Yang.
For questions and comments, please contact Zong-Liang Yang