Hydrology Modeling in Alaska: Model Documentation Template
(please fill out as much as possible)
Your name: Emily Youcha 907 474-2713
Model name: HBV
Authors: Bergstrom, 1972, 1992 Swedish Meteorological and Hydrologic
Institute (SMHI)
Source code location (if public):
Citations and URLs for basic documentation:
www.smhi.se
Source code language:
We use the commercially available GUI, but the model is fortran based.
For the following section, you may wish to use appropriate keywords such as:
Physically-based, statistical, lumped parameter, spatially distributed, transitive
model, equilibrium model, implicit, semi-implicit, explicit, TOPMODEL based,
finite element, finite differences, routing, bottom boundary condition, parallel
code, Richardson equation, optimization, forecast, etc
Model type and/or conceptual framework:
 Semi-distributed conceptual rainfall-runoff model
 Divide the basin into sub-basins and then into elevation/vegetation zones,
and lake areas
 Routines: snow, soil moisture accounting, runoff response, routing
 Can be linked with SMHI real time river forecasting products
Data needed to run the model (inputs):
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Precipitation
Air temperature
Discharge
Potential Evapotranspiration
Net Radiation (optional)
Wind (optional)
Elevation distribution (optional)
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Lake percentage (optional)
Glacier percentage/elevation (optional)
Parameters and how they are derived:
15-25+ parameters to calibrate, several parameters for each routine. Most are
derived through the calibration process.
Snow routine (degree day method):
Snowmelt = cfmax (T-tt)
threshold temperature (tt), snowmelt factor (cfmax), water holding capacity of
snow, precipitation correction factor (snow or rain), refreezing factor. Glacial melt
may also be included.
Soil moisture accounting: Bucket model. BETA controls the increase in soil
moisture from each mm of precipitation (controls the contribution to runoff ratio),
FC is the maximum soil moisture storage, and LP is the value at which ET
reaches potential value, expressed as a fraction of FC.
Runoff response and routing routines: Parameters include: recession
coefficients, K, reservoir storage, UZL. Upper and lower reservoirs represent
quickflow and slow runoff. Linear and non-linear options. Parameter PERC,
controls percolation to lower deeper reservoir. Set PERC=0 for continuous
permafrost. Transformation/Routing – filter technique & time lags using
MAXBAS parameter, can also use parameters LAG/DAMP to delay water in river
channel.
Spatial element used to lump inputs and outputs:
Sub-models (i.e. snow or ground thermodynamics):
Rainfall/runoff transformation mechanism:
Runoff routing within spatial elements and to basin outlet:
Method for including sub-grid scale processes:
Resolution (possible & prudent):
Method of deriving topography:
Calibration approaches:
Manual trial and error calibration in our version. Objective function is the Nash
Sutcliffe coefficient and looking at the accumulated volume difference of runoff.
HBV-light (Siebert, 1997) has an automated Monte-Carlo routine to estimate
parameters. This was attempted, but didn’t get the greatest results due to short
time series of input data (spring and summer per year) and probably
overparameterization. Many different parameter sets can be used to get a good
results but which parameter set is physically realistic?
Treatment of frozen ground:
Set PERC parameter (percolation to the lower flow reservoir) = 0
Publications using this model:
Strengths and Weaknesses in Alaska applications:
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Challenges with manual trial and error calibration. Too many parameters
to calibrate, some parameters may be inter-related.
Need a long dataset for calibration, many of our datasets are too short.
I think it works best in larger watersheds. We have looked at small basins
(2 km2 – 147 km2) and it hasn’t worked that great, but seems to improve
as the basin size gets larger. I will next try the entire Kuparuk basin (8147
km2). Trouble w/ snow damming in Imnavait basin.