Calibration

1
Calibration
DOH Science Conference July 17, 2008
Mike Smith, Victor Koren, Zhengtao Cui, Seann
Reed, Fekadu Moreda
2
Current Status
AWIPS DHM
HL-RDHM
DHM-TF
P ET
P, T ET
(Forecast)
Auto Calibration
SNOW -17
rain
rain melt
SAC-SMA
SAC-SMA, SAC-HT
ICP
surface runoff
surface runoff
base flow
base flow
Hillslope routing
Hillslope routing
Channel routing
Channel routing
Mods
Flows and state variables
Flows and state variables
Forecasting
Calibration
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Manual and Auto Calibration

• Adjustment of parameter scalar multipliers
• Use manual and auto adjustment as a strategy
• Start with hourly lumped calibration
• Model parameters optimized in auto calb
• SAC-SMA
• Hillslope and channel routing
• Snow-17
• Search algorithms
• Simple local search
• Objective function Multi-scale
• Limited to headwater basins

4
Calibration Approach
Multiply each grid
value by the same
scalar
factor.
x 2
Preserve Spatial Pattern of Parameters
Example
I
parameter out of N total model parameters
th
Calibrate distributed model by
uniformly
adjusting all grid values
of each model parameter (i.e., multiply each
parameter grid value by the same factor)
1.
Manual manually adjust the
scalar
factors to get desired hydrograph fit.
2.
Auto use auto
-
optimization techniques to adjust
scalar
factors
.
5
HL-RDHM
P, T ET
SNOW -17
rain melt
Auto Calibration
SAC-SMA, SAC-HT
surface runoff
Execute these components in a loop to find the
set of scalar multipliers that minimize the
objective function
base flow
Hillslope routing
Channel routing
Flows and state variables
6
Multi-Scale Objective Function (MSOF)
Emulates multi- time scale nature of manual
calibration

• Minimize errors over hourly, daily, weekly,
  monthly intervals (k1,2,3,4nuser defined)
• q flow averaged over time interval k
• n number of flow intervals for averaging q
• mk number of ordinates for each interval
• X parameter set

Weight -Assumes uncertainty in simulated
streamflow is proportional to the variability of
the observed flow -Inversely proportional to the
errors at the respective scales. Assume errors
approximated by std.

7
Calibration MSOF Time Scales
Average monthly flow
Average weekly flow
Average daily flow
Multi-scale objective function represents
different frequencies of streamflow and its use
partially imitates manual calibration strategy
Hourly flow
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Auto Calibration Case 1
Example of HL-RDHM Auto Calibration ELDO2 for
DMIP 2 Arithmetic Scale
After autocalibration
Before autocalibration of a priori parameters
Observed
9
Auto Calibration Case 1
Example of HL-RDHM Auto Calibration ELDO2 for
DMIP 2 Semi-Log Scale
Observed
After autocalibration
Before autocalibration of a priori parameters
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Auto Calibration Case 2
Example of HL-RDHM Auto Calibration ELDO2 for
DMIP 2 Arithmetic Scale
After autocalibration
Before autocalibration of a priori parameters
Observed
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HL-RDHM and ICP

• Display time series
• ICP modifications
• Run MCP3 or HL-RDHM
• Copy optimized parameters to HL-RDHM input file
• Re-run HL-RDHM