View source for Building a Model:Calibration and Verification

The complete model should be calibrated and verified to an extended period of data while operating in the '''LONG_TERM''' mode.  For flow models, the model should be calibrated to observed discharges at the outlet and any interior points.  The '''OPTIMIZE''' project card can be used to provide peak discharge and discharge volume for individual events and the entire simulation at the watershed outlet and at any desired internal locations.  These can be used to calculate a cost function, and parameter sets that produce the smallest cost function, minimum error as defined by the cost function, can be determined either manually or preferably with an automated method, such as the SCE method.  Typical calibration parameters listed in order of importance for each process include:

:<font class="uline">Overland Flow</font> <br> 
:Surface roughness<br> 
:Retention depth<br> 
:<font class="uline">Infiltration</font> <br> 
:Saturated hydraulic conductivity (all methods)<br> 
:Suction head (GA, multi-layer GA, GAR) or bubbling pressure (RE)<br> 
:Initial moisture<br> 
:Porosity<br> 
:<font class="uline">Channel Flow</font> <br> 
:Roughness coefficient<br> 
:<font class="uline">Evapo-transpiration</font> <br> 
:Root depth<br> 
:Canopy resistance<br> 
:<font class="uline">Soil Moisture</font> <br> 
:Pore distribution index<br> 
:Wilting-point soil moisture<br> 
:<font class="uline">Groundwater Flow</font> <br> 
:Saturated hydraulic conductivity<br> 
:Porosity<br> 


To use the SCE method, the number of parameters to be calibrated should be kept to a minimum, typically less than 16 (Senarath et al., 2000).  To reduce the number of parameters, the proportions of initial estimates of parameters for different index types can be adjusted as a set, i.e. adjust all values of some parameter, saturated hydraulic conductivity for example, by the same fractional amount.

The model with the calibrated parameter set should be tested against independent verification period, such as a split-sample test (Klemes, 1986).  Once the model demonstrates the ability to predict discharge, or other variables of interest, for the verification period, it can be used with confidence to analyze model scenarios and make predictions under varying hydrologic conditions.
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