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SPDSS_Task48-2_AlluvialGroundwaterModelingCalibration
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SPDSS_Task48-2_AlluvialGroundwaterModelingCalibration
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Last modified
4/17/2013 9:26:40 AM
Creation date
8/11/2008 1:11:50 PM
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Decision Support Systems
Title
SPDSS Task 48.2 - Development of Calibration Targets and Criteria - Phase 4
Description
This Technical Memorandum was undertaken under Task 48.2 of Phase 4 of the SPDSS, to develop calibration criteria, including selection of field data (targets) to be used during the model calibration. This TM summarizes the methodology and data that are anticipated to be used in the model calibration process.
Decision Support - Doc Type
Task Memorandum
Date
10/8/2008
DSS Category
Groundwater
DSS
South Platte
Basin
South Platte
Contract/PO #
C153953
Grant Type
Non-Reimbursable
Bill Number
SB01-157, HB02-1152, SB03-110, HB04-1221, SB05-084, HB06-1313, SB07-122
Prepared By
CDM
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The absolute difference between simulated and observed diversions across all tinge <br />periods will be less than 10 percent of observed diversions. <br />T11e number of flooded and dry cells will be less than one percent of t11e model cells >IZ <br />t11e active model domain and will be randomly distributed. <br />The difference between simulated and mapped areas of groundwater <br />evapotranspiration will be less than 10 percent when examined at the end of the <br />transient simulations. <br />4.2 Objective Function <br />The automated calibration process will utilize a combination of optimization techniques that <br />niininuzes the residual between model-calculated values and observed values for a <br />corresponding set of model inputs (Doherty, 2004). Mininuzing the residual involves use of an <br />objective function that is comprised of a defined set of error terms for eac11 target along with a <br />weighting function for that target. There are three key parameters that constitute the <br />calibrations targets: head, streamflow and stream gain/loss. T11e Head is broken down further <br />into three categories (surveyed wells, non-surveyed wells with multiple measurements, and <br />non-surveyed wells with a single measurement) to allow different weigllt>11g factors to be <br />applied to each, as discussed in Section 4.3. T11is objective function takes the follow>11g form: <br />OF = wi(Hi) + wz(Hz) + wz(H,) + w3(S) + w~(G) <br />Where: <br />OF is fl1e Objective Fwlction <br />H~ is the sum of Head residuals of water level elevations at surveyed wells <br />H~ is t11e sum of head residuals of water level fluctuations atnon-surveyed wells that <br />have more than one measurement <br />Hs is the sum of head residuals of depth to water atnon-surveyed wells that have one <br />measurement <br />S is the sum of streamflow residuals at stream gaging stations <br />G is the sum of stream gain-loss residuals at reaches between gaging stations <br />wi, wz, war w~, and ws are the weight>lzg factors for each target <br />Each target may be subdivided into groups based on geographic location, data accuracy, <br />location along the mainstem or a tributary, or other factors. In these cases there will be a <br />separate target term and weighting factor i11 the objective function. The various measures must <br />also be scaled so that the different error terms are comparable. For example, streamflows are >11 <br />flow rates (cfs) that can vary by hundreds to thousands of units compared to water level <br />elevations that are in length units (feet) and typically vary by tenths of units. Tl1e various terms <br />i11 fl1e objective fwlction will be scaled to remove these unit dependencies. Further details on <br />objective functions are provide >IZ the PEST manual (Doherty 2004) and in Anderson and <br />Woessner (1992), among other references. <br />4.3 Weighting Factors <br />Weightuzg factors will be utilized to develop the goodness of fit statistics for the model <br />calibration by consideruzg the reliability of uzdividual measurements. The weighting factors <br />represent an estimate of the measurement error. These errors are an estimate of t11e underlying <br />accuracy of the measurement, not a measure of variation in fl1e data over time. For example, <br />P~ SPDSS T~8 2 Final TM 10-08-0t~.doc 17 <br />
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