GMS:MODFLOW Solution Properties Dialog: Difference between revisions

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===Point head observation errors===
===Point head observation errors===
: ''Mean Residual (Head)''.  
: ''Mean Residual (Head)''.  
: ''Mean Absolute Residual (Head)'''.  
: ''Mean Absolute Residual (Head)''.  
: ''Root Mean Squared Residual (Head)''.
: ''Root Mean Squared Residual (Head)''.


Revision as of 21:20, 19 December 2014

MODFLOW
Pre-processing
MODFLOW Commands
Building a MODFLOW Model
Map to MODFLOW
Calibration
Packages Supported in GMS
Saving a MODFLOW Simulation
Importing MODFLOW Files
Unsupported MODFLOW Features
Run MODFLOW
Post-processing
MODFLOW Display Options
MODFLOW Post-Processing Viewing Options
Reading a MODFLOW Simulation
Tutorials
Packages
Flow: BCF6, HUF, LPF, UPW
Solvers:

DE4, GMG, NWT, PCG,

PCGN, LMG, SIP, SOR,

SMS
Other:

BAS6, BFH, CHD1, CLN,

DRN1, DRT1, EVT1, ETS1,

GAGE, GHB1, GNC, HFB1,

HUF, LAK3, MNW1, MNW2,

OUT1, RCH1, RIV1, SFR2,

STR1, SUB1, SWI2, WEL1,

UZF1
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The MODFLOW Properties dialog box is opened by right-clicking on the MODFLOW solution folder in the project explorer.

File:ModflowProperties.JPG

The data in this dialog come from the *._os, *._ww, *._r, *._w files computed by the MODFLOW Observation process. The computation from MODFLOW will include any observed flows combined with the observed heads to calculate a single error value. In a transient model, the error value includes all of the observations at the various times. The error shown in this dialog is different from the error found in the Error Summary Plot.

MODFLOW Properties dialog box

Comment on different error values

  • Mean Residual – Average error for the observations. This can be misleading because the positive and negative errors can cancel.
  • Mean Absolute Residual – Mean of the absolute error values for the observations. This is a true mean, not allowing positive and negative errors to cancel.
  • Root Mean Squared Residual – RMS is calculated by taking the sum of the square of the errors for the observations and then taking its square root. This tends to give more weight to cases where a few extreme error values exist.
  • Sum of Squared Weighted Residual – This is the error value that is minimized by a PEST run.

Point head observation errors

Mean Residual (Head).
Mean Absolute Residual (Head).
Root Mean Squared Residual (Head).

Flow observation errors

Mean Residual (Flow).
Mean Absolute Residual (Flow).
Root Mean Squared Residual (Flow).

Combined head and flow error values

Mean Weighted Residual (Head+Flow).
Mean Absolute Weighted Residual (Head+Flow).
Root Mean Squared Weighted Residual (Head+Flow).
Sum of Squared Weighted Residual (Head+Flow).


v • e
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