Calibrating and running RHESSys - Revision history

Dgroulx: /* Calibration strategies */

2009-10-28T21:41:35Z

Calibration strategies

Dgroulx: /* Calibration process */

2009-10-28T21:39:43Z

Calibration process

Dgroulx at 20:39, 8 October 2009

2009-10-08T20:39:44Z

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Dgroulx: New page: Module III - Calibrating and Running RHESSys A number of models are embedded in RHESSys that use mathematical representations of the key controls on ecosystem processes. While these rela...

2009-10-08T20:28:53Z

New page: Module III - Calibrating and Running RHESSys A number of models are embedded in RHESSys that use mathematical representations of the key controls on ecosystem processes. While these rela...

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 ==Calibration strategies==
 Calibration Parameters: Calibration in RHESSys is usually focused on streamflow.  However, if you have other observed data (i.e. daily nitrate, monthly psn, daily snowpack, etc...) it is possible to calibrate using these variables.  It should be noted that m, K, gw1 and gw2 are hydrologic parameters; however, since water often exerts a strong control on biogeochemical cycling, there may be situations where calibration of these parameters using secondary variables (i.e. PSN) is appropriate.
-Standard RHESSys calibration involves varying m and K to achieve the ‘best’ correspondence between observed and modeled daily streamflow patterns - where best is usually defined as a high value of the Nash-Sutcliffe Efficiency measure and a close match between observed and modeled total streamflow over the calibration period.
+Standard RHESSys calibration involves varying m and K to achieve the ‘best’ correspondence between observed and modeled daily streamflow patterns - where best is usually defined as a high value of the [http://en.wikipedia.org/wiki/Nash–Sutcliffe_model_efficiency_coefficient Nash-Sutcliffe efficiency] measure and a close match between observed and modeled total streamflow over the calibration period.
 Some users follow a more hierarchical calibration approach where first total annual streamflow volumes are matched and then further adjustments to m and K  (within ranges that produce reasonable total streamflow volumes) are made.
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 Calibrating is an iterative process that requires refinement as you go along.  Start by testing sets across the full range of possible values.  The range tested should be progressively restricted as a pattern emerges indicating the reasonable range for each parameter for the watershed being modeled.
 ==Calibration process==

@@ Line 164: / Line 164: @@
-     	R> NewFile = rbind(read.table(“eff.tut1”,
+ This step will only be necessary after you run multiple calibrations for a project.  However, this step has already been done
-   header=TRUE), read.table(“eff.tut2”,
+ for the  tutorial data, so you do not need to execute this command for these exercises.  This is for future reference.
-   header=TRUE))
+ When you run calibrations, you will generate multiple calibration result data files (multiple eff files, each with n, i.e. 25,
-******************************************************************************
+ number of results).  However, you will want to have all of the results in one file when you analyze them.  You can bind
@@ Line 204: / Line 205: @@
 Quit out of R:<br>
 '''R> q()'''
 ==Basic Run==