start:hype_tutorials:automatic_calibration
Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision | ||
|
start:hype_tutorials:automatic_calibration [2019/02/25 16:58] cpers [Quasi-Newton methods (task Q1 and Q2)] |
start:hype_tutorials:automatic_calibration [2024/01/25 11:37] (current) |
||
|---|---|---|---|
| Line 23: | Line 23: | ||
| Generally speaking, the purpose of the [[start:HYPE_file_reference:info.txt|info.txt]] is to govern the simulation. Most of the content of the file is the same as for an ordinary simulation. The following file content is relevant for automatic calibration: | Generally speaking, the purpose of the [[start:HYPE_file_reference:info.txt|info.txt]] is to govern the simulation. Most of the content of the file is the same as for an ordinary simulation. The following file content is relevant for automatic calibration: | ||
| * The flag ''Y'' must be passed to the model by the code ''calibration'' to turn on automatic calibration (red arrow in Fig 1). | * The flag ''Y'' must be passed to the model by the code ''calibration'' to turn on automatic calibration (red arrow in Fig 1). | ||
| - | * An objective function must be specified by means of the performance criteria it is composed of. Such a composite criterion, are constructed by linear combination of the already implemented, performance criteria, like: <m> c=w_1*c_1+ w_2*c_2+⋯+ w_N*c_N </m> | + | * An objective function must be specified by means of the performance criteria it is composed of. Such a composite criterion, are constructed by linear combination of the already implemented, performance criteria, like: <m> c=w_1*c_1+ w_2*c_2+ ... + w_N*c_N </m> |
| - | where <m> c_1,c_2,…,c_N </m> are predefined performance criteria, and <m> w_1,w_2,…,w_N </m> are relative weighting factors. The available performance criteria and their id are [[start:hype_file_reference:info.txt:criteria|listed here]]. The criterion id, the [[start:hype_file_reference:info.txt:variables|HYPE variable ID]] of the computed and recorded variables to compare, as well as the period over which the variables are averaged before calculating the criterion, is specified for each performance criterion to be included in the objective function (see the block of data marked in red and green in Fig 1). For details on format see the description of [[start:hype_file_reference:info.txt#performance_criteria_options|the info-file]]. | + | where <m> c_1,c_2, ... ,c_N </m> are predefined performance criteria, and <m> w_1,w_2, ... ,w_N </m> are relative weighting factors. The available performance criteria and their id are [[start:hype_file_reference:info.txt:criteria|listed here]]. The criterion id, the [[start:hype_file_reference:info.txt:variables|HYPE variable ID]] of the computed and recorded variables to compare, as well as the period over which the variables are averaged before calculating the criterion, is specified for each performance criterion to be included in the objective function (see the block of data marked in red and green in Fig 1). For details on format see the description of [[start:hype_file_reference:info.txt#performance_criteria_options|the info-file]]. |
| In the example of Fig 1 the Nash-Sutcliffe efficiency (''MR2'') and relative error (''MRE'') are calculated for daily discharge (''cout'' and ''rout'' are compared on ''meanperiod 1''). The two criteria are weighted together. Most weight is put on MR2 and a little on the volume error. A small weight on relative error is usually enough to minimize the volume error but still get a good NSE. In the example all observations found in Qobs.txt are used to calculate the objective function. If more than one station is found, the MR2 criterion will use the average of each station’s NSE. | In the example of Fig 1 the Nash-Sutcliffe efficiency (''MR2'') and relative error (''MRE'') are calculated for daily discharge (''cout'' and ''rout'' are compared on ''meanperiod 1''). The two criteria are weighted together. Most weight is put on MR2 and a little on the volume error. A small weight on relative error is usually enough to minimize the volume error but still get a good NSE. In the example all observations found in Qobs.txt are used to calculate the objective function. If more than one station is found, the MR2 criterion will use the average of each station’s NSE. | ||
start/hype_tutorials/automatic_calibration.1551110301.txt.gz · Last modified: 2023/11/16 14:28 (external edit)
Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Share Alike 4.0 International
