Difference between revisions of "Calibration"

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|Winter Rapeseed || 10 || CGMS/KUL Univ. & MOCA DB || Calplat || Operational || WOFOST
 
|Winter Rapeseed || 10 || CGMS/KUL Univ. & MOCA DB || Calplat || Operational || WOFOST
 
|-
 
|-
|Spring Rape seed || CGMS/KUL-Univ. DB || CGMS/KUL Univ. & MOCA DB || Calibration || || WOFOST
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|Sunflower || 11 || CGMS/KUL Univ. & MOCA DB || Calplat || Operational || WOFOST
 
|-
 
|-
  
 
|Sunflower || 11 || CGMS/KUL Univ. & MOCA DB || Calplat || Operational || WOFOST
 
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|Soy Bean || CGMS/KUL-Univ. DB || MOCA DB || Calibration || || WOFOST
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|Winter Barley || 13 || CGMS/KUL Univ. and MOCA DB || ? || Not operational || WOFOST
 +
|-
 +
|Spring Rape seed || ? || CGMS/KUL Univ. & MOCA DB || ? || Not operational || WOFOST
 +
|-
 +
|Soy Bean || ? || CGMS/KUL-Univ. DB & MOCA DB || Calibration || Not operational || WOFOST
 
|-
 
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|Rye Grass || LINGRA & PASK DB || PASK DB || Recalibration || || LINGRA
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|Rye Grass || ? || LINGRA & PASK DB || ? || Not operational || LINGRA
 
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|Alfalfa || PASK DB || PASK DB || Calibration || || LINGRA
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|Alfalfa || ? || PASK DB || ? || Not operational || LINGRA
 
|-
 
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|Tomato || No data available || No data available || Calibration || || CGMS SYTEM
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|Tomato || ? || No data available || ? || Not operational || CGMS SYTEM
 
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Revision as of 15:43, 9 April 2018



General description

The (re)calibration of crops for WOFOST and LINGRA are performed using different calibration tools and agropheno datasets.

Tools

  1. WOFOST Control Centre: user interface to run wofost crop model and interactive selection of crop-, soil-, weather-files. Changes interactively model parameters. Analyse results in table and graphical format. Used for manually local calibrations.
  2. Calplat. Optimization platform to create zonations and execute automatic calibrations.
  3. Calibration Manager. Python script that combines Python wofost with open optimizer NLopt to automatically calibrate multiple zones and multiple parameters.

Data sets

  • AETS: Data for Ukraine and Turkey. Added in 2016.
  • Bilateral Austria. Added in 2016.
  • Bilateral Germany. Added in 2016.
  • Bilateral Slovakia. Added in 2016.
  • Bilateral Slovenia. Added in 2016.
  • Bilateral Ukraine. Added in 2017.
  • Boons-Prins study. Added in 2005.
  • Crop-KUL: crop parameters, including Kc coefficients, created with the KUL University. Added in 2006.
  • Geosys/ASEMARS. Added in 2006 and 2007.
  • MARS Activity-B-2001. Added in 2016.
  • MOCA: crop data from (at that time) candidate member states. Added in 2005.
  • MOCCASIN project. Added in 2017.
  • PASK (Pasture Knowledge base) DB which collects the most recent pasture data on new Member States. This DB was released in 2003.
  • MARSOP4 - general target values for LAI and HI. Added in 2017.
  • Zentralanstalt fur meteorologie und geodynamik. Added in 2008.

XY locations of are mapped to grid numbers of the regular target agro climatic that each regional window has.

Crop name Crop number Data sets used Calibration tool Status MODEL
Winter Wheat 1 CGMS/KUL Univ. & MOCA DB Calplat Operational WOFOST
Grain maize 2 CGMS/KUL Univ. & MOCA DB Calplat Operational WOFOST
Spring Barley 3 CGMS/KUL Univ. & MOCA DB Calplat Operational WOFOST
Rye 4 MOCA DB Calplat Operational WOFOST
Rice 5  ?  ? Operational WARM/BLAST
Sugar beet 6 CGMS/KUL Univ. & MOCA DB - Operational WOFOST
Potato 7 CGMS/KUL Univ. & MOCA DB - Operational WOFOST
Field beans 8 MOCA DB  ? Operational WOFOST
Winter Rapeseed 10 CGMS/KUL Univ. & MOCA DB Calplat Operational WOFOST
Sunflower 11 CGMS/KUL Univ. & MOCA DB Calplat Operational WOFOST
Winter Barley 13 CGMS/KUL Univ. and MOCA DB  ? Not operational WOFOST
Spring Rape seed  ? CGMS/KUL Univ. & MOCA DB  ? Not operational WOFOST
Soy Bean  ? CGMS/KUL-Univ. DB & MOCA DB Calibration Not operational WOFOST
Rye Grass  ? LINGRA & PASK DB  ? Not operational LINGRA
Alfalfa  ? PASK DB  ? Not operational LINGRA
Tomato  ? No data available  ? Not operational CGMS SYTEM

The calibration consist in the following subtasks:

  • Consistency check of the datasets (area of interest, make decisions how to calibrate the models and which part of the DBs to exploit).
  • Coherent recalibration from EU15 to EU25 with the results of the consistency check of the existing crops.
  • Calibration of new crops at EU25 level. This includes verifications of the consistency of the CGMS output by runnin simulations up to level 3 in order to verify the output obtained using the new crop parameters.
  • Validation with sub data sets.

The calibration and the validation can be done according to one of the following strategy/approaches based on the data availability:

  • Strong: Based on complete sets of crop parameters from experimental fields.
  • Medium: Based exploiting as much as possible the crop parameters data available in the DBs.
  • Light: Based on TSUM derived from CGMS level 1 and basic crop calendars. As the information of crop start-emergence/flowering/end-of-maturity at grid level are the basic information available in the system, the main tables which are analyzed are the WEATHER_OBS_GRID and the WEATHER_OBS_GRID_LTA to relate meteo data with calendar day to calculate crop TSUM.