Difference between revisions of "Calibration"

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

Revision as of 13:14, 10 April 2018



General description

The 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

Agropheno data are stored in a relational database that contains experimental data, expert knowledge and regional calendars. The database contains the following data sets:

1  PASK: pasture data from candidate member States
2  Boons-Prins study, inserted in 2005
3  MOCA: crop data from candidate member states, inserted in 2005
4  Crop-KUL: crop parameters, inserted in 2006
5  GEOSYS/ASEMARS, inserted in 2006 and 2007
6  ZAMG (Zentralanstalt fur meteorologie und geodynamik), inserted in 2008
7  AETS: Data for Ukraine and Turkey, inserted in 2016
9  MARS Activity-B-2001, inserted in 2016
10 Bilateral Austria, inserted in 2016
11 Bilateral Germany, inserted in 2016
12 Bilateral Slovakia, inserted in 2016
13 Bilateral Slovenia, inserted in 2016
14 Bilateral Russia/Kazakhstan, inserted in 2016 
15 MOCCASIN project, inserted in 2017
16 MARSOP4 - general targets for LAI and HI, inserted in 2017
17 GLOBAM, inserted in 2009
18 Huabei CGMS, inserted in 2009
19 RUBKA, inserted in 2009
20 Asia CGMS (I. Savin), inserted in 2009

XY locations of experiments and regional data are mapped to grid numbers of the regular target agro climatic that is defined for each regional window in the system.

Crop name Crop_no Data sets Calibration Tool Status MODEL WINDOW
Winter Wheat 1 2-4  ? Operational WOFOST EUR
Grain maize 2 2-6 Calplat Operational WOFOST EUR
Spring Barley 3 2-6 Calplat Operational WOFOST EUR
Rye 4 2-5 Calplat Operational WOFOST EUR
Rice 5  ?  ? Operational WARM/BLAST EUR
Sugar beet 6 2-4  ? Operational WOFOST EUR
Potato 7 2-4  ? Operational WOFOST EUR
Field beans 8 3  ? Operational WOFOST EUR
Winter Rapeseed 10 2-6 Calplat Operational WOFOST EUR
Sunflower 11 2-4  ? Operational WOFOST EUR
Winter Wheat Vernalisation 90 2-14, 16 Calibration Manager Under revision WOFOST EUR
Winter Wheat 91 2-5 Calplat Under revision WOFOST EUR
Field beans 92 2-5 Calplat Under revision WOFOST EUR
Sunflower 93 2-5 Calplat Under revision WOFOST EUR
Winter Rapeseed 94 2-5 Calplat Under revision WOFOST EUR
Spring Barley 95 2-6 Calplat + WCC Under revision WOFOST EUR
Spring Barley Ukraine 96 2-7, 15-16 Calibration Manager Under revision WOFOST EUR
Grain maize Ukraine 97 2-7, 15-16 Calibration Manager Under revision WOFOST EUR
Winter wheat 2008 1 19-20 Calplat Operational WOFOST RUK
Winter wheat 2012 2 19-20 Calplat Operational WOFOST RUK
Spring wheat 2008 3 19-20 Calplat Operational WOFOST RUK
Spring wheat 2012 4 19-20 Calplat Operational WOFOST RUK
Grain maize 2008 5 17-18 Calplat Operational WOFOST RUK
Grain maize Rus/Kaz 89 14 Calibration Manager Under revision WOFOST RUK
Field Peas  ? 3  ? Not operational WOFOST EUR
Oat  ? 3  ? Not operational WOFOST EUR
Winter Barley 13 2-4  ? Not operational WOFOST EUR
Spring Rape seed  ? 2-4  ? Not operational WOFOST EUR
Soy Bean  ? 3  ? Not operational WOFOST EUR
Rice  ?  ?  ? Not operational WOFOST EUR
Rye Grass  ? 1  ? Not operational LINGRA EUR
Alfalfa  ? 1  ? Not operational LINGRA EUR
Tomato  ?  ?  ? Not operational CGMS SYTEM EUR

The following calibration levels are identified for regional and local calibrations, and executed in this order, gradually further optimizing results:

Level Regional calibration Local calibration
Phenology TSUM1, TSUM2 TSUMEM, TBASEM, TSUM1, TSUM2, DLO, DLC, TEFFMX
Potential yield level - simple AMAXTB AMAXTB, SLATB, SPAN
Potential yield level - complex SLATB, SPAN, FOTB AMAXTB, SLATB, SPAN, RGRLAI, LAIEM, TDWI, FLTB, FRTB, FOTB, TMPFTB, RDRRTB
Water limited yield level CFET, RDMCR CFET, RDMCR, PERDL, DEPNR

Required agropheno data:

Level Regional calibration Local calibration
Phenology Regional calendars or observations of sowing, emergence, flowering, maturity and harvest observations of sowing, emergence, flowering, maturity and harvest for different years
Potential yield level - simple Observations of total biomass under optimal conditions for locations or regions observations of LAI-max and total biomass under optimal conditions
Potential yield level - complex Observations of LAI-max, total biomass and/or yield under optimal conditions for locations or regions observations of LAI, total biomass, weights of leaves, stems, storage organs and roots over time during the growth period under optimal conditions
Water limited yield level Observations of total biomass and/or yield under rainfed conditions for locations or regions observations of LAI, total biomass, weights of leaves, stems and storage organs and possibly crop transpiration, evaporation and rooting depth over time during the growth period under water-limited conditions

The calibration consist in the following subtasks:

  • Consistency check of the datasets (area of interest, agropheno data).
  • Select calibration tool
  • Create zonation and crop mask
  • Add default crop from which to start calibration.
  • Calibrate phenology: TSUMEM, TSUM1, TSUM2
  • Analyse calibration results: WRMSE's, TSUM1, TSUM2, TSUM1+TSUM2, TSUM1/TSUM2, outliers
  • Optionaly correct input data (e.g. zonation, crop masks, agropheno data or weather data) and restart calibration
  • Implement calibrated TSUMS and simulate full archive over full geographic extent
  • Calculate metrics (long term average crop simulation characteristics) for operational- and newly calibrated crop
  • Calculate yield forecast for operational- and newly calibrated crop
  • Validation with sub data sets.