PowerPointPrsentation

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Dynamic crop growth modelling with AGROSIM
Application on the Bad Lauchstädt site
Wilfried Mirschel
Leibniz-Centre for Agricultural Landscape
Research (ZALF) Müncheberg,
Institute of Landscape
Systems Analysis
Eberswalder Str.84, 15374 Müncheberg
e-mail wmirschel_at_zalf.de
International Workshop Modelling soil processes
in different time scales, Halle, 19th 20th
September 2005
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Content

• Motivation
• 2. Agro-ecosystem model family AGROSIM
• 2.1. AGROSIM model for winter cereals
• 2.2. AGROSIM model for sugar beet
• 2.3. AGROSIM model applications
• 3. AGROSIM model workshop results for Bad
  Lauchstädt (short term experiment)
• 3.1. Without parameter adaptation
• 3.2 With parameter adaptation
• 5. AGROSIM model transfer to other geographical
  sites
• 6. Conclusions

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Motivation
? Yield formation and biomass accumulation in
agriculture play an essential role in water,
energy and nutrient cycles in agro-ecosystems. ?
While crop yield on farm level are mainly in the
focus of interest because of economic
considerations, the total biomass is in the focus
of interest because of changed water, nutrient
and carbon balances as consequence of land use
and climate changes. ? In agro-ecosystems
biomass formation and turnover is influenced by
different factors. climate and weather,
site conditions (incl. water and nutrients
supply ), crop properties (incl. cultivars,
plant physiology and genetics), management
and influences from other system components
(pests and diseases). ? Simulation models are
powerful tools to investigate the effects of
different land use options and/or climate
changes on water and matter cycles as well as to
bridge the gap between different temporal and
spatial scales.
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Agro-ecosystem model family AGROSIM (1)
The model family AGROSIM which consists plant
physiological based agro-ecosystem models for
agricultural crops was developed in the Institute
of Landscape Systems Analysis of the
Leibniz-Centre for Agriucultural Landscape
Research Müncheberg (Germany) beginning in the
1990th.
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Agro-ecosystem model family AGROSIM (2)
The dynamic plant physiologically based AGROSIM
models ? belong to the group of
soil-plant-atmosphere-management models with the
main focus on crop growth processes, ? were
elaborated not for single plants, but for whole
crop stands under field conditions, ? have a
similar model structure on the basis of rate
equations, ? describe the processes with a time
step of 1 day, ? need only standard
meteorological input values (minimum and maximum
temperature, global radiation or sunshine
duration, precipitation, CO2- content in the
atmosphere) as driving forces and generally
available inputs and parameters, ? are
validated for weather and soil conditions of
different locations in North- East Germany.
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AGROSIM model for winter cereals - Model
structure -
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AGROSIM model for sugar beet - Model structure -
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AGROSIM model validation results
Model-experiment-comparison for winter barley,
1993/94, Müncheberg
Model-experiment-comparison for above-ground
biomass, 1991-1995, Müncheberg
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AGROSIM model applications - Influence of water
supply -
Influence of water supply on yield and biomass
for winter wheat (1991/92, N-fertilization 125
kg N ha-1, Hohenfinow, cultivar Alcedo)
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AGROSIM model applications - Influence of
nitrogen supply -
Influence of nitrogen supply on yield and biomass
for winter wheat (1991/92, with irrigation,
Hohenfinow, cultivar Alcedo)
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AGROSIM model applications - Influence of
increased CO2 in the atmosphere on biomass
accumulation (1) -
Basis influence of CO2 on photosynthesis and
respiration processes (not on stomata level)
Michaelis-Menten-equation for C3-plants, basis
level 350 ppm
with CO2 - CO2-content in the atmosphere GS -
global radiation
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AGROSIM model applications - Influence of
increased CO2 in the atmosphere on biomass
accumulation (2) -
Sugar beet, 2001,N 126 kg N ha-1, with
irrigation, Simulation with AGROSIM-ZR
Winter barley, 2002/03,N 179 kg N ha-1, with
irrigation, Simulation with AGROSIM-WG
Data base FACE experiment ( 1999 2005) of
the Federal Agricultural Research Centre
Braunschweig, Germany
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AGROSIM model applications - Influence of CO2
and temperature on biomass accumulation -
Influence of temperature and CO2 increase on
biomass accumulation of winter rye
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AGROSIM model applications - Climate change
effect assessment for winter rye biomass and
yield 1994 vs. 2034 -
Basis climate model ECHAM1/LSG of the
Max- Planck-Institute for Meteorology Hamburg,
Scenario business as usual
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AGROSIM model workshop results for Bad Lauchstädt
? AGROSIM models run for the short time
experiment (1999-2004). ? Because of not
availability of AGROSIM models for potatoes and
spring barley model runs for sugar beet in 1999
and 2003, and winter wheat in 2001/02 were
realized only. 1. Without any parameter
adaptation ? original model parameter set for
Müncheberg was used 2. With parameter
adaptation ? cultivar dependent model
parameters were adapted only
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AGROSIM model workshop results for Bad Lauchstädt
without parameter adaptation (1)
Sugar beet, 1999
? root and leaf biomass estimation with a
good accuracy (light underestimation at harvest
time) ? soil water is overestimated,
especially in 90 cm depth during summer and
late summer
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AGROSIM model workshop results for Bad Lauchstädt
without parameter adaptation (1)
Sugar beet, 2003
? root and leaf biomasses are under- and
overestimated, respectively ? soil water
estimation with a good accuracy (light
overestimation especially in 90 cm depth during
summer and late summer)
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AGROSIM model workshop results for Bad Lauchstädt
without parameter adaptation (2)
Winter wheat, 2001/02
? significant overesti- mation in above- ground
biomass and N- uptake during grain filling
period ? soil water estimation in 45 cm and 90
cm depth is a little bit underesti- mated,
especially in 45 cm depth during spring and
summer
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AGROSIM model workshop results for Bad Lauchstädt
with parameter adaptation (1)
Sugar beet, 1999
? after adaptation of cultivar model
parameters (distribution ratio between leaf
and root) the biomasses can be estimated with
a higher accuracy ? the cultivar parameter
change does not influence the soil water
course
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AGROSIM model workshop results for Bad Lauchstädt
with parameter adaptation (1)
Sugar beet, 2003
? here also the same parameter adaptation
(distribution ratio function between leaf and
root) ? adapted variant (dotted lines) has a
better agreement with the measured biomasses
over the time
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AGROSIM model workshop results for Bad Lauchstädt
with parameter adaptation (2)
Winter wheat, 2001/02
? adaptation of cultivar model parameters gives
significant better results in biomass
accumulation (dotted lines) ? ontogenesis and
soil water are not changed significant
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AGROSIM model transfer to other geographical
sites (1)

• ? To transfer crop growth and ecosystem models
  from one geographical site to another
  successfully it means to recalibrate model
  parameter in every case, more or less intensive!
  This is shown by
• workshop results with the Bad Lauchstädt data set
  from the short time experiment
• transfer investigations with the AGROSIM model
  for winter wheat to different European sites

Russia
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AGROSIM model transfer to other geographical
sites (2) AGROSIM-WW transfer to
European sites -
Latitude 39.3 ... 55.0 Experimental
sites 24 Growing periods 1957 ...
1997 different Cultivars 29
Model-experiment-comparison for winter wheat
grain yield (simulation with AGROSIM-WW)
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Conclusions
? The AGROSIM models for sugar beet and winter
wheat can describe the real situation on the Bad
Lauchstädt experimental station for 1999, 2001/02
and 2003 with a sufficient accuracy only after a
recalibration of cultivar model parameters. ?The
workshop results show that a model transfer to
other geographical and sits conditions model
parameters representing crop, site and other
properties must be re- estimated or newly
derived. ? A model transfer without any
adaptation is not useful ! ? The better
considered the influence of site, weather,
agro-management and cultivar properties the more
accurate the simulation results and the greater
the possibilities to transfer a model from one
geographical site to another and from one time
period to another. ? The chances of a broad
model application increase if model adaptation
could be limeted to weather and soil information
and only a few clearly defined parameters. For
this coherent data series are needed.
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Conclusions
What is the parameter situation of crop growth
models within long-term simulations ? ? In
opposite to the soil processes with more or less
constant laws of soil physics and more or less
constant process parameters, the crop growth
processes are adaptable processes controlled by
genetic memory and genetic information, i.e with
changeable process parameters (ontogenetic rates,
shoot-root-ratio, straw-grain-ratio ...) over a
long time. On the one hand there are
anthropogenious reasons like plant breeding, and
on the other hand there are natural reasons like
the self adaptation of plants to changing
environmental factors. ? Investigation results
that the CO2-reaction of old winter wheat
cultivars from the 1930th differ from that of
modern winter wheat cultivars underlines this
fact (R. Manderscheid, Federal Agricultural
Research Centre Brunswick, Germany). ? Changing
genetic plant-own reactions from plant generation
to plant generation make it necessary to adapt
parameters in crop growth models anew for
different time periods. So it is necessary to
adapt these parameters any times for long-term
simulation runs, like for the about one hundred
years experiment here in Bad Lauchstädt.
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Thank you for your attention !