Main features of the
Biome-BGC MuSo model
Zoltán BARCZA, Dóra HIDY
Training Workshop for Ecosystem Modelling studies
Budapest, 29-30 May 2014
Biome-BGC
Typical process-based biogeochemical model with some
shortcomings
-no management
- problematic phenology
-for grasslands
- very simple soil hydrology
- some parameters are
‘burned in’ within the source
code
- no drought effect
- general PFT parameterization is not applicable at site
level
Drought and heat in 2003 over Europe: response of Biome-BGC was
consistent with other models but cause of this was not plausible
(respiration increased in spite of drought – measurements do not support
this result)
Biome-BGC MuSo – multilayer soil module
• improved phenology – HSGSI method, combination of
heatsum and GSI index (Jolly et al., 2005 GCB)
• multilayer soil module [soil temperature is also
simulated layer by layer]
• effect of long lasting drought on plant mortality [leaf
senescence]
• stomatal conductance control – now with relative soil
moisture content
• root profile is simulated
• + management is implemented [not exclusively for
herbaceous vegetation]
Management
• mowing [hay meadows]
• grazing
• typical agricultural practices [ploughing, sowing, harvest,
use of organic or inorganic fertilizers]
• forest thinning is also implemented
Management
Hegyhátsál grassland:
mowing 1-2 times per year
mowing
mowing
Management
Prior to MuSo v1.3 management was the same in each
simulation year [set by the INI file]. Starting with MuSo v1.3
there is an option to control the normal simulation phase with
ancillary files that define annually varying management.
Example for mowing [this is a separate file!]:
Soil hydrology
MuSo v2.2.1
soil layer depths :
0-10, 10-30, 30-60,
60-100, 100-200,
200-300, and 300500 cm; soil layer
thickness is
calculated
(7 layers!)
Soil hydrology
Exponential root profile
Drought effect on biogeochemical cycles
Nagy et al., 2007 AGEE
Bugac – sandy grass [drought is
typical]
Drought induced plant mortality at Bugac
Hungarian grasslands – satellite view
Credit: Anikó Kern, Space Research Group, ELU
Effect of excess water
- elevated groundwater [flooded areas] are typical in
many lowland ecosystems
- measurements clearly show the effect of soil saturation
on fluxes
Effect of excess water – previous work
Effect of excess water – previous work
Effect of excess water – our approach
- water table depth is prescribed [model does NOT
calculate water table depth]
- another model [watershed model?] is needed
- daily data is needed for the entire normal simulation
period
- with the latest MuSo groundwater can be prescribed
during spinup [1 year of data is needed]
- prior to MuSo v2.2.1 groundwater effect was step-wise;
now rising water table causes smooth transition as a
function of depth and affected soil layer
Biome-BGC MuSo
v2.2.1 developments
Biome-BGC MuSo
v2.2.1 developments
2
GPP (gC/m /day)
22
20
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8
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4
2
0
Credit: Maša Ostrogović, Hrvoje Marjanović
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Jastrebarsko pendunculate oak forest
effect of groundwater on simulated GPP vs.
measurement
simulated GPP without groundwater
simulated GPP with groundwater
measured GPP
Issues with storage/transfer pools
6
New parameter: Ratio of
belowground/
aboveground
management related
mortality (RRM)
top 5%
max LH
5
uncalibrated
site number
4
3
2
1
0
0
0.2
0.4
0.6
0.8
1
Current GROWTH PROPORTION [ratio]
In Biome-BGC MuSo v2.2.1 specific management types (e.g. grazing, mowing
and havest) affects (decrease) the storage/transfer pools and also fine roots.
RRM defines the ratio of the belowground and aboveground pool decline due to
grazing, mowing and harvest. RRM is set to 0.1 in the current model version. This
means that e.g. in case of removing 50% of aboveground plant material (actual
pools of leaf) due to cutting causes 5% decrease in both the leaf and root
storage/transfer pools, and also the root pool itself.
Other developments
• correction of bug related to the calculation of daylight
average temperature
• standing dead biomass [drought related leaf senescence –
intact, turnover might be slow]
• annually varying ecophysiological parameters:
e.g. implementation of annually varying whole plant
mortality (dynamic mortality) – forests
• C4 photosynthesis is improved [Di Vittorio et al. 2010]
Unresolved issues
• soil carbon content is too high after spin-up [recalcitrant
SOM is overestimated]
• if soil carbon is reduced by e.g. increased mortality
during spin-up then fluxes are underestimated
• this is caused by N limitation caused by reduced SOM
• LAI is overestimated
• multilayer soil module might need improvement
• soil organic matter profile is not simulated
Current version of Biome-BGC MuSo
It is version 2.2.1
- installed on the Demo Grid
- MuSo 2.2 is available at the Desktop Grid
[will be replaced with 2.2.1]
Is MuSo better than the original model?
- better performance on eddy-covariance sites
- management seems to be a more important driver of
the carbon balance than climate!
- we have additional parameters + more complicated ini,
so practical application of the model became more
complex
- but thanks to BioVeL now we have great infrastructure,
which will be maintained after BioVeL ended
Carpathian grasslands
- soil control on NPP is dominant – precipitation and
temperature has less effect on NPP!
Legacy effect of climate variability
Documentation
Documentation
Documentation
Biome-BGC MuSo v2.2.1
Biome-BGC MuSo
Models can never be finished, but way may
decide to stop the development at some point

Thank you
for your
attention