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| Titel |
Monte Carlo-based calibration and uncertainty analysis of a coupled plant growth and hydrological model |
| VerfasserIn |
T. Houska, S. Multsch, P. Kraft, H.-G. Frede, L. Breuer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 11, no. 7 ; Nr. 11, no. 7 (2014-04-11), S.2069-2082 |
| Datensatznummer |
250117358
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| Publikation (Nr.) |
 copernicus.org/bg-11-2069-2014.pdf |
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| Zusammenfassung |
Computer simulations are widely used to support decision making and planning
in the agriculture sector. On the one hand, many plant growth models use
simplified hydrological processes and structures – for example, by the use of a small
number of soil layers or by the application of simple water flow approaches.
On the other hand, in many hydrological models plant growth processes are
poorly represented. Hence, fully coupled models with a high degree of
process representation would allow for a more detailed analysis of the dynamic
behaviour of the soil–plant interface.
We coupled two of such high-process-oriented independent models and
calibrated both models simultaneously. The catchment modelling framework
(CMF) simulated soil hydrology based on the Richards equation and the van
Genuchten–Mualem model of the soil hydraulic properties. CMF was coupled
with the plant growth modelling framework (PMF), which predicts plant growth
on the basis of radiation use efficiency, degree days, water shortage and
dynamic root biomass allocation.
The Monte Carlo-based generalized likelihood uncertainty estimation (GLUE)
method was applied to parameterize the coupled model and to investigate the
related uncertainty of model predictions. Overall, 19 model parameters (4
for CMF and 15 for PMF) were analysed through 2 × 106 model runs
randomly drawn from a uniform distribution.
The model was applied to three sites with different management in
Müncheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a
cross-validation experiment. Field observations for model evaluation
included soil water content and the dry matter of roots, storages, stems
and leaves. The shape parameter of the retention curve n was highly
constrained, whereas other parameters of the retention curve showed a large
equifinality. We attribute this slightly poorer model performance to missing
leaf senescence, which is currently not implemented in PMF. The most
constrained parameters for the plant growth model were the
radiation-use efficiency and the base temperature. Cross validation helped to identify deficits in the model
structure, pointing out the need for including agricultural management
options in the coupled model. |
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