Understanding the DayCent model: Calibration, sensitivity, and identifiability through inverse modeling

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation so...

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Bibliographic Details
Published in:Environmental modelling & software : with environment data news 2015-04, Vol.66, p.110-130
Main Authors: Necpálová, Magdalena, Anex, Robert P., Fienen, Michael N., Del Grosso, Stephen J., Castellano, Michael J., Sawyer, John E., Iqbal, Javed, Pantoja, José L., Barker, Daniel W.
Format: Article
Language:English
Subjects:
agroecosystems
ammonium compounds
Calibration
Carbon
Computer programs
computer software
DayCent model
Ecosystems
environmental models
Inverse
Inverse modeling
Mathematical models
nitrates
nitrous oxide
Parameter correlations
Parameter estimation
Parameter identifiability
PEST
prediction
Sensitivity analysis
Software
Soil (material)
soil temperature
soil water
soil water content
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