A Simple Crop Phenology Algorithm in the Land Surface Model CN‐CLASS. (1st January 2014)

• Record Type: Journal Article
• Authors: Chang, Kuo‐Hsien; Warland, Jon S.; Bartlett, Paul A.; Arain, Altaf M.; Yuan, Fengming
• Is Part Of: Agronomy Journal. Volume 106:Number 1(2014)
• Page Start: 297
• Page End: 308
• Publication Date: 2014-01-01
• Subjects: Agronomy -- Periodicals; 630
• DOI: 10.2134/agronj2013.0164
• Languages: English
• ISSNs: 0002-1962

Abstract

Abstract : Land surface models are useful tools for estimating the contribution and response to climate change of C dynamics in various terrestrial ecosystems. In many land surface models, plant phenological algorithms are incorporated based on field studies in forests. However, to simulate adequately the C cycle over a large area, there is a need to include and validate algorithms for other ecosystems. The Carbon and Nitrogen‐coupled Canadian Land Surface Scheme (CN‐CLASS) is a land surface model that has been applied successfully to the study of C stocks in forest ecosystems. The objective of this study is to incorporate a simple crop phenology algorithm into CN‐CLASS and validate its ability to simulate C cycles at an agricultural site in southern Ontario, Canada. The model was validated on a corn crop ( Zea mays L.) in 2005 and 2008 based on measurements of aboveground biomass and net ecosystem productivity (NEP), as well as a well‐tested agricultural model, DayCENT (the daily time‐step version of the CENTURY model). The modified CN‐CLASS showed similar dynamics of biomass allocation compared with field measurements and DayCENT simulations. Regression analysis indicated that the modifications improved the NEP simulation for a cornfield, with the coefficient of determination ( R 2 ) relating simulated and observed NEP increasing from 0.51 in the original CN‐CLASS to 0.78 in the modified model. Other crop species could be further validated to expand the model application to crop rotation studies and large areas covered by forests and crop fields in consideration of land management practices.