Journal
ECOLOGICAL MODELLING
Volume 377, Issue -, Pages 26-34Publisher
ELSEVIER
DOI: 10.1016/j.ecolmodel.2018.03.005
Keywords
Community land model; Maize; Phenology; Crop yield; Northeast China
Categories
Funding
- National Basic Research Program of China [2015CB954102]
- Natural Science Foundation of Jiangsu Province of China [BK20150975]
- National Natural Science Foundation of China [41601413, 41431177]
- Natural Science Research Program of Jiangsu [14KJA170001]
- PAPD [164320H116]
- Vilas Associate Award
- Hammel Faculty Fellow Award
- Manasse Chair Professorship from University of Wisconsin-Madison
- One- Thousand Talents Program of China
- NJNU Visiting Prof. Programme
- Program of Innovative Research Team of Jiangsu Higher Education Institutions of China
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Climate change has significant impacts on crop yields and could greatly affect global food security. As an advanced process-based land surface model, the Community Land Model (CLM) includes a comprehensive crop model (CLM-Crop), which aims to simulate crop growth globally. Although this model has been evaluated in the United States, it is not clear whether it can be applied successfully in other parts of the world. In this study we evaluate the applicability of CLM-Crop for maize growth simulation in Northeast China, one of the major agricultural production areas in China. Simulated LAI, plant carbon, phenology and yields of maize were compared with observations at agricultural experiment and meteorological stations and with statistical reports. The CLM-Crop model overestimated LAI and underestimated leaf and stem carbon during the growing period. Planting and harvesting dates were overestimated in the eastern part of the study area, but underestimated in the southern part. Correlation (r = 0.26) between simulated and reported yield was poor. Yields were generally overestimated especially in the east and south parts, which may be due to imperfect farming practices on working farms. Some parameters, including temperature thresholds of planting and crop management parameters, have spatial heterogeneity rather than the default fixed parameters in CLM-Crop. Development of gridded crop parameters is expected to improve simulation of crop phenology and yield estimation at the regional and global scales.
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