کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8846057 | 1617370 | 2018 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Evaluation of CLM-Crop for maize growth simulation over Northeast China
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
بوم شناسی، تکامل، رفتار و سامانه شناسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
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 (râ¯=â¯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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Modelling - Volume 377, 10 June 2018, Pages 26-34
Journal: Ecological Modelling - Volume 377, 10 June 2018, Pages 26-34
نویسندگان
Meiling Sheng, Junzhi Liu, A-Xing Zhu, David G. Rossiter, Liming Zhu, Guoqiang Peng,