A remote sensing-based scheme to improve regional crop model calibration at sub-model component level
文献类型：期刊论文
| 作者 | Zhang, Jing2; Chen, Yi1; Zhang, Zhao2 |
| 刊名 | AGRICULTURAL SYSTEMS
 |
| 出版日期 | 2020-05-01 |
| 卷号 | 181页码:12 |
| 关键词 | Calibration Crop model MCWLA SMC scheme Remote sensing |
| ISSN号 | 0308-521X |
| DOI | 10.1016/j.agsy.2020.102814 |
| 通讯作者 | Zhang, Zhao(zhangzhao@bnu.edu.cn) |
| 英文摘要 | Parameter calibration is an importantly preliminary step before using a crop model to simulate crop growth and final yield. Compared with the traditionally accepted calibration method parameterizing the whole model simultaneously (called as "Global Scheme"), the Sub-Model Component (SMC) Scheme emphasizes on parameterizing different functional modules in a crop model sequentially. However, the SMC Scheme receives less attention, especially at regional scales. Therefore, this study led a performance evaluation of the two calibration schemes through using them to incorporate remote sensing data into a crop model (MCWLA-Rice) independently in Northeast China. We found the SMC Scheme reduced root mean square error (RMSE) on average by 4 days for heading date and 2 days for harvest date. Using the Pearson correlation coefficient (R) to assess the similarity between time series of modelled LAI and remotely-sensed LAI, the SMC Scheme decreased LAI estimation error by 0.04. Finally, the SMC Scheme greatly decreased relative RMSE (RRMSE) for yield by 11%. In addition, temperature and topography could affect the performance of SMC Scheme. Our findings demonstrated that the SMC Scheme calibrated the crop model more effectively and reliably, suggesting its potentially wide application in other regions and crops. |
| WOS关键词 | LEAF-AREA INDEX ; CLIMATE-CHANGE ; SENSITIVITY-ANALYSIS ; SIMULATION-MODEL ; RICE YIELD ; TEMPERATURE STRESS ; LOWLAND RICE ; GROWTH-MODEL ; MAIZE YIELD ; TIME-SERIES |
| 资助项目 | National Key Research and Development Program of China[2017YFD0300301] ; National Key Research and Development Program of China[2016YFD0300201] ; National Natural Science Foundation of China[31761143006] ; National Natural Science Foundation of China[31561143003] ; National Natural Science Foundation of China[41571493] ; National Natural Science Foundation of China[41571088] ; State Key Laboratory of Earth Surface Processes and Resource Ecology |
| WOS研究方向 | Agriculture |
| 语种 | 英语 |
| WOS记录号 | WOS:000525785000009 |
| 出版者 | ELSEVIER SCI LTD |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; State Key Laboratory of Earth Surface Processes and Resource Ecology |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/134078]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Zhao |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, MoE Key Lab Environm Change & Nat Hazards, Beijing 100875, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Jing,Chen, Yi,Zhang, Zhao. A remote sensing-based scheme to improve regional crop model calibration at sub-model component level[J]. AGRICULTURAL SYSTEMS,2020,181:12. |
| APA | Zhang, Jing,Chen, Yi,&Zhang, Zhao.(2020).A remote sensing-based scheme to improve regional crop model calibration at sub-model component level.AGRICULTURAL SYSTEMS,181,12. |
| MLA | Zhang, Jing,et al."A remote sensing-based scheme to improve regional crop model calibration at sub-model component level".AGRICULTURAL SYSTEMS 181(2020):12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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