Uncertainty from model structure is larger than that from model parameters in simulating rice phenology in China
文献类型：期刊论文
| 作者 | Zhang, Shuai1; Tao, Fulu1,3,4; Zhang, Zhao2 |
| 刊名 | EUROPEAN JOURNAL OF AGRONOMY
 |
| 出版日期 | 2017-07-01 |
| 卷号 | 87页码:30-39 |
| 关键词 | Crop model Extreme weather Impacts Rice development rate Uncertainty |
| ISSN号 | 1161-0301 |
| DOI | 10.1016/j.eja.2017.04.004 |
| 通讯作者 | Tao, Fulu(taofl@igsnrr.ac.cn) |
| 英文摘要 | Rice models have been widely used in simulating and predicting rice phenology in contrasting climate zones, however the uncertainties from model structure (different equations or models) and/or model parameters were rarely investigated. Here, five rice phenological models/modules (Le., CERES-Rice, ORYZA2000, RCM, Beta Model and SIMRIW) were applied to simulate rice phenology at 23 experimental stations from 1992 to 2009 in two major rice cultivation regions of China: the northeastern China and the southwestern China. To investigate the uncertainties from model biophysical parameters, each model was run with randomly perturbed 50 sets of parameters. The results showed that the median of ensemble simulations were better than the simulation by most models. Models couldn't simulate well in some specific years despite of parameters optimization, suggesting model structure limit model performance in some cases. The models adopting accumulative thermal time function (e.g., CERES-Rice and ORYZA2000) had better performance in the southwestern China, in contrast, those adopting exponential function (e.g., Beta model and RCM model) had better performance in the northeastern China. In northeastern China, the contribution of model structure and model parameters to model total variance was, respectively, about 55.90% and 44.10% in simulating heading date, and about 75.43% and 24.57% in simulating maturity date. In the southwestern China, the contribution of model structure and model parameters to model total variance was, respectively, about 79.97% and 27.03% in simulating heading date, about 92.15% and 7.85% in simulating maturity date. Uncertainty from model structure was the most relevant source. The results highlight that the temperature response functions of rice development rate under extreme climate conditions should be improved based on environment-controlled experimental data. |
| WOS关键词 | CLIMATE-CHANGE ; GROWTH DURATION ; CROP MODEL ; CERES-RICE ; WHEAT ; TEMPERATURE ; IMPACT ; YIELD ; OPTIMIZATION ; PERFORMANCE |
| 资助项目 | National Key Research and Development Program of China[2016YFD0300201] ; National Science Foundation of China[31561143003] ; National Science Foundation of China[41571088] ; FACCE MACSUR project through Finnish Ministry of Agriculture and Forestry |
| WOS研究方向 | Agriculture |
| 语种 | 英语 |
| WOS记录号 | WOS:000405043200004 |
| 出版者 | ELSEVIER SCIENCE BV |
| 资助机构 | National Key Research and Development Program of China ; National Science Foundation of China ; FACCE MACSUR project through Finnish Ministry of Agriculture and Forestry |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/62949]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tao, Fulu |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 2.Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 4.Nat Resources Inst Finland Luke, PI-00790 Helsinki, Finland |
| 推荐引用方式 GB/T 7714 | Zhang, Shuai,Tao, Fulu,Zhang, Zhao. Uncertainty from model structure is larger than that from model parameters in simulating rice phenology in China[J]. EUROPEAN JOURNAL OF AGRONOMY,2017,87:30-39. |
| APA | Zhang, Shuai,Tao, Fulu,&Zhang, Zhao.(2017).Uncertainty from model structure is larger than that from model parameters in simulating rice phenology in China.EUROPEAN JOURNAL OF AGRONOMY,87,30-39. |
| MLA | Zhang, Shuai,et al."Uncertainty from model structure is larger than that from model parameters in simulating rice phenology in China".EUROPEAN JOURNAL OF AGRONOMY 87(2017):30-39. |
入库方式： OAI收割
来源：地理科学与资源研究所
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