Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1016/j.ecolmodel.2014.07.013 |
Assimilating remote sensing information into a coupled hydrology-crop growth model to estimate regional maize yield in arid regions | |
Li, Yan1![]() | |
通讯作者 | Zhou, Jian |
来源期刊 | ECOLOGICAL MODELLING
![]() |
ISSN | 0304-3800 |
EISSN | 1872-7026 |
出版年 | 2014 |
卷号 | 291页码:15-27 |
英文摘要 | Regional crop yield prediction is a significant component of national food policy making and security assessments. A data assimilation method that combines crop growth models with remotely sensed data has been proven to be the most effective method for regional yield estimates. This paper describes an assimilation method that integrates a time series of leaf area index (LAI) retrieved from ETM+ data and a coupled hydrology-crop growth model which links a crop growth model World Food Study (WOFOST) and a hydrology model HYDRUS-1D for regional maize yield estimates using the ensemble Kalman filter (EnKF). The coupled hydrology-crop growth model was calibrated and validated using field data to ensure that the model accurately simulated associated state variables and maize growing processes. To identify the parameters that most affected model output, an extended Fourier amplitude sensitivity test (EFAST) was applied to the model before calibration. The calibration results indicated that the coupled hydrology-crop growth model accurately simulated maize growth processes for the local cultivation variety tested. The coefficient of variations (CVs) for LAI, total above-ground production (TAGP), dry weight of storage organs (WSO), and evapotranspiration (ET) were 13%, 6.9%, 11% and 20%, respectively. The calibrated growth model was then combined with the regional ETM+ LAI data using a sequential data assimilation algorithm (EnKF) to incorporate spatial heterogeneity in maize growth into the coupled hydrology-crop growth model. The theoretical LAI profile for the near future and the final yield were obtained through the EnKF algorithm for 50 sample plots. The CV of the regional yield estimates for these sample plots was 8.7%. Finally, the maize yield distribution for the Zhangye Oasis was obtained as a case study. In general, this research and associated model could be used to evaluate the impacts of irrigation, fertilizer and field management on crop yield at a regional scale. Crown Copyright (C) 2014 Published by Elsevier B.V. All rights reserved. |
英文关键词 | EnKF Coupled hydrology-crop growth model Remote sensing information EFAST |
类型 | Article |
语种 | 英语 |
国家 | Peoples R China |
收录类别 | SCI-E |
WOS记录号 | WOS:000343386500003 |
WOS关键词 | LEAF-AREA INDEX ; WINTER-WHEAT YIELD ; GROWING-SEASON ; SOIL-MOISTURE ; LAND-SURFACE ; WATER-USE ; VEGETATION ; SIMULATION ; WOFOST ; COVER |
WOS类目 | Ecology |
WOS研究方向 | Environmental Sciences & Ecology |
来源机构 | 兰州大学 ; 中国科学院西北生态环境资源研究院 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/181696 |
作者单位 | 1.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China; 2.Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China; 3.Lanzhou Inst Arid Meteorol, China Meteorol Adm, Key Lab Arid Climat Change & Reducing Disaster Ga, Key Open Lab Arid Climate Change & Disaster Reduc, Lanzhou 730000, Peoples R China |
推荐引用方式 GB/T 7714 | Li, Yan,Zhou, Qingguo,Zhou, Jian,et al. Assimilating remote sensing information into a coupled hydrology-crop growth model to estimate regional maize yield in arid regions[J]. 兰州大学, 中国科学院西北生态环境资源研究院,2014,291:15-27. |
APA | Li, Yan,Zhou, Qingguo,Zhou, Jian,Zhang, Gaofeng,Chen, Chong,&Wang, Jing.(2014).Assimilating remote sensing information into a coupled hydrology-crop growth model to estimate regional maize yield in arid regions.ECOLOGICAL MODELLING,291,15-27. |
MLA | Li, Yan,et al."Assimilating remote sensing information into a coupled hydrology-crop growth model to estimate regional maize yield in arid regions".ECOLOGICAL MODELLING 291(2014):15-27. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
Assimilating remote (5609KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。