globalchange  > 过去全球变化的重建
DOI: 10.1016/j.envsoft.2019.02.006
WOS记录号: WOS:000460643900012
论文题名:
A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies
作者: Shelia, Vakhtang1,2; Hansen, James3; Sharda, Vaishali4; Porter, Cheryl1; Aggarwal, Pramod5; Wilkerson, Carol J.; Hoogenboom, Gerrit1,2
通讯作者: Shelia, Vakhtang
刊名: ENVIRONMENTAL MODELLING & SOFTWARE
ISSN: 1364-8152
EISSN: 1873-6726
出版年: 2019
卷: 115, 页码:144-154
语种: 英语
英文关键词: Ensemble simulations ; Decision support ; Crop model ; Yield forecast ; Food security
WOS关键词: WATER PRODUCTIVITY ; SIMULATION-MODELS ; YIELD PREDICTION ; WHEAT YIELDS ; DROUGHT ; MAIZE ; TOOL
WOS学科分类: Computer Science, Interdisciplinary Applications ; Engineering, Environmental ; Environmental Sciences
WOS研究方向: Computer Science ; Engineering ; Environmental Sciences & Ecology
英文摘要:

Regional crop production forecasting is growing in importance in both, the public and private sectors to ensure food security, optimize agricultural management practices and use of resources, and anticipate market fluctuations. Thus, a model and data driven, easy-to-use forecasting and a risk assessment system can be an essential tool for end-users at different levels. This paper provides an overview of the approaches, algorithms, design, and capabilities of the CCAFS Regional Agricultural Forecasting Toolbox (CRAFT) for gridded crop modeling and yield forecasting along with risk analysis and climate impact studies. CRAFT is a flexible and adaptable software platform designed with a user-friendly interface to produce multiple simulation scenarios, maps, and interactive visualizations using a crop engine that can run the pre-installed crop models DSSAT, APSIM, and SARRA-H, in concert with the Climate Predictability Tool (CPT) for seasonal climate forecasts. Its integrated and modular design allows for easy adaptation of the system to different regional and scientific domains. CRAFT requires gridded input data to run the crop simulations on spatial scales of 5 and 30 arc-minutes. Case studies for South Asia for two crops, including wheat and rice, shows its potential application for risk assessment and in-season yield forecasting.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/137880
Appears in Collections:过去全球变化的重建

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作者单位: 1.Univ Florida, Dept Agr & Biol Engn, Gainesville, FL USA
2.Univ Florida, Inst Sustainable Food Syst, Gainesville, FL USA
3.Columbia Univ, Int Res Inst Climate & Soc IRI, CGIAR Res Program Climate Change Agr & Food Secur, New York, NY 10027 USA
4.Univ Nebraska, Nebraska Water Ctr, Robert B Daugherty Water Food Global Inst, Lincoln, NE USA
5.Int Maize & Wheat Improvement Ctr CIMMYT), Borlaug Inst South Asia BISA, CGIAR Res Program Climate Change Agr & Food Secur, New Delhi, India

Recommended Citation:
Shelia, Vakhtang,Hansen, James,Sharda, Vaishali,et al. A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies[J]. ENVIRONMENTAL MODELLING & SOFTWARE,2019-01-01,115:144-154
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