气候变化领域集成服务门户(CCPortal): Dashboard for Agricultural Water Use and Nutrient Management-A Predictive Decision Support System to Improve Crop Production in a Changing Climate

CCPortal

DOI	10.1175/BAMS-D-22-0221.1
	Dashboard for Agricultural Water Use and Nutrient Management-A Predictive Decision Support System to Improve Crop Production in a Changing Climate
	Liang, Xin-Zhong; Gower, Drew; Kennedy, Jennifer A.; Kenney, Melissa; Maddox, Michael C.; Gerst, Michael; Balboa, Guillermo; Becker, Talon; Cai, Ximing; Elmore, Roger; Gao, Wei; He, Yufeng; Liang, Kang; Lotton, Shane; Malayil, Leena; Matthews, Megan L.; Meadow, Alison M.; Neale, Christopher M. U.; Newman, Greg; Sapkota, Amy Rebecca; Shin, Sanghoon; Straube, Jonathan; Sun, Chao; Wu, You; Yang, Yun; Zhang, Xuesong
发表日期	2024
ISSN	0003-0007
EISSN	1520-0477
起始页码	105
结束页码	2
卷号	105 期号:2
英文摘要	Climate change presents huge challenges to the already -complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN's goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN's framework for integrating climate-agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.
英文关键词	Climate prediction; Agriculture; Climate services; Communications/ decision making; Decision support; Water resources
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:001181654800001
来源期刊	BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/294204
作者单位	University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park; University of Minnesota System; University of Minnesota Twin Cities; University of Nebraska System; University of Nebraska Lincoln; University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; Colorado State University; United States Department of Agriculture (USDA); Colorado State University; University System of Maryland; University of Maryland College Park; University of Arizona; University of Nebraska System; University of Nebraska Lincoln; Mississippi State University; United States Department of Agriculture (USDA)
推荐引用方式 GB/T 7714	Liang, Xin-Zhong,Gower, Drew,Kennedy, Jennifer A.,et al. Dashboard for Agricultural Water Use and Nutrient Management-A Predictive Decision Support System to Improve Crop Production in a Changing Climate[J],2024,105(2).
APA	Liang, Xin-Zhong.,Gower, Drew.,Kennedy, Jennifer A..,Kenney, Melissa.,Maddox, Michael C..,...&Zhang, Xuesong.(2024).Dashboard for Agricultural Water Use and Nutrient Management-A Predictive Decision Support System to Improve Crop Production in a Changing Climate.BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY,105(2).
MLA	Liang, Xin-Zhong,et al."Dashboard for Agricultural Water Use and Nutrient Management-A Predictive Decision Support System to Improve Crop Production in a Changing Climate".BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 105.2(2024).