CAREER: Predicting Climate Impacts on Irrigated Agriculture

职业：预测气候对灌溉农业的影响

• 批准号: 1848018
• 负责人: Jonathan Winter
• 金额: $ 49.89万
• 依托单位: Dartmouth College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1848018&HistoricalAwards=false
• 关键词: CAREER; Predicting; Climate; Impacts; Irrigated

This project will assess the effects of climate and water supply on future irrigated agricultural production. Increasing agricultural production through irrigation is an essential part of the complex solution to global hunger. Irrigation can make marginal land suitable for agriculture and existing croplands more productive. However, irrigation is limited by its massive use of water. Determining the potential of irrigation to reduce global hunger requires a thorough understanding of multiple factors such as climate, agricultural water supply, and crop production. This project will improve predictions of climate impacts on irrigated croplands by advancing the understanding of key constraints on irrigated agricultural productivity. As a result, it will develop strategies for enhancing future irrigation management. Knowledge, data, and models will be widely disseminated both directly and through collaborations with the Agricultural Model Intercomparison and Improvement Project and Kansas Geological Survey. This project will also increase knowledge of physical geography, climate science, numerical modeling, and data analysis for students at critical STEM stages. Additionally, the investigator will create a teaching model that enables high-school students to explore the impacts of climate and water resources on crop production, develop an educator professional development course for the teaching model, and provide research experiences for diverse graduate and undergraduate students intending to major in a STEM field.Irrigated agricultural projections that directly simulate the impacts of water supply on yield are few, and typically have simplistic representations of crop growth and irrigation. This project will address this key deficiency through four main efforts: (1) Construct a modeling framework that connects climate and hydrologic data with a crop model capable of simulating limited automatic irrigation; (2) Evaluate and improve the modeling framework using reported yields and satellite-derived evapotranspiration, soil moisture, and vegetation index data; (3) Force the modeling framework with climate and water supply scenarios; and (4) Explore crop water use and production across irrigation scenarios and modeling assumptions. These efforts will provide answers to three important questions at the interface of climate, water, and agriculture: (1) What are the effects of water supply shortages on irrigated agricultural production?currently and in the future? (2) Which irrigation management practices can reduce water use without harming yields, and ultimately decrease the impacts of water scarcity on irrigated crop production? (3) How can satellite data improve crop model simulations of irrigated agricultural production? This project will focus on irrigated corn, soybean, rice, and wheat in the United States, where irrigation is responsible for approximately 90% of consumptive water use and $120 billion of agricultural production. However, datasets, models, and methods developed by this project will provide opportunities to improve projections of irrigated agriculture globally.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将评估气候和供水对未来灌溉农业生产的影响。 通过灌溉增加农业产量是解决全球饥饿问题的复杂办法的重要组成部分。 灌溉可以使边际土地适合农业和现有农田更有生产力。然而，灌溉因其大量用水而受到限制。 确定灌溉减少全球饥饿的潜力需要对气候、农业供水和作物生产等多个因素有透彻的了解。 该项目将通过促进对灌溉农业生产力的关键制约因素的理解，改善对灌溉农田气候影响的预测。因此，它将制定加强未来灌溉管理的战略。 知识、数据和模型将直接或通过与农业模型相互比较和改进项目和堪萨斯地质调查局的合作广泛传播。 该项目还将增加自然地理，气候科学，数值建模和数据分析的知识，为学生在关键STEM阶段。 此外，研究者还将创建一个教学模式，使高中生能够探索气候和水资源对作物生产的影响，为教学模式开发教育者专业发展课程，并为打算主修STEM领域的不同研究生和本科生提供研究经验。直接模拟供水对产量影响的灌溉农业预测很少，并且通常具有作物生长和灌溉的简单表示。 该项目将通过以下四个主要努力来解决这一关键缺陷：（1）构建一个模型框架，将气候和水文数据与能够模拟有限自动灌溉的作物模型联系起来;（2）利用报告的产量和卫星获得的蒸散量、土壤湿度和植被指数数据评估和改进模型框架;（3）强制模型框架与气候和供水情景相结合;（4）建立一个能够模拟有限自动灌溉的作物模型。以及（4）探索跨灌溉情景和建模假设的作物用水和生产。 这些努力将为气候、水和农业之间的三个重要问题提供答案：（1）水供应短缺对灌溉农业生产的影响是什么？现在和将来？ (2)哪些灌溉管理措施可以在不损害产量的情况下减少用水，并最终减少缺水对灌溉作物生产的影响？ (3)卫星数据如何改进灌溉农业生产的作物模型模拟？ 该项目将重点关注美国的灌溉玉米、大豆、水稻和小麦，灌溉约占美国用水量的90%，农业生产总值达1200亿美元。 然而，该项目开发的数据集、模型和方法将为改善全球灌溉农业的预测提供机会。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Integrated crop growth and radiometric modeling to support Sentinel synthetic aperture radar observations of agricultural fields

• DOI: 10.1117/1.jrs.14.044508
• 发表时间: 2020-10
• 期刊: Journal of Applied Remote Sensing
• 影响因子: 1.7
• 作者: A. Davitt;J. Winter;K. McDonald

Brazilian maize yields negatively affected by climate after land clearing

土地清理后巴西玉米产量受到气候负面影响

• DOI: 10.1038/s41893-020-0560-3
• 发表时间: 2020
• 期刊: Nature Sustainability
• 影响因子: 27.6
• 作者: Spera, Stephanie A.;Winter, Jonathan M.;Partridge, Trevor F.
• 通讯作者: Partridge, Trevor F.

Sustainable Use of Groundwater May Dramatically Reduce Irrigated Production of Maize, Soybean, and Wheat

• DOI: 10.1029/2021ef002018
• 发表时间: 2021-12
• 期刊: Earth's Future
• 作者: José R. López;J. Winter;J. Elliott;A. Ruane;C. Porter;G. Hoogenboom;Martha C. Anderson;C. Hain

Cross-scale evaluation of dynamic crop growth in WRF and Noah-MP-Crop

WRF 和 Noah-MP-Crop 中作物动态生长的跨尺度评估

• DOI: 10.1016/j.agrformet.2020.108217
• 发表时间: 2021
• 期刊: Agricultural and Forest Meteorology
• 影响因子: 6.2
• 作者: Partridge, Trevor F.;Winter, Jonathan M.;Kendall, Anthony D.;Hyndman, David W.
• 通讯作者: Hyndman, David W.

Mid-20th century warming hole boosts US maize yields

• DOI: 10.1088/1748-9326/ab422b
• 发表时间: 2019-11-01
• 期刊: ENVIRONMENTAL RESEARCH LETTERS
• 影响因子: 6.7
• 作者: Partridge, Trevor F.;Winter, Jonathan M.;Hyndman, David W.
• 通讯作者: Hyndman, David W.