课题基金 / 基金详情

PFI-TT: Gravity Satellite Observation System for Water Resource Management

PFI-TT: Gravity Satellite Observation System for Water Resource Management
PFI-TT:水资源管理重力卫星观测系统
批准号:
2044704
负责人:
Yu Zhang
金额:
$25.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-01-01 至 2024-11-30

项目摘要

项目成果

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中文摘要
翻译
这一创新-技术转化伙伴关系(PFI-TT)项目的更广泛影响/商业潜力旨在将一种新的卫星观测技术商业化,这将使美国和世界其他气候紧张地区的地下水资源得到更好的管理。该项目的重点是加利福尼亚州,因为该州的农业生产在2017年超过了500亿美元--是美国最大的。这项技术转换将使加州水利部和537个特殊水区的开支减少10%-20%,每年可净节省高达1000万美元,并对其经济发展产生积极影响。该团队将培养一批代表性不足的学生,使他们能够实现自己作为企业家的抱负,并用他们的创新发明丰富人们的生活。这项技术可能会开发一系列输出,以提供用户友好的当地信息,以便及时监测自然灾害,制定可持续计划,并保护美国和世界的脆弱地区和人口。该项目旨在利用市场需求,有效和高效地监测加利福尼亚州以及美国和世界其他气候压力地区日益稀缺的水资源。加州60%的供水来自地下水,地下水是主要的灌溉水源。不断加剧的极端天气加剧了因频繁干旱而过度抽水造成的水资源短缺。该项目的智力优势包括展示了一种新技术,其原型和商业化,使其能够使用NASA/GFZ的重力恢复和气候实验后续(GRACE-FO)重力测量卫星的数据,全天候和及时地量化加州的地下水储量。该团队将改善巨大的空间数据差距限制,并通过使用机器学习算法来提高时间分辨率,该算法使用一系列额外的数据集,以有效地缩小及时的地下水估计。这项技术可以通过缩小数据差距和有效遵守与水使用有关的法律来显著降低水管理和使用的费用。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project aims at the commercialization of a novel satellite observational technology, which would enable better management of groundwater resources in the United States and other climate-stressed regions in the world. The project focuses on the State of California as its agricultural productions exceeded $50 billion in 2017 - the largest in the United States. The technology translation would reduce the expenses of California’s Department of Water Resources and 537 Special Water Districts by 10–20%, which could net a savings of up to $10 million a year and positively impact its economic development. The team will train a underrepresented students, enabling them to realize their aspiration as entrepreneurs and enriching people’s lives with their innovative inventions. The technology is likely to develop a range of outputs to provide user-friendly local information for timely monitoring of natural hazards, formulating sustainable programs, and protecting vulnerable areas and populations in the United States and the world. The project seeks to capitalize on the market need to efficiently and efficiently monitor increasingly scarce water resources in the State of California and other climate-stressed regions in the United States and the world. Sixty percent of California’s water supply is from groundwater, which is the main irrigation source. Intensifying extreme weather exacerbates the scarcity of water due to excessive pumping due to frequent droughts. The intellectual merits of this project include the demonstration of a novel technology, its prototyping, and commercialization, to enable all-weather and timely quantification of groundwater storage in California using data from NASA’s/GFZ’s Gravity Recovery And Climate Experiment Followon (GRACE-FO) gravimetry satellites. The team will ameliorate large spatial data gap limitations and improve temporal resolutions by employing machine learning-enabled algorithms using an ensemble of additional datasets to effectively downscale timely groundwater estimates. The technology may significantly reduce the expense of water management and usage by closing the data gap and enabling efficient compliance with laws pertaining to water usage.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.
期刊论文(4)
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科研奖励(0)
会议论文
DOI: 10.1016/j.scitotenv.2023.169476
发表时间: 2023-12-29
期刊: SCIENCE OF THE TOTAL ENVIRONMENT
影响因子: 9.8
作者: [Forootan,Ehsan, Mehrnegar,Nooshin, Shum,C. K.]
通讯作者: Shum,C. K.
Bridging the gap between GRACE and GRACE-FO missions with deep learning aided water storage simulations
通过深度学习辅助储水模拟缩小 GRACE 和 GRACE-FO 任务之间的差距
DOI: 10.1016/j.scitotenv.2022.154701
发表时间: 2022
期刊: Science of The Total Environment
影响因子: 9.8
作者: [Uz, Metehan, Atman, Kazım Gökhan, Akyilmaz, Orhan, Shum, C.K., Keleş, Merve, Ay, Tuğçe, Tandoğdu, Bihter, Zhang, Yu, Mercan, Hüseyin]
通讯作者: Mercan, Hüseyin
CAREER: When Reality Fails Expectations: Containing Reflective Domain Models for Human-Aware Planning and Learning of Robotic Teammates
  • 批准号:
    2047186
  • 项目类别:
    Standard Grant
  • 资助金额:
    $56.94万
  • 财政年份:
    2021
  • 负责人:
    Yu Zhang
  • 依托单位:
Collaborative Research: RAPID--Forensic Analysis of Flood-Wind-Rainfall Interactions during Hurricanes Florence and Michael
  • 批准号:
    1909367
  • 项目类别:
    Standard Grant
  • 资助金额:
    $3.06万
  • 财政年份:
    2019
  • 负责人:
    Yu Zhang
  • 依托单位:
EAGER: Reconciling Model Discrepancies in Human-Robot Teams
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    1844524
  • 项目类别:
    Standard Grant
  • 资助金额:
    $24.99万
  • 财政年份:
    2018
  • 负责人:
    Yu Zhang
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Evolutionary Virtual Expert System
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    EP/R029741/1
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    Research Grant
  • 资助金额:
    $12.28万
  • 财政年份:
    2018
  • 负责人:
    Yu Zhang
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    省市级项目
  • 资助金额:
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  • 批准年份:
    2024
  • 负责人:
    郭亮星
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苯并呋喃-6-酮类化合物TT01f通过调控Jagged1/Notch信号通路改善特发性肺纤维化的药理学机制研究
TT3.2通过自噬体-液泡途径调控水稻盐胁迫抗性的分子机制研究
  • 批准号:
    32301745
  • 项目类别:
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  • 资助金额:
    30万元
  • 批准年份:
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  • 负责人:
    张海
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基于Glypian3-TT3oB新型聚集诱导发光复合体的NIR-IIb靶向成像及cGAS-STING通路激活在肝癌精准标记并增敏免疫治疗中的研究
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    LQ23H160042
  • 项目类别:
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  • 资助金额:
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  • 批准年份:
    2023
  • 负责人:
    吴迪
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