US Egypt Cooperative Research: Improving Rainfall Estimation over the Nile Basin Using Merged Multi-Channel Infrared and Microwave Satellite Observations

美埃合作研究：利用合并的多通道红外和微波卫星观测改进尼罗河流域降雨量估算

• 批准号: 0914618
• 负责人: Emad Habib
• 金额: $ 5.85万
• 依托单位: University of Louisiana at Lafayette
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0914618&HistoricalAwards=false
• 关键词: US; Egypt; Cooperative; Research; Improving

This collaborative research project is being undertaken by Dr. Emad Habib, University of Louisiana at Lafayette, and Dr. Mohamed Abdel-Motaleb, Egyptian Ministry of Water Resources and Irrigation. Egypt is expected to face increasing water needs due to rapidly growing population, economic growth and urbanization. To prepare for such challenges, the Nile Forecasting Center (NFC) in the Egyptian Ministry of Water Resources and Irrigation operates a suite of hydrologic simulation models and analysis tools that support current and future strategies for sustainable water resources management and planning. NFC relies on satellite infrared (IR) imagery to estimate rainfall information over the Nile Basin, which is the main input to NFC hydrologic models. Due to the inherent limitations of IR-based rainfall estimates, the proposed project aims to improve on the current NFC rainfall estimation algorithms. Two types of enhancements are proposed for improving the current NFC algorithm: (1) adding more infrared channels that have become recently available to NFC from the Spinning Enhanced Visible Infrared Imager (SEVIRI) onboard a Meteosat Second Generation (MSG) satellite, and (2) integrating other valuable satellite data from passive microwave sensors which are not currently used by the NFC algorithm (the Special Sensor Microwave/Imager (SSM/I) and the Advanced Microwave Sounding Unit (AMSU)). These enhancements will be implemented within a self-calibrating satellite-rainfall estimation algorithm to be configured and tested over the Nile basin. The project activities will be conducted as collaboration between researchers at NFC and the University of Louisiana (UL) at Lafayette. Satellite data and algorithm support will be contributed by the NOAA's National Environmental Satellite Data and Information Service (NESDIS). The new rainfall estimates developed in the project will be statistically validated using surface gauge measurements and will be evaluated in comparison to infrared-only estimates that are currently produced at NFC.The research will inform the scientific community regarding the accuracy of satellite rainfall products in understudied regions, and it will also provide feedback on the added benefit of incorporating additional satellite sensors which are only available in Europe and Africa. The outcome of the project has significant implications for water resource management in Egypt and has the potential to validate algorithms for use in the US. Additionally, the project will present opportunities for US undergraduates and graduate students to obtain international research experience in Egypt.The project is funded under the US-Egypt Joint Fund Program, which provides grants to scientists and engineers in both countries to undertake cooperative research.

这项合作研究项目由路易斯安那大学拉斐特分校的Emad Habib博士和埃及水资源和灌溉部的Mohamed Abdel-Motaleb博士共同承担。由于人口快速增长、经济增长和城市化，埃及预计将面临日益增长的水需求。为了应对这些挑战，埃及水资源和灌溉部的尼罗河预报中心（NFC）运行了一套水文模拟模型和分析工具，以支持当前和未来的可持续水资源管理和规划战略。NFC依靠卫星红外图像来估计尼罗河流域的降雨信息，这是NFC水文模型的主要输入。由于基于ir的降雨估计的固有局限性，本项目旨在改进当前的NFC降雨估计算法。针对当前NFC算法的改进，提出了两种改进方法：(1)增加最近可用的NFC红外通道，这些通道来自气象卫星第二代（MSG）卫星上的旋转增强可见红外成像仪（SEVIRI）；(2)集成目前NFC算法未使用的其他有价值的无源微波传感器卫星数据（特殊传感器微波/成像仪（SSM/I）和先进微波探测单元（AMSU））。这些增强功能将在一个自校准卫星降雨估计算法中实现，该算法将在尼罗河流域进行配置和测试。该项目活动将由NFC和路易斯安那大学（UL）拉斐特分校的研究人员合作进行。卫星数据和算法支持将由NOAA的国家环境卫星数据和信息服务（NESDIS）提供。在项目中开发的新的降雨量估计将使用地面测量数据进行统计验证，并将与目前在NFC产生的仅红外估计进行比较。这项研究将使科学界了解未充分研究区域的卫星降雨产品的准确性，它还将提供反馈意见，说明采用仅在欧洲和非洲可用的额外卫星传感器的额外好处。该项目的结果对埃及的水资源管理具有重要意义，并有可能验证在美国使用的算法。此外，该项目将为美国本科生和研究生提供在埃及获得国际研究经验的机会。该项目由美国-埃及联合基金项目资助，该项目向两国的科学家和工程师提供赠款，以开展合作研究。