I-Corps: Real-Time Big Data Based Decision Support System for Water Use
I-Corps: Real-Time Big Data Based Decision Support System for Water Use
批准号:
1738057
负责人:
Sen Chiao
金额:
$5.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-04-01 至 2018-09-30
中文摘要
I-Corps项目的更广泛影响/商业潜力是在降雨和水文极端事件(包括强烈洪水和干旱事件)期间为水资源管理提供准确和及时的降水预报。I-Corps团队开发了一种独特的高分辨率天气预报模型,该模型使用高性能计算机框架,利用所有可用的当地天气观测和最先进的当地多普勒雷达数据来改进当地短期降水预报。结合降水预报,我们的系统将支持与水资源相关的决策。将提供一项基于网络的服务,以提供这些精确的降雨预报和其他相关的水文数据产品。企业和政府机构(即水区、农场、保险公司、能源公司)的运营经理依靠非常准确和精确的降雨预报来做出基于经济的决策,他们将能够在用户定义的位置快速访问定制的降雨预报和水文产品。在短期水文极端情况下,这些精确的降雨预报和产品将提高公司和机构本身的效率和决策能力,并有助于他们更好地向最终用户和公众传达他们的决策。这个I-Corps项目将采用高分辨率天气预报模型。它可以有1公里或更小的水平分辨率,并使用特定的3d变分数据同化方法,其中包括来自多个来源的所有可用的实时天气观测。这些输入来源包括卫星数据(如GOES-R)、气象站和雨量计数据、来自当地多普勒雷达的定量降水估计以及其他全球和区域预报模式(如NOAA?s高分辨率快速刷新和北美模式)。该模型可以针对最终用户感兴趣的任何特定区域和位置单独执行,可以提取精确的降雨预报,并且可以根据情况每3或6小时更新一次。该项目提供的其他水文产品也可以协助决策支持,如干旱情况(如土壤湿度和干旱严重程度指数)和当地水库的水位。预计这一高分辨率建模和大数据系统的产品将为政府机构和私营部门的水管理和消费决策提供指导。
英文摘要
The broader impact/commercial potential of this I-Corps project is to provide accurate and timely precipitation forecasts for water resource management during rainfall and hydrological extremes including intense flooding and droughts events. This I-Corps team has developed a unique high resolution weather forecasting model using a high-performance computer framework that employed all available local weather observations and state-of-the-art local doppler radar data to improve local precipitation forecasts on a short-term basis. In conjunction with precipitation forecasts, our system will support water resources related decision-making. A web-based service to provide these pinpoint rainfall forecasts and other related hydrological data products will be available. Operations managers of businesses and government agencies (i.e., water districts, agricultural farms, insurance companies, energy companies) who rely on very accurate and precise rainfall forecasts to make economic-based decisions will be able to have quick access to customized rainfall forecasts and hydrological products at their user-defined locations. During short-term hydrological extremes, these pinpoint accurate rainfall forecasts and products will improve the efficiency and decision-making abilities within the companies and agencies themselves, and it will help them to better communicate their decisions to their end-users and the public.This I-Corps project will employ a high-resolution weather forecasting model. It can have a horizontal resolution of 1 km or finer and uses specific 3D-Variational data assimilation methods which incorporate all available real-time weather observations from multiple sources. These input sources include satellite data (e.g., GOES-R), weather station and rain gauge data, quantitative precipitation estimates from local doppler radars, and other global and regional forecasting models (e.g., NOAA?s High Resolution Rapid Refresh and North American Model). The model can be executed separately for any specific region and location of interest to the end-user, can extract pinpoint rainfall forecasts, and can be updated every 3 or 6 hours depending on the circumstance. Other hydrological products available from the project that can also assist in decision support such as drought conditions (e.g., soil moisture and drought severity indices) and water levels of local reservoirs. It is anticipated that the products from this high-resolution modeling and big-data system will provide guidance to support water management and consumption decisions for government agencies and the private sectors.
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