Collaborative Research: Facility Support: Transformation of Distributed Environmental Sensing
Collaborative Research: Facility Support: Transformation of Distributed Environmental Sensing
批准号:
0929638
负责人:
Scott Tyler
金额:
$44.69万
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
项目状态:
已结题
起止时间:
2009-09-15 至 2012-08-31
中文摘要
0929638TylerThis award is funded under the American Recovery and Reinvestment Act of 2009(Public Law 111-5). 获得的资金将支持建立一个原型?水文测量设施?将被命名为环境多尺度传感中心(CMSE),允许第一次广泛的社区访问光纤拉曼温度测量能够接近连续(1米)和精确(+/- 0.1 ℃)河底、湖底或河口底部的观测,雪包或土壤层温度的距离高达10公里,广泛的目标是允许前所未有的高分辨率的空间和时间观测水库的性质,改进了水库之间的通道和通量的量化。 当放置在溪流或河流中时,光纤传感器可以观察每个地下水流入的位置,温度和流量,计算精确的热预算以确定潜流交换,并观察对成功招募仔鱼至关重要的微热栖息地。 CMSE将在俄勒冈州州立大学和内华达州大学之间的合作伙伴关系中管理和运营?里诺(UNR)。 需要对环境参数进行密集观测,并迅速传播数据,以支持先进的水文系统模型的开发和验证。 需要改进模型,以支持健全的水资源、林业和渔业管理,并更好地了解水库分布和气候之间的无数反馈。 资金将支持UNR的博士后科学家和ORST的半职技术职位。
英文摘要
0929638TylerThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Granted funds will support establishment of a prototype ?Hydrologic Measurement Facility? to be named the Center for Multiscale Sensing of the Environment (CMSE), allowing for the first time broad community access to fiber optic Raman temperature measurement capable of near continuous (1 m) and precise (+/- 0.1 deg C) observations of river bottom, lake, or estuary bottom, snow pack or soil horizon temperatures over distances as great at 10 km with the broad goal of allowing for unprecedented high resolution spatial and temporal observations of water reservoir properties and improved quantification of the pathways and fluxes between reservoirs. When placed in a stream or river, fiber optic DTS allows for observation of the location, temperature, and flux of each groundwater inflow, calculation of an exact heat budget to determine hyporheic exchange, and observation of micro-thermal habitats critical to successful larval fish recruitment. CMSE will be managed and operated in a collaborative partnership between Oregon State University (ORST) and the University of Nevada ? Reno (UNR). Dense observations of environmental parameters with rapid data dissemination are needed to support advanced hydrologic system model development and validation. Refined models are needed to support sound water resource, forestry and fisheries management and a better understanding of the myriad feedbacks between water reservoir distribution and climate. Funds will support a postdoctoral scientist at UNR and a half time technical position at ORST.
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依托单位:
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批准号:1043154
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依托单位:
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依托单位:
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依托单位:
国内基金
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