RAPID: Monitoring subsurface water storage dynamics associated with the 2023 extreme snowfall events in precipitation-limited systems

RAPID：监测降水有限系统中与 2023 年极端降雪事件相关的地下水储存动态

• 批准号: 2330004
• 负责人: Qifei Niu
• 金额: $ 4.97万
• 依托单位: Boise State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330004&HistoricalAwards=false
• 关键词: RAPID; Monitoring; subsurface; water; storage

Many areas in mountainous regions are experiencing more frequent and extreme weather conditions, such as heavy snowfall and drought, due to global warming. The impacts of these changing weather patterns on water resources available to society and ecosystems are still not fully understood. In spring 2023, many cooler regions in the western US received extremely heavy snowfalls, and in some locations, the recorded snow water equivalent exceeded historical values. This research aims to determine how mountain hydrological systems respond to such exceptionally heavy snowfall. This research will focus on determining how much of the melted snow water seeps into the ground during the wet season and how plants utilize the water stored in the soil and rocks during the dry summer. The scientific data collected through this study will provide valuable insights into how groundwater mitigates the adverse effects of climate change. Additionally, this project will offer training opportunities for one graduate student and produce educational materials for a course offered to hydrology graduate students from approximately ten universities. The valuable data collected for this project has potential to improve computational simulation techniques, which could inform future water resource management and benefit society.This research will use advanced geophysical imaging techniques to understand how anomalously wet conditions impact how meltwater enters and travels through the subsurface, and how subsurface water becomes available for use by vegetation, streamflow, and groundwater recharge. The study will be carried out at two sites in the Dry Creek Experimental Watershed near Boise, Idaho, where existing hydrometeorological information will supplement new geophysical imaging methods. Time-lapse electrical resistivity tomography will be used to monitor the daily or weekly resistivity variations related to subsurface water storage changes. A newly developed resistivity inversion scheme incorporating critical zone subsurface structure will be used to reconstruct the spatiotemporal resistivity distribution along a transect at each study site. The site-specific petrophysical relationship between resistivity and water content will also be determined such that the subsurface water dynamics can be estimated from resistivity data. The study will complement ongoing efforts investigating water uptake strategies by plants, streamflow generation, and groundwater recharge to enhance understanding of how extreme weather events impact hydrological processes in mountain systems. This award is co-funded by the Hydrologic Sciences and Geophysics programs.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.

由于全球变暖，许多山区正在经历更频繁和更极端的天气状况，如大雪和干旱。这些不断变化的天气模式对社会和生态系统可用水资源的影响仍未得到充分了解。2023年春季，美国西部许多较冷的地区迎来了特大降雪，在某些地区，记录的雪水当量超过了历史值。这项研究旨在确定山区水文系统如何应对这种异常大雪。这项研究的重点是确定有多少融化的雪水在雨季渗入地下，以及植物如何在干燥的夏季利用土壤和岩石中储存的水。通过这项研究收集的科学数据将为地下水如何减轻气候变化的不利影响提供宝贵的见解。此外，该项目还将为一名研究生提供培训机会，并为大约10所大学的水文学研究生开设的课程编写教材。为该项目收集的宝贵数据有可能改善计算模拟技术，这可以为未来的水资源管理提供信息，造福社会。该研究将使用先进的地球物理成像技术来了解异常潮湿的条件如何影响融水进入和穿过地下水，以及地下水如何被植被，径流和地下水补给所利用。这项研究将在爱达荷州博伊西附近的干溪实验流域的两个地点进行，现有的水文气象信息将补充新的地球物理成像方法。将使用延时电阻率层析成像来监测与地下水储存变化有关的每日或每周电阻率变化。一个新开发的电阻率反演方案，结合临界区地下结构将被用来重建时空电阻率分布沿着在每个研究地点的横断面。还将确定电阻率和含水量之间的特定场地岩石物理关系，以便根据电阻率数据估计地下水动态。该研究将补充正在进行的调查植物，径流产生和地下水补给的水吸收战略的努力，以加强对极端天气事件如何影响山区系统水文过程的理解。该奖项由水文科学和地球物理学项目共同资助。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。