CAREER: UAV-Based Radar Suite for Bulk-Snow Characterization and Risk Management

职业：基于无人机的雷达套件，用于大块雪的特征描述和风险管理

• 批准号: 2238620
• 负责人: Jay McDaniel
• 金额: $ 62.52万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238620&HistoricalAwards=false
• 关键词: CAREER; UAV; Based; Radar; Suite

Snow is a crucial component of the earth’s climate system due to its extensive surface coverage and the critical role it plays as part of the cryosphere. Seasonal snowpack runoff profoundly influences the distribution of meltwater in watersheds, which constitutes roughly one-sixth of the freshwater needs globally, and the majority of water resources in mountainous regions. Moreover, snow acts as a thermal blanket between the atmosphere and underlying ice, that leads to impacts on freshwater lake ecosystems and has socioeconomic implications given its critical role in transportation (e.g., ice-road duration) and ice-jam flooding. Therefore, studying this hydrological cycle is crucial, especially with model projections suggesting a low-to-no snow future due to persistent emissions of greenhouse gases and globally rising temperatures. However, there are large uncertainties in capturing the fine details of this cycle and the hydrological consequences. This is partly because there are not enough measurements of distributed bulk-snow characteristics in important areas such as inaccessible mountainous regions. These observational gaps limit our ability to accurately develop robust modeling and forecasting techniques for improved risk management and hazard mitigation proposes. This CAREER project addresses this data need by equipping a small unmanned aerial vehicle (UAV) with an advanced radar suite to produce fine spatial and temporal resolution measurements of snowpack properties such as snow depth, snow water equivalent, relative density, and liquid water content. The integrated research and education project also involves preparing, training, and exciting the next generation of remote sensing engineers to engage in multi-disciplinary careers. Beyond providing research opportunities to undergraduate and graduate students, this project will integrate research concepts into the teaching and laboratory curriculum, providing academic and experiential learning opportunities.This CAREER project would encompass both the development of a new UAV-based custom snow-penetrating sensor technology and enable research on the snow hydrology and snow-loading on freshwater lakes and river ice. The technological research will produce fine spatiotemporal data using intelligent monitoring capabilities that allow mapping of snow loading and ice thickness on freshwater lakes and rivers through 3D echogram formation and wind redistribution of snow using coherent change detection. These data would support actionable risk management strategies that drastically improve residents’ lives and socioeconomic resiliency. The CAREER project will also incorporate aspects of this research in graduate and undergraduate courses, includes experiential laboratory exercises through design-build projects, and as part of the RISING STudent Ambassador Research (RISING STAR) program will involve Native American and first-generation students to increase diversity and interest in STEM careers.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.

雪是地球气候系统的重要组成部分，因为它覆盖了广泛的表面，并作为冰冻圈的一部分发挥着关键作用。季节性积雪径流深刻地影响着流域融水的分布，流域约占全球淡水需求的六分之一，山区的大部分水资源也是如此。此外，雪在大气和底层冰之间充当热毯，导致对淡水湖生态系统的影响，并具有社会经济影响，因为它在运输(例如，冰路持续时间)和冰堵洪水中发挥关键作用。因此，研究这种水文循环是至关重要的，特别是模型预测表明，由于温室气体的持续排放和全球气温的上升，未来将出现低降雪或无雪。然而，在捕捉这一循环的细节和水文后果方面存在很大的不确定性。这在一定程度上是因为在重要地区，如人迹罕至的山区，没有足够的测量数据来衡量分布的大雪特征。这些观察差距限制了我们为改进风险管理和减灾建议而准确开发稳健的建模和预测技术的能力。这个CARAPE项目通过为小型无人机(UAV)配备先进的雷达套件来满足这种数据需求，以便对积雪深度、雪水当量、相对密度和液态水含量等积雪属性进行精细的空间和时间分辨率测量。综合研究和教育项目还包括准备、培训和激发下一代遥感工程师从事多学科职业。除了为本科生和研究生提供研究机会外，该项目还将把研究概念整合到教学和实验室课程中，提供学术和经验学习机会。这个职业项目将包括开发一种新的基于无人机的定制积雪穿透传感器技术，并使对淡水湖泊和河冰上的积雪水文和积雪负荷的研究成为可能。这项技术研究将使用智能监测能力产生精细的时空数据，这些能力允许通过3D超声图形成和使用相干变化检测的雪的风重新分布来绘制淡水湖泊和河流上的积雪负荷和冰层厚度。这些数据将支持可操作的风险管理战略，这些战略将显著改善居民的生活和社会经济弹性。CARAPE项目还将在研究生和本科课程中纳入这项研究的各个方面，包括通过设计-建造项目进行体验性实验室练习，并作为正在崛起的学生大使研究(正在崛起的新星)计划的一部分，将让美国原住民和第一代学生增加对STEM职业的多样性和兴趣。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。