Collaborative Research: Revealing the hidden groundwater storage dynamics of the Great Lakes Basin by synthesizing geodesy, hydrologic modeling, and remote sensing

了解气候和土地利用变化对水文的复杂和相互交织的影响对于管理水资源是必要的。五大湖盆地是世界上最大的地表淡水资源，在过去十年中，湖泊水位从创纪录的低点到创纪录的高点经历了戏剧性的变化。尽管有一个多世纪的湖泊水位测量，我们并不完全了解是什么驱动了五大湖水位的这种波动。其中一个原因是，该盆地大量的地下水资源监测不力，在模型中往往被忽视。在这里，我们建议开发一个更准确地模拟地表和地下水流动的水文模型，该模型由地面GPS仪器和卫星提供的数据驱动并得到验证。这个模型将提供一个前所未有的视角，来了解地下水--“第六大湖”--如何影响整个格拉斯哥大湖的湖面。我们提出了一种融合GPS、InSAR、卫星图像和GRACE数据的水文模拟方法，以更准确地模拟GLB中的表层和次表层流动。这将是首次将大地测量学(形变和重力变化)、从遥感测量与地下水耦合的地表水范围和综合水文模型结合在一起。通过数据同化，我们将产生历史和现在预测的地下水流动和储存再分析产品，以揭示整个盆地地下水的时空分布，并将其与湖泊水位的波动联系起来。这将提供有关水资源管理所需的地表水和地下水储量、湖泊水位和流量的可靠信息。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。

Understanding the complex and interwoven effects of changing climate and land use on hydrology is necessary to manage water resources. The Great Lakes Basin (GLB), the world’s largest surface freshwater resource, has experienced dramatic shifts in lake levels from record lows to record highs over the last decade. Despite over a century of lake level measurements, we do not fully understand what drives such fluctuations in Great Lakes levels. One reason is that the basin’s extensive groundwater resources are poorly monitored, and often ignored in models. Here, we propose to develop a hydrologic model that more accurately simulates both surface and groundwater flows, driven by and validated using data from both ground GPS instruments and satellites. This model will provide an unprecedented view of how groundwater, the “sixth Great Lake”, affects lake levels across the GLB. We propose a fusion of hydrologic modeling with GPS, InSAR, satellite imagery, and GRACE data to more accurately simulate surface and subsurface flows in the GLB. This will be the first such integration of geodesy (deformation and gravity change), measurements of groundwater-coupled surface water extent from remote sensing, and integrated hydrologic modeling. Through data assimilation, we will produce both historical and nowcast groundwater flow and storage reanalysis products to reveal the spatio-temporal distribution of groundwater across the basin, and relate this to fluctuating lake levels. This will provide reliable information about surface and groundwater storage, lake levels, and flow rates that are needed for water resource management.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.