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

了解气候变化和土地利用对水文的复杂和相互交织的影响是管理水资源所必需的。五大湖盆地（GLB）是世界上最大的地表淡水资源，在过去十年中，湖泊水位经历了从创纪录的低点到创纪录的高点的巨大变化。尽管进行了一个多世纪的湖泊水位测量，但我们并不完全了解是什么导致了五大湖水位的这种波动。一个原因是该盆地丰富的地下水资源监测不足，而且经常在模型中被忽略。在这里，我们建议开发一个水文模型，更准确地模拟地表和地下水流动，并使用地面GPS仪器和卫星的数据进行驱动和验证。该模型将提供一个前所未有的视角，了解地下水（“第六大湖”）如何影响整个GLB的湖泊水位。我们建议将水文建模与GPS、InSAR、卫星图像和GRACE数据融合，以更准确地模拟GLB的地表和地下流动。这将是第一次将大地测量学（变形和重力变化）、地下水耦合地表水范围的遥感测量和综合水文建模结合起来。通过数据同化，我们将生成历史和临近预测的地下水流量和储水量再分析产品，以揭示整个盆地地下水的时空分布，并将其与湖泊水位波动联系起来。这将提供有关地表水和地下水储存量、湖泊水位和水资源管理所需的流量的可靠信息。该奖项反映了美国国家科学基金会的法定使命，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。

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.