Impact of Precipitation and Managed Aquifer Recharge on Post-Drought Groundwater Storage Recovery in California's Central Valley

水资源短缺是一个严峻的全球性挑战，了解含水层中的地下水如何从长期干旱中恢复对于可持续水资源管理至关重要。在加州的中央谷，一个重要的农业枢纽面临地下水枯竭，这项研究探讨了与大气河流和厄尔尼诺现象相关的大降雨事件对地下水枯竭和恢复的贡献。此外，它还研究了管理含水层补给（MAR）作为地下水枯竭问题的战略解决方案。这项研究旨在提高地下水的恢复力，减轻洪水风险，与加州最近的可持续地下水管理法案（SGMA）保持一致。预期成果，如不同气候情景下的地下水储量图，为优先实施MAR和促进SGMA框架内的决策提供了宝贵的工具。该项目还培养了一名博士。该项目是可持续水资源管理专业的学生，通过纳入项目数据集、模型和情景，丰富了加州大学洛杉矶分校的水资源课程。第一个问题探讨降水趋势对地下水干旱恢复的影响。该方法集成了历史数据分析和计算机模型模拟。研究任务包括确定年度和季节性地下水恢复与降水之间的关系，并评估降水特征对恢复的影响。第二个问题是调查MAR在提高含水层复原力方面的潜力。该方法利用数值实验，使用计算机模型来模拟各种气候情景和MAR实施下的地下水储存恢复。研究结果将为MAR在缓解地下水超采方面的有效性提供深入的见解，并对低流量增加和洪水风险降低产生影响。该奖项反映了NSF的法定使命，并被认为值得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来支持。

Water scarcity is a critical global challenge, and understanding how groundwater in aquifers recovers from prolonged droughts is essential for sustainable water resource management. In California's Central Valley, a crucial agricultural hub facing groundwater depletion, this research explores the contribution of large rainfall events associated with Atmospheric Rivers and El Nino to groundwater depletion and recovery. Additionally, it examines Managed Aquifer Recharge (MAR) as a strategic solution to the groundwater depletion issue. This research aims to enhance groundwater resilience and mitigate flooding risks, aligning with California's recent Sustainable Groundwater Management Act (SGMA). Anticipated outcomes, such as groundwater storage maps under diverse climate scenarios, provide invaluable tools for prioritizing MAR implementation and facilitating decision-making within the SGMA framework. The project also trains a Ph.D. student in sustainable water resources management and enriches water resources curricula at UCLA through the inclusion of project datasets, models, and scenarios.The project addressed two main research questions. The first question explores the impact of precipitation trends on groundwater drought recovery. The approach integrates historical data analysis and computer model simulations. Research tasks include identifying relationships between annual and seasonal groundwater recovery and precipitation and assessing the influence of precipitation characteristics on recovery. The second question investigates the potential of MAR in increasing aquifer resiliency. The approach utilizes numerical experiments using a computer model to simulate groundwater storage recovery under various climate scenarios and MAR implementations. The results will provide insights into the effectiveness of MAR in mitigating groundwater overdrafts, with implications for low-flow augmentation and flood risk reduction.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.