CAREER:Characterizing Mountain System Aquifer Recharge in the Sierra Nevada Mountains of California

地球上超过16%的人口依赖于季节性积雪和冰川供水，但人们对高海拔山脉地下水补给和径流的机制知之甚少。对地下水补给进行量化对于地下水管理至关重要，特别是在依赖山区流域径流和补给的灌溉农业地区。加州的内华达州山脉的降水（雪和雨）是中央谷的主要自然补给机制，中央谷是一个至关重要的农业区。频繁的干旱和内华达州积雪的变化预计将改变补给率，对水安全、可持续水管理和农业生产构成挑战。该项目将整合几种研究方法，调查内华达州南部卡威河流域地下水补给的最重要驱动因素，并将量化地下水对气候变化、干旱和植被变化的响应。该项目旨在通过让本科生和研究生参与研究，以及开发侧重于山区集水区水文过程的在线学习模块，改善在STEM学科中代表性不足的群体的水文科学教育和解决问题的技能。该项目将培训高中教师，并为高中STEM教学设计在线教育资源。通过让卡威河流域的公民参与数据收集，该项目将提高公众对影响加州水资源的复杂因素的认识。虽然地下水补给供应66.5%的径流在干旱和半干旱山区集水区，了解山区系统含水层补给率和地下水流路径从山区到山谷含水层是有限的。该项目将通过野外数据收集、实验室分析和数值模拟，研究加州Sierra内华达州的Kaweah河流域山谷含水层系统的地下水补给。一套水文观测和水化学示踪剂将测量集水区水平衡动态，地表水和地下水的停留时间，以及基岩地下水对河流的贡献。一个综合的水文模型通知多个观测来源，将限制从山区到山谷含水层的地下水流路径，并改善补给估计。对补给进行量化并了解山区和山谷含水层系统之间的连通程度，将有助于了解山区和山谷系统对可持续水资源的水文贡献。研究结果将为土壤水分和径流模拟工具包（SMART）的计算效率高的地下水模块的开发提供信息，这是一个半分布式水文建模框架。新的SMART-G计算框架将调查山区流域的地表水-地下水相互作用，并预测气候变异和土地覆盖变化对水资源的影响。该项目将使本科生参与研究和开发教育材料，以培养水文科学方面的熟练劳动力。该项目将培训高中教师，使学生为大学入学的STEM要求做好准备，并让公民科学家参与提高公众对水资源的认识。建模工具将在全球范围内传播，并将为地方和州一级的政策和地下水管理决策提供信息。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。

More than 16% of Earth's population relies on seasonal snowpack and glaciers for water supply, yet the mechanisms of groundwater recharge and streamflow in high elevation mountain ranges are poorly understood. Quantifying groundwater recharge is essential for groundwater management particularly in irrigated agricultural regions relying on streamflow and recharge from mountain watersheds. Precipitation (snow and rain) in California's Sierra Nevada is the dominant natural recharge mechanism for the Central Valley, a vitally important agricultural region. Frequent drought and changes in snowpack in the Sierra Nevada are expected to change recharge rates, posing challenges to water security, sustainable water management, and agriculture production. This project will integrate several research methods to investigate the most important drivers of groundwater recharge in the Kaweah River watershed in southern Sierra Nevada, and will quantify groundwater response to climate variability, droughts, and changes in vegetation. The project aims to improve hydrologic sciences education and problem-solving skills for groups underrepresented in STEM disciplines by engaging undergraduate and graduate students in research, and developing online learning modules focused on hydrologic processes of mountain catchments. The project will train high school teachers and design online educational resources for STEM teaching in high schools. By involving the Kaweah River watershed citizens in data collection, the project will increase public awareness of complex factors that affect water resources in California. Although groundwater recharge supplies 66.5% of streamflow in arid and semi-arid mountain catchments, understanding of mountain system aquifer recharge rates and groundwater flow paths from mountains to valley aquifers is limited. This project will investigate groundwater recharge in a mountain-valley aquifer system in the Kaweah River watershed of California’s Sierra Nevada through field data collection, laboratory analysis and numerical modeling. A suite of hydrometric observations and hydrochemical tracers will measure catchment water balance dynamics, residence times of surface water and groundwater, and bedrock groundwater’s contribution to streams. An integrated hydrologic model informed by multiple sources of observations, will constrain groundwater flow paths from mountain to valley aquifers, and improve recharge estimation. Quantifying recharge and understanding the degree of connectivity between the mountain and valley aquifer system will provide understanding of the hydrologic contributions from mountain-valley systems for sustainable water resources. Results will inform development of a computationally efficient groundwater module of the Soil Moisture and Runoff simulation Toolkit (SMART), a semi-distributed hydrologic modeling framework. The novel SMART-G computational framework will investigate surface water-groundwater interactions in mountain watersheds, and predict impacts of climate variability and land cover changes on water resources. The project will engage undergraduate students in research and develop educational materials to prepare skilled workforce in hydrologic sciences. The project will train high school teachers to prepare students in STEM requirements for university admission, and involve citizen scientists to increase public awareness about water resources. Modeling tools will be disseminated worldwide and will inform policy and groundwater management decisions at the local and state level.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.