Collaborative Research: Quantifying how groundwater modulates streamflow response to hydrologic extremes

About This Grant

Mountainous regions are the primary source of water for much of the western United States. Many mountain streams are sustained by groundwater, but conceptual and hydrologic models often oversimplify groundwater processes. As a result, it is challenging to predict how streamflow responds to changes in groundwater recharge and storage caused by extreme wet and dry conditions. This project is evaluating how groundwater regulates stream responses to hydrologic extremes by integrating high-resolution stream and groundwater observations with hydrologic models. The knowledge generated from this work will improve understanding of how stored groundwater impacts mountain streamflow generation, thereby enhancing streamflow predictions. Broader impact activities include an early-career workshop on data-model integration in Earth surface processes, with the goal of fostering cross-disciplinary collaboration. Additionally, the project will integrate field infrastructure and models into undergraduate coursework at three institutions to expose more students to hydrologic science. This project aims to determine the role of groundwater in regulating streamflow response to hydrologic extremes across a groundwater storage gradient using a data-model integration approach. Field observations of stream discharge, source, and age in two mountain watersheds will be integrated with an iteratively calibrated process-based hydrologic model capable of simulating groundwater-surface water interactions under future long-term and short-term hydrologic extremes and with variable subsurface structure. Study sites include two mountain watersheds with high- and low-groundwater storage settings. The project will address how the structure of the subsurface influences the source, age, and magnitude of streamflow, as well as the extent to which upstream heterogeneity affect conditions at the watershed outlet. The project will improve understanding of how groundwater storage modulates streamflow during hydrologic extremes. The project will develop a transferable data-model integration framework to address critical zone science questions. The framework will be the focus of a broader impacts workshop that will provide early-career scientists the opportunity to learn field data or modeling techniques from peers, as well as foster new collaborations and cross-disciplinary learning within the critical zone community. 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.