Collaborative Research: High Resolution Sensor Networks for Quantifying and Predicting Surface-Groundwater Mixing and Nutrient Delivery in the Santa Fe River, Florida.

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ABSTRACTThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Intellectual Merit: This project proposes to test the hypothesis that natural tracers measured at temporal resolution similar to water fluxes (i.e., daily or sub-daily) can be used to predict coupling between riverine hydrology, surface water-groundwater mixing, and biogeochemistry. The hypothesis will be tested with high temporal resolution monitoring and measurements of selected solutes. These results will inform and improve conceptual and numerical models of hydrologic, hydrogeologic, and chemical dynamics and fluxes. Hypothesis testing will address three specific science questions: 1) What are the temporal and longitudinal dynamics of surface/groundwater mixing, and how do these affect the delivery of ecologically relevant solutes (nitrate, phosphate, H+, dissolved organic carbon)? 2) How does assimilation of high resolution stream chemistry data into integrated, parallel watershed models (e.g., PARFLOW) improve predictions of stream flow, groundwater elevation, surface/groundwater mixing and solute transport? 3) How does the incorporation of high resolution chemical measurements and mission agency data into Bayesian network models improve real-time predictions of stream flow and surface/groundwater mixing ratios? The work will be focus on the Santa Fe River in North Florida. This river crosses the boundary of the confined and unconfined karstic Floridan Aquifer, resulting in two chemically well-characterized source water end-members: surface runoff and groundwater. These end members mix in dynamic proportions depending on river discharge. The end members should be able to be discriminated using in situ continuous sensors, primarily for specific conductivity, and high resolution auto-sampling to allow complimentary measurements of color, pH, nitrate, phosphate, and major ion concentrations.Broader Impacts: This work will impact the scientific community by contributing to the development of distributed hydrologic sensing capabilities, which is the basis of the WATERS test-bed sites. High resolution sampling techniques and modeling of hydrologic and hydrogeologic dynamics will be tested across sites by interactions with the Baltimore WATERS test-bed site. The sampling will be co-located with existing flow infrastructure (e.g., USGS gaging stations) and results will be combined with agency data to discern where river water comes from, how long it took to get there, and what it carries. This information will be provided to cognizant water management agencies and stakeholder groups to better inform management and policy decisions. The data will be organized in the CUAHSI hydrologic information system for data storage and retrieval, concatenation with mission agency data, and to provide web-based access to archival data. The project will support on-going graduate and undergraduate research.