Integrated Groundwater Surface Quality Modelling

Intensive agricultural practices within the South Nation River watershed and the large number of uses of the underlying aquifers makes it paramount that the aquitard properties and regional recharge patterns are adequately understood and protected. Conservation of natural capital (NC) and minimizing anthropogenic impacts within the recharge-discharge capture zones of these features are ways to help achieve this.

Develop and demonstrate the capability to utilize fully integrated hydrologic modeling tools for operational hydrologic forecasting in the context of water quality, groundwater-surface water, and their respective interactions, as well as NC value and ecological services (ES) endpoints. This project will provide significant advancement in the ability to track and predict the occurrence of water-borne contaminants such bacteria and agricultural nutrients at high spatial and temporal resolutions.

The work required by this contract aims to quantify the role of groundwater in sustaining natural capital, and to value groundwater in terms of ES. The project will leverage and build upon previous and ongoing research in the South Nation Watershed (SNW). The contractor will be expected to complete the following tasks.

1. Have access to and capability to run the HGS model of South Nation watershed.
2. Apply Machine Learning to complement and assist HGS analysis
3. Quantified ecological services endpoints directly from HGS simulation output, or hybrid HGS-Machine Learning simulations.
4. Write two scientific manuscripts (drafts) for submission to peer reviewed journals.