Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization

A wide variety of stream and wetland restoration projects are implemented globally with the goal of restoring hydrologic, ecological, and biogeochemical function to waterways. However, restoration is often implemented on an ad-hoc basis with little attention paid to drivers of issues within the watershed or upslope area and projects are focused on restoring the form of a waterway assuming that improvements to catchment condition and function will follow, yet fail to treat the root cause of the impairment. This lack of focus on watershed function can lead to misspent dollars and project placement that may not address water quality and quantity issues appropriately. To address these limitations, there is a critical need for a functionally-based, high-resolution restoration priority system that can be implemented at broad spatial scales to maximize ecological benefits. This article in the journal Environmental Management describes the River Basin Restoration Prioritization tool developed in conjunction with the North Carolina Department of Environmental Quality to incorporate data models into a catchment scale restoration prioritization framework. It is designed specifically as a state-wide screening tool that assesses hydrologic, water quality, and aquatic habitat quality conditions with peak flood flow, nitrogen and phosphorus loading, and aquatic species distribution models. Although the application of the tool in this analysis is for the state of North Carolina, the methodology and model datasets are readily applicable to other states or regions to assess a large volume of data to better inform restoration choices.