Development of a multi-scale management tool for predicting and mitigating HABs in Ohio River watershedsEPA Grant Number: RD839269
Title: Development of a multi-scale management tool for predicting and mitigating HABs in Ohio River watersheds
Investigators: Sullivan, Mažeika , Pintor, Lauren , Zhao, Kaiguang
Institution: The Ohio State University
EPA Project Officer: Packard, Benjamin H
Project Period: January 1, 2018 through December 31, 2020
Project Amount: $681,343
RFA: Freshwater Harmful Algal Blooms (2017) RFA Text | Recipients Lists
Research Category: Water , Water Quality , Water and Watersheds
We propose to develop a watershed classification system to diagnose and manage harmful algal blooms (HABs) in the upper Ohio River basin. The goal is a multi-scale, hierarchical tool that links climate and land use with river physicochemical gradients and ecological condition to predict and prevent HABs. Our overarching hypothesis is that the timing and magnitude of HABs are related, directly and indirectly, to variability in anthropogenic and natural factors in watersheds, and that these relationships are scalable. Our objectives are to: (1) Determine in-stream characteristics related to distribution, duration, and intensity of HABs, (2) Determine climate and land-use features strongly linked with HABs, and (3) Develop and validate a classification system for use by communities and local and state agencies to predict and prevent HABs.
Our experimental approach includes model-building and validation phases. For model building, we will build on our current research in 3 southern Ohio watersheds and add 4 watersheds from Indiana and Kentucky. Each watershed will have 7 stream reaches and 3-5 receiving reservoir/river sites, representing a suite of non-agricultural land uses (e.g., forested, urban). At each study site, we will quantify physicochemical characteristics and biological metrics. We will use remote sensing, GIS, and local environmental data to develop metrics for climate, land use, and anthropogenic impacts, along with structuralequation modeling and multivariate techniques to quantify relationships among predictors and HABs. Land-use change modeling (GIS), hydrologic modeling (SWAT), and δ18Ophosphate analysis will identify land areas that contribute to watershed impairment under current and projected land-use and climate scenarios. Modeling the direct and indirect links among climate, watershed condition, and in-stream characteristics will allow us to develop a classification system that we will validate in larger watersheds of the upper Ohio River basin, including areas of the mainstem Ohio River.
The resulting classification system will be presented in a framework that can be used by managers as a regular part of watershed planning and risk assessment efforts to prevent and predict HABs. This management tool represents a novel application of theoretical knowledge of hierarchical processes in watersheds and an innovative approach to predicting and managing HABs. The proposed research will improve risk assessment, management, and sustainability by: (1) identifying key measurement endpoints for watershed-level risk assessment and management, (2) constructing exposure-response profiles for impacts of climate and land-use change, (3) providing improved data on multiscale watershed effects, and (4) developing a classification system that will contribute to prioritizing risks and maintaining aquatic resources of the Ohio River basin for current and future generations of local communities.