Grantee Research Project Results
2020 Progress Report: Development of a multi-scale management tool for predicting and mitigating HABs in Ohio River watersheds
EPA Grant Number: R839269Title: 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 (Extended to December 31, 2024)
Project Period Covered by this Report: January 1, 2020 through December 31,2020
Project Amount: $681,343
RFA: Freshwater Harmful Algal Blooms (2017) RFA Text | Recipients Lists
Research Category: Water , Water Quality , Watersheds
Objective:
The overarching objective of this project is to develop a watershed/catchment 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 to variability in anthropogenic and natural factors in catchments. Our objectives are to: (1) Determine in-stream characteristics related to distribution, duration, and intensity of HABs, (2) Determine local climate and land-use features strongly linked with HABs, (3) Assess the ability of our system to scale up to large catchments, and (4) Develop and validate a classification system for use by communities and local and state agencies to predict and prevent HABs.
Progress Summary:
The project is staffed with permanent employees, and seasonal research assistants are hired as necessary. Major equipment has been purchased. The COVID-19 pandemic significantly altered our planned activities for 2020. All field and laboratory work was fully halted for several months, preventing collection of field data and preparation and submittal of samples for analysis. We were able to access in-state (Ohio) field sites in late summer/early fall with limited personnel and collection capabilities. We were also able to resume laboratory work with reduced personnel in late summer. In light of these unanticipated circumstances – as well as some delays relative to weather and the extensive travel required to complete fieldwork across four states – we requested a no-cost extension thru December, 2022, which was approved.
In fall 2020, 110 solid phase adsorption toxin tracking (SPATT) bags from all study catchments were sent for analysis of cyanotoxins using LC-MS (EPA Method 544). Microcystin congeners (MC-LF, MC-LR, MC-LY, MC-RR, MC-LW, MC-YR) were measured along with Cylindrospermopsin, Saxitoxin, Anatoxin, and Euglenophycin. A preliminary test round of 10 SPATTs detected microcystin in 8 samples, with the two highest values detected in Indian Lake, Ohio. In fall 2020, 15 SPATT bags were deployed and collected from sites in Hoover Reservoir, Ohio.
Isotope samples measuring δ18O of phosphate (δ18OP) in water were collected at stream and reservoir sampling locations in Ohio and Kentucky during 2016-2019 and 2018-2019, respectively. We used δ18O of phosphate as a tracer of inorganic P inputs to streams and reservoirs. Our survey included several sites within each lake (usually 3 sites), which were sampled in the hypolimnion and epilimnion when there was vertical stratification. In this way, we captured the temporal and spatial variability of the phosphate pool within lakes. During 2020, we analyzed the data corresponding to the samples collected in Ohio catchments during 2016-2018. Additionally, the contribution of streams to the inorganic P pool in lakes/reservoirs was estimated from δ18OP values by using mixing models.
In September-October 2020, periphyton (to quantify chlorophyll concentration, biomass, and species composition) was collected at 9 sites and phytoplankton (to quantify chlorophyll) was collected at 11 sites in Hoover Reservoir, Ohio. Laboratory sample processing using a fluoroprobe continued in summer and fall of 2020, and will be completed in 2021. During September-October 2020, additional samples were collected throughout stream sites in Hoover Reservoir (4 samples per site) with corresponding water-quality samples and measurement of physicochemical parameters. These efforts will produce a dataset encompassing stream and reservoir phytoplankton samples from 2016-2021, and periphyton samples from 2019-2021.
In addition to the watershed characterization through hydrological modeling, we began to derive a set of catchment-level metrics based on landscape data (i.e., land composition and satellite observations). These metrics have and will be tested as empirical predictors in our proposed statistical modeling framework. Specifically, we implemented a multi-directional flow algorithm to capture water flows across a watershed based on fine-resolution LiDAR DEM data; the algorithm was applied to all the individual surveyed stream reaches to delineate the contributing drainage basins. We combined the DEM-based drainage areas with annual land-cover maps (i.e., cropland data layers) to characterize the land-use change dynamics over the past two decades. The cropland data layers allowed us to compute land composition metrics down to the levels of individual crop types (e.g., corn, soybean, and wheat). These land-use history and dynamics metrics will be tested as predictors to explain spatial patterns in field-based water quality measurements.
Future Activities:
Geomorphic, physicochemical, and ecological data will continue to be collected at stream and reservoir sites in Indiana and Kentucky/Tennessee. Additional data will be collected at Ohio sites where necessary. Data buoys will be deployed during the spring, summer, and autumn of the next two years at Burr Oak, Hoover, Taylorsville, and Monroe lakes/reservoirs. Isotopic sampling and model building will continue across all catchments. Data analysis for Objectives 1 and 2 continue. The hydrological modeling framework will be configured and will begin to build our global model using statistical modeling (structural equation modeling) to seek predictive relationships from data, which will serve as the basis for our classification system. An initial classification system will be developed and tested to predict harmful algal bloom regimes.
Journal Articles:
No journal articles submitted with this report: View all 11 publications for this projectSupplemental Keywords:
catchments, cumulative effects, ecological condition, ecosystem, habitat, EPA Regions 4 and 5, Midwest, scaling, sediments, vulnerabilityRelevant Websites:
The Ohio State Stream & River Ecology Lab Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.