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Geology topics

Research about Maumee River watershed

Source-linked reports with geographic coverage including Maumee River watershed.

2 recordsLinked to original sources

Prioritizing chemicals of emerging concern in the Great Lakes Basin using covariance of chemical concentrations and diverse biological responses from a variety of species

The Great Lakes Restoration Initiative aims to protect and restore the nation’s largest freshwater resource, in part, by furthering our understanding of the effects of contaminants of emerging concern (CECs) and chemical mixtures on aquatic and terrestrial organisms. To address this goal, an interagency team conducted field studies at sites along the Maumee River in Ohio, USA, in 2016–2017, monitoring CEC levels along with diverse in vitro and in vivo biological effects in ecologically relevant species (fathead minnows, tree swallows, and golden clams). The objective of the present work was to prioritize the CECs in these studies for further monitoring and assessment by determining if there are patterns in chemical–bioeffect relations across data sets, species, and response types that indicate relatively high or low hazard to aquatic life from CEC exposure. Of the 748 monitored chemicals, 425 were detected and were analyzed for covariance with bioeffects. All 748 chemicals were placed into 10 bins based on their frequencies of monitoring, detection, and covariance with bioeffects across studies and species. We describe how chemicals can be prioritized across bins to aid monitoring and assessment efforts. Our approach using effects-based monitoring data is especially useful for prioritizing chemicals with little or no traditional toxicity testing data. Similar evidence-based prioritizations will allow agencies to more efficiently allocate limited resources to improve the ability to protect aquatic and terrestrial organisms from adverse impacts due to contaminant exposure.

Ohio

Uncertainty in critical source area predictions from watershed-scale hydrologic models

Watershed-scale hydrologic models are frequently used to inform conservation and restoration efforts by identifying critical source areas (CSAs; alternatively 'hotspots'), defined as areas that export relatively greater quantities of nutrients and sediment. The CSAs can then be prioritized or ‘targeted’ for conservation and restoration to ensure efficient use of limited resources. However, CSA simulations from watershed-scale hydrologic models may be uncertain and it is critical that the extent and implications of this uncertainty be conveyed to stakeholders and decision makers. We used an ensemble of four independently developed Soil and Water Assessment Tool (SWAT) models and a SPAtially Referenced Regression On Watershed attributes (SPARROW) model to simulate CSA locations for flow, phosphorus, nitrogen, and sediment within the ~17,000-km 2 Maumee River watershed at the HUC-12 scale. We then assessed uncertainty in CSA simulations determined as the variation in CSA locations across the models. Our application of an ensemble of models - differing with respect to inputs, structure, and parameterization - facilitated an improved accounting of CSA prediction uncertainty. We found that the models agreed on the location of a subset of CSAs, and that these locations may be targeted with relative confidence. However, models more often disagreed on CSA locations. On average, only 16%–46% of HUC-12 subwatersheds simulated as a CSA by one model were also simulated as a CSA by a different model. Our work shows that simulated CSA locations are highly uncertain and may vary substantially across models. Hence, while models may be useful in informing conservation and restoration planning, their application to identify CSA locations would benefit from comprehensive uncertainty analyses to avoid inefficient use of limited resources.

Ohio