Christopher C. Obropta

Application of an Environmental Decision Support System to a Water Quality Trading Program Affected by Surface Water Diversions

Environmental decision support systems (EDSSs) are an emerging tool used to integrate the evaluation of highly complex and interrelated physicochemical, biological, hydrological, social, and economic aspects of environmental problems. An EDSS approach is developed to address hot-spot concerns for a water quality trading program intended to implement the total maximum daily load (TMDL) for phosphorus in the Non-Tidal Passaic River Basin of New Jersey. Twenty-two wastewater treatment plants (WWTPs) spread throughout the watershed are considered the major sources of phosphorus loading to the river system. Periodic surface water diversions to a major reservoir from the confluence of two key tributaries alter the natural hydrology of the watershed and must be considered in the development of a trading framework that ensures protection of water quality. An EDSS is applied that enables the selection of a water quality trading framework that protects the watershed from phosphorus-induced hot spots. The EDSS employs Simon’s (1960) three stages of the decision-making process: intelligence, design, and choice. The identification of two potential hot spots and three diversion scenarios enables the delineation of three management areas for buying and selling of phosphorus credits among WWTPs. The result shows that the most conservative option entails consideration of two possible diversion scenarios, and trading between management areas is restricted accordingly. The method described here is believed to be the first application of an EDSS to a water quality trading program that explicitly accounts for surface water diversions.

USE OF BIOLOGICAL INDICATORS IN TMDL ASSESSMENT AND IMPLEMENTATION

Most states in the U.S. have a general water quality standard intended to protect water from all potential pollutants not specifically named or identified in other standards. Biological indicators are used, in part, to assess the level of water quality with respect to this general standard. Under EPA’s Total Maximum Daily Load (TMDL) program, impaired waters based on a biological assessment require an additional step compared with non-biological TMDLs. In non-biological TMDLs, the “pollutant” is typically the parameter being monitored, with a direct link to the impairment. In biological TMDLs, cause and effect must first be established between one or more pollutants and the impacted biological community. This article presents examples of approaches taken in different states to monitor and assess the biological health of our streams based on varying combinations of algal, macroinvertebrate, and fish communities. While fish are the ultimate integrator of lower ecological organisms, their occurrence and abundance has been greatly manipulated by humankind. Periphytic algae are perhaps the fastest responding biological population and can be used for some pollutant-specific diagnoses, but most states lack the expertise required for detailed taxonomic classification. Macroinvertebrates, the most commonly monitored biological community, are abundant in most streams, but most metrics are not diagnostic of specific stressors. Within the TMDL framework, issues are discussed related to setting TMDL targets, linking biological impairments with pollutants, and defining biological target endpoints. Although surrogate measures are often used for setting TMDL target loads, biological recovery is measured against biological endpoints. The use of biological indicators for assessment and development of biological TMDLs can be improved through modeling procedures that better define cause-and-effect relationships, through a better understanding of the limits of restoration, and through a more unified national policy that focuses on restoration.

Preliminary Field Evaluation of Soil Compaction in Rain Gardens

AbstractRain gardens are implemented to mitigate runoff volume and associated pollutants to restore the health of a watershed. Rain gardens reduce runoff volume through infiltration and improve water quality as pollutants are filtered through soil media. Infiltration rates, however, can be reduced as a result of soil compaction. Knowledge about the factors that control compaction in rain gardens is currently limited, and studies are lacking on the ability of rain gardens to infiltrate runoff over a long-term period. Twenty-six rain gardens in New Jersey were evaluated during the summers of 2010 and 2011. Depth to soil compaction was measured in the field, and soil texture, site information, and oxidation-reduction potential data were collected to compare different ages of rain gardens with various soil types. There was no significant difference in soil compaction between surveys based upon the age of the rain gardens, but soil texture was found to have an influence on compaction levels. This knowledge wil...

Assessment of Car Wash Runoff Treatment Using Bioretention Mesocosms

AbstractCar wash runoff is known to be a pollution source to surface water bodies. Many groups hold car-washing fundraisers unaware of pollution issues associated with car wash runoff. This preliminary study investigated whether rain gardens are an appropriate management practice for reducing car wash pollutants, specifically surfactants. The concentrations of total phosphorus (TP), total suspended solids (TSS), and surfactants were measured in car wash runoff before and after treatment in three rain garden mesocosms. Mean TSS and surfactant effluent concentrations were significantly lower than the car wash runoff with TSS reductions ranging from 84 to 95% and surfactant reductions ranging from 89 to 96%. The removal efficiencies for surfactants were not enough to reduce concentrations below literature-based values for aquatic toxicity. Mean TP effluent concentrations were higher than the car wash runoff with increases ranging from 197 to 388%, although the increase was not statistically significant. This...

Use of Biological Indicators in TMDL Assessment and Implementation

Most states have a general water quality standard intended to protect water quality from all potential pollutants not specifically named or identified in other standards. Biological indicators are used, in part, to assess the level of water quality with respect to this general standard. Under EPA’s Total Maximum Daily Load (TMDL) program, impaired waters based on a biological assessment require an additional step compared with non-biological TMDLs. In non-biological TMDLs, the “pollutant” is typically the parameter being monitored, with a direct link to the impairment. In biological TMDLs, cause and effect must first be established between one or more pollutants and the impacted biological community. This condensed paper, focused on biological indicators, is one of a series developed by members of the CSREES Southern Regional Project S1004 to present an overview of the modeling and assessment tools currently used to develop TMDLs. Examples are presented of approaches taken in different states to assess the biological health of streams based on varying combinations of the macroinvertebrate, fish, and algal biological communities, together with an assessment of the strengths and limitations of each approach. Within the TMDL framework, issues are discussed related to using stressor analysis to link biological impairments with pollutants, to setting TMDL endpoints, and to linking BMP implementation with biological recovery. Our analysis also identifies programmatic needs and recommendations for future research.