Review of Urban Stormwater Quality Models: Deterministic,Stochastic, and Hybrid Approaches1

Abstract: The growing impact of urban stormwater on surface‐water quality has illuminated the need for more accurate modeling of stormwater pollution. Water quality based regulation and the movement towards integrated urban water management place a similar demand for improved stormwater quality model predictions. The physical, chemical, and biological processes that affect stormwater quality need to be better understood and simulated, while acknowledging the costs and benefits that such complex modeling entails. This paper reviews three approaches to stormwater quality modeling: deterministic, stochastic, and hybrid. Six deterministic, three stochastic, and three hybrid models are reviewed in detail. Hybrid approaches show strong potential for reducing stormwater quality model prediction error and uncertainty. Improved stormwater quality models will have wide ranging benefits for combined sewer overflow management, total maximum daily load development, best management practice design, land use change impact assessment, water quality trading, and integrated modeling.     

ADDRESSING TOTAL PHOSPHORUS IMPAIRMENTS WITH WATER QUALITY TRADING1

ABSTRACT: Water quality trading is a voluntary economic process that provides an opportunity for dischargers to reduce the costs associated with meeting a discharge limitation. Trading can provide a cost effective solution for point sources (i.e., wastewater treatment plants) to meet strict effluent limitations set in response to total maximum daily loads (TMDLs). A successful trading program often depends on first determining the trading suitability of a pollutant for a particular watershed. A simple technical approach has been developed to identify sub‐watersheds within the Raritan River Basin, New Jersey, where water quality trading could provide a cost effective and scientifically feasible method for addressing total phosphorus impairments. The methodology presented will serve as a model to conduct similar analyses in other watersheds. The Raritan River Basin was divided into 12 subwatershed‐based study areas. Point‐nonpoint source trading opportunities were examined for each study area by examining the point and nonpoint source total phosphorus loading to impaired water bodies. Of the 12 subwatersheds examined, four had a high potential for implementing a successful trading program. Since instream phosphorus concentrations are closely related to soil erosion, an additional analysis was performed to examine soil erodibility. Recommendations are presented for conducting an economic analysis following the feasibility study.     

Water Quality Model Uncertainty Analysis of a Point‐Point Source Phosphorus Trading Program1

Kardos, Josef S. and Christopher C. Obropta, 2011. Water Quality Model Uncertainty Analysis of a Point‐Point Source Phosphorus Trading Program. Journal of the American Water Resources Association (JAWRA) 47(6):1317–1337. DOI: 10.1111/j.1752‐1688.2011.00591.x Abstract: Water quality modeling is a major source of scientific uncertainty in the Total Maximum Daily Load (TMDL) process. The effects of these uncertainties extend to water quality trading programs designed to implement TMDLs. This study examines the effects of water quality model uncertainty on a nutrient trading program. The study builds on previous work to design a phosphorus trading program for the Nontidal Passaic River Basin in New Jersey that would implement the watershed TMDL for total phosphorus (TP). The study identified how water quality model uncertainty affects outcomes of potential trades of TP between wastewater treatment plants. The uncertainty analysis found no evidence to suggest that the outcome of trades between wastewater treatment plants, as compared with command and control regulation, will significantly increase uncertainty in the attainment of dissolved oxygen surface water quality standards, site‐specific chlorophyll a criteria, and reduction targets for diverted TP load at potential hot spots in the watershed. Each simulated trading scenario demonstrated parity with or improvement from the command and control approach at the TMDL critical locations, and low risk of hot spots elsewhere.     

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.