Long-term Continuous Simulations for Evaluating Storage-Treatment Design Options of Stormwater Filters.

Robert Pitt, John Voorhees and Shirley Clark.


The performance of a stormwater treatment filter is dependent on the amount of the annual runoff that is treated by the unit and by the level of treatment that is provided by the filter to the water passing through it. Most performance summaries assume that all of the runoff is treated, and therefore overestimate the level of treatment provided. Over a long period this is not a reasonable assumption, as the largest peak flows are substantially greater than flows that occur most of the time. Most filters usually have maximum treatment flow rates that can be utilized per filter unit (per unit area of filter surface, per filter module, or some other measure) to obtain the stated treatment level of the treated water. However, the use of up-gradient storage can moderate the high flows, decreasing the amount of stormwater that bypasses without treatment. The sizing of this adjacent storage should be done in conjunction with a continuous model that can evaluate many storage-treatment combinations.

This chapter presents a framework for conducting long term simulations of stormwater treatment filters. These simulations can be used to predict performance and to prepare design curves in order to size stormwater filters for specific areas. The use of correctly conceived urban hydrologic processes is critical, especially when calculating flows associated with small and intermediate sized rains. These processes, in conjunction with long term simulations, allow accurate estimates to be made. Probability distributions of modeling outcomes that relate to many receiving water objectives in urban areas can also be prepared from the results of long term water quality simulations. The use of single design storms and hydrological calculations that focus on larger events do not provide accurate information for the rains which affect receiving water resources and distort information pertaining to the sources of flows and pollutants.

Examples for several different treatment objectives are presented for Madison, Wisconsin, using a five year rainfall record that was selected as being representative of long term conditions. These examples show how the treatment flow rate is dependent on treatment objectives, and how storage can be used in some cases to reduce the overall expected costs of the treatment systems. The framework presented in this chapter can be used by regulators to assist in the development of regulations pertaining to treatment goals for local conditions; by manufactures of stormwater filters in the preparation of design curves to assist in the sizing of filter units to meet these objectives; and by stormwater designers to help select alternative stormwater treatment systems.

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