The performance of a stormwater treatment filter is dependent on the amount of the total long-term runoff that is actually treated by the filter, and by the level of treatment that is provided to the water passing through the filter. Most performance summaries assume that all of the runoff is treated, and are therefore over-estimates of the actual level of treatment provided. Most filters usually have a maximum treatment flow rate 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 flow rate of the treated water. However, the use of up-gradient storage can moderate the high flows, decreasing the amount of stormwater that is bypassed without treatment. The sizing of this adjacent storage must be done in conjunction with a continuous model that can evaluate many storage-treatment combinations.
This paper presents a framework for conducting long-term simulations of stormwater treatment filters. These analyses can be effectively used to predict performance, and to prepare design curves that can assist in sizing stormwater filters for specific areas. The paper starts with a discussion on the need for continuous long-term simulations for water quality stormwater controls and then describes some basic aspects of urban hydrology that affect filter performance and design. The use of correctly conceived urban hydrologic processes is critical, especially when calculating flows associated with small and intermediate-sized rains. These accurate processes, in conjunction with long-term simulations, enable accurate calculations 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 affecting receiving water resources while distorting information pertaining to the sources of flows and pollutants.
Examples for several different treatment objectives are presented for Madison, WI, using a five year rainfall record that was selected as being representative of long-term conditions. These examples, using WinSLAMM, show how dramatically 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 paper 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.