Stormwater Abatement

Perez-Pedini C, Limbrunner JF, Vogel RM (2005) “Optimal location of infiltration-based best management practices for storm water management,” JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 131(6) pp. 441-448

This week’s paper represents a move away from the employment of large scale projects and land use for controlling storm water runoff in favor of multiple smaller scale infiltration based practices. Perez-Pedini et. al studied a watershed in Massachusetts in an attempt to apply a genetic algorithm approach to finding the optimal method for controlling storm water runoff. They began by dividing the watershed into ~4500 hydrologic response units that could be characterized in terms of their overall contribution to runoff during storm events. They calibrated and validated their distributed model using two events from 2002 and 2003. By comparing the predicted hydrograph at the output of the watershed to the hydrograph from the corresponding storm events they found that the distributed model based on hydrologic response units was able to accurately predict runoff volumes within the watershed.

Perez-Pedini et al then selected ~1900 hydrologic response units within the watershed that met the criteria of either:
1) Being highly impervious (CN > 89) or
2) Were likely to contribute to runoff due to close physical proximity to a discharge stream.
The selected hydrologic response units were used as the fodder for optimizing best management practices within the watershed using a genetic algorithm approach. The genetic algorithm produced a series of possible solutions to achieving a targeted reduction in storm water runoff using the 2003 storm simulation. From these possible solutions Perez-Pedini et. al were able to build a trade off curve that effectively related costs to runoff reduction.

The creation of the trade off curve ties in nicely with a point that was discussed in one of the opening papers of the semester regarding the nature of public (wicked) problems and the role of optimization models. While the GA approach was able to find numerous possible solutions for reducing storm water runoff within the watershed the end result was the creation of a “guide” rather than a absolute answer. Balancing the costs of construction against the needs for runoff reduction requires more direction and inputs than can be easily programmed into a GA or any other optimization method. I also enjoyed that this paper focused on smaller BMPs, e.g. swales and curb cuts, rather than large detention ponds. Detention pond based BMPs can work will in developing areas, where large amounts of land are available and land costs are lower but the BMPs tested in this paper are applicable to areas that are already highly developed. Using the methods of this paper makes it more feasible to redevelop storm water management in highly developed areas to reduce runoff and lessen the impacts of existing developments on stream systems.