Captured Runoff Prediction Model by Permeable Pavements Using Artificial Neural Networks

Abstract

AbstractIndustrialization has degraded water resources over the last century due to increasing stormwater runoff. Increased impervious area utilization has substantially reduced infiltration into the ground, raised flood risk, and transferred contaminant materials into water bodies. Sustainable stormwater management is needed in order to manage runoff in urban areas and prevent pollution from water resources. Low-impact development (LID) practices, such as permeable pavement, manage a large volume of surface runoff during rain events and prevent combined sewer systems from overflowing. Predicting the captured runoff volume from watershed area by permeable pavements provides useful resources to achieve more efficient designs. Artificial neural network (ANN) models have been developed to predict the captured runoff with higher accuracy. The ANN models relate rainfall parameters and site characteristics to the stored runoff volume. A comprehensive database is obtained from the recorded data of the monitored ...