作者: William R. Trenouth , Bahram Gharabaghi
DOI: 10.1016/J.JHYDROL.2016.08.058
关键词: Environmental science 、 Suspended solids 、 Ditch 、 Hydrology 、 Quality (business) 、 Pollutant 、 Surface runoff 、 Storm
摘要: This paper presents novel highway runoff quality models using artificial neural networks (ANN) which take into account site-specific traffic and seasonal storm event meteorological factors to predict the mean concentration (EMC) statistics daily unit area load (MDUAL) of common pollutants for design roadside ditch treatment systems (RDTS) protect sensitive receiving environs. A dataset 940 monitored events from fourteen sites located in five countries (Canada, USA, Australia, New Zealand, China) was compiled used develop ANN prediction suspended solids (TSS) EMC statistical distribution parameters, as well MDUAL four different heavy metal species (Cu, Zn, Cr Pb). TSS EMCs are needed estimate minimum required removal efficiency RDTS order improve meet applicable standards MDUALs calculate capacity ensure performance longevity.