Literature DB >> 31526980

Taxonomy of influential factors for predicting pollutant first flush in urban stormwater runoff.

Thamali Perera1, James McGree2, Prasanna Egodawatta2, K B S N Jinadasa3, Ashantha Goonetilleke4.   

Abstract

Pollutant first flush in urban stormwater runoff is an important phenomenon influenced by a range of rainfall and catchment related variables. Even though numerous studies have been undertaken to mathematically define the first flush and the influential variables of first flush, limited research have been carried out to rank such variables in terms of their level of importance in generating first flush. Identifying the degree of importance of the variables is critical for accurate predictions of first flush occurrence and understanding the main drivers of first flush. This research study undertook a comprehensive analysis of the variables influencing the predictions of first flush occurrence and their relative importance. The study results are expected to contribute to more accurate predictions of first flush by affording greater importance to the highly ranked factors and their impacts. The study outcomes confirmed that total rainfall depth was the most important variable influencing the prediction of first flush events while the maximum intensity was the second. Rain duration, runoff depth, runoff peak and average intensity were the next four most important variables. Antecedent dry period and effective impervious area fraction had relatively low ranking while the time of concentration and the event mean concentration were found to be the least important variables. Furthermore, the study outcomes highlight that the use of a combination of variables and due consideration of their interactions can yield better results than considering their individual roles.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Classification and regression tree; Pollutant first flush; Random forest; Stormwater pollutant processes; Stormwater quality; Stormwater treatment design

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Year:  2019        PMID: 31526980     DOI: 10.1016/j.watres.2019.115075

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  1 in total

1.  Turbidity in Combined Sewer Sewage: An Identification of Stormwater Detention Tanks.

Authors:  Yang Liu; Liangang Hou; Wei Bian; Banglei Zhou; Dongbo Liang; Jun Li
Journal:  Int J Environ Res Public Health       Date:  2020-04-28       Impact factor: 3.390

  1 in total

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