[HTML][HTML] Classifying pollutant flush signals in stormwater using functional data analysis on TSS MV curves

DMR Jensen, S Sandoval, JB Aubin… - Water Research, 2022 - Elsevier
DMR Jensen, S Sandoval, JB Aubin, JL Bertrand-Krajewski, L Xuyong, PS Mikkelsen
Water Research, 2022Elsevier
Pollution levels in stormwater vary significantly during rain events, with pollutant flushes
carrying a major fraction of an event pollutant load in a short period. Understanding these
flushes is thus essential for stormwater management. However, current studies mainly focus
on describing the first flush or are limited by predetermined flush categories. This study
provides a new perspective on the topic by applying data-driven approaches to categorise
Mass Volume (MV) curves for TSS into distinct classes of flush tailored to specific monitoring …
Abstract
Pollution levels in stormwater vary significantly during rain events, with pollutant flushes carrying a major fraction of an event pollutant load in a short period. Understanding these flushes is thus essential for stormwater management. However, current studies mainly focus on describing the first flush or are limited by predetermined flush categories. This study provides a new perspective on the topic by applying data-driven approaches to categorise Mass Volume (MV) curves for TSS into distinct classes of flush tailored to specific monitoring location. Functional Data Analysis (FDA) was used to investigate the dynamics of MV curves in two large data sets, consisting of 343 measured events and 915 modelled events, respectively. Potential links between classes of MV curves and combinations of rain characteristics were explored through a priori clustering. This yielded correct class assignments for 23-63% of the events using different combinations of MV curve clustering and rainfall characteristics. This suggests that while global rainfall characteristics influence flush, they are not sufficient as sole explanatory variables of different flush phenomena, and additional explanatory variables are needed to assign MV curves into classes with a predictive power that is suitable for e.g. design of stormwater control measures. Our results highlight the great potential of the FDA methodology as a new approach for classifying, describing, and understanding pollutant flush signals in stormwater.
Elsevier
以上显示的是最相近的搜索结果。 查看全部搜索结果

Google学术搜索按钮

example.edu/paper.pdf
查找
获取 PDF 文件
引用
References