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Article Dans Une Revue Science of the Total Environment Année : 2018

Online monitoring and conditional regression tree test: Useful tools for a better understanding of combined sewer network behavior.

Résumé

A good knowledge of the dynamic of pollutant concn. and flux in a combined sewer network is necessary when considering solns. to limit the pollutants discharged by combined sewer overflow (CSO) into receiving water during wet weather. Identification of the parameters that influence pollutant concn. and flux is important. Nevertheless, few studies have obtained satisfactory results for the identification of these parameters using statistical tools. Thus, this work uses a large database of rain events (116 over one year) obtained via continuous measurement of rainfall, discharge flow and COD (COD) estd. using online turbidity for the identification of these parameters. We carried out a statistical study of the parameters influencing the max. COD concn., the discharge flow and the discharge COD flux. In this study a new test was used that has never been used in this field: the conditional regression tree test. We have demonstrated that the antecedent dry weather period, the rain event av. intensity and the flow before the event are the three main factors influencing the max. COD concn. during a rainfall event. Regarding the discharge flow, it is mainly influenced by the overall rainfall height but not by the max. rainfall intensity. Finally, COD discharge flux is influenced by the discharge vol. and the max. COD concn. Regression trees seem much more appropriate than common tests like PCA and PLS for this type of study as they take into account the thresholds and cumulative effects of various parameters as a function of the target variable. These results could help to improve sewer and CSO management in order to decrease the discharge of pollutants into receiving waters.
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Dates et versions

hal-01689446 , version 1 (22-01-2018)

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Thomas Bersinger, Gilles Bareille, Thierry Pigot, Noëlle Bru, Isabelle Le Hécho. Online monitoring and conditional regression tree test: Useful tools for a better understanding of combined sewer network behavior.. Science of the Total Environment, 2018, 625, pp.336-343. ⟨10.1016/j.scitotenv.2017.12.239⟩. ⟨hal-01689446⟩
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