TY - JOUR
T1 - The evaluation of rainfall influence on combined sewer overflows characteristics
T2 - The Berlin case study
AU - Sandoval, S.
AU - Torres, A.
AU - Pawlowsky-Reusing, E.
AU - Riechel, M.
AU - Caradot, N.
PY - 2013
Y1 - 2013
N2 - The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSOs), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of partial least squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main in fluences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutant concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutant loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R2 < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.
AB - The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSOs), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of partial least squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main in fluences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutant concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutant loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R2 < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.
KW - CSO
KW - Canonical correlation
KW - Online monitoring
KW - Partial least squares regression
KW - UV-Vis spectrometry
UR - http://www.scopus.com/inward/record.url?scp=84892744769&partnerID=8YFLogxK
U2 - 10.2166/wst.2013.524
DO - 10.2166/wst.2013.524
M3 - Article
C2 - 24355858
AN - SCOPUS:84892744769
SN - 0273-1223
VL - 68
SP - 2683
EP - 2690
JO - Water Science and Technology
JF - Water Science and Technology
IS - 12
ER -