UV/Vis spectrometers are powerful tools for online monitoring of wastewater constituents and processes. However, most studies only focus on typical parameters such as chemical oxygen demand (COD) and total suspended solids. This work presents a multi-parameter approach for calibration of a UV/Vis spectrometer for online monitoring of sewer systems. Parameters studied include soluble and total COD, nitrate, ammonium, sulphate and orthophosphate, as well as total dissolved sulphide, bisulphide and hydrogen sulphide, because they are one of the main causes for odour and corrosion in sewer systems. Two calibration methods are compared: multiple linear regression included in the manufacturer's software, and partial least square (PLS) computed using the pls package of the R library. Performance of the methods is evaluated for calibration and validation data sets employing four different criteria: relative root mean square error (RMSErel), RMSE-observations standard deviation ratio, Nash-Sutcliffe efficiency and percentage bias. A method-parameter dependency was revealed during the calibration phase but, when predicting new data, the PLS method showed higher robustness for almost all parameters. Both methods were able to predict concentration trends associated with sewer processes, some of which are strongly correlated to the sulphide species.