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Theoretical studies have shown that discharges from retention tanks could have a negative impact on the WWTP's (Wastewater Treatment Plant) effluent. Characterization of such discharges is necessary to better understand these impacts. This study aims at: (1) characterizing water quality during emptying of a tank; and (2) characterizing the temporal variation of settling velocities of the waters released to the WWTP. Two full-scale sampling campaigns (18 rain events) have been realized in Quebec City and laboratory analyses have shown a wide variability of total suspended solids (TSS) and Chemical Oxygen Demand (COD) concentrations in the water released from the tank. Suspended solids seem to settle quickly because they are only found in large amounts during the first 15 min of pumping to the WWTP. These solids are hypothesized to come from the pumping in which solids remained after a previous event. When these solids are evacuated, low TSS containing waters are pumped from the retention tank. A second concentration peak occurs at the end of the emptying period when the tank is cleaned with wash water. Finally, settling velocity studies allowed characterizing combined sewer wastewaters by separating three main fractions of pollutants which correspond to the beginning, middle and end of emptying. In most cases, it is noticed that particle settling velocities increase as the pollutant load increases. [ABSTRACT FROM AUTHOR]

In the Saint-Charles River watershed, it is necessary to better manage water from both a qualitative and quantitative point of view. Hydrological modelling can help managers in their decision making regarding water. This work concerns the implementation of the semi-distributed water quality model soil and water assessment tool (SWAT) for the simulation of stream flows in this urbanized and relatively mountainous watershed. This first approach is compared with two others, one relying on the use of the GR4J global hydrological model, and the other relying on the use of an artificial neural network. The amount of water resulting from the melting of snow, here calculated by SWAT’s snowmelt algorithm, has been provided to the models used in these other two approaches. The watershed offers an important challenge to hydrologists because of the scarcity of its database, namely the quasi absence of spatial information on precipitation and the absence of detailed pedological studies. Results show that the hydrological performance resulting from all three approaches is limited by the availability of data, but the performance of the approach using SWAT is more so than the other two. The lack of information hinders exploiting the full modelling capability of SWAT. Moreover, SWAT’s complexity turns out to be disadvantageous when compared with the simpler model structures of GR4J and of the neural network. It thus appears essential, considering the Saint-Charles River watershed’s strategic importance for water supply and touristic and recreational activities, that more effort should be spent in gaining climatological and pedological observations within the watershed. [ABSTRACT FROM AUTHOR]