Assessment of stormwater and snowmelt quality based on water management priorities and the consequent water quality parameters

Sammanfattning: Stormwater and snowmelt pollution contributes to degradation of quality of the receiving waters. For assessing such impacts, it is effective to focus on specific causes of degradation, as done in this study of the quality of stormwater and snowmelt discharges into the receiving waters serving for supply of raw drinking water and water-based recreation. While the main priority were faecal indicator bacteria (FIBs), the understanding of their occurrence, and of other potential effects on the receiving waters, required addressing additional water quality parameters as well.     Exports of FIBs in stormwater and snowmelt discharged from four urban catchments yielded the following findings: (a) E.coli, with mean concentration of all stormwater data Cmean = 430 cfu (colony forming units)/100 mL, and enterococci (Cmean=1380 cfu/100 mL) were the best indicators of faecal pollution of stormwater, but total coliform (Cmean=3130 cfu/100 mL) and C. perfringens (Cmean=150 cfu/100 mL) were much less effective: the former indicator includes non-faecal bacteria and the latter one barely varied; (b) Among the different catchments, the central catchment with mixed land use produced the highest concentrations of FIBs; (c) FIB concentrations in snowmelt were significant only in the case of enterococci (400 cfu/100 mL); and, (d) Baseflows in two catchments were practically devoid of FIBs, with Cmean=10 cfu/100 mL for both E.coli and enterococci. Hence, there were no contributions of sanitary sewage to the storm sewer baseflows.FIB concentrations varied with stormwater or snowmelt quality, described by associated parameters, which were identified by cluster analysis as: temperature, conductivity, TSS, flow rate, and TP. Such findings were used in statistical regressions indicating that E. coli and enterococci could be statistically modelled in three of the four catchments, with determination coefficients R2 ranging from 38-66%. In spite of uncertainties, such modelling would be useful for future FIB monitoring, or for comparing remediation alternatives. Estimation of FIBs by microbial partitioning to settleable solids (represented by gully pot sediments) was infeasible, because these highly mineral sediments contained little FIBs.Storm sewer outfall effluents were also analyzed for mineral (Al, Ca, Fe, K, Mg, Na) and anthropogenic indicator trace metal (TM) inorganics (Cd, Cr, Cu, Ni, Pb, Zn). The total mass of inorganics exported from the catchments by runoff or snowmelt was dominated by mineral inorganics, which were particularly high in baseflows. TM concentrations were compared to the tentative guidance limits suggested in Sweden as annual mean, or maximum event mean, total TM concentrations. Effluents from the catchments studied clearly exceeded the recommended values 5 times in the case of Zn.Field studies drew attention to uncertainties in measured FIBs and solids. Automated sampling of greatly varying FIB concentrations was affected by sampling line water residuals, which can be minimized by short sampling lines and avoidance of sags in the sampling line. Stormwater and snowmelt solids were underestimated by the conventional TSS method requiring withdrawal of aliquots from total samples. This bias can be eliminated by using whole-sample methods; either the existing SSC (suspended sediment concentration) method, or the newly proposed (and easier to use) multiple filter procedure (MFP), filtering whole samples through progressively finer filters (pore sizes 25, 1.6 and 0.45 µm). The MFP produced data equivalent to those obtained with SSC, as confirmed by the Limits of Agreement (LoA) statistical procedure.