The estimation of stormwater pollutant concentrations is a primary requirement of integrated urban water management. In order to determine effective sampling strategies for estimating pollutant concentrations, data from extensive field measurements at seven different catchments was used. At all sites, 1-min resolution continuous flow measurements, as well as flow-weighted samples, were taken and analysed for total suspend solids (TSS), total nitrogen (TN) and Escherichia coli (E. coli). For each of these parameters, the data was used to calculate the Event Mean Concentrations (EMCs) for each event. The measured Site Mean Concentrations (SMCs) were taken as the volume-weighted average of these EMCs for each parameter, at each site. 17 different sampling strategies, including random and fixed strategies were tested to estimate SMCs, which were compared with the measured SMCs. The ratios of estimated/measured SMCs were further analysed to determine the most effective sampling strategies. Results indicate that the random sampling strategies were the most promising method in reproducing SMCs for TSS and TN, while some fixed sampling strategies were better for estimating the SMC of E. coli. The differences in taking one, two or three random samples were small (up to 20% for TSS, and 10% for TN and E. coli), indicating that there is little benefit in investing in collection of more than one sample per event if attempting to estimate the SMC through monitoring of multiple events. It was estimated that an average of 27 events across the studied catchments are needed for characterising SMCs of TSS with a 90% confidence interval (CI) width of 1.0, followed by E.coli (average 12 events) and TN (average 11 events). The coefficient of variation of pollutant concentrations was linearly and significantly correlated to the 90% confidence interval ratio of the estimated/measured SMCs (R² = 0.49; P < 0.01) as well as the number of events required to achieve certain accuracy, and hence could be a promising surrogate for determining the sampling frequency needed to accurately estimate SMCs of pollutants

An episode of microbiological contamination of the drinking water supply of the City of Östersund, Sweden (63°10′45″N; 14°38′09″E) prompted a study of fecal pollution in four storm drainage catchments discharging in the vicinity of the water treatment plant intake, with the overall aim of determining the presence and variation of standard fecal indicator bacteria strains and total suspended solids (TSS) in stormwater from urban catchments with specific land uses and sizes varying from 5 to 40 ha. Four bacteria strains used as indicators of fecal pollution in Sweden were studied: total coliforms, enterococci, Escherichia coli (E. coli) and Clostridium perfringens (C. perfringens). In dry weather, indicator bacteria concentrations in storm sewers conveying baseflow did not exceed 100  colony forming units (CFU)/100  mL 100  colony forming units (CFU)/100  mL, but during wet weather, total coliform and enterococci concentrations increased 10 2 102 to 10 3 103 times, compared to those in baseflow, and considerably less in the case of E. coli and C. perfringens. Bacteria concentrations differed significantly among the sampling sites and in the majority of events observed in the four catchments; higher bacteria concentrations were observed during the early phases of runoff. Only in one catchment, positive correlations were observed between TSS and total coliforms, E. coli, and enterococci, suggesting similar sources; in the remaining catchments, no such correlations were observed. The collected indicator bacteria data represent a useful addition to the available data on indicator bacteria in stormwater in cold-climate regions.

A comparative study of five methods measuring suspended sediment or solid concentrations in water–sediment mixtures indicated that, depending on the method used, broadly varying results can be obtained. For water–sediment mixtures containing sand size particles, the standard TSS method produced negatively biased results, accounting for 0 to 90% of the present solids; the negative bias directly depended on the magnitude of the sand fraction in the water–sediment mixture. The main reason for the differences between the TSS and the rest of the methods laid in the handling of samples; in the former methods, whole samples were analysed, whereas the TSS analysis was performed on sub-samples withdrawn from the water sample, the withdrawal process tending to exclude large particles. The methods using whole water–solid samples, rather than aliquots withdrawn from such samples, produced accurate estimates of solid concentrations, with a fairly good precision. Two whole-sample methods were studied in detail, a slightly modified standard SSC-B method and the newly proposed operational procedure referred to as the Multiple Filter Procedure (MFP), using three filters arranged in a series with decreasing pore sizes (25, 1.6 and 0.45 µm). Both methods assessed accurately concentrations of solids in a broad range of concentrations (200–8000 mg L−1) and particle sizes (0.063–4.0 mm). The newly introduced MFP was in good agreement with the SSC procedure, the differences between the two procedures not exceeding the standard bias defined for the SSC-B method. The precision of both SSC and MFP was generally better than ±10%. Consequently, these methods should be used when the total mass of transported solids is of interest.

A comparative study of five methods measuring suspended sediment or solid concentrations in water–sediment mixtures indicated that, depending on the method used, broadly varying results can be obtained. For water–sediment mixtures containing sand size particles, the standard TSS method produced negatively biased results, accounting for 0 to 90% of the present solids; the negative bias directly depended on the magnitude of the sand fraction in the water–sediment mixture. The main reason for the differences between the TSS and the rest of the methods laid in the handling of samples; in the former methods, whole samples were analysed, whereas the TSS analysis was performed on subsamples withdrawn from the water sample, the withdrawal process tending to exclude large particles. The methods using whole water–solid samples, rather than aliquots withdrawn from such samples, produced accurate estimates of solid concentrations, with a fairly good precision. Two whole-samplemethods were studied in detail, a slightly modified standard SSC-B method and the newly proposed operational procedure referred to as the Multiple Filter Procedure (MFP), using three filters arranged in a series with decreasing pore sizes (25, 1.6 and 0.45 mm). Both methods assessed accurately concentrations of solids in a broad range of concentrations (200–8000 mg L1) and particle sizes(0.063–4.0 mm). The newly introduced MFP was in good agreement with the SSC procedure, the differences between the two procedures not exceeding the standard bias defined for the SSC-B method. The precision of both SSC and MFP was generally better than 10%. Consequently, these methods should be used when the total mass of transported solids is of interest.

High-velocity runoff from snow deposit transports suspended grain-attached contaminants while underground snow storages trapped these contaminants within the storage. The aim here is to quantify pollutant masses from an urban snow deposit and to investigate the conditions when pollutant control was increased by turning a snow deposit into a snow cooling plant with permeable underground snow storage. Pollutant masses in an urban snow deposit in northern Sweden were: Cu = 67, Pb = 17, Zn = 160, P = 170, SS = 620, 000, Cl = 1, 200, N = 380 kg. A theoretical analysis showed that the fraction of surface runoff from a surface deposit largely depends on the hydraulic conductivity (K, m s-1) of the soil. For a melt rate of 30 mm, day-1, surface runoff would be about 97% for a soil with K = 10-8, while nonexistent for K>10-6. Similar soil conductivities are needed to ensure that all snow melt could be transported as groundwater from an underground storage. The largest pollution-control advantage with underground snow storage compared to a surface deposit would thus be that piping and filters for operation of the plant could be used to filter surface snow melt runoff before rejection

Flooding is one of the main concerns in seeking safe and sustainable urban areas. In many cases the design criteria are based on intense rainfall. It is, therefore, assumed that the peak flow in cities’ drainage systems is due to heavy and fast rainfalls. However snowmelt pattern could be more important for places with cold climate; therefore the need of a better snowmelt and runoff simulation becomes more important particularly when the effects of climate change needs to be considered. Two main methods are basically used for urban snowmelt simulation i.e. temperature index and energy budged methods. Studies done previously show that the energy balance method gives a better estimation for volume and time compare to the temperature index. For urban areas though, it is argued that the data demanding of the energy balance method can be a disadvantage and it could affect the model precision. However, the advances in geographical information systems (GIS) and the requirement for better time resolution than daily have increased the tendency of applying it for urban snow melt. There are couples of studies during recent years e.g. (Ho& Valeo 2005) applying energy budget method in urban areas, even though the efforts basically focused on developing routines and comparing it with the degree day method. There is still a gap in parameter sensitivity analysis especially with two main features of urban snowmelt modeling; firstly, the importance of input data along with difficulties in providing them; and secondly the classification of snow in urban areas based on snow properties. These two concerns were the motives to go one step ahead and to conduct a sensitivity analysis. The aim of the study is therefore to investigate the dependency of the simulation results to the different model parameters as built-in parameters and input data. Such analysis eventually can be used for snow classification which along with GIS technology can provide a reliable platform to simulate snowmelt over an urban catchment more precisely than what the current models are capable of today. Here in this study, a model namely Utah Energy Balance Snow Model (UEB) is used. The model uses a complete energy and mass balance routine to simulate snow accumulation and melt at a point scale. Except using the measured climatic values to run the model, the routines in this model has the capability of producing (simulating) solar radiation and albedo if the measured values are not available. The model has simulated the snow accumulation and melts in rural area with reasonable accuracy in previous studies i.e. (Tarboton et al. 1995). For this research, three snow deposits from 1991 and 1992 are taken to calibrate the model with. The pilot snow packs are identical to municipal snow deposit with density more than natural snow, around 700 Kg/m3. The snowmelt runoff has been measure between March and Jun 1991 and 1992. The necessary input values are collected from Meteorological and Hydrological Institute (SMHI) for the same periods. All input parameters are available on hourly and 3 hourly periods. The method is to run the model with real values collected from SMHI and calibrate it versus the measured data. The model is run using modified parameters to investigate the possible change in the simulation result. Eventually an analysis is done on each parameter and the dependency of the model. An analysis also is done by running the model with different time resolution, i.e. hourly, 3-hourly, and 6-hourly and to investigate the effect of time span in modeling snowmelt and simulation precision.

Various types of solids conveyed with rainfall and snowmelt runoff into receiving waters cause numerous environmental impacts, including reduced sunlight penetration, blanketing of fish spawning substrates, and transport of pollutants contributing to aquatic pollution. For the assessment of such impacts, it is important to measure solids concentrations in both runoff and snowmelt. In this study, accuracies of three analytical methods used to measure solids were assessed: (a) A TSS (total suspended solids) method, (b) Suspended sediment method (SSC-B), and (c) a multiple filter method (MFM). For rainfall runoff samples containing 90% of particles smaller than 5 μm, the MFM measurements produced concentrations significantly higher than those obtained with SSC-B and TSS methods, at a 95% confidence level. In the case of snowmelt runoff, the SSC-B and MFM methods yielded similar concentrations, which were 10-20% higher than those measured by the TSS method, and the coefficient of variation of repeated TSS readings was up to three times higher than that of the former methods. The results indicate the importance of choosing the “best” analytical method for assessing the operational and environmental impacts of solids conveyed by urban runoff and snowmelt.

The pathways and mass balance of selected pollutants, released during the snowmelt process, were investigated for urban bulk snow placed in small, intermediate, and large-scale lysimeters. The results showed that low percentages of TSS (total suspended solids) and heavy metal (Cu, Zn, Pb) loads contained in snow were transported with snowmelt, the rest remained in situ with the particulate residue. The TSS loads transported with snowmelt were 3, 3.4, and 4.8% of the initial TSS mass in the small, intermediate and large lysimeters, respectively. Particulate heavy metal loads transported with snowmelt, during the whole melting process, were measured in the intermediate lysimeter for copper and zinc, and for lead in the large lysimeter. The measured mass loads in snowmelt leaving the intermediate lysimeter were 7.5 and 7.2% for copper and zinc, respectively, and 1.7% for lead leaving the large lysimeter. The remainder of the loads stayed in situ with the particulate residue. The loads transported with snowmelt were independent of the initial TSS and metal concentrations in bulk snow. These findings have implications for siting and operating snow disposal facilities; most of the initial TSS and particulate heavy metal loads can be retained on site, rather than released with snowmelt into the receiving environments.

Water and pollutant release from a disturbed urban snowpack was studied in an experimental plot encompassing a road section and the adjacent grassed boulevard in the city of Lulea, in northern Sweden. Winter road maintenance in this area includes snow ploughing and applications of grit without any road salts. During the study period, 18 snowmelt events were observed. Compared to rural areas and urban areas with extensive use of chloride in winter road maintenance, in the former case, the observed snowmelt quality differed by relatively high and uniform pH (7.7-8.1) and, in the latter case, by low chloride event-mean-concentrations (EMCs) (5.7-123.4 mg/L) and conductivity (11.6-60.7 mS/m). Total suspended solids (TSS) EMCs greatly exceeded those reported for rural snowmelt and urban rainfall runoff and contributed to the high pH buffering capacity of deposited snow. Observed concentrations of total and dissolved heavy metals were compared to water quality guidelines that suggested a high likelihood of biological effects. Chloride was the only pollutant that indicated an early release and all other constituents showed a uniform release with snowmelt from the snowpack. The partitioning of heavy metals between total and dissolved phases indicated the highest dissolved fractions for Cu, followed by Cd, Ni and Zn, and the lowest values were observed for Pb. The urban snowmelt characteristics substantially differed from those reported for undisturbed sites with respect to higher pollutant loads, high pH buffering capacity and a general absence of early or delayed pollutant release from the snowpack

In this paper, a simple conceptual model is presented to describe the dynamics of total suspended solid (TSS) transport during snowmelt- and rainfall-induced road runoff from a small urban runoff plot in northern Sweden. The study period (28 March to 28 May 2000) included both snowmelt and rainfall. A temperature-index method is used to describe snowmelt and the accumulation and transport of TSS is described by a linear build-up function and a wash-off model. The model was verified through measurements taken from 22 March to 22 May 2001. The simulation results showed that the simple model concept was capable of describing the dynamics of road runoff and TSS well, based on the continuous course of events for the whole modelling period. However, if the model was used for simulating a snowmelt period, or single events during snowmelt, the model approach would be too simple.