Estimation of Storm Water Quality Characteristics and Overflow Loads from Treatment Plant Influent Data

1990 ◽  
Vol 22 (10-11) ◽  
pp. 77-85
Author(s):  
Roelof H. Aalderink
Keyword(s):  
Water Quality ◽  
Treatment Plant ◽  
Storm Water ◽  
Quality Data ◽  
Combined Sewer Overflows ◽  
Water Quality Data ◽  
Frequency Distributions ◽  
Simulation Techniques ◽  
Combined Sewer ◽  
In Series

A simple model, based on tanks in series, for the estimation of mean annual loads and frequency distributions of loads from combined sewer systems is presented. The input data, dry weather flow, dry weather quality, and storm water quality are estimated from treatment plant influent data. Two similar methods for the estimation of flow-average storm water quality were tested by using treatment plant influent data generated by the model in comparison with the model input. Both methods are based on daily mass balances, but differ slightly with respect to the averaging procedures used. The performance of both methods is about the same. They show a small bias, but the variability introduced is small when compared with the variation occurring in real storm water quality data. Application of one of the methods on field data revealed no distinct relationships between the flow-averaged storm water quality concentration and the dry weather period or the total daily rain depth. By combination of continuous and Monte Carlo simulation techniques the model can be used to estimate mean annual loads and frequency distribution of loads from combined sewer overflows. For the extreme events a large 90 % confidence interval was found due to the large variations in storm water quality.

Toxicity and pollutant impact analysis in an urban river due to combined sewer overflows loads

2010 ◽  
Vol 61 (1) ◽  
pp. 207-215 ◽  
Author(s):  
A. Casadio ◽  
M. Maglionico ◽  
A. Bolognesi ◽  
S. Artina
Keyword(s):  
Water Quality ◽  
Impact Analysis ◽  
Waste Water Treatment ◽  
Treatment Plant ◽  
Quality Data ◽  
Waste Water Treatment Plant ◽  
Combined Sewer Overflows ◽  
Water Quality Data ◽  
Combined Sewer ◽  
Sewer Overflows

The Navile Channel (Bologna, Italy) is an ancient artificial water course derived from the Reno river. It is the main receiving water body for the urban catchment of Bologna sewer systems and also for the Waste Water Treatment Plant (WWTP) main outlet. The aim of this work is to evaluate the Combined Sewer Overflows (CSOs) impact on Navile Channel's water quality. In order to collect Navile flow and water quality data in both dry and wet weather conditions, two measuring and sampling stations were installed, right upstream and downstream the WWTP outflow. The study shows that even in case of low intensity rain events, CSOs have a significant effect on both water quantity and quality, spilling a considerable amount of pollutants into the Navile Channel and presenting also acute toxicity effects. The collected data shown a good correlations between the concentrations of TSS and of chemical compounds analyzed, suggesting that the most part of such substances is attached to suspended solids. Resulting toxicity values are fairly high in both measuring points and seem to confirm synergistic interactions between heavy metals.

Long-Term Simulation of Pollutant Loads in Treatment Plant Effluents and Combined Sewer Overflows

1990 ◽  
Vol 22 (10-11) ◽  
pp. 69-76 ◽  
Author(s):  
A. Durchschlag
Keyword(s):  
Waste Water Treatment ◽  
Treatment Plant ◽  
Storm Water ◽  
Water Runoff ◽  
Storage Tanks ◽  
Combined Sewer Overflows ◽  
Storm Water Runoff ◽  
Combined Sewer ◽  
Hydraulic Load ◽  
Water Tanks

As a result of urbanization, the pollutant discharges from sources such as treatment plant effluents and polluted stormwaters are responsible for an unacceptable water quality in the receiving waters.In particular, combined sewer system overflows may produce great damage due to a shock effect. To reduce these combined sewer overflow discharges, the most frequently used method is to build stormwater storage tanks. During storm water runoff, the hydraulic load of waste water treatment plants increases with additional retention storage. This might decrease the treatment efficiency and thereby decrease the benefit of stormwater storage tanks. The dynamic dependence between transport, storage and treatment is usually not taken into account. This dependence must be accounted for when planning treatment plants and calculating storage capacities in order to minimize the total pollution load to the receiving waters. A numerical model will be described that enables the BOD discharges to be continuously calculated. The pollutant transport process within the networks and the purification process within the treatment plants are simulated. The results of the simulation illustrate; a statistical balance of the efficiency of stormwater tanks with the treatment plant capacity and to optimize the volume of storm water tanks and the operation of combined sewer systems and treatment plants.

An approach for determining the most critical among a suite of chemical contaminants at a drinking water intake

2013 ◽  
Vol 13 (3) ◽  
pp. 835-845
Author(s):  
Fei Chen ◽  
William B. Anderson ◽  
Peter M. Huck
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Water Intake ◽  
Treatment Plant ◽  
Quality Data ◽  
Exceedance Probability ◽  
Raw Water ◽  
Water Quality Data ◽  
Treatment Processes ◽  
Raw Water Quality

An integrated approach for the identification and assessment of the most critical chemical contaminant(s) at a drinking water intake has been developed. It involves the determination of a threshold or critical raw water concentration (CRWC) for target contaminants using the observed overall removal efficiency of a specific water treatment plant (WTP) and regulated drinking water concentrations for the target contaminants. The exceedance probability relative to the CRWC based on historical raw water quality monitoring data is then calculated. Finally, the integration of the raw water quality data and the overall efficiency of a particular WTP sequence allows for identification of the most critical contaminant(s) as well as an advance indication of which contaminants are most likely to challenge a plant. The proactive nature of this approach gives a utility the impetus and time to assess current treatment processes and potential alternatives. In addition, it was found that three- or four-parameter theoretical distributions are more appropriate than two-parameter probability distributions for the fitting of raw water quality data. This study reveals that the reliance on raw and/or treated water contaminant concentrations in isolation or on theoretical removals through treatment processes can, in some circumstances, be misguided.

Application of a Nonparametric Approach for Monitoring and Detecting Trends in Water Quality Data for the St

1986 ◽  
Vol 21 (2) ◽  
pp. 153-167 ◽  
Author(s):  
Michael D. Cailas ◽  
George Cavadias ◽  
Ronald Gehr
Keyword(s):  
Water Quality ◽  
Parametric Method ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Quality Data ◽  
Seasonal Adjustment ◽  
Positive Trend ◽  
Water Quality Data ◽  
Nonparametric Approach

Abstract To overcome some of the restrictions due to the irregular structure of water quality data, a nonparametric approach has been developed based on Kendall’s T and a seasonal adjustment model, which enables one to test for the significance of trends as well as to monitor the trend variations with time. This methodology has been applied to water quality data for the St. Lawrence river obtained from Environment Canada and the municipality of Varennes. The results from the first source indicate that a positive trend is developing for conductivity and pH downstream from the Island of Montreal, whereas upstream from the Island pH is the only parameter indicating a positive trend. Data from the municipality of Varennes, due to their excellent quality, were used to verify the validity of the previous results as well as the reliability of the applied methodology. Analysis of the Varennes data with a parametric method indicated that a positive trend in pH is indeed evident. This finding will be of consequence for future studies to ascertain the effect on the river of the new Montreal Urban Community Sewage Treatment Plant.

Advanced monitoring of water systems using in situ measurement stations: data validation and fault detection

2013 ◽  
Vol 68 (5) ◽  
pp. 1022-1030 ◽  
Author(s):  
Janelcy Alferes ◽  
Sovanna Tik ◽  
John Copp ◽  
Peter A. Vanrolleghem
Keyword(s):  
Water Quality ◽  
Treatment Plant ◽  
Principal Component ◽  
Quality Data ◽  
Water Quality Data ◽  
Data Set ◽  
Data Quality Assessment ◽  
Multiple Sensor ◽  
Pertinent Information

In situ continuous monitoring at high frequency is used to collect water quality information about water bodies. However, it is crucial that the collected data be evaluated and validated for the appropriate interpretation of the data so as to ensure that the monitoring programme is effective. Software tools for data quality assessment with a practical orientation are proposed. As water quality data often contain redundant information, multivariate methods can be used to detect correlations, pertinent information among variables and to identify multiple sensor faults. While principal component analysis can be used to reduce the dimensionality of the original variable data set, monitoring of some statistical metrics and their violation of confidence limits can be used to detect faulty or abnormal data and can help the user apply corrective action(s). The developed algorithms are illustrated with automated monitoring systems installed in an urban river and at the inlet of a wastewater treatment plant.

Updating the U.S. Nationwide Urban runoff quality data base

1999 ◽  
Vol 39 (12) ◽  
pp. 9-16 ◽  
Author(s):  
James T. Smullen ◽  
Amy L. Shallcross ◽  
Kelly A. Cave
Keyword(s):  
Water Quality ◽  
Data Base ◽  
Oxygen Demand ◽  
Urban Runoff ◽  
The United States ◽  
Geographic Region ◽  
Storm Water ◽  
Quality Data ◽  
Water Quality Data ◽  
Urban Stormwater Quality

Urban stormwater quality data collected over the past 20 years for several large government-sponsored sampling programs in the United States were assembled and analyzed to develop new nationwide estimators and statistics for urban storm water quality. We believe that this is the first attempt to assemble and analyze these major storm water quality data sets for this purpose. In this paper, the first public report of our work to-date, we present the results of the data acquisition, data base assembly, quality assurance, computation of new stormwater event mean concentrations and associated statistics, and comparisons with the original U.S. Environmental Protection Agency's Nationwide Urban Runoff Program (NURP) results. The differences between the pooled means and those estimated from our analysis of the NURP data range from a 79% lower estimate for Copper to a 36% higher estimate for Biochemical Oxygen Demand. It is concluded that the variations between the NURP results and those developed here from the pooling of the three national data bases are important and that future work may provide a basis for differentiating Event Mean Concentrations among urban land uses, geographic region and seasons.

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