Geneviève Pelletier

Global optimal real-time control of the Quebec urban drainage system

Abstract A global optimal control (GOC) system was implemented in 1999 on the Quebec Urban Communitys (QUC) Westerly sewer network to manage flows and water levels in real-time in order to, among others, reduce the frequency and volumes of combined sewer overflows discharged into the St. Charles River and St. Lawrence River. This paper presents some of the salient results of the first three years of operation. The configuration of the GOC system is discussed and operational observations are made about the reliability of some of the major components. Furthermore, an economical analysis presents how cost-effective the real-time control system is for the QUC.

Gauging Rivers during All Seasons Using the Q2D Velocity Index Method

This paper presents a new model (Q2D) for the velocity distribution in a channel cross section for use in estimating discharge. It describes the model and its theoretical basis and presents the results of a case study. The distribution is determined by combining the principle of maximum entropy with a probability distribution obtained by the solution of the Poisson equation over the cross section. The model uses observed depth and velocity in the water column, where an acoustic Doppler current profiler is installed to determine three key flow parameters to obtain velocity and discharge. In addition, if supporting field discharge measurements are available, the model can be further calibrated to account for any asymmetry in the flow. If velocity distribution data exist for the entire cross section, the model can be adjusted to stretch the predicted velocity pattern to better conform to experimental observations. When applied to the Châteauguay River, Quebec, for both ice covered and open water, Q2D predict...

Characterization of the potential impact of retention tank emptying on wastewater primary treatment: a new element for CSO management.

Theoretical studies have shown that discharges from retention tanks could have a negative impact on the WWTPs (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.

Characterization of 1-h rainfall temporal patterns using a Kohonen neural network: a Quebec City case study

After only a few years of operation, an extensive rain gauge network provides fruitful information on temporal patterns of local storms, helping urban water, managers with in the difficult choice of appropriate design storms. A total of 1470 1-h storms were identified for the period 1999–2005 in Quebec City based on rainfall depth and interevent time criteria. Taking advantage of a clustering technique, the Kohonen neural network, 1-h storms were divided into 16 clusters depending on similarities in their temporal patterns, and then lumped into four groups. The database revealed that about one-third of all storms have a uniform intensity, one-third are early-peaking, and one-third are either symmetrical or late-peaking. Early-peaking patterns include the highest maximal 5-min intensity: 0.22–0.30 of the rainfall depth range, therefore in the same range as common Canadian 10-year design storms.

Behavior of non-regulated disinfection by-products in water following multiple chlorination points during treatment.

In this study, the behavior of regulated (trihalomethanes-THMs, haloacetic acids-HAAs) and non-regulated (haloacetonitriles-HANs, haloketones-HKs, chloropicrin-CPK) disinfection by-products (DBPs) was investigated during treatment and distribution in a municipal drinking water system that adds chlorine at multiple points within the water treatment plant (WTP). Three to eight locations in the WTP and four locations in the distribution network were sampled weekly for DBP measurements during the warmest period of the year. The results show that most DBPs found in the study area are formed during treatment, not distribution. However, the DBP species studied behave differently during treatment and distribution. Moreover, the location where DBP concentration is the highest in the distribution network differs among species of the same family, especially HAAs and HKs, and between the sampling campaigns. As a result, the relevance of using the sum of the concentrations of the species of the same DBP family to select sampling sites for DBP monitoring is questionable. This study illustrates the difficulties that drinking water supply managers must face to control and monitor the presence of DBPs.

Reliability and Robustness in Real-Time Control Applications

The risk of flooding due to measurement errors, equipment and software defaults or power failures is the highest priority of wet-weather management of collection systems. It is consequently not surprising that safety and reliability issues are raised when looking at the automatic control of sewer networks for better CSO control. If not properly designed, a Real Time Control (RTC) strategy can initiate actions that threaten public safety by causing flooding and structural damages in the absence of quality measurements. For this reason, it is mandatory that all RTC schemes implemented guarantee robust and safe management for all possible degraded situations including the worst case scenario that can happen. The concept of reliability can be largely associated with system performance and especially the difference between the measured performances and those expected. Therefore, one way of guaranteeing system reliability consists in implementing a system for which degraded modes are the exception rather than the rule. To reach such an objective, reliable sensors, actuators, radios, gates, pumps recognized in the industry for their robustness and long life expectancy should be purchased. Equipment redundancy can also be used to improve the reliability of the system. Specifically, two or three water level sensors can be used at strategic locations to guarantee that a valid measurement level will always be available at these sites. Equipment redundancy enables to define data validation procedures and, therefore, to improve the quality of the information process to the decision-making system. Consequently, less uncertainties are introduced in the control strategy and better system performance can be achieved. The telecommunication architecture can also be designed to minimize the frequency of degraded situations due to breakdowns in communications. To achieve this goal, different communication mediums and multiple communication channels can be implemented. Therefore, if a communication link is lost, other channels can be used to process the information between the local control points and the central station. During degraded situations, system reliability must be guaranteed by the implementation of degraded control modes. For maximal performance, each control station will have its own set of degraded management modes in relation to the communication status and the configuration of the station. All degraded modes will be specifically designed to guarantee the protection of the citizen and of the sewer network while achieving the best possible management performance considering available information. The degraded modes will be characterized in terms of the anomaly itemized.

Relationships between DBP concentrations and differential UV absorbance in full-scale conditions

Differential UV spectroscopy, defined as the difference in UV absorbance spectra before and after chlorination, has shown great potential to predict disinfection by-product (DBP) concentrations at laboratory scale. However, so far, no results have been reported on the full scale application of differential UV spectroscopy in drinking water treatment facilities. The objectives of this study are to determine if relationships can be developed between differential UV absorbance and DBP concentrations, for both regulated and unregulated DBPs, in a full-scale facility and to determine if these relationships vary throughout the year with variations in raw water quality and treatment conditions. The results show that linear and power relationships between differential UV absorbance and DBP concentrations can be developed (0.62 ≤ R2 ≤ 0.99), although differences between relationships obtained in lab- and full-scale conditions need further investigation. Finally, the relationships obtained are different from one sampling campaign to another, which raises the question of whether it is possible to determine relationships that are stable enough to be used as adequate feedback on DBP concentrations.

Optimization methods applied to stormwater management problems: a review

Abstract Stormwater management essentially aims at controlling the surface runoff to reduce water pollution and restore ecosystem integrity. This paper reviews and discusses several optimization problems associated with this field. Different features of such problems were identified to provide a classified investigation of the literature in terms of control approach, performance criteria, stormwater management approach, and uncertainty consideration. Having evaluated the relevant literature based on these factors, the knowledge gaps were extracted. We have noticed that there is an upward trend towards sustainable management of stormwater systems to deal with climate change. Despite this progress, there are still many areas to further develop stormwater management models, many of which relate to uncertainty identification, system-level real-time control, and the proper formulation of multi-objective optimization models. Hence, integration of different criteria in optimization models, and also the study of design vs. operation of stormwater management systems are proposed as further studies.

Conceptual Framework for Integrating Real-Time Control and Source Control Solutions for CSO Frequency Control

Combined sewer overflows (CSO) are associated with water quality degradation and health risks, but limited knowledge exists on the optimal solutions applicable to reach maximal overflow frequency targets as specified by some regulatory agencies. This study assesses the potential benefit of integrating source control with real-time control solutions based on hydrological/hydraulic modelling of urban catchments of the Province of Quebec (Canada). Firstly, modelling procedures for volume sizing of CSO solutions are improved by determining the proper rainfall input among the three most common types of rainfall data (continuous simulation, historical rainstorms and IDF-derived storms) excluding winter months in the analysis to be aligned with Quebec legislation. Secondly, a methodological framework is developed to integrate source control and optimal real-time control solutions based on a cost-efficiency performance objective. Thirdly, two optimization software are coupled to iteratively solve for the best flow management strategy according to physical and operating constraints; iPOP for source control design and CSoft for dynamic control. Preliminary results showed that simulation of continuous rainfall series results in the most accurate volume estimations for sizing CSO solutions and IDF-derived design storms could serve as input data for initial optimization runs. Based on the determined appropriate rainfall data, source control optimization showed considerable solutions implementation cost reduction for acceptable runoff reduction. Future work includes refining the integrated solution framework and comparative analysis of modelling results under optimal implementation of source control and real-time control solutions.

Optimizing disinfection by-product monitoring points in a distribution system using cluster analysis

Trihalomethanes (THMs) and Haloacetic Acids (HAAs) are the main groups detected in drinking water and are consequently strictly regulated. However, the increasing quantity of data for disinfection byproducts (DBPs) produced from research projects and regulatory programs remains largely unexploited, despite a great potential for its use in optimizing drinking water quality monitoring to meet specific objectives. In this work, we developed a procedure to optimize locations and periods for DBPs monitoring based on a set of monitoring scenarios using the cluster analysis technique. The optimization procedure used a robust set of spatio-temporal monitoring results on DBPs (THMs and HAAs) generated from intensive sampling campaigns conducted in a residential sector of a water distribution system. Results shows that cluster analysis allows for the classification of water quality in different groups of THMs and HAAs according to their similarities, and the identification of locations presenting water quality concerns. By using cluster analysis with different monitoring objectives, this work provides a set of monitoring solutions and a comparison between various monitoring scenarios for decision-making purposes. Finally, it was demonstrated that the data from intensive monitoring of free chlorine residual and water temperature as DBP proxy parameters, when processed using cluster analysis, could also help identify the optimal sampling points and periods for regulatory THMs and HAAs monitoring.