Analysis, design, and maintenance of isolation valves in water distribution networks: State of the art review, insights from field experiences and future directions.

Isolation valves play a primary role in water distribution networks as their operation enables isolating the part of the network undergoing planned or extraordinary maintenance, in the context of rehabilitation or pipe break repairs, respectively. This paper presents a review of the current state of the art of isolation valves, with a focus on the problems of analysis, e.g., assessment of the performance of the network in segment isolation scenarios, design of optimal valve locations, and selection criteria/methods for identification of the valves to maintain. After describing and classifying the main scientific contributions, the paper proceeds by reporting the results of a survey to water utility staff in the United States, Italy, Portugal, and Iran, aimed at analysing the current practices adopted for the positioning and maintenance of isolation valves in real case studies. The paper ends with a discussion on the analysis of scientific literature and results of on-field surveys, highlighting critical points for potential future developments, including the connection between the design and maintenance of isolation valves, the trade-off between increasing validity and reducing complexity of reliability assessment methods, and more precise modeling of isolation valves systems.

New optimization strategies for SWMM modeling of stormwater quality applications in urban area.

Build-up/wash-off models were originally developed for small-scale laboratory facilities with uniform properties. The effective translation of these models to catchment scale necessitates the meticulous calibration of model parameters. The present study combines the Mat-SWMM tool with a genetic algorithm (GA) to improve the calibration of build-up and wash-off parameters. For this purpose, Mat-SWMM was modified to equip it with the capacity to provide comprehensive water quality analysis outcomes. Additionally, this research also conducts a comparative examination of two distinct types of objective functions in the optimization. Rather than depending on previous literature, this study undertook a numerical campaign to ascertain an appropriate range for the relevant parameters within the case study, thereby ensuring the optimization algorithm's efficient functionality. This research also implements an integrated event calibration approach, i.e., a novel method that calibrates all rainfall events collectively, thus improving systemic interaction representation and model robustness. The findings indicate that employing this methodology significantly enhances the reliability of the outcomes, thereby establishing a more robust procedure. The first objective function (TSS instantaneous less squared difference function, OF 1), which is widely employed in the literature, was designed to minimize the difference between observed and predicted instantaneous Total Suspended Solids (TSS) concentrations. In contrast, the second function (mass and mass peak consistency function, OF 2) considers integral model outputs, i.e., the overall mass balance, the time of the peak mass flow rate, and its intensity. The analysis of the outputs revealed that both objective functions demonstrated sufficient performance. OF 1 provided slightly better performance in predicting the TSS concentrations, whereas OF 2 demonstrated superior ability in capturing global event characteristics. Notably, the optimal parameter set identified through OF 2 aligned with the physically plausible ranges traditionally recommended in technical manuals for urban catchments. In contrast, OF 1's optimal set necessitated an expansion in the acceptable parameter ranges. Finally, from a computational burden viewpoint, OF 1 demanded a significantly higher number of function evaluations, thus implying an escalating computational cost as the range expands. Conversely, OF 2 necessitated fewer evaluations to converge toward the optimal solution.

Water quality modeling in sewer networks: Review and future research directions.

Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs. Given the proliferation of different water quality models and the promise they have shown, it is timely to assess the state-of-the-art in this field, to identify potential challenges and suggest future research directions. In this review, model types, modeled quality parameters, modeling purpose, data availability, type of case studies and model performance evaluation are critically analyzed and discussed based on a review of 110 papers published between 2010 and 2019. The review identified that applications of empirical and kinetic models dominate those of data-driven models for addressing water quality issues. The majority of models are developed for prediction and process understanding using experimental or field sampled data. While many models have been applied to real problems, the corresponding prediction accuracies are overall moderate or, in some cases, low, especially when dealing with larger SNs. The review also identified the most common issues associated with water quality modeling of SNs and based on these proposed several future research directions. These include the identification of appropriate data resolutions for the development of different SN models, the need and opportunity to develop hybrid SN models and the improvement of SN model transferability.

Comparison of topological, empirical and optimization-based approaches for locating quality detection points in water distribution networks.

The positioning of quality detection points as well as the frequency of sampling is a crucial aspect for the implementation of Water Safety Plans (WSPs), which have been proposed worldwide to ensure water quality and to minimize the risk from contamination in water distribution networks (WDNs). In this regard, some international legislations and best practices about quality of drinking water suggest very fine sampling frequencies, but they do not specify where the detection points should be located in a WDN. In this paper, three different approaches, based on empiricism, optimization and topology, respectively, were applied to locate detection quality points in a WDN. The comparison highlighted that empirical approach commonly adopted by water utility practitioners is unsatisfactory. The optimization-based approach, although performing significantly better, is difficult to apply, since it requires a calibrated hydraulic model. The topological approach, based on the use of the betweenness centrality and not requiring any hydraulic information and simulation, proves to be effective, and it can be easily adopted by water utilities to identify the location for quality detection points, due to its simplicity compared with the optimization-based approach.

A model for non-uniform sediment transport induced by flushing in sewer channels.

A novel unsteady flow numerical model for the simulation of the transport of non-uniform non-cohesive sediment mixtures (SM) during flushing operation in sewers is presented in this paper. The model was applied to the case of a flush experimental test that was recently carried out in a combined sewer channel of the sewer system of Paris city that exhibits depositional problems due to relatively coarse sediments. The model output was compared to the results of the field experiments as well as to those obtained with a model for the transport of uniform sediments (US). The model for SM provided a reliable interpretation of the selective transport of the sediments deposited in the channel bed as induced by the flush. The comparison showed the model for SM to provide an enhanced description of the erosional effects of the flush on the deposits, including improved evaluation of the volume of sediments flushed out of the experimental channel in the field.

Testing an innovative first flush identification methodology against field data from an Italian catchment.

This paper studies in depth the first flush concept with the aim of exploiting the potential of this phenomenon for an effective and economical implementation of stormwater quality control practices. A quantitative first flush methodology recently proposed in the scientific literature is applied to discrete water quality data of different pollution parameters from an Italian database. The methodology is rigorous and effective for characterising the dynamics of different pollutant types in wet-weather runoff, allowing an assessment of the first flush strength and the detection of the runoff volume required to reduce concentrations to background levels peculiar of the catchment. A strong reduction in concentration is attained after 3 mm runoff, but the achievement of background levels for all pollutant parameters requires the transit of 6 mm runoff. Sensitivity analysis shows the crucial role of the event selection criteria for enhancing the robustness of the methodology. The advantages of the adopted procedure are also highlighted by comparison with the widely used Mass First Flush Ratio method. The results are also compared with Italian guidelines for the design of stormwater quality control measures, pointing out the fruitfulness and profitability of the methodology for decision making in this context.