Copula-based frequency analysis of overflow and flooding in urban drainage systems

Copyright © 2014 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Hydrology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Hydrology (2014), DOI: 10.1016/j.jhydrol.2013.12.006The performance evaluation of urban drainage systems is essentially based on accurate characterisation of rainfall events, where a particular challenge is development of the joint distributions of dependent rainfall variables such as duration and depth. In this study, the copula method is used to separate the dependence structure of rainfall variables from their marginal distributions and the different impacts of dependence structure and marginal distributions on system performance are analysed. Three one-parameter Archimedean copulas, including Clayton, Gumbel, and Frank families, are fitted and compared for different combinations of marginal distributions that cannot be rejected by statistical tests. The fitted copulas are used, through the Monte Carlo simulation method, to generate synthetic rainfall events for system performance analysis in terms of sewer flooding and Combined Sewer Overflow (CSO) discharges. The copula method is demonstrated using an urban drainage system in the UK, and the cumulative probability distributions of maximum flood depth at critical nodes and CSO discharge volume are calculated. The results obtained in this study highlight the importance of taking into account the dependence structure of rainfall variables in the context of urban drainage system evaluation and also reveal the different impacts of dependence structure and marginal distributions on the probabilities of sewer flooding and CSO volume. © 2013 Elsevier B.V

Frequency analysis of river water quality using integrated urban wastewater models

Copyright © IWA Publishing 2012.The definitive peer-reviewed and edited version of this article is published in Water Science and Technology Volume 65 Issue 12, pp. 2112–2117 (2012), DOI: 10.2166/wst.2012.127 and is available at www.iwapublishing.com.In recent years integrated models have been developed to simulate the entire urban wastewater system, including urban drainage systems, wastewater treatment plants, and receiving waterbodies. This paper uses such an integrated urban wastewater model to analyze the frequency of receiving water quality in an urban wastewater system with the aim of assessing the overall system performance during rainfall events. The receiving water quality is represented by two indicators: event mean dissolved oxygen (DO) concentration and event mean ammonium concentration. The compliance probability of the water quality indicators satisfying a specific threshold is used to represent the system performance, and is derived using the rainfall events from a series of 10 years' rainfall data. A strong correlation between the depth of each rainfall event and the associated volume of combined sewer overflow (CSO) discharges is revealed for the case study catchment, while there is a low correlation between the intensity/duration of the rainfall event and the volume of the CSO discharges. The frequency analysis results obtained suggest that the event mean DO and ammonium concentrations have very different characteristics in terms of compliance probabilities at two discharging points for CSO and wastewater treatment plant effluent, respectively. In general, the simulation results provide an understanding of the performance of the integrated urban wastewater system and can provide useful information to support water quality management

Cost-efficient control of wastewater treatment plants to reduce greenhouse gas emissions

IWA World Water Congress and Exhibition, Lisbon, Portugal, 21-26 September 2014This research investigates the potential of improved wastewater treatment plant control for the cost-efficient reduction of greenhouse gas (GHG) emissions, providing a detailed exploration of the decision variable search space. Key operational parameters identified using global sensitivity analysis are sampled to provide sets of values for testing in two pre-defined control strategies. It is shown that significant reductions in emissions and costs can be realized by improved selection of parameter values. The importance of considering GHGs when selecting a control strategy is also highlighted, as the two strategies tested are shown to produce effluent of a similar quality but with significantly different emissions and operating costs

Identifying sensitive sources and key control handles for the reduction of greenhouse gas emissions from wastewater treatment

Copyright © 2014 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Water Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Water Research Vol. 62 (2014), DOI: 10.1016/j.watres.2014.06.002This research investigates the effects of adjusting control handle values on greenhouse gas emissions from wastewater treatment, and reveals critical control handles and sensitive emission sources for control through the combined use of local and global sensitivity analysis methods. The direction of change in emissions, effluent quality and operational cost resulting from variation of control handles individually is determined using one factor-at-a-time sensitivity analysis, and corresponding trade-offs are identified. The contribution of each control handle to variance in model outputs, taking into account the effects of interactions, is then explored using a variance-based sensitivity analysis method, i.e., Sobol's method, and significant second order interactions are discovered. This knowledge will assist future control strategy development and aid an efficient design and optimisation process, as it provides a better understanding of the effects of control handles on key performance indicators and identifies those for which dynamic control has the greatest potential benefits. Sources with the greatest variance in emissions, and therefore the greatest need to monitor, are also identified. It is found that variance in total emissions is predominantly due to changes in direct N2O emissions and selection of suitable values for wastage flow rate and aeration intensity in the final activated sludge reactor is of key importance. To improve effluent quality, costs and/or emissions, it is necessary to consider the effects of adjusting multiple control handles simultaneously and determine the optimum trade-off

Does carbon reduction increase sustainability? A study in wastewater treatment

This is the author accepted manuscript. The final version is available from Elsevier as an open access article via the DOI in this record.This study investigates the relationships between carbon reduction and sustainability in the context of wastewater treatment, focussing on the impacts of control adjustments, and demonstrates that reducing energy use and/or increasing energy recovery to reduce net energy can be detrimental to sustainability. Factorial sampling is used to derive 315 control options, containing two different control strategies and a range of sludge wastage flow rates and dissolved oxygen setpoints, for evaluation. For each, sustainability indicators including operational costs, net energy and multiple environmental performance measures are calculated. This enables identification of trade-offs between different components of sustainability which must be considered before implementing energy reduction measures. In particular, it is found that the impacts of energy reduction measures on sludge production and nitrogen removal must be considered, as these are worsened in the lowest energy solutions. It also demonstrates that a sufficiently large range of indicators need to be assessed to capture trade-offs present within the environmental component of sustainability. This is because no solutions provided a move towards sustainability with respect to every indicator. Lastly, it is highlighted that improving the energy balance (as may be considered an approach to achieving carbon reduction) is not a reliable means of reducing total greenhouse gas emissions.Thanks are given for the Matlab/Simulink implementation of the BSM2G from the Department of Industrial Engineering and Automation, Lund University, Lund, Sweden. This work forms part of a 5-year fellowship for the last author funded by the UK Engineering & Physical Sciences Research Council (EP/K006924/1)

Multiobjective optimisation of urban wastewater systems using ParEGO: a comparison with NSGA II

Commercial and research-based simulation models are now available to represent the performance and control of the sewer network, wastewater treatment plant and receiving water as a whole. To improve overall system performance, these models can be combined with optimisation methods to derive optimal control strategies. The popular evolutionary algorithms (EAs) have been proven to be a powerful method in developing optimal control strategies; however, the high computational requirements of these methods impose a limit on their application due to the complexity of the system. This paper explores the potential of a surrogate based multi-objective optimisation method, ParEGO, for real time control of urban wastewater systems. An existing integrated model is used to evaluate the multiple objectives. This method is compared with NSGA II by using two performance indicators: the hypervolume indicator and the additive binary ε ε-indicator. Comparative results show that ParEGO is an efficient and effective method in deriving optimal control strategies for the multiple objective control problems. It is suggested that ParEGO can greatly improve the computational efficiency, particularly for complex systems

Use of surrogate modelling for multiobjective optimisation of urban wastewater systems

Copyright © IWA Publishing 2009. The definitive peer-reviewed and edited version of this article is published in Water Science and Technology Volume 60 Issue 6, pp. 1641–1647 (2009), DOI: 10.2166/wst.2009.508 and is available at www.iwapublishing.comSimulation models are now available to represent the sewer network, wastewater treatment plant and receiving water as an integrated system. These models can be combined with optimisation methods to improve overall system performance through optimal control. Evolutionary algorithms (EAs) have been proven to be a powerful method in developing optimal control strategies; however, the intensive computational requirement of these methods imposes a limit on their application. This paper explores the potential of surrogate modelling in multiobjective optimisation of urban wastewater systems with a limited number of model simulations. A surrogate based method, ParEGO, is combined with an integrated urban wastewater model to solve real time control problems. This method is compared with the popular NSGA II, by using performance indicators: the hypervolume indicator, additive binary epsilon-indicator and attainment surface. Comparative results show that ParEGO is an efficient and effective method in deriving optimal control strategies for multiple objective control problems with a small number of simulations. It is suggested that ParEGO can greatly improve computational efficiency in the multiobjective optimisation process, particularly for complex urban wastewater systems

Comparison of control strategies for multi-objective control of urban wastewater systems

In recent years much attention has been paid to integrated management and control of urban wastewater systems. With the application of integrated system modelling tools, overall system performance can be improved to a great extent in terms of receiving water quality, through development of optimal control strategies. Most studies to date, however, have used a single objective to demonstrate the potential benefits. Control of urban wastewater systems is actually a multiple objective optimisation problem, involving balancing different, possibly conflicting objectives required by stakeholders with different interests. This paper compares three different control strategies for multi-objective optimal control of the urban wastewater system, including one global control strategy and two integrated control strategies. A popular multiple objective evolutionary algorithm, NSGA II, is applied to derive the Pareto optimal solutions for the three strategies. The comparative results show the benefits of application of integrated control in achieving an improved system performance in terms of dissolved oxygen and ammonium concentrations in the receiving river. The simulation results also illustrate the effectiveness of NSGA II in deriving the optimal control strategies with different complexities