- Email: [email protected]
Modelling and automation of water and wastewater treatment processes
Environmental Modelling & Software 25 (2010) 613–615
Contents lists available at ScienceDirect
Environmental Modelling & Software journal homepage: www.elsevier.com/locate/envsoft
Preface
Modelling and automation of water and wastewater treatment processes
1. Background to the thematic issue The 8th International Symposium on Sanitary and Environmental Engineering (SIDISA 08) was held in Florence, Italy, on June 24–28, 2008 and hosted a special session on the applications of modelling and automation to water and wastewater treatment processes. The session, under the auspices of IWA, ISWA Italy, GE Water & Process Technologies and many other local institutions, was attended by over 150 participants and included 24 extended oral presentations, 6 short orals and 9 posters. It is my pleasure to acknowledge the cooperation of Giuseppe d’Antonio, Professor of Environmental and Sanitary Engineering at the University of Naples ‘‘Federico II’’ and President of ANDIS (National Association of Sanitary Engineers), who with great open-mindedness agreed to include this Special Session in the SIDISA annual general meeting. I am equally grateful to the Conference Chairman Professor Claudio Lubello, Department of Civil and Environmental Engineering, University of Florence, for the opportunity of organizing and chairing the session. The wide and qualified participation confirmed the growing interest of the sanitary engineering world towards new technologies which can successfully complement and enhance their profession, with automation figuring prominently among the new disciplines required to improve the performance of modern water processing systems. The fusion of these disciplines was advocated in two pioneering books (Olsson and Newell, 1999; Dochain and Vanrolleghem, 2001), whose prophetic value was confirmed by subsequent specialized conferences (Olsson, 2002; Olsson, 2006), a specific technical publication (Olsson et al., 2005) and this session. The Environmental Modelling and Software journal welcomed the opportunity to publish such a set of papers that convey innovative and interdisciplinary modelling approaches to meaningful instances of advanced sanitary engineering. 2. Topics and the core theme The topics presented in the session ranged from advanced kinetics modelling to the use of artificial intelligence tools, either neural networks or fuzzy systems, for process control to new methods for a better model calibration. From the operational viewpoint, many papers considered conventional activated sludge processes, to which unconventional and innovative control strategies were applied. But there were also other interesting contributions regarding respirometry, constructed wetlands, and drinking water purification systems. Many papers showed a considerable effort to extend the analysis from the single plant unit to a wider 1364-8152/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.envsoft.2009.11.002
context, in line with the current approach of plant-wide benchmarking (Olsson and Jeppsson, 2006), including sewage systems and surrounding land use. From the methodological viewpoint, the session was particularly rich showing a mature use of many cutting edge techniques, such as the systematic identifiability approach (see e.g. MarsiliLibelli and Giusti, 2008; Cunha Machado et al., 2009) or fuzzy multi-criteria analysis and uncertainty evaluation (Benetto et al., 2008). Many papers showed a robust theoretical background in model calibration, artificial intelligence, neural networks, and global optimization methods, showing that excellence in performance can be achieved only by introducing these advanced techniques into the water treatment process design and operation. From the application viewpoint the largest number of contributions involved conventional wastewater treatment plants (WWTP), for which several control improvements were proposed, mainly based on very detailed models derived from the ASM family (Henze et al., 2000) and advanced calibration techniques. Many papers straddled more than one application area or integrated methodology and applications. In the first set many advanced modelling results were presented, based on the Benchmark extension (Copp, 2002) of the ASM models (Henze et al., 2000). Advanced modelling was not confined to WWTP and MBR, but was also extended to constructed wetlands for which models were presented as complex as those normally used for more conventional processes, such as WWTP and MBR. The session demonstrated the potential benefits of integration between sanitary engineering practice and automation techniques. In fact the thematic issue common to all the selected papers is a strong and innovative methodological background coupled to an advanced sanitary application. In this sense, artificial intelligence techniques were largely applied to WWTP, potabilization and constructed wetlands, producing advanced models or innovative modelling and control solution to well-known problems.
3. The individual contributions Of the session contributions, nine appear in extended form in this Thematic Issue and one as a short communication. These ten papers convey the theme of the session, which is the fusion of system-theoretic and information technology tools on one side and sanitary engineering concepts on the other. The main criteria for their selection was innovative methodological content (models,
614
Preface / Environmental Modelling & Software 25 (2010) 613–615
estimation algorithms, data-processing techniques) coupled to the relevance of the target application. The contribution of Benedetti, De Baets, Nopens, and Vanrolleghem, entitled Multi-criteria analysis of wastewater treatment plant design and control scenarios under uncertainty considers the complex, highly non-linear nature of a wastewater treatment plant, especially when controllers are introduced, and propose a method similar to Benetto et al. (2008) for scenario analysis of process designs based on Monte Carlo simulations and multi-criteria evaluation of the results. Using the Benchmark Simulation Model no. 2 to represent the plant, with dissolved oxygen and ammonium controllers, the paper compares differing control structure and conclude that a cascade controller, in which the ammonium controller determines the dissolved oxygen set-point, performs much better that two simple separated controllers. In the last part, an uncertainty analysis of the optimal designs, confirms the improvements attainable with the more sophisticated controller in terms of a more stable effluent quality. The paper Software sensors are a real alternative to true sensors by Cecil and Kozlowska describes the design and use of a software sensor to predict the ammonium-, nitrate- and nitrite-nitrogen concentration in real-time, based on ammonium and ORP potential measurements. The predicted ammonium concentration is used to control the length of the nitrification phase in a BiodeniphoÒ activated sludge unit, given better response characteristics of the software sensor with respect to the ammonium meter. The software sensor simplifies meter service and reduces maintenance costs, in addition to being much less expensive. In their paper Modelling respirometric tests for the assessment of kinetic and stoichiometric parameters on MBBR biofilm for municipal wastewater treatment, Ferrai, Guglielmi and Andreottola present a new respirometric test to be used in conjunction with the Moving Bed Biofilm Reactor (MBBR) technology used to upgrade conventional WWTPs. Experimental OUR profiles of heterotrophic biomass were obtained from biofilm and modelled with the ASM3 model in order to assess the biokinetics of heterotrophic and autotrophic biomass. Through this approach the fractions of used and stored substrate were determined and the related parameters estimated. This paper represents a valuable advance in the procedure, long advocated by the authors, of carefully calibrating the ASM model before it could be used for design. A complex multi-phase kinetic model of a constructed wetland system was described by Giraldi, de Michieli Vitturi, and Iannelli in their paper FITOVERT: A dynamic numerical model of subsurface vertical flow constructed wetlands, specifically developed to model vertical subsurface flow constructed wetlands, providing a practical tool for design and optimization of discontinuous feeding-emptying operation. The improvement with respect to previous models is the inclusion of the porosity reduction due to bacteria growth and accumulation of particulate components. In this way progressive clogging can be described. The model performance was analyzed through hydrodynamic tests with differing saturation levels of the medium and the calibration aspects are also discussed. Giusti and Marsili-Libelli have used a fuzzy approach to model the dynamics of the relatively new (to modellers) composting process. In their paper Fuzzy modelling of the composting process. Composting is a solid waste treatment process consisting of the biochemical degradation of organic materials to produce stabilized organic materials. Given the complexity of the microbial processes involved in composting, a fuzzy model was proposed, composed of clustered antecedents, describing the process regimes, and consequent linear models driven by the aeration cycle and in-cycle temperature evolution. This fuzzy model was adapted to the data by cluster training and minimization of a model/data error criterion. The calibrated model was able to
describe the temperature profile during the most significant part of the composting batch. A complex patter recognition strategy is illustrated in the paper by Luccarini, Bragadin, Colombini, Mancini, Mello, Montali, and Sottara, entitled Formal verification of wastewater treatment processes using events detected from continuous signals by means of artificial neural networks. Case study: SBR plant. An algorithm using neural networks is used to extract the relevant qualitative patterns from the operation of a Sequencing Batch Reactor (SBR) process. They are then analyzed using tools commonly applied for the Verification of Business Processes. The SBR process is regarded as a suitable case study because the commonly acknowledged criteria for monitoring the biological processes (nitrification and denitrification) can be expressed in the form or qualitative constraints, which are easily translated into formal rules with desirable characteristics of flexibility and abstraction. A fundamental ten-step procedure for model building and validation has now been established by a number of landmark publications (see Jakeman et al. 2006; Robson et al., 2008; and Welsh, 2008) and the paper by Rietveld, van der Helm, van Schagen, and van der Aa, entitled Good modelling practice in drinking water treatment, applied to the Weesperkarspel plant of Waternet applies this procedure to the modelling of a complex drinking water treatment plant. This study was carried out in the belief that good modelling practice increases the credibility, acceptance and impact of the information and insight into the process being modelled. The authors make their point by applying their methodology to a complete drinking water plant consisting of several process units: ozonation, pellet softening, biological activated carbon filtration and slow sand filtration. The models developed for each unit were used for operational improvements by providing fresh insights into their working. Several practical advantages were obtained with this approach: chemical dosing related to pellet softening was optimized; likewise ozonation was optimized by modelling ozone exposure, bromate formation and biologically degradable natural organic matter. Another paper applying fuzzy methodologies is A systematic approach for fine-tuning of fuzzy controllers applied to WWTPs by Ruano, Ribes, Sin, Seco, and Ferrer. It describes a systematic approach for fine-tuning fuzzy controllers for the aeration control system in a WWTP, similar to that described in Cunha Machado et al. (2009). One of the difficulty of designing fuzzy controllers is their tuning, given the large number of the parameters involved. The proposed approach has the merit of representing a viable alternative to conventional step-by-step heuristic tuning recipes. In this paper three methods are used in sequence: a Monte Carlo procedure to find proper initial conditions, an identifiability analysis to find an identifiable parameter subset of the fuzzy controller, and lastly the minimization algorithm proper, to fine-tune the identifiable parameter subset of the controller. This composite methodology resulted in a dramatic reduction in the number of identified parameters and improved the performance of the control system as measured by the integral absolute deviation between the set-point and the controlled variable. The paper by Worm, van der Helm, Lapikas, van Schagen, and Rietveld, entitled Integration of models, data management, interfaces and training support in a drinking water treatment plant simulator, deals again with a drinking water plant, exploring the implications of a centralized, full automation of the process. This paper is coordinated with the previous paper by Rietveld et al., as both deal with the drinking water treatment plant at Weesperkarspel as a case study and are part of a larger project named ‘‘Waterspot’’. This last paper describes the set-up of a full simulator to be used for operator training. Using familiar interfaces, the simulator can be used by operators who are normally accustomed to the SCADA ‘‘look and feel’’, though the underlying models are much more sophisticated.
Preface / Environmental Modelling & Software 25 (2010) 613–615
Further the operator can delve into deeper levels of the process, each providing dynamic information on relevant process parameters. Therefore, the strong point in this paper is the integration of models, command and data management, training and decisionsupport features, and a GUI. All these features sum up to provide a very sophisticated simulator for a complex water treatment process. The short communication by Doglioni, Primativo, Laucelli, Monno, Soon-Thiam, and Giustolisi is entitled An integrated modelling approach for the assessment of land use change effects on wastewater infrastructures. Though it was published separately (Doglioni et al., 2009) it is nonetheless part of this Thematic Issue. It describes a clever example of integration to obtain a comprehensive model of both the wastewater pathway and of its implication on the surrounding territory, in terms of the impact of urban expansion and land use. The authors point out how the three main model components have widely differing dynamics: the land use model accounts for the urban expansion according to developers’ guidelines; the sewers model reflects the urbanization impact on wastewater production, and the wastewater treatment model describes the varying load depending on the new sewage routing and human pressure. The proposed framework is convincingly demonstrated with the case study of a small town located in Scotland. Editing this Special Issue was a particularly rewarding experience: reviewing many interesting contributions and keeping in touch with a host of dedicated reviewers, whom I deeply thank for their commitment to the initiative. I wish to thank all the authors, for their readiness in revising their manuscripts according to the reviewers’ suggestions and for their patience in waiting for the completion of this long editing process. I hope that they will be satisfied by the end result. This Thematic Issue, however, would not have seen the light without the enthusiastic support and the unwavering backing of the Editor-in-Chief, Professor Tony Jakeman, always ready to help with suggestions, opinions, and encouragement. At the end of this adventure, I wish to express my deepest gratitude to the scientist, the editor, the friend, all of the purest grade.
615
References Benetto, E., Dujet, C., Rousseaux, P., 2008. Integrating fuzzy multicriteria analysis and uncertainty evaluation in life cycle assessment. Environmental Modelling & Software 23, 1461–1467. Copp, J.B., 2002. The COST Simulation Benchmark: Description and Simulator Manual. EC Publication Office. Cunha Machado, V., Tapia, G., Gabriel, D., Lafuente, J., Baeza, J.A., 2009. Systematic identifiability study based on the Fisher Information Matrix for reducing the number of parameters calibration of an activated sludge model. Environmental Modelling & Software 24, 1274–1284. Dochain, D., Vanrolleghem, P.A., 2001. Dynamical Modelling and Estimation in Wastewater Treatment Processes. IWA Publishing, London, pp. 342. Doglioni, A., Primativo, F., Laucelli, D., Monno, V., Soon-Thiam, K., Giustolisi, O., 2009. An integrated modelling approach for the assessment of land use change effects on wastewater infrastructures. Environmental Modelling & Software 24, 1522–1528. Henze, M., Gujer, W., Mino, T., van Loosdrecht, M.C.M., 2000. Activated sludge models ASM1, ASM2, ASM2d, and ASM3. In: IWA Scientific and Technical Report No. 9. Jakeman, A.J., Letcher, R.A., Norton, J.P., 2006. Ten iterative steps in development and evaluation of environmental models. Environmental Modelling & Software 21, 602–614. Marsili-Libelli, S., Giusti, E., 2008. Water quality modelling for small river basins. Environmental Modelling & Software 23, 451–463. Olsson, G., 2002. Lessons learned at ICA2001. Water Science & Technology 45 (4–5),1–8. Olsson, G., Nielsen, M.K., Yuan, Z., Lynggaard-Jensen, A., Steyer, J.Ph., 2005. Instrumentation, control and automation in wastewater systems. Scientific and Technical Report n. 15. IWA Publ., London. Olsson, G., Jeppsson, U., 2006. Plant-wide control: dream, necessity or reality? Water Science & Technology 53 (3), 121–129. Olsson, G., Newell, B., 1999. Wastewater Treatment Systems – Modelling, Diagnosis and Control. IWA Publishing, London, 742 pp. Robson, B.J., Hamilton, D.P., Webster, I.T., Chan, T., 2008. Ten steps applied to development and evaluation of process-based biogeochemical models of estuaries. Environmental Modelling & Software 23, 369–384. Welsh, W., 2008. Water balance modelling in Bowen, Queensland, and the ten iterative steps in model development and evaluation. Environmental Modelling & Software 23, 195–205.
Stefano Marsili-Libelli* Department of Systems and Computers, University of Florence, Via S. Marta 3, I-50139 Florence, Italy * Tel./fax: þ39 055 4796264. E-mail address: [email protected]fi.it 9 November 2009 Available online 22 December 2009
Contents lists available at ScienceDirect
Environmental Modelling & Software journal homepage: www.elsevier.com/locate/envsoft
Preface
Modelling and automation of water and wastewater treatment processes
1. Background to the thematic issue The 8th International Symposium on Sanitary and Environmental Engineering (SIDISA 08) was held in Florence, Italy, on June 24–28, 2008 and hosted a special session on the applications of modelling and automation to water and wastewater treatment processes. The session, under the auspices of IWA, ISWA Italy, GE Water & Process Technologies and many other local institutions, was attended by over 150 participants and included 24 extended oral presentations, 6 short orals and 9 posters. It is my pleasure to acknowledge the cooperation of Giuseppe d’Antonio, Professor of Environmental and Sanitary Engineering at the University of Naples ‘‘Federico II’’ and President of ANDIS (National Association of Sanitary Engineers), who with great open-mindedness agreed to include this Special Session in the SIDISA annual general meeting. I am equally grateful to the Conference Chairman Professor Claudio Lubello, Department of Civil and Environmental Engineering, University of Florence, for the opportunity of organizing and chairing the session. The wide and qualified participation confirmed the growing interest of the sanitary engineering world towards new technologies which can successfully complement and enhance their profession, with automation figuring prominently among the new disciplines required to improve the performance of modern water processing systems. The fusion of these disciplines was advocated in two pioneering books (Olsson and Newell, 1999; Dochain and Vanrolleghem, 2001), whose prophetic value was confirmed by subsequent specialized conferences (Olsson, 2002; Olsson, 2006), a specific technical publication (Olsson et al., 2005) and this session. The Environmental Modelling and Software journal welcomed the opportunity to publish such a set of papers that convey innovative and interdisciplinary modelling approaches to meaningful instances of advanced sanitary engineering. 2. Topics and the core theme The topics presented in the session ranged from advanced kinetics modelling to the use of artificial intelligence tools, either neural networks or fuzzy systems, for process control to new methods for a better model calibration. From the operational viewpoint, many papers considered conventional activated sludge processes, to which unconventional and innovative control strategies were applied. But there were also other interesting contributions regarding respirometry, constructed wetlands, and drinking water purification systems. Many papers showed a considerable effort to extend the analysis from the single plant unit to a wider 1364-8152/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.envsoft.2009.11.002
context, in line with the current approach of plant-wide benchmarking (Olsson and Jeppsson, 2006), including sewage systems and surrounding land use. From the methodological viewpoint, the session was particularly rich showing a mature use of many cutting edge techniques, such as the systematic identifiability approach (see e.g. MarsiliLibelli and Giusti, 2008; Cunha Machado et al., 2009) or fuzzy multi-criteria analysis and uncertainty evaluation (Benetto et al., 2008). Many papers showed a robust theoretical background in model calibration, artificial intelligence, neural networks, and global optimization methods, showing that excellence in performance can be achieved only by introducing these advanced techniques into the water treatment process design and operation. From the application viewpoint the largest number of contributions involved conventional wastewater treatment plants (WWTP), for which several control improvements were proposed, mainly based on very detailed models derived from the ASM family (Henze et al., 2000) and advanced calibration techniques. Many papers straddled more than one application area or integrated methodology and applications. In the first set many advanced modelling results were presented, based on the Benchmark extension (Copp, 2002) of the ASM models (Henze et al., 2000). Advanced modelling was not confined to WWTP and MBR, but was also extended to constructed wetlands for which models were presented as complex as those normally used for more conventional processes, such as WWTP and MBR. The session demonstrated the potential benefits of integration between sanitary engineering practice and automation techniques. In fact the thematic issue common to all the selected papers is a strong and innovative methodological background coupled to an advanced sanitary application. In this sense, artificial intelligence techniques were largely applied to WWTP, potabilization and constructed wetlands, producing advanced models or innovative modelling and control solution to well-known problems.
3. The individual contributions Of the session contributions, nine appear in extended form in this Thematic Issue and one as a short communication. These ten papers convey the theme of the session, which is the fusion of system-theoretic and information technology tools on one side and sanitary engineering concepts on the other. The main criteria for their selection was innovative methodological content (models,
614
Preface / Environmental Modelling & Software 25 (2010) 613–615
estimation algorithms, data-processing techniques) coupled to the relevance of the target application. The contribution of Benedetti, De Baets, Nopens, and Vanrolleghem, entitled Multi-criteria analysis of wastewater treatment plant design and control scenarios under uncertainty considers the complex, highly non-linear nature of a wastewater treatment plant, especially when controllers are introduced, and propose a method similar to Benetto et al. (2008) for scenario analysis of process designs based on Monte Carlo simulations and multi-criteria evaluation of the results. Using the Benchmark Simulation Model no. 2 to represent the plant, with dissolved oxygen and ammonium controllers, the paper compares differing control structure and conclude that a cascade controller, in which the ammonium controller determines the dissolved oxygen set-point, performs much better that two simple separated controllers. In the last part, an uncertainty analysis of the optimal designs, confirms the improvements attainable with the more sophisticated controller in terms of a more stable effluent quality. The paper Software sensors are a real alternative to true sensors by Cecil and Kozlowska describes the design and use of a software sensor to predict the ammonium-, nitrate- and nitrite-nitrogen concentration in real-time, based on ammonium and ORP potential measurements. The predicted ammonium concentration is used to control the length of the nitrification phase in a BiodeniphoÒ activated sludge unit, given better response characteristics of the software sensor with respect to the ammonium meter. The software sensor simplifies meter service and reduces maintenance costs, in addition to being much less expensive. In their paper Modelling respirometric tests for the assessment of kinetic and stoichiometric parameters on MBBR biofilm for municipal wastewater treatment, Ferrai, Guglielmi and Andreottola present a new respirometric test to be used in conjunction with the Moving Bed Biofilm Reactor (MBBR) technology used to upgrade conventional WWTPs. Experimental OUR profiles of heterotrophic biomass were obtained from biofilm and modelled with the ASM3 model in order to assess the biokinetics of heterotrophic and autotrophic biomass. Through this approach the fractions of used and stored substrate were determined and the related parameters estimated. This paper represents a valuable advance in the procedure, long advocated by the authors, of carefully calibrating the ASM model before it could be used for design. A complex multi-phase kinetic model of a constructed wetland system was described by Giraldi, de Michieli Vitturi, and Iannelli in their paper FITOVERT: A dynamic numerical model of subsurface vertical flow constructed wetlands, specifically developed to model vertical subsurface flow constructed wetlands, providing a practical tool for design and optimization of discontinuous feeding-emptying operation. The improvement with respect to previous models is the inclusion of the porosity reduction due to bacteria growth and accumulation of particulate components. In this way progressive clogging can be described. The model performance was analyzed through hydrodynamic tests with differing saturation levels of the medium and the calibration aspects are also discussed. Giusti and Marsili-Libelli have used a fuzzy approach to model the dynamics of the relatively new (to modellers) composting process. In their paper Fuzzy modelling of the composting process. Composting is a solid waste treatment process consisting of the biochemical degradation of organic materials to produce stabilized organic materials. Given the complexity of the microbial processes involved in composting, a fuzzy model was proposed, composed of clustered antecedents, describing the process regimes, and consequent linear models driven by the aeration cycle and in-cycle temperature evolution. This fuzzy model was adapted to the data by cluster training and minimization of a model/data error criterion. The calibrated model was able to
describe the temperature profile during the most significant part of the composting batch. A complex patter recognition strategy is illustrated in the paper by Luccarini, Bragadin, Colombini, Mancini, Mello, Montali, and Sottara, entitled Formal verification of wastewater treatment processes using events detected from continuous signals by means of artificial neural networks. Case study: SBR plant. An algorithm using neural networks is used to extract the relevant qualitative patterns from the operation of a Sequencing Batch Reactor (SBR) process. They are then analyzed using tools commonly applied for the Verification of Business Processes. The SBR process is regarded as a suitable case study because the commonly acknowledged criteria for monitoring the biological processes (nitrification and denitrification) can be expressed in the form or qualitative constraints, which are easily translated into formal rules with desirable characteristics of flexibility and abstraction. A fundamental ten-step procedure for model building and validation has now been established by a number of landmark publications (see Jakeman et al. 2006; Robson et al., 2008; and Welsh, 2008) and the paper by Rietveld, van der Helm, van Schagen, and van der Aa, entitled Good modelling practice in drinking water treatment, applied to the Weesperkarspel plant of Waternet applies this procedure to the modelling of a complex drinking water treatment plant. This study was carried out in the belief that good modelling practice increases the credibility, acceptance and impact of the information and insight into the process being modelled. The authors make their point by applying their methodology to a complete drinking water plant consisting of several process units: ozonation, pellet softening, biological activated carbon filtration and slow sand filtration. The models developed for each unit were used for operational improvements by providing fresh insights into their working. Several practical advantages were obtained with this approach: chemical dosing related to pellet softening was optimized; likewise ozonation was optimized by modelling ozone exposure, bromate formation and biologically degradable natural organic matter. Another paper applying fuzzy methodologies is A systematic approach for fine-tuning of fuzzy controllers applied to WWTPs by Ruano, Ribes, Sin, Seco, and Ferrer. It describes a systematic approach for fine-tuning fuzzy controllers for the aeration control system in a WWTP, similar to that described in Cunha Machado et al. (2009). One of the difficulty of designing fuzzy controllers is their tuning, given the large number of the parameters involved. The proposed approach has the merit of representing a viable alternative to conventional step-by-step heuristic tuning recipes. In this paper three methods are used in sequence: a Monte Carlo procedure to find proper initial conditions, an identifiability analysis to find an identifiable parameter subset of the fuzzy controller, and lastly the minimization algorithm proper, to fine-tune the identifiable parameter subset of the controller. This composite methodology resulted in a dramatic reduction in the number of identified parameters and improved the performance of the control system as measured by the integral absolute deviation between the set-point and the controlled variable. The paper by Worm, van der Helm, Lapikas, van Schagen, and Rietveld, entitled Integration of models, data management, interfaces and training support in a drinking water treatment plant simulator, deals again with a drinking water plant, exploring the implications of a centralized, full automation of the process. This paper is coordinated with the previous paper by Rietveld et al., as both deal with the drinking water treatment plant at Weesperkarspel as a case study and are part of a larger project named ‘‘Waterspot’’. This last paper describes the set-up of a full simulator to be used for operator training. Using familiar interfaces, the simulator can be used by operators who are normally accustomed to the SCADA ‘‘look and feel’’, though the underlying models are much more sophisticated.
Preface / Environmental Modelling & Software 25 (2010) 613–615
Further the operator can delve into deeper levels of the process, each providing dynamic information on relevant process parameters. Therefore, the strong point in this paper is the integration of models, command and data management, training and decisionsupport features, and a GUI. All these features sum up to provide a very sophisticated simulator for a complex water treatment process. The short communication by Doglioni, Primativo, Laucelli, Monno, Soon-Thiam, and Giustolisi is entitled An integrated modelling approach for the assessment of land use change effects on wastewater infrastructures. Though it was published separately (Doglioni et al., 2009) it is nonetheless part of this Thematic Issue. It describes a clever example of integration to obtain a comprehensive model of both the wastewater pathway and of its implication on the surrounding territory, in terms of the impact of urban expansion and land use. The authors point out how the three main model components have widely differing dynamics: the land use model accounts for the urban expansion according to developers’ guidelines; the sewers model reflects the urbanization impact on wastewater production, and the wastewater treatment model describes the varying load depending on the new sewage routing and human pressure. The proposed framework is convincingly demonstrated with the case study of a small town located in Scotland. Editing this Special Issue was a particularly rewarding experience: reviewing many interesting contributions and keeping in touch with a host of dedicated reviewers, whom I deeply thank for their commitment to the initiative. I wish to thank all the authors, for their readiness in revising their manuscripts according to the reviewers’ suggestions and for their patience in waiting for the completion of this long editing process. I hope that they will be satisfied by the end result. This Thematic Issue, however, would not have seen the light without the enthusiastic support and the unwavering backing of the Editor-in-Chief, Professor Tony Jakeman, always ready to help with suggestions, opinions, and encouragement. At the end of this adventure, I wish to express my deepest gratitude to the scientist, the editor, the friend, all of the purest grade.
615
References Benetto, E., Dujet, C., Rousseaux, P., 2008. Integrating fuzzy multicriteria analysis and uncertainty evaluation in life cycle assessment. Environmental Modelling & Software 23, 1461–1467. Copp, J.B., 2002. The COST Simulation Benchmark: Description and Simulator Manual. EC Publication Office. Cunha Machado, V., Tapia, G., Gabriel, D., Lafuente, J., Baeza, J.A., 2009. Systematic identifiability study based on the Fisher Information Matrix for reducing the number of parameters calibration of an activated sludge model. Environmental Modelling & Software 24, 1274–1284. Dochain, D., Vanrolleghem, P.A., 2001. Dynamical Modelling and Estimation in Wastewater Treatment Processes. IWA Publishing, London, pp. 342. Doglioni, A., Primativo, F., Laucelli, D., Monno, V., Soon-Thiam, K., Giustolisi, O., 2009. An integrated modelling approach for the assessment of land use change effects on wastewater infrastructures. Environmental Modelling & Software 24, 1522–1528. Henze, M., Gujer, W., Mino, T., van Loosdrecht, M.C.M., 2000. Activated sludge models ASM1, ASM2, ASM2d, and ASM3. In: IWA Scientific and Technical Report No. 9. Jakeman, A.J., Letcher, R.A., Norton, J.P., 2006. Ten iterative steps in development and evaluation of environmental models. Environmental Modelling & Software 21, 602–614. Marsili-Libelli, S., Giusti, E., 2008. Water quality modelling for small river basins. Environmental Modelling & Software 23, 451–463. Olsson, G., 2002. Lessons learned at ICA2001. Water Science & Technology 45 (4–5),1–8. Olsson, G., Nielsen, M.K., Yuan, Z., Lynggaard-Jensen, A., Steyer, J.Ph., 2005. Instrumentation, control and automation in wastewater systems. Scientific and Technical Report n. 15. IWA Publ., London. Olsson, G., Jeppsson, U., 2006. Plant-wide control: dream, necessity or reality? Water Science & Technology 53 (3), 121–129. Olsson, G., Newell, B., 1999. Wastewater Treatment Systems – Modelling, Diagnosis and Control. IWA Publishing, London, 742 pp. Robson, B.J., Hamilton, D.P., Webster, I.T., Chan, T., 2008. Ten steps applied to development and evaluation of process-based biogeochemical models of estuaries. Environmental Modelling & Software 23, 369–384. Welsh, W., 2008. Water balance modelling in Bowen, Queensland, and the ten iterative steps in model development and evaluation. Environmental Modelling & Software 23, 195–205.
Stefano Marsili-Libelli* Department of Systems and Computers, University of Florence, Via S. Marta 3, I-50139 Florence, Italy * Tel./fax: þ39 055 4796264. E-mail address: [email protected]fi.it 9 November 2009 Available online 22 December 2009