Keywords
system dynamics, agent-based modelling, urban water system, sociotechnical system, integrated modelling
Start Date
1-7-2012 12:00 AM
Abstract
A (truly) integrated approach to the management of urban water should take into account, further to the characteristics of the technical system, a range of socio-economic processes and interactions – combined into what has been termed the “socio-technical system”. This is by no means an easy endeavour: conventional simulation tools often fail to capture socio-economic processes and their interactions with the technical urban water system. Variables depicting the socioeconomic environment are usually static and estimated from literature and/or expert opinion. To address this issue, new socio-technical modelling approaches are emerging aiming to explicitly account for the feedback loops between the socioeconomic environment and the urban water system. In this paper we develop a hybrid artificial intelligence (AI) conceptual model using System Dynamics (SD), Agent Based Modelling (ABM) and urban water modelling tools to investigate the urban water system’s response to different policies. The SD model simulates the broader socio-economic, natural and technical context and links to more specialised tools for the social and technical sub-systems: For the social subsystem, ABM is used to model preferences and decisions of water users, whereas for the technical system, the Urban Water Optioneering Tool (UWOT) is used to provide a detailed representation of the urban water cycle, affected by the endusers’ decisions. The proposed modelling framework allows for the dynamic nature of the socio-economic variables to be explicitly included in the assessment in order to test the effectiveness of different policies, such as awareness raising campaigns, and dynamically simulate the subsequent response of the urban water system in time. The paper discusses the integration of urban water and social simulation models at a higher modelling level via a System Dynamics platform and the suitability of such a framework for the assessment of the performance and pressures on urban water systems under varying conditions and scenarios.
A hybrid artificial intelligence modelling framework for the simulation of the complete, socio-technical, urban water system
A (truly) integrated approach to the management of urban water should take into account, further to the characteristics of the technical system, a range of socio-economic processes and interactions – combined into what has been termed the “socio-technical system”. This is by no means an easy endeavour: conventional simulation tools often fail to capture socio-economic processes and their interactions with the technical urban water system. Variables depicting the socioeconomic environment are usually static and estimated from literature and/or expert opinion. To address this issue, new socio-technical modelling approaches are emerging aiming to explicitly account for the feedback loops between the socioeconomic environment and the urban water system. In this paper we develop a hybrid artificial intelligence (AI) conceptual model using System Dynamics (SD), Agent Based Modelling (ABM) and urban water modelling tools to investigate the urban water system’s response to different policies. The SD model simulates the broader socio-economic, natural and technical context and links to more specialised tools for the social and technical sub-systems: For the social subsystem, ABM is used to model preferences and decisions of water users, whereas for the technical system, the Urban Water Optioneering Tool (UWOT) is used to provide a detailed representation of the urban water cycle, affected by the endusers’ decisions. The proposed modelling framework allows for the dynamic nature of the socio-economic variables to be explicitly included in the assessment in order to test the effectiveness of different policies, such as awareness raising campaigns, and dynamically simulate the subsequent response of the urban water system in time. The paper discusses the integration of urban water and social simulation models at a higher modelling level via a System Dynamics platform and the suitability of such a framework for the assessment of the performance and pressures on urban water systems under varying conditions and scenarios.
