Final report with DSS methodology, software and case study from a pilot city (Deliverable 54.3)
Behzadian, Kourosh; Morley, Mark S.; Vitorino, Diogo; et al.Coehlo, Sergio; Ugarelli, R.; Kapelan, Zoran
Date: 30 April 2015
TRUST (TRansitions to the Urban Water Services of Tomorrow) Project
The report presents a detailed description of a Decision Support System (DSS) methodology and software tool for use as a decision support tool to assist in the management of Urban Water Systems (UWS). The report is divided into the following three principal sections: An initial description of the DSS methodology and modelling concept ...
The report presents a detailed description of a Decision Support System (DSS) methodology and software tool for use as a decision support tool to assist in the management of Urban Water Systems (UWS). The report is divided into the following three principal sections: An initial description of the DSS methodology and modelling concept is followed by a definition of the DSS problem and the elements of the DSS decision matrix and, finally, the ranking of alternatives in the DSS. Specifically, this section describes the DSS structure which encapsulates a framework for the assessment of intervention strategies in an UWS. The internal structure of the DSS engine comprises three principle modules including Environment, Performance and Multi-Criteria Decision Analysis (MCDA). The ‘Environment’ module manages the specifications of the analysis including timing, intervention strategies, PIs, scenarios and customised model input. The ‘Performance’ module is responsible for evaluating the two categories of metrics: (1) quantitative performance metrics calculated by WaterMet2 and the Risk Assessment module; (2) qualitative metrics defined within the DSS and quantified by external tools or third-parties outside the immediate scope of the DSS. The MCDA module applies a user-configured ranking approach to the specified intervention strategies for the purposes of scoring and ranking them for each scenario and user preference combination. The principal stages of the DSS map to four steps including 1) problem definition, 2) population of decision matrix and calculation of metrics (or impact assessment), 3) ranking of alternatives and viewing detailed results and 4) viewing result modification and re-evaluation of intervention strategies. The second part describes the DSS software tool itself. Two complementary interface instances are presented for the DSS, representing Desktop and web-based tools. The overviews of both tools consist of an introduction to how input data are prepared, how to run a simulation and, finally, how to interpret results in different formats. The final part of this report illustrates the use of DSS applied to the case study problem. This describes the configuration of the DSS for the case study problem for a city which faces water scarcity problems over a 30-year planning horizon, starting from year 2015. Seven intervention strategies for ameliorating this issue are examined through both implementations of the DSS. Six performance metrics are considered including five quantitative measures and a single qualitative criterion. The analysis accommodates two rates of future population growth (i.e. low and high) can be envisaged as two individual scenarios for a 30 year planning period starting from 2010. Comparison of the intervention strategies with respect to these performance metrics is also conducted based on three weighting schemes representing differing stakeholder perspectives. These weighting schemes include equal weights, and the perspectives of the Water Company and Consumers. The DSS is able to rank and prioritise the proposed intervention strategies under different individual specified scenarios and weighting schemes and to ultimately combine them to produce a single ranking for each intervention strategy.
College of Engineering, Mathematics and Physical Sciences
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