Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361564
Title: Decision-support system for domestic water demand forecasting and management
Author: Froukh, Mohammed Lu’ay Jamal
ISNI:       0000 0001 3484 8518
Awarding Body: Newcastle University
Current Institution: University of Newcastle upon Tyne
Date of Award: 1997
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Abstract:
A generic but flexible decision-support system for domestic water demand forecasting and management (DFMS) has been developed as part of a highlyintegrated decision-support system for river-basin management. Its purpose is to provide water-resources planners with the facilities for estimating future water demand for any demand region and time period, having regard to the possibility of introducing demand-management measures. The system has the capability of predicting domestic-water demand by various methods according to the data availability, computing conservation effectiveness due to the implementation of various demand-management measures, forecasting the number of customers for different consumption units (person, household, water connection) and facilitating the development of demand-scenarios for eveluating various options. The system is designed in such a way that makes it easy to use for both novice and experienced users since it is driven by a menu system which relies on a mouse rather than the keyboard. Moreover, the communication between user and the system is by means of a user-friendly interface which makes extensive use of hypertext and colour graphics in presenting the results. Briefly, DFMS comprises the following components: a GIS that stores, displays and analyses all geo-coded information such as satellite imagery, urban areas, cities and towns, etc.; • a database which provides access to non-spatial data such as demand-area location and characteristics including top-level descriptors such as population, total demand, per-capita consumption, etc.; • an expert system which uses the rule-based inference for data entry and predicting values (quantitative or qualitative) of variables from the knowledgebase; . four methods of demand forecasting ranging from superficial to detailed, namely time extrapolation, econometric variables, end-uses variables and households classification; a multi-objective decision component which helps the user to determine the most appropriate forecasting method and conservation measures; • a set of mathematical models to provide the analytical capability for quantifying descriptors, producing multiple outputs etc.; • a user-interface with access to the various functional components of the system and the various help/explain files; • a set of pre- and post-processors which support editing of the inputs data and the visualisation or analysis of model output, in addition to handling scenarios for each of the models or variables; • a set of help files which are used to provide the user with the necessary assistance if for any reason, a more detailed explanation is required, based on a hypertext; In order to demonstrate the system capability, DFMS has been applied to the Swindon demand area of Thames Water Utilities Ltd.
Supervisor: Not available Sponsor: Department of Civil Engineering, University of Newcastle upon Tyne ; World Bank (Joint/Japan Scholarship Program) ; British Embassy, Amman
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.361564  DOI: Not available
Keywords: Expert systems
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