Description
Existing water distribution system models are inadequate for water poor and developing communities that lack technical design expertise. We propose a novel approach to network optimization by using a decision support system. This interactive system is intended to help the non-technical manager compile information from raw data, personal knowledge, and business models to identify and solve water allocation problems. The rural community of El Socorro, Honduras presented as a demonstration of the model.
Abstract
Water supply networks are a key component of any community blueprint. Their planning and design requires the expertise of professional engineers who must consider factors such as location, allocation, pressure and pipe size. Traditional network analysis models assume water availability that will continuously meet demand, and act as a function of textbook resource management. These mathematical models are inadequate for water poor and developing communities that lack sufficient water supply, funds, or technical capacity to develop a distribution system. We propose a novel approach to distribution system modeling using a decision support system (DSS.) The DSS includes data management, an adaptive knowledge base and a graphic user interface. This interactive system is intended to help the non-technical manager compile useful information from raw data, personal knowledge, and business models to identify and solve water allocation problems and make unbiased distribution decisions. This paper outlines the development of an Excel-based DSS for Water Distribution Network Optimization (DSS-WDNO) to increase the design capability of development workers in rural communities. The case of a proposed distribution system in the rural community of El Socorro, Honduras, designed in collaboration with the US Peace Corps is presented as a demonstration of the effectiveness of the model.
Author(s): Caitlin Augustin, University of Miami; Shihab Asfour, University of Miami
Learn more at:Decision Support System for Water Distribution Network Optimization by Non-Technical Workers
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