A Systems Approach for the Selection of Appropriate Water Supply and Sanitation Infrastructure in Developing Communities

Bouabid, Ali, Systems Engineering - School of Engineering and Applied Science, University of Virginia
Louis, Garrick, Systems and Information Engineering, University of Virginia

40% of the world’s population lacks access to adequate supplies of water and sanitation to sustain human health. In fact, more than 780 million people lack access to safe water supplies and more than 2.5 billion lack access to basic sanitation. Appropriate technology for water supply and sanitation (Watsan) systems is critical for sustained access to these services. Current approaches for the selection of Watsan technologies in developing communities have a high failure rate. Based on a study done by the World Health Organization (WHO), 30% to 60% of Watsan installed infrastructures in developing countries are not operating.
This research presents an original framework for the selection of appropriate Watsan technologies for developing communities. The proposed decision model has three components. The first component is a standardized model, the capacity factor analysis (CFA), used for the assessment of a community’s capacity to manage a municipal sanitation service (MSS) such as, drinking water supply (DWS), wastewater and sewage treatment (WST), and management of solid waste (MSW). The assessment of the community’s capacity is based on seven capacity factors (CF) that capture the community’s capacity level (CCL) to manage a MSS. The CFA uses five capacity levels to assess the overall capacity of a community to operate and manage sustainably an MSS. The second component of the decision model is a database of Watsan technologies with proven sustainability in developing communities. The Watsan technologies are classified using a statistical learning technique, the support vector machines (SVM) model applied to classification problems. The classification of Watsan technologies is defined by a metric, the technology requirement level (TRL). This metric defines the capacity level a community must have to operate and maintain sustainably a given Watsan technology. The third component of the decision model is the appropriate matching model. The matching model selects from the database appropriate Watsan technology options that have a TRL metric consistent with the host community CCL metric, and that are implemented and operating sustainably in communities that have a similar regional specificity and profile as the host community. Case studies are used to demonstrate the applicability and the performance of the decision model.

PHD (Doctor of Philosophy)
Capacity Factors, Appropriate technology, SVM classification, Watsan DSS
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