

@mastersthesis {6329,
	title = {Planning rural water supply systems in developing countries: {The} case of {Rwanda}},
	year = {2004},
	note = {3156156},
	school = {The University of North Carolina at Chapel Hill},
	type = {phdPh.{D}.},
	address = {Ann Arbor},
	abstract = {In the past decade, international donors and governments have generally required water supply systems to be financially self-sufficient, with stakeholder participation in their planning and operation so as to ensure sustainability. This research presents a new approach for planning rural water supply in developing countries that addresses many of the most common and vexing problems facing planners: where to locate point sources, how many sources to build, what prices to charge, and how to estimate the number of users. The models developed herein are based on two well-established methodologies: (1) contingent valuation (CV) surveys for assessing household willingness to pay, and (2) planning models built around the results from the CV survey. The results of a CV study conducted in Rwanda in 2000 are used to show how the findings can be embedded in optimization models to address key planning questions. Nonetheless, these models are deterministic and unrealistically assume certainty about input parameters. A Monte Carlo simulation is used to address the effects of parameter uncertainty. The cumulative distribution functions of model outputs can be used to address key water-supply planning decisions. Analysis of normalized squared values of rank correlation coefficients by model inputs on planning decisions shows that uncertainty in willingness to pay is not as important in determining where to locate improved sources as uncertainty in water-carrying distances. In addition to the primary objective of minimizing distances between households and improved water sources, there may exist a range of secondary objectives that are implicit or otherwise not included in the model formulation that result in uncertainty in the planning objectives. This source of uncertainty is addressed by identifying sets of maximally different solutions that are near to the solution of the original deterministic model, using the Modeling to Generate Alternatives methodology. The models can be used to (1) screen out grossly inferior solutions and (2) provide essentially equivalent alternatives to the stakeholders that can be evaluated against the secondary planning criteria. This approach provides stakeholders an opportunity to make choices based on their intimate knowledge of local conditions.},
	keywords = {0501:Economics, 0543:Civil engineering, 0796:Operations research, Applied sciences, Civil engineering, Developing Countries, economics, Operations research, Rural, Rwanda, Social sciences, Water Supply},
	url = {http://search.proquest.com/docview/305170059?accountid=14270},
	author = {Hopkins, Omar Snowden}
}
