An application of decision theory to water quality management

• Main Author: Hershman, Stanley
• Language: English
• Published: 2010
• Online Access: http://hdl.handle.net/2429/18737

The thesis presents an algorithm for applying decision theory to the management of water quality of a lake that is becoming culturally eutrophic. The algorithm was formulated using Utility theory and Bayesian decision strategy as a theoretical basis. It pays particular attention to the following three elements of the management problem: (1) the interdisciplinary nature of the problem; the need to co-ordinate the efforts of biologists, limnologists, engineers, etc., as well as providing a role for the public; (2) the extent of uncertainty with respect to the behavior of a nutrient enriched lake and the effect of various abatement measures upon the future water quality of the lake; (3) the need for long-term planning strategies so that the problem can be controlled and not just delayed. The technique provides the planners with a systematic procedure for evaluating the scientific data. It measures deterioration of the lake in non-economic units of utility. Alternatives are compared according to their "expected utility" over a planning period. Skaha Lake, located in the Okanagan Basin in British Columbia is used as a case study for the development and application of the technique. The lake receives treated sewage effluent from a growing municipality and has recently exhibited a sharp increase in biological production. Several possible management programs for the lake are compared using data obtained by limnologists and engineers. A computer program was written in WATFIV that can store and analyse data corresponding to a specific lake. The output of the program is a graphical plot of an expected utility function over some planning period for a particular pollution control measure. The expected utility scale relates directly to the water quality and degree of eutrophication of the lake and can thus be used to compare the effectiveness of proposed alternative measures. === Applied Science, Faculty of === Civil Engineering, Department of === Graduate