A methodology for hydrometric monitoring network design
Hydrometric data are the basis of many important decisions. A hydrometric monitoring network saves an ever increasing demand for more data and better quality data. Unfortunately, a widely faced problem by the hydrometric data collectors and maintainers is the reduced budget for the monitoring network. This budget reduction has forced many monitoring stations out of service, and is threatening the retention of many other stations. A methodology that helps to properly select stations for removal is needed by network management agencies. There are many factors to be considered in determining the removal of a station. Information losses associated with a station removal is usually a great concern since it impacts the effectiveness of the network. But some factors like the operation cost, the importance to the users, the importance to the sustainable development etc. are important too. In fact, not all factors in consideration are inter-comparable. This makes the station selection a challenge. This thesis presents a methodology that is able to integrate all impact factors to the station removals and help to determine the removal stations from a network. In this methodology, entropy is used to calculate the net information a station can collect, the information relationship to other stations and value of the data length. Analytic Hierarchy Process is used to combine non-inter-comparable concerns to derive an overall evaluation index for every station. This methodology is applied to the Pembina River basin in Canada to simulate the station removals. The conclusion of such a simulation does ot totally agree with the removals that have been made, and suggests that some of the historical removals may need review.