Water resources managers rely on information collected by hydrometric networks without a quantitative way to assess their efficiency, and most Canadian water monitoring networks still do not meet the minimum density requirements. There is also no established way to quantify the importance of each existing station in a hydrometric network. This research examines the properties of Combined Regionalization Dual Entropy Multi-Objective Optimization (CR-DEMO), a robust network design technique which combines the merits of information theory and multi-objective optimization. Another information theory based method called transinformation (TI) which can rank the contribution of unique information from each specific hydrometric station in the network is tested for use with CR-DEMO. When used in conjunction, these methods can not only provide an objective measure of network efficiency and the relative importance of each station, but also allow the user to make recommendations to improve existing hydrometric networks across Canada. The Ottawa River Basin, a major Canadian watershed in Ontario and Quebec, was selected for analysis. Various regionalization methods which could be used in CR-DEMO such as distance weighting and a rainfall runoff model were compared in a leave one out cross validation. The effect of removing stations with regulated and unnatural flow regimes from the regionalization process is also tested. The analysis is repeated on a smaller tributary of the Ottawa River Basin, the Madawaska Watershed, to examine scale effects in TI analysis and CR-DEMO application. In this study, tests were conducted to determine whether to include stations outside of the river basin in order to provide more context to the basin boundaries. It was found that the TI analysis complemented CR-DEMO well and it provided a detailed station ranking which was supported by CR-DEMO results. The inverse distance weighting drainage area ratio method was found to provide more accurate regionalization results compared to the rainfall-runoff model, and was thus chosen for CR-DEMO. Regionalization was shown to be more accurate when the regulated basins were omitted using leave one out cross validation. It was discovered that CR-DEMO is sensitive to scaling because some sub-basins which are relatively “well-equipped” compared to others in dire conditions may be penalized. The TI analysis was not as sensitive to scaling. Including stations outside of the Ottawa River Basin improved the information density and regionalization accuracy in the Madawaska Watershed because they provided context to sparse areas. Finally, Pareto optimal network solutions for both the Ottawa River Basin and the Madawaska Watershed were presented and analyzed. A number of optimal networks are proposed for each watershed along with “hot-spots” where new stations should be added whatever the end users’ choice of network. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/20509 |
| Date | January 2016 |
| Creators | Werstuck, Connor |
| Contributors | Coulibaly, Paulin, Civil Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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