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The discharge and stage measurements in a river system are characterized by a number of sources of uncertainty, which affects the accuracy of a rating curve established from measurements. This paper presents a fuzzy set theory based methodology for consideration of different sources of uncertainty in the stage and discharge measurements and their aggregation into a combined uncertainty. The uncertainty in individual measurements of stage and discharge is represented using triangular fuzzy numbers, and their spread is determined according to the International Organization for Standardization (ISO) standard 748 guidelines. The extension principle based fuzzy arithmetic is used for the aggregation of various uncertainties into overall stage-discharge measurement uncertainty. In addition, a fuzzified form of ISO 748 formulation is used for the calculation of combined uncertainty and comparison with the fuzzy aggregation method. The methodology developed in this paper is illustrated with a case study of the Thompson River near Spences Bridge in British Columbia, Canada. The results of the case study show that the selection of number of velocity measurement points on a vertical is the largest source of uncertainty in discharge measurement. An increase in the number of velocity measurement points provides the most effective reduction in the overall uncertainty. The next most important source of uncertainty for the case study location is the number of verticals used for velocity measurements. The study also shows that fuzzy set theory provides a suitable methodology for the uncertainty analysis of stage-discharge measurements. [ABSTRACT FROM AUTHOR]

Climate change has significant effects on the management of complex water resource systems. The objective of this study was to assess climate change effects on reservoir system operations. The assessment was performed using three greenhouse gas emission scenarios, four global climate models (GCMs), six downscaling methods, one hydrologic model, and a system dynamics simulation model (SDM). The analyses were conducted for a future time period (2036–2065) and results were compared with the historical time period (1984–2013). The Campbell River basin in British Columbia, Canada, was used as a case study area. The Campbell River basin consists of three reservoirs: Strathcona, Ladore, and John Hart. The results show that the inflow in all three reservoirs decreases during summer and fall, which decreases power production. In addition, it was observed that power production from downstream reservoirs (Ladore and John Hart) will decrease more drastically than the upstream reservoir (Strathcona) in the future. Results show that downscaling models contribute the highest level of uncertainty, which propagates from reservoir inflow to power production. The results of the study show that hydropower reliability will decrease more than 50% for all three reservoirs under future changing climate conditions. [ABSTRACT FROM AUTHOR]