Uncertainty surrounds the understanding of natural variability in hydrologic extremes such as droughts and floods and how these events are projected to change in the future. This thesis leverages Global Climate Model (GCM) data to analyse 738 year streamflow scenarios in the Nelson-Churchill River Basin. Streamflow scenarios include a 500 year stationary period and future projections forced by two forcing scenarios. Fifty three GCM simulations are evaluated for performance in reproducing observed runoff characteristics. Runoff from a subset of nine simulations is routed to generate naturalized streamflow scenarios. Quantile mapping is then applied to reduce volume bias while maintaining the GCM’s sequencing of events. Results show evidence of future increases in mean annual streamflow and evidence that mean monthly streamflow variability has decreased from stationary conditions and is projected to decrease further into the future. There is less evidence of systematic change in droughts and floods. / May 2016

This project summarizes the findings of research organized in two parts. The first involved the characterization of changes in the variability of climate that lead to extreme events. The second focused on the predictability of extreme climate on time-scales ranging from short forecast lead-times to long-lead climate predictions exceeding a year. Initial studies focused on three interrelated, yet regionally unique extreme climate phenomena. First, the relationship between increasing greenhouse gas (GHG) emissions and particulate matter (PM) concentration in basin terrain was investigated. Next, we evaluated changes in large-scale atmospheric circulation associated with two climate phenomena at either extreme side of the water cycle--droughts and floods. In the final analysis, an attempt was made to understand the mechanisms that link two North Pacific ENSO precursor patterns to the ENSO cycle.