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We describe an efficient and flexible statistical modeling framework for projecting nonstationary streamflow extremes for the Fraser River basin in Canada, which is dominated by nival flow regime. The framework is based on an extreme value analysis technique that allows for nonstationarity in annual extreme streamflow by relating it to antecedent winter and spring precipitation and temperature. We used a representative suite of existing Variable Infiltration Capacity hydrologic model simulations driven by Coupled Model Intercomparison Project Phase 3 (CMIP3) climate simulations to train and evaluate a nonlinear and nonstationary extreme value model of annual extreme streamflow. The model was subsequently used to project changes under CMIP5-based climate change scenarios. Using this combination of process-based and statistical modeling, we project that the moderate (e.g., 2-20-year return period) extreme streamflow events will decrease in intensity. In contrast, projections of high intensity events (e.g., 100-200-year return period), which reflect complex interactions between temperature and precipitation changes, are inconclusive. The results provide a basis for developing a general understanding of the future streamflow extremes changes in nival basins and through careful consideration and adoption of appropriate covariates, the methodology could be employed for basins spanning a range of hydro-climatological regimes.