Model-based decomposition reveals spatially varying temporal shifts in seasonal streamflow profiles across north temperate US Rivers

Understanding changes in the timing and magnitude of streamflows available to maintain riverine biodiversity and ecological function, while also meeting the increasing societal demands on water resources, is a global priority. A rigorous quantification of seasonal changes in streamflow is needed to inform water management and policy under global change. We introduce a hierarchical Bayesian model that quantifies spatiotemporal variation in seasonal streamflow profiles and allows for inferences on temporal trends in model-based indices related to streamflow timing and magnitude shifts.