Intensity-Duration-Frequency (IDF) curves describe the relationship between rainfall intensity, duration, and return period at a given location. They are crucial for infrastructure design, flood risk assessment, and stormwater management but are typically available only at specific measurement sites. A previous approach was developed to interpolate IDF curves by incorporating past climatology into a hierarchical Bayesian model using a Gaussian Markov random field. While this method improved accuracy and computational efficiency, its application was limited to Eastern Canada. This talk presents the integration of the Canadian Surface Reanalysis (CaSR) for interpolating extreme precipitation characteristics across Canada. The use of this reanalysis has been shown to enhance predictive performance, enabling more accurate IDF curve interpolation across Canada. By refining IDF curve estimation, this research supports improved planning, infrastructure resilience, and more effective water management strategies.
