Advancing nonstationarity hydroclimate frequency analysis through regional information and multi-covariate models

This project aims to improve the prediction of extreme precipitation by enhancing a widely used open-source tool for frequency analysis. Predicting these extremes remains challenging, particularly when incorporating physical covariates and complex models, which often lead to instability in estimation methods. The updated framework will include advanced models that account for a changing climate using one or more physical covariates and leveraging regional hydroclimate information across Canada to improve predictions. The project will provide practical solutions for water management agencies, researchers, and policymakers. Through collaboration between USask and UNAM, this initiative will strengthen expertise in climate-resilient water management and deliver tools to help protect communities and infrastructure from the growing flood risks. The partnership will also result in joint publications and future research proposals to pursue additional funding opportunities.

Faculty Supervisor:

Cuauhtemoc Tonatiuh Vidrio Sahagun

Student:

Partner:

Universidad Nacional Autónoma de México

Discipline:

Engineering

Sector:

Education

University:

University of Saskatchewan

Program: