Introducing Non-Stationarity Into the Development of Intensity-Duration-Frequency Curves under a Changing Climate

Intensity-duration-frequency (IDF) relationships are traditional tools in water infrastructure planning and design. IDFs are developed under a stationarity assumption which may not be realistic, neither in the present nor in the future, under a changing climatic condition. This paper introduces a framework for generating non-stationary IDFs under climate change, assuming that probability of occurrence of quantiles changes over time. Using Extreme Value Theory, eight trend combinations in Generalized Extreme Value (GEV) parameters using time as covariate are compared with a stationary GEV, to identify the best alternative. Additionally, a modified Equidistance Quantile Matching (EQM(NS)) method is implemented to develop IDFs for future conditions, introducing non-stationarity where justified, based on the Global Climate Models (GCM). The methodology is applied for Moncton and Shearwater gauges in Northeast Canada. From the results, it is observed that EQM(NS) is able to capture the trends in the present and to translate them to estimated future rainfall intensities. Comparison of present and future IDFs strongly suggest that return period can be reduced by more than 50 years in the estimates of future rainfall intensities (e.g., historical 100-yr return period extreme rainfall may have frequency smaller than 50-yr under future conditions), raising attention to emerging risks to water infrastructure systems.

Automated summary

This study introduces a framework for generating non-stationary IDFs under climate change by assuming that the probability of occurrence of quantiles changes over time. The results show that EQM(NS) can capture trends in the present and translate them to estimated future rainfall intensities. The comparison of present and future IDFs suggests a significant reduction in return period for future rainfall intensities, highlighting emerging risks to water infrastructure systems.