Extreme-value analysis for the characterization of extremes in water resources: A generalized workflow and case study on New Mexico monsoon precipitation

In this arid watershed, extreme precipitation events substantially contribute to total runoff. An improved understanding of the drivers and extent of changes in extreme precipitation is essential for water resource and risk management. In addition to a stationary PP model without covariates, several covariates are examined for inclusion in the location and scale parameters.

The significance of including the covariates is assessed, as well as several additional criteria, including if the covariate (s) make intuitive sense and if it is a good candidate for statistical downscaling (i.e., methods that relate largescale variables to the local scale). A final PP model is selected that includes the wet weather types in the location and scale parameters. This model is applied in a downscaling context using a large ensemble of climate projections, which shows that the frequency of exceeding a high threshold increases after 2050, but the conditional likelihood of exceeding the maximum observed precipitation stays relatively constant.