PS1: Nonstationary Rainfall Frequency Analysis (Due Oct 6)
Houston Daily Rainfall Extremes and Climate Change
Comprehensive analysis of nonstationary rainfall extremes using EVT, Bayesian methods, and hierarchical modeling
1 Tasks
- Fit stationary GEV model to Houston Hobby station data using MLE and Bayesian approaches
- Assess nonstationarity evidence using rolling window analysis and Mann-Kendall test; repeat for 5 nearby stations to identify spatial patterns
- Compare station-level analyses to identify which locations show strongest trends and evaluate consistency across the region
- Fit nonstationary GEV model with time-varying location parameter; choose and defend covariate selection (year vs. temperature indices)
- Implement regional partial pooling across all stations using hierarchical Bayesian model to improve parameter estimates
- Address stakeholder concerns: In 2 paragraphs, explain how you would respond to a senior engineer who is skeptical about using climate-informed design values instead of stationary historical analysis