Statistical Analysis of Rainfall Intensity-Duration-Frequency Curves

Rainfall Intensity-Duration-Frequency (IDF) curves form the foundation of hydrologic design in water resources engineering. As climate patterns shift, traditional methods require enhancement with modern statistical techniques and updated datasets.

Extreme Value Theory Application

Gumbel and Generalized Extreme Value (GEV) distributions remain standard for frequency analysis. Recent research demonstrates that the GEV distribution provides superior fit for short-duration, high-intensity events common in urban environments. Parameter estimation via L-moments offers improved reliability compared to method of moments, particularly for limited record lengths.

Non-Stationarity Considerations

Historical IDF curves assume stationary climate conditions—an assumption increasingly challenged by observed trends. Time-varying parameters in GEV models can capture temporal trends in rainfall extremes. Engineers should consider updating IDF curves every 10-15 years using the most recent 30-50 years of data.

Practical Implementation

Python’s scipy.stats library provides robust tools for distribution fitting. Combined with precipitation data from NOAA Atlas 14, engineers can develop site-specific IDF curves that account for local topography and recent climatic trends.