# Modeling Extreme Rainfall Using the Generalized Extreme Value Distribution and Exceedance Analysis in Colima, Mexico

## TL;DR

This paper uses statistical models and maps to study extreme rainfall in Colima, Mexico, helping assess flood risks and improve planning.

## Contribution

The study integrates GEV distribution and spatial visualization to model extreme rainfall and create exceedance maps for Colima.

## Key findings

- Northern and western Colima experience the highest frequencies of extreme rainfall events.
- Exceedance maps reveal consistent geographic patterns in rainfall intensity.
- Integration of real-time sensors and satellite data could enhance flood monitoring.

## Abstract

This study develops a statistical and technological framework to analyze extreme rainfall in Colima, Mexico, by integrating historical precipitation records, probabilistic modeling, and spatial visualization. Using data from CONAGUA meteorological stations, we identify high-intensity rainfall events and model their recurrence using the Generalized Extreme Value (GEV) distribution to estimate key return periods. The results support flood-risk assessment and territorial planning in Colima. Spatial interpolation was performed in Python (version 3.13), and QGIS (version 3.38) produces exceedance maps that illustrate geographic variations in rainfall intensity across the state. These exceedance maps reveal a consistent spatial pattern, with the northern and western areas of Colima experiencing the highest frequencies of extreme events. Based on these results, the integration of real-time sensor technologies and satellite observations may improve flood monitoring and risk management frameworks.