Forecasting Rainfall Cycles to Support Irrigation in the Arch Hurley Conservancy District

Rainfall across eastern New Mexico is highly variable, creating uncertainty for farmers and water managers who depend on Conchas Lake and the Arch Hurley Conservancy District’s 41,000 irrigated acres. The problem is to determine whether computer modeling can use historical rainfall data to forecast future wet, dry, and moderate seasons that affect irrigation planning.

The purpose of this project is to analyze rainfall records from 1999 to 2023 and simulate future rainfall cycles through 2030 to improve drought preparation and water management in Quay County. Accurate seasonal forecasts can help communities plan for water shortages, reduce risk, and promote long-term sustainability.

To address this, I will develop a NetLogo simulation that inputs annual rainfall data, classifies each year by category using statistical thresholds, and applies forecasting algorithms to predict upcoming conditions. Model output will be compared to historical cycles to test accuracy. Research with local experts and data from sources such as NOAA, NMSU, and the Arch Hurley Conservancy District will guide model validation.

By combining real data with computational modeling, this project demonstrates how supercomputing and data analysis can be applied to solve real-world environmental challenges in New Mexico.