Development of an integrated rainfall prediction and water allocation model for improved runoff dam management.

Abstract

Water scarcity is a persistent challenge in semi-arid regions like Karamoja in northeastern Uganda, where effective water resource management is critical for agricultural sustainability. This study presents a decision-support model for the Kobebe Dam catchment that integrates rainfall prediction, runoff estimation, and dynamic water allocation to optimize water availability and usage. A machine learning approach was employed to forecast rainfall using 33 years of historical weather data from NOAA and NASA, including variables such as temperature, humidity, wind speed, and pressure. Among the three models tested Random Forest, XGBoost, and Linear Regression the Random Forest Regressor demonstrated superior performance, achieving an RMSE of 0.00575 mm, MAE of 0.00244 mm, and an R² of 0.99998. Its high accuracy provided reliable monthly rainfall forecasts, including a predicted 35 mm for May 2025. Using the Soil Conservation Service Curve Number (SCS-CN) method, rainfall predictions were converted into runoff estimates. Soil and land use data sourced from FAO and local hydrological assessments produced a weighted average Curve Number of 69.33. For May 2025, the runoff depth was estimated at 0.89 mm, corresponding to a total runoff volume of approximately 9.72 million litres flowing into Kobebe Dam—highlighting its potential for meaningful rainwater harvesting. A flexible water allocation algorithm was then applied to simulate various distribution strategies based on available runoff, crop water requirements, and management priorities. Initial tests used demonstration ratios of 80%, 15%, and 5% to validate the algorithm’s capacity to model diverse allocation scenarios. These ratios are not fixed but are intended to explore “what-if” situations, allowing iterative evaluation of water distribution outcomes under changing conditions. This adaptability supports the identification of optimal allocation strategies that ensure sustainable water use and continuous crop production, ultimately enhancing water security in the region.