Asian Journal of Geographical Research

Accurate estimation of reference evapotranspiration (ETo) is essential for effective irrigation scheduling, water-resource management, and crop-climate modelling in tropical regions where weather data are often limited. This study presents the development and validation of a Flutter-based Android application capable of computing near-real-time ETo using the FAO-56 Penman–Monteith (FAO-56 PM) model. The app integrates meteorological data from the OpenWeatherMap API and utilises firebase geolocator for site-specific retrieval of temperature, humidity, wind speed, and solar radiation. Validation was performed against the NASA POWER database for 11 consecutive days (4–14 April 2024) using 24-hour averaged datasets to remove diurnal bias. Results showed close agreement between app- and NASA-derived parameters: temperature (mean bias = +0.35 °C), relative humidity (-0.9 %), wind speed (+0.01 m s^-¹), and ETo (+0.03 mm day^-¹). Statistical evaluation indicated a strong correlation (r = 0.93; R² = 0.86) and low root mean square error (RMSE = 0.05 mm day^-¹). These results confirm the app’s reliability and computational fidelity. Comparative analysis with existing tools such as EVAPO, EvapoCalc, and pyfao56 revealed comparable accuracy while offering the advantage of real-time mobile accessibility. The application bridges a technological gap by providing a cost-effective, portable, and adaptive system for field-level ETo estimation, particularly valuable for smallholder farmers and irrigation managers in data-scarce environments.