Abstract
ABSTRACT The empirical models commonly employed as alternatives for estimating evapotranspiration provide constraints and yield inaccurate results when applied to Nigeria. This study aims to develop novel empirical models to enhance evapotranspiration (ET0) estimation accuracy in Nigeria. The coefficients of non-linear equations were optimised using the particle swarm optimisation (PSO) algorithm for the development of the two new ET0 models for Nigeria, Awhari1 (temperature-based) and Awhari2 (mass transfer-based). ERA5 reanalysis data with a 0.1° × 0.1° resolution was used. The models were rigorously assessed against the FAO-56 Penman–Monteith method, resulting in Kling–Gupta efficiency (KGE) and percentage bias (Pbias) values of 0.75, 6.49, and 0.92, 5.67, respectively. The spatial distribution analysis of performance metrics showed both equations exhibited superior accuracy in estimating ET0 across diverse climatic zones in Nigeria. The incorporation of PSO in model development, coupled with spatial analysis, highlights the study's multidimensional approach. The spatial performance of the models indicates that they can be valuable tools for water resource management, irrigation planning, and sustainable agriculture practices in Nigeria.
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