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Engineering Advances

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Article Open Access http://dx.doi.org/10.26855/ea.2022.12.002

Modelling of Reference Evapotranspiration Parameters in South Africa Using Fuzzy Inference Systems

Akinola Ikudayisi1, Andre Calitz2, Mahmoud Nasr3, Samuel Abejide1,*

1Department of Civil Engineering, Walter Sisulu University, East London, 5200, South Africa.

2Department of Computing Sciences, Nelson Mandela University, Gqeberha, South Africa.

3Sanitary Engineering Department, Faculty of Engineering, Alexandria University, P.O. Box 21544, Alexandria, Egypt.

*Corresponding author: Samuel Abejide

Published: November 10,2022

Abstract

Effective planning, design and management of irrigation water resources requires the estimation of reference evapotranspiration (ET₀). Standard Penman - Monteith (PM) equation, also called FAO – 56 method, was approved by the United Nations for estimating ET₀. However, in many developing countries, such as South Africa, a major limitation to the successful use of this FAO – 56 method, is the non-availability or limited data sets of the required input variables. It is imperative to develop alternative methods for estimating ETₒ . This study models weather and meteorological parameters considered in the estimation of ETₒ by performing multivariate analysis of the correlated variables, using adaptive neuro-fuzzy inference systems (ANFIS). Weather and Meteorological data between 2001 and 2020 for Winterton irrigation scheme (WIS) in South Africa were used in this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind-speed (m/s) were inputs to the ANFIS model, with ETₒ as output. ANFIS indicated that temperature gradients and wind-speed have the highest impact on ETₒ while rainfall and relative humidity have lower significance on ETₒ. The correlation of temperature and wind speed with ETₒ was presented using input-output surface viewer. This study improves ETₒ estimation.

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How to cite this paper

Modelling of Reference Evapotranspiration Parameters in South Africa Using Fuzzy Inference Systems

How to cite this paper: Akinola Ikudayisi, Andre Calitz, Mahmoud Nasr, Samuel Abejide. (2022). Modelling of Reference Evapotranspiration Parameters in South Africa Using Fuzzy Inference Systems. Engineering Advances2(2), 147-155.

DOI: http://dx.doi.org/10.26855/ea.2022.12.002