Evaluating the generalizability of GEP models for estimating reference evapotranspiration in distant humid and arid locations

Evapotranspiration estimation is of crucial importance in arid and hyper-arid regions, which suffer from water shortage, increasing dryness and heat. A modeling study is reported here to cross-station assessment between hyper-arid and humid conditions. The derived equations estimate ET₀ values based on temperature-, radiation-, and mass transfer-based configurations. Using data from two meteorological stations in a hyper-arid region of Iran and two meteorological stations in a humid region of Spain, different local and cross-station approaches are applied for developing and validating the derived equations. The comparison of the gene expression programming (GEP)-based-derived equations with corresponding empirical-semi empirical ET₀ estimation equations reveals the superiority of new formulas in comparison with the corresponding empirical equations. Therefore, the derived models can be successfully applied in these hyper-arid and humid regions as well as similar climatic contexts especially in data-lack situations. The results also show that when relying on proper input configurations, cross-station might be a promising alternative for locally trained models for the stations with data scarcity.

     

Predicting daily pan evaporation by soft computing models with limited climatic data

Abstract

Accurate prediction of daily pan evaporation (PE) is important for monitoring, surveying, and management of water resources as well as reservoir management and evaluation of drinking water supply systems. This study develops and applies soft computing models to predict daily PE in a dry climate region of south-western Iran. Three soft computing models, namely the multilayer perceptron-neural networks model (MLP-NNM), Kohonen self-organizing feature maps-neural networks model (KSOFM-NNM), and gene expression programming (GEP), were considered. Daily PE was predicted at two stations using temperature-based, radiation-based, and sunshine duration-based input combinations. The results obtained by the temperature-based 3 (TEM3) model produced the best results for both stations. The Mann-Whitney U test was employed to compute the rank of different input combination for hypothesis testing. Comparison between the soft computing models and multiple linear regression model (MLRM) demonstrated the superiority of MLP-NNM, KSOFM-NNM, and GEP over MLRM. It was concluded that the soft computing models can be successfully employed for predicting daily PE in south western Iran.

Editor D. Koutsoyiannis     

New alternatives for reference evapotranspiration estimation in West Africa using limited weather data and ancillary data supply strategies.

Accurate estimation of reference evapotranspiration (ET ₀ ) is essential for the computation of crop water requirements, irrigation scheduling, and water resources management. In this context, having a battery of alternative local calibrated ET ₀ estimation methods is of great interest for any irrigation advisory service. The development of irrigation advisory services will be a major breakthrough for West African agriculture. In the case of many West African countries, the high number of meteorological inputs required by the Penman-Monteith equation has been indicated as constraining. The present paper investigates for the first time in Ghana, the estimation ability of artificial intelligence-based models (Artificial Neural Networks (ANNs) and Gene Expression Programing (GEPs)), and ancillary/external approaches for modeling reference evapotranspiration (ET ₀ ) using limited weather data. According to the results of this study, GEPs have emerged as a very interesting alternative for ET ₀ estimation at all the locations of Ghana which have been evaluated in this study under different scenarios of meteorological data availability. The adoption of ancillary/external approaches has been also successful, moreover in the southern locations. The interesting results obtained in this study using GEPs and some ancillary approaches could be a reference for future studies about ET ₀ estimation in West Africa.