Generalized gene expression programming models for estimating reference evapotranspiration through cross-station assessm

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RESEARCH ARTICLE

Generalized gene expression programming models for estimating reference evapotranspiration through cross-station assessment and exogenous data supply Mohammad Hossein Kazemi 1 & Abolfazl Majnooni-Heris 1 & Ozgur Kisi 2,3 & Jalal Shiri 1,4 Received: 7 July 2020 / Accepted: 17 September 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020

Abstract Adopting methodologies utilizing exogenous data from ancillary stations for determining crop water requirement is a suitable approach to exempt local shortcomings due to the lack of meteorological data/stations. Meanwhile, soft computing techniques might be suitable tools to be used with such data management scenarios. The present paper aimed at evaluating the generalizability of the gene expression programming (GEP) technique for estimating reference evapotranspiration (ET0) through crossstation assessment and exogenous data supply, using data from Turkey and Iran. The GEP-based models were established and learnt using data from 10 stations in Turkey, and then the developed models were tested (validated) in 18 stations of Iran with considerable latitude differences. Different time periods (beginning and the end of time series) were selected for the training and testing stations so that there was no overlap among the dates of the events in both the groups. A comparison was also performed between the GEP models and the corresponding commonly used empirical equations. The obtained results revealed that the generalized GEP models presented promising outcomes in simulating daily ET0 values when they were trained and tested in quite distant stations with different chronological periods of the applied parameters. The performance accuracy of the empirical equations calibrated using exogenous data was reduced in comparison with their original (non-calibrated) versions. Further, although the generalization ability of the GEP models was reduced when the climatic context of the training-testing stations was different, the overall performance accuracy of those models was higher than those of the commonly used classic empirical equations. Keywords Data management . Data supplanting . Extrapolation . Generalized models

Introduction The simulation of reference evapotranspiration (ET0) that is an important parameter of hydrological cycle is substantial for water resources management, hydrological/environmental Responsible Editor: Marcus Schulz * Jalal Shiri [email protected] 1

Water Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

2

Civil Engineering Department, Ilia State University, Tbilisi, Georgia

3

Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam

4

Center of Excellence in Hydro-informatics, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

studies, and irrigation scheduling. By precisely simulating ET0, irrigation can be made with considerable savings. ET0 can be identified by lysimeters, which produce precise measurements typically utilized in validating som