Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate Stations

Reference evapotranspiration (ET0) plays important roles in environmental, hydrological and agricultural studies and its accurate prediction is significant in water resources management and water productivity increase. This study focused on evaluating the ability of support vector regression (SVR) m...

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Main Authors: Ala Tahsin, Jazuli Abdullahi
Format: Article
Language:English
Published: Ishik University 2020-06-01
Series:Eurasian Journal of Science and Engineering
Subjects:
Online Access:https://eajse.tiu.edu.iq/index.php/volume-6-issue-1-article-7/
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spelling doaj-885778b932e04f1997058806223dd9b32021-02-14T11:39:42ZengIshik UniversityEurasian Journal of Science and Engineering2414-56292414-56022020-06-01618910310.23918/eajse.v6i1p89Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate StationsAla Tahsin0Jazuli Abdullahi1Department of Civil Engineering, Faculty of Engineering, Tishk International University, IraqDepartment of Civil Engineering, Faculty of Civil and Environmental Engineering, Near East University, Nicosia, CyprusReference evapotranspiration (ET0) plays important roles in environmental, hydrological and agricultural studies and its accurate prediction is significant in water resources management and water productivity increase. This study focused on evaluating the ability of support vector regression (SVR) model for modeling ET0 in arid and semiarid climate stations of Iraq. For comparison, multiple linear regression (MLR) and calibrated Hargreaves and Samani (HS) empirical models were also applied. Daily meteorological data from Basra and Erbil stations including minimum, maximum and mean temperatures, relative humidity, wind speed, precipitation, solar radiation and surface pressure were collected for two consecutive years (2017 – 2018) and used as inputs to the models. FAO 56 Penman-Monteith was used as the benchmark ET0. Root mean square error (RMSE) and Nash Sutcliffe efficiency criterion (NSE) were the performance evaluation criteria employed. The results revealed that, all the applied models led to reliable results, but SVR model provided the best performance with NSEs of 0.9949, 0.9871 and RMSEs of 0.0009, 0.0016 in the validation phase for Basra and Erbil stations, respectively. The general results implied that SVR model could be employed successfully for estimation of ET0 in arid and semiarid climate stations of Iraq.https://eajse.tiu.edu.iq/index.php/volume-6-issue-1-article-7/deep excavationfinite elementpre-stressed tie back anchorscontiguous pile wallplaxishorizontal deflectionground settlement
collection DOAJ
language English
format Article
sources DOAJ
author Ala Tahsin
Jazuli Abdullahi
spellingShingle Ala Tahsin
Jazuli Abdullahi
Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate Stations
Eurasian Journal of Science and Engineering
deep excavation
finite element
pre-stressed tie back anchors
contiguous pile wall
plaxis
horizontal deflection
ground settlement
author_facet Ala Tahsin
Jazuli Abdullahi
author_sort Ala Tahsin
title Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate Stations
title_short Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate Stations
title_full Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate Stations
title_fullStr Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate Stations
title_full_unstemmed Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate Stations
title_sort reference evapotranspiration modeling using heuristic computing model in distinct climate stations
publisher Ishik University
series Eurasian Journal of Science and Engineering
issn 2414-5629
2414-5602
publishDate 2020-06-01
description Reference evapotranspiration (ET0) plays important roles in environmental, hydrological and agricultural studies and its accurate prediction is significant in water resources management and water productivity increase. This study focused on evaluating the ability of support vector regression (SVR) model for modeling ET0 in arid and semiarid climate stations of Iraq. For comparison, multiple linear regression (MLR) and calibrated Hargreaves and Samani (HS) empirical models were also applied. Daily meteorological data from Basra and Erbil stations including minimum, maximum and mean temperatures, relative humidity, wind speed, precipitation, solar radiation and surface pressure were collected for two consecutive years (2017 – 2018) and used as inputs to the models. FAO 56 Penman-Monteith was used as the benchmark ET0. Root mean square error (RMSE) and Nash Sutcliffe efficiency criterion (NSE) were the performance evaluation criteria employed. The results revealed that, all the applied models led to reliable results, but SVR model provided the best performance with NSEs of 0.9949, 0.9871 and RMSEs of 0.0009, 0.0016 in the validation phase for Basra and Erbil stations, respectively. The general results implied that SVR model could be employed successfully for estimation of ET0 in arid and semiarid climate stations of Iraq.
topic deep excavation
finite element
pre-stressed tie back anchors
contiguous pile wall
plaxis
horizontal deflection
ground settlement
url https://eajse.tiu.edu.iq/index.php/volume-6-issue-1-article-7/
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