Arid
DOI10.1016/j.compag.2014.08.007
Comparison of heuristic and empirical approaches for estimating reference evapotranspiration from limited inputs in Iran
Shiri, Jalal1; Nazemi, Amir Hossein1; Sadraddini, Ali Ashraf1; Landeras, Gorka2; Kisi, Ozgur3; Fard, Ahmad Fakheri1; Marti, Pau4
通讯作者Shiri, Jalal
来源期刊COMPUTERS AND ELECTRONICS IN AGRICULTURE
ISSN0168-1699
EISSN1872-7107
出版年2014
卷号108页码:230-241
英文摘要

Accurate estimation of reference evapotranspiration (ET0) values is of crucial importance in hydrology, agriculture and agro-meteorology issues. The present study reports a comprehensive comparison of empirical and semi empirical ET equations with the corresponding Heuristic Data Driven (HDD) models in a wide range of weather stations in Iran. Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM) and Gene Expression Programming (GEP) techniques are applied for modeling ET0 values considering different data management scenarios, and compared with corresponding Hargreaves-Samani (HS), Makkink (MK), Priestley-Taylor (PT), and Turc (T) ET0 models as well as their linear and non-linear calibrated versions along with the regression-based Copais algorithm. The obtained results confirm the superiority of GEP-based models. Further, the HDD models generally outperform the applied empirical models. Among the empirical models, the calibrated HS model found to give the most accurate results in all local and pooled scenarios, followed by the Copais and the calibrated PT models. In both local and pooled applications, the calibrated HS equation should be applied when no training data are available for the use of HDD models. The best results of the models correspond to the humid regions, while the arid regions provide the poorest estimates. This may be attributed to higher ET0 values associated with these stations and the high advective component of these locations. (C) 2014 Elsevier B.V. All rights reserved.


英文关键词ET0 models Heuristic data driven Iran Local application Pooled application
类型Article
语种英语
国家Iran ; Spain ; Turkey
收录类别SCI-E
WOS记录号WOS:000344436100026
WOS关键词ARTIFICIAL NEURAL-NETWORK ; FUZZY INFERENCE SYSTEM ; COUNTRY NORTHERN SPAIN ; ETO ANN MODELS ; COMPUTING TECHNIQUE ; CLIMATIC DATA ; SEMIARID CLIMATE ; HUMID CONDITIONS ; EVAPORATION ; ANFIS
WOS类目Agriculture, Multidisciplinary ; Computer Science, Interdisciplinary Applications
WOS研究方向Agriculture ; Computer Science
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/181460
作者单位1.Univ Tabriz, Fac Agr, Water Engn Dept, Tabriz, Iran;
2.AB Basque Country Res Inst Agr Dev, NEIKER, Alava, Basque Country, Spain;
3.Canik Basari Univ, Fac Engn & Architecture, Dept Civil Engn, Samsun, Turkey;
4.Univ Politecn Valencia, Dept Engn Rural Agr, Valencia, Spain
推荐引用方式
GB/T 7714
Shiri, Jalal,Nazemi, Amir Hossein,Sadraddini, Ali Ashraf,et al. Comparison of heuristic and empirical approaches for estimating reference evapotranspiration from limited inputs in Iran[J],2014,108:230-241.
APA Shiri, Jalal.,Nazemi, Amir Hossein.,Sadraddini, Ali Ashraf.,Landeras, Gorka.,Kisi, Ozgur.,...&Marti, Pau.(2014).Comparison of heuristic and empirical approaches for estimating reference evapotranspiration from limited inputs in Iran.COMPUTERS AND ELECTRONICS IN AGRICULTURE,108,230-241.
MLA Shiri, Jalal,et al."Comparison of heuristic and empirical approaches for estimating reference evapotranspiration from limited inputs in Iran".COMPUTERS AND ELECTRONICS IN AGRICULTURE 108(2014):230-241.
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