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	Estimating the Hourly Reference Evapotranspiration with Fuzzy Inference Systems
	Naderianfar, Mohammad; Moradi, Hourie; Ansari, Hossein
通讯作者	Naderianfar, M
来源期刊	INTERNATIONAL JOURNAL OF ADVANCED BIOTECHNOLOGY AND RESEARCH
ISSN	0976-2612
EISSN	2278-599X
出版年	2017
卷号	8 页码:50-59
英文摘要	Evapotranspiration is the most important part of the hydrological cycle, which plays a key role in water resource management, crop yield simulation, and irrigation scheduling. Therefore, developing a cost-effective and precise model is essential for estimating hourly grass crop reference evapotranspiration (ETo). In this study the potential of the fuzzy inference system (FIS) is investigated as a simple technique for modeling hourly ETo obtained using the FAO-56 Penman-Monteith and ASCE equations. Then, combinations of efficient hourly climatic data namely temperature, wind speed, relative humidity and solar radiation were used as inputs to the fuzzy model. Four fuzzy models were developed based on different combinations of inputs. Common statistics such as Mean square error, average absolute relative error and determination coefficient and two more statistics of Jacovides (t) and R-2/t are used as comparison criteria for evaluation of the model performance. Here, Training and testing fuzzy models were done with Fariman meteorological data - an arid region in the northeast of Iran. The fuzzy model whose inputs are solar radiation, air temperature, relative humidity and wind speed, yield the highest correlation and compatibility to reference models of FAO-56 PM and ASCE, based on common statistics. Whereas, the fuzzy model whose inputs are solar radiation, air temperature and relative humidity, are selected as the best model based on combination of common and additional statistics. The fuzzy model with two inputs namely solar radiation and relative humidity has acceptable results, too. The results show that solar radiation is the most effective parameter on hourly reference evapotranspiration and temperature, relative humidity and wind speed were other effective parameters, respectively. These results for training and testing phase are alike. It was found that the developed fuzzy models could be successfully employed in estimating the hourly ETo with a limited weather data.
英文关键词	Fuzzy Inference System Hourly Reference Evapotranspiration ASCE model FAO-56 Penman-Monteith Model
类型	Article
语种	英语
收录类别	ESCI
WOS记录号	WOS:000417344700005
WOS类目	Biotechnology & Applied Microbiology
WOS研究方向	Biotechnology & Applied Microbiology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/332394
作者单位	[Naderianfar, Mohammad] Univ Jiroft, Water Engn Dept, Jiroft, Iran; [Moradi, Hourie] Ferdowsi Univ Mashhad, Water Engn Dept, Irrigat & Drainage, Mashhad, Iran; [Ansari, Hossein] Ferdowsi Univ Mashhad, Water Engn Dept, Mashhad, Iran
推荐引用方式 GB/T 7714	Naderianfar, Mohammad,Moradi, Hourie,Ansari, Hossein. Estimating the Hourly Reference Evapotranspiration with Fuzzy Inference Systems[J],2017,8:50-59.
APA	Naderianfar, Mohammad,Moradi, Hourie,&Ansari, Hossein.(2017).Estimating the Hourly Reference Evapotranspiration with Fuzzy Inference Systems.INTERNATIONAL JOURNAL OF ADVANCED BIOTECHNOLOGY AND RESEARCH,8,50-59.
MLA	Naderianfar, Mohammad,et al."Estimating the Hourly Reference Evapotranspiration with Fuzzy Inference Systems".INTERNATIONAL JOURNAL OF ADVANCED BIOTECHNOLOGY AND RESEARCH 8(2017):50-59.