Volume 11, Issue 2 (8-2024)
Journal of Spatial Analysis Environmental Hazards 2024, 11(2): 0-0 |
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Jahanbakhsh ASL S, Dinpashoh Y, Azadeh Garebagh A. Investigation of Relative Importance of Meteorological Variables on Potential Reference Crop Evapotranspiration in Southern Alborz Region Introduction. Journal of Spatial Analysis Environmental Hazards 2024; 11 (2)
URL: http://jsaeh.khu.ac.ir/article-1-3436-en.html
URL: http://jsaeh.khu.ac.ir/article-1-3436-en.html
1- , Dept. of Climatology, University of Tabriz , s_jahan@tabrizu.ac.ir
2- Dept. of Water Engineering, University of Tabriz
3- , Dept. of Climatology, University of Tabriz
2- Dept. of Water Engineering, University of Tabriz
3- , Dept. of Climatology, University of Tabriz
Abstract: (622 Views)
Evapotranspiration is one of the main elements of hydrologic cycle. Accurate determination of reference crop potential evapotranspiration (ET0) is crucial in efficient use of water in irrigation practices. ET0 can be measured directly by lysimeters or estimated indirectly by many different empirical methods. Direct measurement is cumbersome, needs for more time and costly. Therefore, many investigators used empirical methods instead of direct measurements to estimate ET0. Nowadays, the FAO-56 Penman Monteith (PMF56) method is known a bench mark for comparing the other empirical methods. For example, in the works of Zare Abyaneh et al. (2016), Biazar et al. (2019), Dinpashoh et al. (2021) and Dinpashoh et al. (2011) PMF56 method was used to estimate ET0 and comparing the outputs of other empirical methods. Many researchers analyzed trends in ET0 time series in different sites around the Earth. Among them it can be referred to the works of Sabziparvar et al. (2008), Babamiri & Dinpashoh (2015), Dinpashoh et al. (2021), Dinpashoh (2026) and Tabari et al. (2013). ET0 can be affected by many different climatic factors such as maximum air temperature (Tmax), minimum air temperature (Tmin), relative humidity (RH), wind speed, and actual sunshine hours. Factor analysis (FA) is a multivariate method that reduces data dimensionality. In general, climatic variables have high correlation with each other. On the other hand, these variables affect ET0. The FA can be used to reduce data dimensionality in which correlated variables converted to few uncorrelated factors.
Type of Study: Research |
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Received: 2024/03/13 | Accepted: 2024/08/21 | Published: 2024/09/15
Received: 2024/03/13 | Accepted: 2024/08/21 | Published: 2024/09/15
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