F. Khadempour; B. Bakhtiari; S. Golestani
Abstract
Introduction: In drainage and irrigation network capacity design and determination, reference evapotranspiration (ETo) plays significant role. Methods applied for estimated reference evapotranspiration classified in two direct and computational methods. Amongst computational methods it might point to ...
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Introduction: In drainage and irrigation network capacity design and determination, reference evapotranspiration (ETo) plays significant role. Methods applied for estimated reference evapotranspiration classified in two direct and computational methods. Amongst computational methods it might point to Penman-Monteith method. This method requires radiation, temperature, humidity and wind speed data with high reliability rate in vast ranges of climates and areas represent precise outcome from reference plant Evapotranspiration.
Materials and Methods: Study stations in De Martonne classification system are divided into 6 climates such as Hyper-arid, Arid, Semi-arid, Mediterranean, Humid and Very humid (a) climates. Study stations statistical span during 19 years (1996-2015) were selected and temperature, relative humidity, sunshine hours, and wind speed in 2 meter height daily data were used. Figure 1 showed studied stations position all over the country. In this study, in order to obtain daily ETo, Penman-Monteith standard method represented by FAO-56 was used. In local sensitivity analysis, factors local influences on model output were shown. Such an analysis usually carried out through output functions minor deviants computation due to input variables. In this analysis, usually it was used one-factor- at-a- time method (OAT), so that, one variable factor and other input factors kept constant.
Figure 1. The geographical location of weather stations
The FAO-56 PM model for estimating ETo is as follows (3).
(1)
where ETo is reference crop evapotranspiration (mm day−1), Δ is the slope of vapor pressure versus temperature curve at temperature Tmean (kPa°C−1), γ is the psychometric constant (kPa °C−1), u2 is the wind speed at a 2 m height (m s−1), Rn is the net radiation at crop surface (MJ m−2 d−1), G is the soil heat flux density (MJ m−2 d−1), T is the mean daily air temperature at 2 m height (°C), and (es-ea) is the saturation vapor pressure deficit (kPa).
Results and Discussion: Weather parameters in stations showed that mean temperature sensitivity coefficient ( ) in all study stations varied between 0.21 to 0.78 so that the maximum temperature sensitivity coefficient related to Bushehr station in arid climate (in April, May, June, July, October and November) and minimum temperature sensitivity coefficient related to Shahrekordstation in semi-arid climate (in January, March, April and November). Maximum and minimum net radiation sensitivity coefficient value ( ) related to Rasht and Zahedanstations respectively. Also, maximum and minimum wind speed sensitivity coefficient value ( ) related to Zahedan and Ardebilstations are 0.54 and 0.07 respectively. Yazd station in Hyper-arid climate showed minimum relative humidity sensitivity coefficient value ( ) about 0.20 and Rasht station in very-humid (a) showed the maximum values 0.45. So the northern coastal areas are more sensitive to and SRH. The highest value is in northern coastal areas and lowest in southern coastal and southwest areas of the country. Some other studies showed that in many climates evapotranspiration was more sensitive to Rn (6, 14 and 17).In current study, also, showed the highest sensitivity in Very-humid climate (a) includes Rasht station in February, March, April, October and November. For example, = 0.82 means that 100% increase in Rn parameter result in 82% increase in ETo.
Conclusion: Sensitivity analysis experiment on FAO Penman-Monteith standard method is one of the most efficient methods to understand various climate parameters influence on reference evapotranspiration (ETo). In this study, results showed that computed ETo in all climates showed highest sensitivity to Rn and temperature respectively. Temperature sensitivity coefficient showed the highest value at April. May, June, July, October and November and Rn showed its highest value at March, April, October and November. While, minimum in all of months but May and July and maximum value showed in January, July, August and September by 0.07 and 0.54 respectively. So, in most months of the spring and the fall was larger and smaller during the winter months. Sensitivity coefficient related to mean temperature is higher during summer season and lower during winter season. Results of this study may be useful for assessing the response of the standardized FAO Penman-Monteith model in different climatic conditions. The results can also be used to predict changes in ETo values with respect to climatic variable changes obtained from climate change models.
