poster - International Conference of Agricultural Engineering
poster - International Conference of Agricultural Engineering
poster - International Conference of Agricultural Engineering
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indicates that ET o will increase/decrease as the variable increases. The larger the sensitivity<br />
coefficient, the larger effect a given variable has on ET o . In graphical form, the sensitivity<br />
coefficient is the slope <strong>of</strong> the tangent at the origin <strong>of</strong> the sensitivity curve. A sensitivity<br />
coefficient <strong>of</strong> 0.1 for a variable would in this case mean that a 10% increase <strong>of</strong> that variable,<br />
while all other variables are held constant, may increase ET o by 1%. Many researchers have<br />
used this methodology to characterize sensitivity models (Saxton, 1975; Coleman and<br />
DeCoursey, 1976; Piper, 1989; Meyer et al., 1989; Rana and Katerji, 1998) using different<br />
variables and equations. In the present study, sensitivity coefficients for each station were<br />
calculated on a daily basis for air temperature, wind speed, relative humidity and solar<br />
radiation. Monthly and yearly average sensitivity coefficients were obtained by averaging<br />
daily values.<br />
3. Results and Discussion<br />
Global warming due to greenhouse effect is expected to cause major changes in climate <strong>of</strong><br />
some areas (Goyal, 2004). The increase in temperature affects ET o primarily by increasing<br />
the capacity <strong>of</strong> air to hold water vapor. Daily sensitivity coefficients exhibit large fluctuations<br />
during the year at all locations. The same feature has also been reported by Hupet and<br />
Vanclooster (2001) and Gong et al. (2006). In general, net radiation (R n ) had large sensitivity<br />
coefficients thought the year at all cities. At all locations, the coefficients for temperature are<br />
systematically and significantly lower very close from zero to 0.15 than all other variables,<br />
but all variables exhibited large fluctuations during the year. Daily variation patterns <strong>of</strong><br />
sensitivity coefficients for air temperature (S T ) agree with those <strong>of</strong> air temperature. ET o is<br />
insensitive to temperature in winter and the sensitivity gradually increases and achieves its<br />
maximum value in summer (Fig. 1). The similar patterns <strong>of</strong> ST and air temperature indicate<br />
that air temperature determines the extent <strong>of</strong> the seasonal variation <strong>of</strong> ST. Fig. 1 shows that<br />
ET o is most sensitive to wind in winter season in Baft, Bam and Kerman, but, the fluctuations<br />
<strong>of</strong> the sensitivity coefficients <strong>of</strong> wind speed (S U2 ) is large in all <strong>of</strong> the day in Jir<strong>of</strong>t (Fig. 1d). In<br />
general, temperature and wind speed were less influential to ET o and their sensitivities were<br />
similar to each other in warm months. Sensitivity coefficients <strong>of</strong> vapor pressure deficit (S VPD )<br />
shows a pronounced seasonal cycle with a maximum value in January, February, March,<br />
October, November and December, similar to the seasonal cycle <strong>of</strong> the S U2 . The effects <strong>of</strong><br />
VPD, which increases the evaporation, reached higher levels during the winter and cold<br />
months. As it shown in Figs. 1a, b, c, S U2 and S VPD had a similar pattern in all cities. In<br />
winter, 10% change in VPD could cause approximately a 5%, 3.7%, 3.8% and 1.8% change<br />
in ET o in Kerman, Baft, Bam and Jir<strong>of</strong>t, respectively. But in summer months, 10% change in<br />
VPD could cause a 3.5%, 2.7%, 2.5% and 1.7% change in ET o in these cities. There was<br />
also a considerable difference Between Jir<strong>of</strong>t from others. The sensitivity coefficients <strong>of</strong> U 2 ,<br />
VPD and T are changes between zero to 0.4 in Jir<strong>of</strong>t. The sensitivity <strong>of</strong> evapotranspiration<br />
rates to changes in temperature and wind speed is less in Jir<strong>of</strong>t than in other study areas. In<br />
general, R n was the most sensitive variable at the daily scale in all <strong>of</strong> cities. Strong positive<br />
sensitivity coefficients indicated that increases in Rn greatly induce the potential<br />
evapotranspiration. In summer, 10% change in Rn could cause approximately a 6.5%, 7.4%,<br />
7.5% and 8.3% change in ET o in Kerman, Baft, Bam and Jir<strong>of</strong>t, respectively. In other words,<br />
The ET o estimates were very sensitive to R n , with an annual mean value <strong>of</strong> 0.58, 0.68, 0.70<br />
and 0.83 in Kerman, Bam, Baft and Jir<strong>of</strong>t, respectively (Table 2). This confirms that the<br />
radiation term in Penman-Monteith equation is generally dominant over the aerodynamic<br />
term in the prediction equation as reported by Beven (1979).<br />
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