Projected Crop Coefficients Under Climate Change in Egypt
275
on Kc values of different crops. Furthermore, there is no local studies were done to
tackle this subject.
Thus, the objective of this chapter was to quantify how climate change will affect
the value of Kc for several important crops in Egypt. One way to do so is to develop
a procedure to accurately estimate Kc values for 14 field crops, 7 fruit crops and 13
vegetable crops in the five agro-climatic zones of Egypt in 2030.
2 Methodology
2.1 Climate Change Scenario
Climate change scenario RCP6.0 resulted from MIROC5 model in 2030 was used in
this analysis. It is available from the following website: http://www.ccafs.cgiar.org/
marksimgcm#.Ujh1gj-GfMY. The MIROC5 model is one on the CMIP5 General Circulation Models developed by Atmosphere and Ocean Research Institute (The University of Tokyo), National Institute for Environmental Studies, and Japan Agency
for Marine-Earth Science and Technology. The model has a horizontal resolution
equal to 1.40° × 1.40°.
MIROC5 model produces four RCPs climate change scenarios. RCP6.0 climate
change scenario is one of them, where it represents a larger set of mitigation scenarios
and radiative forcing targets in 2100. In this scenario, the total radiative forcing
is stabilized shortly after 2100, without overshoot by the application of a range
of technologies and strategies for reducing greenhouse gas emissions. Thus, it is
considered as a stabilization scenario [29, 30].
2.2 The Projected Value of ETo Using Hargreaves-Samani
Equation
The RCP6.0 climate change scenario contained maximum and minimum temperature, as well as solar radiation data, which are suitable to calculate ETo using
Hargreaves-Samani (H-S) equation [31]. However, the accuracy of HargreavesSamani (H-S) equation is lower than its counterpart of Penman-Monteith (P-M)
equation [16], which requires using solar radiation, maximum, minimum and dew
point temperature, as well as wind speed. Furthermore, Penman-Monteith (P-M)
equation is widely recommended because of its detailed theoretical base and its
accommodation of small time periods [32]. To solve this problem, a linear regression equation can be established with ETo values resulted from P-M plotted as the
dependent variable and ETo values from H-S equation to be plotted as the independent variable. The intercept (a) and calibration slope (b) of the best-fit regression line
can be used as regional calibration coefficients. This methodology was developed by
275
on Kc values of different crops. Furthermore, there is no local studies were done to
tackle this subject.
Thus, the objective of this chapter was to quantify how climate change will affect
the value of Kc for several important crops in Egypt. One way to do so is to develop
a procedure to accurately estimate Kc values for 14 field crops, 7 fruit crops and 13
vegetable crops in the five agro-climatic zones of Egypt in 2030.
2 Methodology
2.1 Climate Change Scenario
Climate change scenario RCP6.0 resulted from MIROC5 model in 2030 was used in
this analysis. It is available from the following website: http://www.ccafs.cgiar.org/
marksimgcm#.Ujh1gj-GfMY. The MIROC5 model is one on the CMIP5 General Circulation Models developed by Atmosphere and Ocean Research Institute (The University of Tokyo), National Institute for Environmental Studies, and Japan Agency
for Marine-Earth Science and Technology. The model has a horizontal resolution
equal to 1.40° × 1.40°.
MIROC5 model produces four RCPs climate change scenarios. RCP6.0 climate
change scenario is one of them, where it represents a larger set of mitigation scenarios
and radiative forcing targets in 2100. In this scenario, the total radiative forcing
is stabilized shortly after 2100, without overshoot by the application of a range
of technologies and strategies for reducing greenhouse gas emissions. Thus, it is
considered as a stabilization scenario [29, 30].
2.2 The Projected Value of ETo Using Hargreaves-Samani
Equation
The RCP6.0 climate change scenario contained maximum and minimum temperature, as well as solar radiation data, which are suitable to calculate ETo using
Hargreaves-Samani (H-S) equation [31]. However, the accuracy of HargreavesSamani (H-S) equation is lower than its counterpart of Penman-Monteith (P-M)
equation [16], which requires using solar radiation, maximum, minimum and dew
point temperature, as well as wind speed. Furthermore, Penman-Monteith (P-M)
equation is widely recommended because of its detailed theoretical base and its
accommodation of small time periods [32]. To solve this problem, a linear regression equation can be established with ETo values resulted from P-M plotted as the
dependent variable and ETo values from H-S equation to be plotted as the independent variable. The intercept (a) and calibration slope (b) of the best-fit regression line
can be used as regional calibration coefficients. This methodology was developed by