Crop yield response to water - Cra

After LAI of the planting is estimated, the corresponding CC can be read off Figure 1 or similarrelations, and used as CC x for the simulation. As is obvious in Figure 1, for cases where thecanopy is full or nearly full and the plant density is not widely different from that of thereference, the CC x estimate made with the above procedure should be accurate within a fewpercentage points. The estimates become less and less reliable as the difference in densitybecomes greater, or if CC x or reference CC x is substantially less than full cover. On the otherhand, for cases where there is little interplant competition for PAR because of a sparse canopy(e.g. CC < 0.5), Equation 1 can be used along with Figure 1 to obtain a reasonable estimate ofCC x by setting F adj close to 1.0.Canopy growth coefficient (CGC)CGC is a measure of the intrinsic ability of the canopy to expand. A CGC of 0.11, for example,means that each day the CC is 11 percent greater than the CC of the day before during thefirst half of canopy development. CGC is virtually a constant when temperature effects areaccounted for by using GDD as the driver and there is no stress. Because CGC is based on firstorder kinetics (Bradford and Hsiao, 1982), a good way to derive CGC is to plot the log of CCvs. time and take the slope of the linearly fitted curve to be CGC, provided that only CC datameasured from shortly after seedling emergence to approximately 60 percent cover, that donot include periods of heavy fruit load on the crop, are used. If CC data are too limited forthe period specified above, but additional data have been collected up to canopy closure ornear full cover, CGC can be parameterized using the canopy growth components of AquaCrop.Instead of running the model, which is more time consuming, a simple Excel programmelimited only to canopy growth is available on the FAO AquaCrop website for this purpose.Commonly, both cc o and CGC would be unknown, requiring trial-and-error iterations to findthe best values for the two parameters. As general guiding principles for parameterizing CGC,the main considerations appear to be whether the crop is C 3 or C 4 , and whether the crop ismore efficient in the capture of PAR. For maize and sorghum, two important C 4 crops alreadyparameterized for AquaCrop, the CGC is 0.17 per day on a calendar time basis and 0.013 on aGDD basis. For a number of C 3 species, the CGC is around 0.09 to 0.12 per day on a calendartime basis. There are exceptions. One is the C 3 crop sunflower, its CGC is in the order of 0.22per day (calendar time), presumably because of its solar tracking ability to capture more PARper unit of canopy. In the trial-and-error runs to parameterize cc o and CGC, several scenariosof outcome are possible when the simulated CC over time are compared with the measureddata. These are listed in the first column of Table 3. In the second column are given possiblecauses for the lack of agreement and adjustments to make.If the comparison of simulated vs. measured data does not follow any of the scenarios in thetable, it is possible that either the experimental data are questionable, or the weather datamay be deficient. The weather data are particularly suspect if 10-day or monthly minimum andmaximum temperature are used instead of daily valuesAquaCrop has built in an alternative to estimate CGC, based on the time required for CC toreach CC x . This feature is provided for users who want to simulate roughly the production andwater use of a crop with some or many of the crop parameters not known. It should not berelied on to parameterize CGC, because in such cases cc o and plant density or initial canopycover (CC o ), which are equally important in determining the time to reach maximum cover, aremost certainly not known.AquaCrop parameterization, calibration, and validation Guide 81