The A&P approach, developed by Allen and Pereira (2009), estimates single and basal crop coefficients (K_c and K_cb) from the observed fraction of ground cover (f_c) and crop height (h). The practical application of the A&P for several crops was reviewed and tested in a companion paper (Pereira et al., 2020). The current study further addresses the derivation of optimal values for A&P parameter values representing canopy transparency (M_L) and stomatal adjustment (F_r), and tests the resulting model performance. Values reported in literature of M_L and F_r were analysed. Optimal M_L and F_r values were derived by a numerical search that minimized the differences between K_{cb A&P} with standard K_cb for vegetable, field, and fruit crops as tabulated by Pereira et al. (2021a, 2021b) and Rallo et al. (2021). Sources for f_c were literature reviews supplemented by a remote sensing survey. Computed K_cb and K_c for mid- and end-season together with associated parameters values were tabulated. To improve the usability of the M_L and F_r parameters a cross validation was performed, which consisted of the linear regression between K_cb computed by A&P and observed K_cb relative to independent data sets obtained from field observations. Results show that both series of K_cb match well, with regression coefficients very close to 1.0, coefficients of determination near 1.0, and root mean square errors (RMSE) of 0.06 for the annual crops and RMSE = 0.07 for the trees and vines. These errors represent less than 10% of most of the computed tabulated K_cb. The tabulated F_r and M_L of this paper can be regarded as defaults to support A&P field practice when observations of f_c and h are performed. Therefore, the A&P approach shows to be appropriate for use in irrigation scheduling and planning when f_c and h are observed using ground and/or remote sensing, hence supporting irrigation water savings.

由Allen和Pereira（2009）开发的A＆P方法根据观测到的地面覆盖率（f _c）和作物高度（h）估算单一和基础作物系数（K _c和K _cb）。A＆P在几种作物上的实际应用已在配套文件中进行了审查和测试（Pereira等人，2020年）。当前的研究进一步解决了代表冠层透明度（M _L）和气孔调整（F _r）的A＆P参数值的最佳值的推导，并测试了所得模型的性能。分析了文献M _L和F _r中报告的值。最佳M _L和F _r值是通过数值搜索得出的，该搜索将Pereira等人列出的蔬菜，田地和水果作物的K _{cb A＆P}与标准K _cb之间的差异最小化。（2021a，2021b）和Rallo等人。（2021年）。f _c的来源是文献综述，并附加了遥感调查。将计算得出的中期和夏季的K _cb和K _c以及相关的参数值制成表格。为了提高M的可用性_大号和F _{- [R}进行了交叉验证的参数，其中包括k之间的线性回归的_CB通过A＆P计算和观察ķ _CB相对于从野外观测获得的独立数据集。结果表明，这两个系列的K _cb匹配良好，回归系数非常接近1.0，确定系数接近1.0，一年生作物的均方根误差（RMSE）为0.06，树木和藤本植物的均方根误差（RMSE）= 0.07。这些误差代表了大多数计算得出的列表K _cb的不到10％_。当进行f _c和h观测时，本文的列表F _r和M _L可被视为默认值，以支持A＆P现场实践。因此，当f _c时，A＆P方法显示适用于灌溉调度和计划 使用地面和/或遥感可以观测到h和h，因此可以节省灌溉用水。