Prediction of crop coefficients is important to establish optimized irrigation water scheduling and management practices. In the present study, regression modeling was utilized to predict the field crop coefficients of crops grown in the humid sub-tropical agro-climate of Hamirpur (Himachal Pradesh, India). Field experiments were conducted on seven crops categorized as Cereals (Wheat and Maize), Oilseed (Indian mustard), Vegetable (Potato), Fodder crop (Sorghum), Green manure crop (Guar), and Legumes (Pea). The crop coefficients were determined using a modification and field-based approach. In the modification approach, FAO-recommended standard crop coefficients were modified using the crop coefficient modification procedure given in FAO-56. In the field-based approach, crop coefficients were obtained as the ratio of field crop evapotranspiration to the reference evapotranspiration. FAO modified crop coefficients presented satisfactory performance with the field crop coefficients (squared error = 0.0009-0.0225; R-2 = 0.80-0.89; bias error = - 0.09-0.15). New crop coefficients were developed by performing regression modeling between the FAO modified and field-based crop coefficients. Furthermore, new crop evapotranspiration values were obtained using new crop coefficients, which presented a strong and reliable agreement with the field crop evapotranspiration values, i.e., they exhibited small bias error = 10-24 mm, and high R-2 = 0.90-0.93. The developed regression equations can be employed as useful tools for predicting field crop coefficients from the FAO-56 modified crop coefficients, subsequently resulting in the precise estimation of the crop evapotranspiration.
