Single and dual crop coefficients and their impact on the irrigation management of sugarcane cycles in the Brazilian savanna

Abstract

Brazil is the world’s leading producer of sugarcane, with a substantial portion of its production (87.5%) located within the Brazilian savanna biome, a region characterized by severe water deficit from May to September, which limits crop yield. Therefore, accurate and up-to-date information on key variables for optimizing irrigated sugarcane cultivation in this area is essential. This study aimed to determine the crop water requirement, the single (Kc) and dual (Kcdual) crop coefficients for sugarcane (plant cane and ratoon) cycles in the Brazilian savanna, using a multi-method approach that integrates lysimetry and FAO-56–based modeling. The water requirement was determined through lysimetry (ETcL), and the values of Kc and Kcdual, including tabulated, experimental, and estimated coefficients, were compared and utilized in irrigation simulations. Total ETcL was 1756.5 mm in the first cycle (plant cane) and 1201.4 mm in the first ratoon cycle. For plant cane, lysimeter-derived Kc values were more consistent with values from the literature than those observed for ratoon; however, the dual Kc values were similar in both cycles. In the plant cane cycle, irrigation depth increased when the lysimetric Kc (KcL=+10.3%) and the experimental dual Kc (Kcdual E =+6.6%) were applied. In contrast, water savings were achieved using the estimated single (KcSE = −11.2%) and estimated dual (Kcdual e = −0.8%) coefficients compared to the tabulated Kc. In the ratoon cycle, all coefficients indicated lower irrigation depths (KcL= −27.1%; KcSE = −3.6%; Kcdual E = −20.1%; Kcdual e = −21.1%). Furthermore, factors such as the limited experimental area, potential border effects, local microclimatic disturbances, and constraints related to root system dynamics in lysimeter-based experiments should be considered. The integration of lysimetric measurements with FAO-56 estimates provides practical crop coefficients, enabling more precise irrigation scheduling and optimized water use in the Brazilian savanna.