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Aiming to verify the applicability of the linear regression correction scheme for Hargreaves-Samani (HS) equation under the framework of agricultural comprehensive division of China, by using 124 stations meteorological data from 1957 to 2016 released by China Meteorological Data Service Center, the multiyear reference crop evapotranspiration ET0-PM and ET0-HS were calculated by monthly based on Penman-Monteith (PM) equation and the HS, respectively. Then, taking ET0-PM as the true value, linear regression analysis method was used to collect the monthly correction coefficients a and b of the HS by ET0-PMand ET0-HS from 1957 to 2010 for 38 agricultural management subareas of China. Thirdly, by comparing the relative error changes before and after ET0-HS correction during 2011—2016, the applicability of HS equation linear regression correction method in China’s agricultural areas was verified. Lastly, combined with the specific error results during 2011—2016, the optimal monthly values of the HS correction coefficients a and b in each agricultural area were determined. The results showed that the ET0-PM and ET0-HS had good correlation (more than 0.6) in most months and in most agricultural areas. Therefore, the regression analysis can be carried out. Coefficient a obtained by regression correction had a significant seasonal change, while coefficient bwas relatively stable, which implied that there were obvious seasonal differencing between ET0-PM andET0-HS. There were relative errors for ET0-HS before and after correction in different degrees, but the error range of ET0-HS after correction was significantly reduced. In specific verification applications, ET0-HS after correction was not the best result for all areas in each month. Therefore, the optimization of a and b coefficients was the best scheme in practice. The linear regression correction of the HS was a simple and feasible scheme in practice, which had practical significance and popularization value for rapid acquisition of highprecision reference crop evapotranspiration in large-scale area.