Journal of Geographical Sciences ›› 2021, Vol. 31 ›› Issue (7): 997-1014.doi: 10.1007/s11442-021-1882-4

• Research Articles • Previous Articles     Next Articles

Monthly calibration and optimization of Ångström-Prescott equation coefficients for comprehensive agricultural divisions in China

XIA Xingsheng1,2(), PAN Yaozhong1,2, ZHU Xiufang1,3,*(), ZHANG Jinshui1,3   

  1. 1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China
    2. Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810016, China
    3. Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2021-02-20 Accepted:2021-04-28 Online:2021-07-25 Published:2021-09-25
  • Contact: ZHU Xiufang;
  • About author:Xia Xingsheng, PhD and Instructor, specialized in crop water requirements research. E-mail:
  • Supported by:
    National High Resolution Earth Observation System (the Civil Part) Technology Projects of China;Local Scientific & Technological Development Projects of Qinghai Guided by Central Government of China;Disaster Research Foundation of PICC P&C(2017D24-03)


?ngstr?m-Prescott equation (AP) is the algorithm recommended by the Food and Agriculture Organization (FAO) of the United Nations for calculating the surface solar radiation (Rs) to support the estimation of crop evapotranspiration. Thus, the as and bs coefficients in the AP are vital. This study aims to obtain coefficients as and bs in the AP, which are optimized for China’s comprehensive agricultural divisions. The average monthly solar radiation and relative sunshine duration data at 121 stations from 1957-2016 were collected. Using data from 1957 to 2010, we calculated the monthly as and bs coefficients for each subregion by least-squares regression. Then, taking the observation values of Rs from 2011 to 2016 as the true values, we estimated and compared the relative accuracy of Rs calculated using the regression values of coefficients as and bs and that calculated with the FAO recommended coefficients. The monthly coefficients, as and bs, of each subregion are significantly different, both temporally and spatially, from the FAO recommended coefficients. The relative error range (0-54%) of Rs calculated via the regression values of the as and bs coefficients is better than the relative error range (0-77%) of Rs calculated using the FAO suggested coefficients. The station-mean relative error was reduced by 1% to 6%. However, the regression values of the as and bs coefficients performed worse in certain months and agricultural subregions during verification. Therefore, we selected the as and bs coefficients with the minimum Rs estimation error as the final coefficients and constructed a coefficient recommendation table for 36 agricultural production and management subregions in China. These coefficient recommendations enrich the case study of coefficient calibration for the AP in China and can improve the accuracy of calculating Rs and crop evapotranspiration based on existing data.

Key words: solar radiation, coefficient calibration, ?ngstr?m-Prescott equation, least-squares regression, agricultural divisions, China