LAUSR

Abstract Accurately monitoring the spatial-temporal distribution of drought events is helpful for reducing the meteorological risk. The monthly integrated surface drought index (mISDI) dataset of the Hanjiang River Basin (HJRB) from 2001 to 2017 was established by using the Cubist algorithm, and the Run theory was applied to identify and characterize the drought events. Two gross primary productivity (GPP) datasets, obtained from the Global Land Surface Satellite (GLASS GPP) program and the Numerical Terradynamic Simulation Group (NTSG GPP), were used to investigate the impact of drought events on GPP changes and the relative importance of climate factors in GPP changes. The results showed that (1) the mISDI had good accuracy and reliability in drought events monitoring (R = 0.95; MAE = 0.503; RMSE = 0.707). The problem of missing land surface temperature data was solved, and the filled LST dataset has good accuracy. In addition, the model accuracy was significantly improved by using the time variables; (2) Five drought events were identified by using the Run theory, and the drought event occurred from August 2013 to August 2014 had the largest drought intensity (1.309) and drought affected area (81.12%). Spatially, the western HJRB had more frequent droughts than the eastern region, but the eastern HJRB had longer average drought duration and higher mean drought intensity and severity; (3) During the drought event occurred from August 2013 to August 2014, mainly occurred in the eastern basin. The correlation between GLASS GPP anomalies and mISDI (R = 0.553, p   0.1). The decreased area of GLASS GPP (78.36%) was larger than that of NTSG GPP (49.08%), both were mainly distributed in the eastern HJRB. Among different climate factors, temperature was an important drought factor affecting GPP changes. This study provides a good way to understand the evolution process of drought events and the impact of drought events on vegetation productivity.