Abstract

Abstract The daily gross primary productivity (GPP) and evapotranspiration (ET) in the Xilingol grassland ecosystem of Inner Mongolia were simulated using the BioGeochemical Cycles (Biome-BGC) model for 2003–2019 and under future climate-change scenarios. The system was optimized using the System Response Parameter Calibration Method (SRPCM). The temporal variations of GPP, ET and water use efficiency (WUE) were investigated, and the impacts of precipitation and temperature were explored. Results showed that (i) the BIOME-BGC model performed better when optimized using the SRPCM than by applying the Model-Independent Parameter Estimation approach (PEST); (ii) GPP and ET at annual and seasonal scales showed an insignificant increasing trend; (iii) WUE at the annual scale and in growing seasons showed an insignificant increasing trend and a slight decreasing trend in non-growing seasons; (iv) annual GPP and ET were more sensitive to changes in precipitation than changes in temperature with WUE keeping relatively stable with years; (v) precipitation is a critically controlling factor for GPP and ET in growing seasons and for ET and WUE in non-growing seasons; and (vi) combined temperature and precipitation changes had greater impacts on GPP/ET/WUE than individual changes.

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