Understanding the impact of drought and climate factors on vegetation dynamics in China and elucidating the response of vegetation’s gross total primary productivity (GPP) to drought events in different climatic zones has been of paramount importance for predicting future climate-carbon cycle feedbacks. However, the response of vegetation dynamics to climate factors and droughts in different climatic zones, as well as their intrinsic mechanisms remains uncertain. Therefore, in this study, based on precipitation, temperature, standardized precipitation evapotranspiration index (SPEI), and GPP data, we conducted a deep analysis of the response of GPP to climate factors and drought in different climate zones. The cumulative effects of drought in different climatic zones and vegetation types were explored. The results indicated significant variations in GPP across geographic distribution in China, with the highest values observed in Climate Zone VII and the lowest values in Climate Zone I. Linear regression analysis showed that the annual changes in temperature and precipitation showed a continuous upward trend. While SPEI displayed a declining trend, indicating an overall tendency towards aridification. Temperature showed a significant positive correlation with GPP in climatic zones I, IV, V, and VI, while precipitation exhibited a significant positive correlation with GPP in climatic zones I, II, and IV. About 45.10% of the vegetation showed a cumulative response to drought, with an average cumulative duration of 5.3 months. Forests had the longest cumulative duration (6 months), followed by grasslands (5.4 months), croplands (3.9 months), and shrublands (3.8 months). The cumulative response time of GPP to drought was the longest in Climate Zones I and II, while in Climate Zone VII, the cumulative response time of GPP to drought increased linearly with rising SPEI. In conclusion, the water balance gradient and vegetation characteristics were the key factors influencing the cumulative response of GPP to drought.

Understanding the controlling factors of spatial and temporal changes in runoff is critical for the integrated management and utilization of water resources. This study used the stepwise regression analysis to determine the expressions of eight regional controlling parameters and their climate and human factors in the middle Yellow River (MYR) based on the Budyko framework of the Fu equation. The contribution rate of climate and human factors to runoff change was analyzed using the elastic coefficient. The results showed that climate change caused runoff increase, and comprehensive human activities played an important role in runoff reduction. Human factors affecting runoff varied greatly in different regions. Vegetation restoration could lead to runoff reduction while constructing terraces and check-dams could cause an increase in runoff. Urban expansion contributed to runoff collection, and its contribution rate to runoff change was more than 200% in absolute value. The runoff change in the arid and semi-arid regions in the north was more sensitive to human factors.