Terrestrial net primary productivity (NPP) plays an essential role in the global carbon cycle as well as for climate change. However, in the past three decades, terrestrial ecosystems across mainland China suffered from frequent drought and, to date, the adverse impacts on NPP remain uncertain. This study explored the spatiotemporal features of NPP and discussed the influences of drought on NPP across mainland China from 1982 to 2015 using the Carnegie Ames Stanford Application (CASA) model and the standardized precipitation evapotranspiration index (SPEI). The obtained results indicate that: (1) The total annual NPP across mainland China showed an non-significantly increasing trend from 1982 to 2015, with annual increase of 0.025 Pg C; the spring NPP exhibited a significant increasing trend (0.031 Pg C year⁻¹, p < 0.05) while the summer NPP showed a higher decreasing trend (0.019 Pg C year⁻¹). (2) Most areas of mainland China were spatially dominated by a positive correlation between annual NPP and SPEI and a significant positive correlation was mainly observed for Northern China; specific to the nine sub-regions, annual NPP and SPEI shared similar temporal patterns with a significant positive relation in Northeastern China, Huang-Huai-Hai, Inner Mongolia, and the Gan-Xin Region. (3) During the five typical drought events, more than 23% areas of mainland China experienced drought ravage; the drought events generally caused about 30% of the NPP reduction in most of the sub-regions while the NPP in the Qinghai-Tibet Plateau Region generally decreased by about 10%.

Climate change and human activity are typically regarded as the two most important factors affecting runoff. Quantitative evaluation of the impact of climate change and human activity on runoff is important for the protection, planning, and management of water resources. This study assesses the contributions of climate change and human activity to runoff change in the Dongjiang River basin from 1960 to 2005 by using linear regression, the Soil and Water Assessment Tool (SWAT) hydrologic model, and the climate elasticity method. Results indicate that the annual temperature in the basin significantly increased, whereas the pan evaporation in the basin significantly decreased (95%). The natural period ranged from 1960 to 1990, and the affected period ranged from 1991 to 2005. The percentage of urban area during the natural period, which was 1.94, increased to 4.79 during the affected period. SWAT modeling of the Dongjiang River basin exhibited a reasonable and reliable performance. The impacts induced by human activity on runoff change were as follows: 39% in the upstream area, 13% in the midstream area, 77% in the downstream area, and 42% in the entire basin. The impacts of human activity on runoff change were greater in the downstream area than in either upstream and midstream areas. However, the contribution of climate change (58%) is slightly larger than that of human activity (42%) in the whole basin.

Floods are widespread and dangerous natural hazards worldwide. It is essential to grasp the causes of floods to mitigate their severe effects on people and society. The key drivers of flood susceptibility in rapidly urbanizing areas can vary depending on the specific context and require further investigation. This research developed an index system comprising 10 indicators associated with factors and environments that lead to disasters, and used machine learning methods to assess flood susceptibility. The core urban area of the Yangtze River Delta served as a case study. Four scenarios depicting separate and combined effects of climate change and human activity were evaluated using data from various periods, to measure the spatial variability in flood susceptibility. The findings demonstrate that the extreme gradient boosting model outperformed the decision tree, support vector machine, and stacked models in evaluating flood susceptibility. Both climate change and human activity were found to act as catalysts for flooding in the region. Areas with increasing susceptibility were mainly distributed to the northwest and southeast of Taihu Lake. Areas with increased flood susceptibility caused by climate change were significantly larger than those caused by human activity, indicating that climate change was the dominant factor influencing flood susceptibility in the region. By comparing the relationship between the indicators and flood susceptibility, the rising intensity and frequency of extreme precipitation as well as an increase in impervious surface areas were identified as important reasons of heightened flood susceptibility in the Yangtze River Delta region. This study emphasized the significance of formulating adaptive strategies to enhance flood control capabilities to cope with the changing environment.