The Three Gorges Reservoir (TGR) intervening basin is one of the most important, ecologically fragile and sensitive areas in the upper reaches of the Yangtze River. Since the completion and operation of the TGR, the change of the ecological environment in this region—with vegetation as an indicator—has been a consistent focus of attention. Based on the six phases of land use data and normalized difference vegetation index (NDVI), temperature and precipitation data from 1998 to 2017, the change and trend of land use and vegetation cover in the TGR intervening basin were analyzed quantitatively by using a transition matrix, linear regression and partial correlation analysis. The area of unchanged land use type is 56,565 km², accounting for 97.27% of the total area of the basin. The vegetation coverage with NDVI as the indicator showed a significant upward trend, with a growth rate of 7.5%/10a. The impact of temperature on vegetation was greater than that of precipitation on vegetation. The non-linear fitting curve of NDVI to temperature and precipitation rose with the time course of TGR impoundment, although the mechanism remains to be studied further. In general, climate change, ecological restoration measures, urbanization and reservoir impoundment did not significantly change the spatial distribution pattern of land use and the climate driving mechanism of vegetation growth in the TGR intervening basin.

Data analysis and mathematical statistics are used to analyze the Interannual variation of runoff and precipitation in the Jinsha River basin from 1961 to 2015. The area average annual precipitation showed no significant upward trend, and the annual runoff showed no significant downward trend. The results of cumulative anomaly test, MK mutation test and sliding t test are consistent, there were three mutation years of 1984, 1997 and 2005 in the time series of annual precipitation and runoff in the Jinsha River basin. This study also provides necessary hydrometeorological basic information for quantitative assessment of the contribution rate of climate change and human activities to runoff change.