The ecosystem of the Source Region of Yangtze River (SRYR) is highly susceptible to climate change. In this study, the spatial–temporal variation of NPP from 2000 to 2014 was analyzed, using outputs of Carnegie–Ames–Stanford Approach model. Then the correlation characteristics of NPP and climatic factors were evaluated. The results indicate that: (1) The average NPP in the SRYR is 100.0 gC/m² from 2000 to 2014, and it shows an increasing trend from northwest to southeast. The responses of NPP to altitude varied among the regions with the altitude below 3500 m, between 3500 to 4500 m and above 4500 m, which could be attributed to the altitude associated variations of climatic factors and vegetation types; (2) The total NPP of SRYR increased by 0.18 TgC per year in the context of the warmer and wetter climate during 2000–2014. The NPP was significantly and positively correlated with annual temperature and precipitation at interannual time scales. Temperature in February, March, May and September make greater contribution to NPP than that in other months. And precipitation in July played a more crucial role in influencing NPP than that in other months; (3) Climatic factors caused the NPP to increase in most of the SRYR. Impacts of human activities were concentrated mainly in downstream region and is the primary reason for declines in NPP.

It has become a hot issue to study extreme climate change and its impacts on water quality. In this context, this study explored the evolution characteristics of drought–flood abrupt alternation (DFAA) and its impacts on total nitrogen (TN) and total phosphorous (TP) pollution, from 2020 to 2050, in the Luanhe river basin (LRB), based on the predicted meteorological data of the representative concentration pathways (RCPs) climate scenarios and simulated surface water quality data of the Soil and Water Assessment Tool (SWAT) model. The results show that DFAA occurred more frequently in summer, with an increasing trend from northwest to southeast of the LRB, basically concentrated in the downstream plain area, and the irrigation area. Meanwhile, most of the DFAA events were in light level. The incidence of TN pollution was much larger than the incidence of TP pollution and simultaneous occurrence of TN and TP pollution. The TN pollution was more serious than TP pollution in the basin. When DFAA occurred, TN pollution almost occurred simultaneously. Also, when TP pollution occurred, the TN pollution occurred simultaneously. These results could provide some references for the effects and adaptation-strategies study of extreme climate change and its influence on surface water quality.

It is of great significance to study the effects and mechanisms of the key driving forces of surface water quality deterioration—climate change and LUCC (land use and land cover change). The Luanhe River Basin (LRB) in north-eastern China was examined for qualitatively and quantitatively assessing the responses of total nitrogen (TN) and total phosphorus (TP) loads on different climate scenarios and LUCC scenarios. The results show that from 1963 to 2017, the TN and TP loads basically presented a negative correlation with the temperature change (except for winter), while showing a significant positive correlation with the precipitation change. The incidence of TN pollution is sensitive to temperature increase. From 2020 to 2050, the annual average loads of TN and TP were slightly lower than from 1963 to 2017. The contribution of rising temperature was more significant on nutrient loads. Also, the incidence of TN pollution is sensitive to the future climate change. Under LUCC scenarios, the TN and TP loads and pollution incidence increased correspondingly with the decrease of natural land. The evolution characteristics analysis can provide support for the effect and adaptation-strategies study of climate change and LUCC on surface water quality.

The Erhai Lake Basin is a crucial water resource of the Dali prefecture. This research used the soil and water assessment tool (SWAT) and the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) to estimate blue and green water flows. Then the spatial and temporal change of blue and green water flows was investigated. With the hypothetical climate change scenarios, the sensitivity of blue and green water flows to precipitation and temperature has also been analyzed. The results showed that: (1) The CMADS reanalysis dataset can capture the observed probability density functions for daily precipitation and temperature. Furthermore, the CMADS performed well in monthly variables simulation with relative bias and absolute bias less than 7% and 0.5 °C for precipitation and temperature, respectively; (2) blue water flow has increased while green water flow has decreased during 2009 to 2016. The spatial distribution of blue water flow was uneven in the Erhai Lake Basin with the blue water flow increased from low altitudes to mountain areas. While the spatial distribution of green water flow was more homogeneous; (3) a 10% increase in precipitation can bring a 20.8% increase in blue water flow with only a 2.5% increase in green water flow at basin scale. When temperature increases by a 1.0 °C, the blue water flow and green water flow changes by −3% and 1.7%, respectively. Blue and green water flows were more sensitive to precipitation in low altitude regions. In contrast, the water flows were more sensitive to temperature in the mountainous area.

Quantifying the contributions of climate change and human activities on runoff changes is of great importance for water resource management, sustainable water resource utilization, and sustainable development of society. In this study, hydrological and climatic data from hydrological and meteorological stations in the headwaters of the Yangtze River (YRHA) from 1966 to 2013 were used to quantitatively attribute the runoff change to the impacts of climate change and human activities separately. Firstly, the change trends in precipitation, runoff depth and potential evapotranspiration were analyzed by the Mann-Kendall test method. Three methods, secondly, including ordered clustering, Mann-Kendall and cumulative anomaly curve were adopted to detect the change points of runoff at Zhimenda hydrological station and partition the whole study period into two sub-periods at the change point (base and impacted periods). Then, the elasticity coefficient method based on the Budyko hypothesis was applied to calculate elasticity coefficients of runoff to precipitation, potential evapotranspiration and land use/cover during the two periods, and to evaluate the contributions of climate change and human activities. Results indicated that during 1966–2013, runoff depth, precipitation and potential evapotranspiration all showed a significant increasing trend, with increasing rates of 7.26 mm decade⁻¹, 18.725 mm decade⁻¹ and 7.228 mm decade⁻¹, respectively. One change point (2004) was detected for the annual runoff, and 1966–2003 and 2004–2013 were respectively identified as base and impacted periods. The results of elasticity coefficients showed that the runoff depth was most sensitive to the change of precipitation during the two periods. The relative contributions of precipitation, potential evapotranspiration and parameter n to runoff changes were 99.7%, −6.08% and 3.88%, respectively. Furthermore, the coupled contribution rate of other factors was less than 2.5%. Generally, results indicated that precipitation is the main factor on the historical runoff changes in this basin.

Based on daily maximum temperature (Tmax), minimum temperature (Tmin), and precipitation of the Yangtze River Basin (YRB) from 1961 to 2020, we employed the trend analysis method and correlation analysis method to analyze spatiotemporal variations in 10 extreme indices and their associations with atmospheric and oceanic circulations. Results indicated that maximum Tmax (TXx), maximum Tmin (TNx), and minimum Tmin (TNn) all increased significantly, at rates of 0.19 °C, 0.19 °C, and 0.37 °C per decade, respectively, whereas minimum Tmax (TXn) did not show any significant trend. The diurnal temperature range (DTR) decreased by 0.09 °C per decade as minimum temperatures increased faster than maximum temperatures. TNx and TNn increased significantly in the majority of the YRB, but TXn showed no significant increases. TXn increased significantly in the upper reaches of the Yangtze River. The DTR increased significantly in the Jinsha River Basin and the lower reaches of the Yangtze River. Rx1day (maximum 1-day precipitation), SDII (Simple daily intensity index) and R99p (extremely wet-day precipitation) increased significantly, at rates of 1.12 mm, 0.09 mm, and 5.87 mm per decade, respectively, but the trends of Rx5day (maximum 5-day precipitation) and PRCPTOT (total wet-day precipitation) were not significant. However, the trends of precipitation extreme indices were not statistically significant in most of the YRB. In the future, maximum temperature and minimum temperature might increase while DTR might decrease. But, the trends of precipitation extremes in the future were ambiguous. Nearly all the extreme indices were related to the variability of Atlantic multidecadal oscillation (AMO) in the YRB. In addition, the correlations between extreme temperature indices and AMO are higher than that of extreme precipitation indices.