Using monthly streamflow data from the 1960-2000 period and annual 16 streamflow data from the 2001-2014 period, and also meteorological data from the 17 1960-2014 period from 815 meteorological stations across China, the Budyko-based 18 hydrothermal balance model was used to quantitatively evaluate the fractional 19 contributions of climate change and human activities to streamflow changes in ten 20 river basins across China. Particular importance was attached to human activities, 21 such as population density and Gross Domestic Product (GDP), and also water 22 reservoirs in terms of their relationship with streamflow changes. Results indicated 23 that: (1) streamflow changes of river basins in northern China were more sensitive to 24 3 climate change than those of river basins in southern China. Based on the degree of 25 sensitivity, the influencing factors to which streamflow changes are sensitive included: 26 precipitation > human activities > relative humidity > solar radiation > maximum 27 temperature > wind speed > minimum temperature. Hence, it can be argued that 28 hydrological systems in northern China are more fragile and more sensitive to 29 changing environment than those in southern China and hence water resources 30 management in northern China is more challenging; (2) during 1980-2000, climate 31 change tended to increase streamflow changes across China and have a dominant role 32 in streamflow variation. However, climate change tends to decrease streamflow in 33 river basins of northern China. Generally, human activities cause a decrease of 34 streamflow across China; (3) In recent years such as a period of 2001-2014, human 35 activities tend to have increasing or enhancing impacts on instream flow changes, and 36 fractional contributions of climate change and human activities to streamflow changes 37 are, respectively, 53.5% and 46.5%. Increasing human-induced impacts on 38 streamflow changes have the potential to add more uncertainty in the management of 39 water resources at different spatial and temporal scales.40 41

Abstract:Variations in streamflows of five tributaries of the Poyang Lake basin, China, because of the influence of human activities and climate change were evaluated using the Australia Water Balance Model and multivariate regression. Results indicated that multiple regression models were appropriate with precipitation, potential evapotranspiration of the current month, and precipitation of the last month as explanatory variables. The NASH coefficient for the Australia Water Balance Model was larger than 0.842, indicating satisfactory simulation of streamflow of the Poyang Lake basin. Comparison indicated that the sensitivity method could not exclude the benchmark-period human influence, and the human influence on streamflow changes was overestimated. Generally, contributions of human activities and climate change to streamflow changes were 73.2% and 26.8% respectively. However, human-induced and climate-induced influences on streamflow were different in different river basins. Specifically, climate change was found to be the major driving factor for the increase of streamflow within the Rao, Xin, and Gan River basins; however, human activity was the principal driving factor for the increase of streamflow of the Xiu River basin and also for the decrease of streamflow of the Fu River basin. Meanwhile, impacts of human activities and climate change on streamflow variations were distinctly different at different temporal scales. At the annual time scale, the increase of streamflow was largely because of climate change and human activities during the 1970s-1990s and the decrease of streamflow during the 2000s. At the seasonal scale, climate change was the main factor behind the increase of streamflow in the spring and summer season. Human activities increase the streamflow in autumn and winter, but decrease the streamflow in spring. At the monthly scale, different influences of climate change and human activities were detected. Climate change was the main factor behind the decrease of streamflow during May to June and human activities behind the decrease of streamflow during February to May. Results of this study can provide a theoretical basis for basin-scale water resources management under the influence of climate change and human activities.

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Abstract. The partitioning of precipitation into runoff (R) and evapotranspiration (E), governed by the controlling parameter in the Budyko framework (i.e., n parameter in the Choudhury and Yang equation), is critical to assessing the water balance at global scale. It is widely acknowledged that the spatial variation in this controlling parameter is affected by landscape characteristics, but characterizing its temporal variation remains yet to be done. Considering effective precipitation (Pe), the Budyko framework was extended to the annual water balance analysis. To reflect the mismatch between water supply (precipitation, P) and energy (potential evapotranspiration, E0), we proposed a climate seasonality and asynchrony index (SAI) in terms of both phase and amplitude mismatch between P and E0. Considering streamflow changes in 26 large river basins as a case study, SAI was found to the key factor explaining 51 % of the annual variance of parameter n. Furthermore, the vegetation dynamics (M) remarkably impacted the temporal variation in n, explaining 67 % of the variance. With SAI and M, a semi-empirical formula for parameter n was developed at the annual scale to describe annual runoff (R) and evapotranspiration (E). The impacts of climate variability (Pe, E0 and SAI) and M on R and E changes were then quantified. Results showed that R and E changes were controlled mainly by the Pe variations in most river basins over the globe, while SAI acted as the controlling factor modifying R and E changes in the East Asian subtropical monsoon zone. SAI, M and E0 have larger impacts on E than on R, whereas Pe has larger impacts on R.

Decreased streamflow of the Yellow River basin has become the subject of considerable concern in recent years due to the critical importance of the water resources of the Yellow River basin for northern China. This study investigates the changing properties and underlying causes for the decreased streamflow by applying streamflow data for the period 1960 to 2014 to both the Budyko framework and the hydrological modelling techniques. The results indicate that (1) streamflow decreased 21% during the period 1980-2000, and decreased 19% during the period 2000-2014 when compared to 1960-1979; (2) higher precipitation and relative humidity boost streamflow, while maximum/minimum air temperature, solar radiation, wind speed, and the underlying parameter, n, all have the potential to adversely affect them; (3) decreased streamflow is also linked to increased cropland, grass, reservoir, urban land, and water areas and other human activities associated with GDP and population; (4) human activity is the main reason for the decrease of streamflow in the Yellow River basin, with the mean fractional contribution of 73.4% during 1980-2000 and 82.5% during 2001-2014. It is clear that the continuing growth of human-induced impacts on streamflow likely to add considerable uncertainty to the management of increasingly scarce water resources. Overall, these results provide strong evidence to suggest that human activity is the key factor behind the decreased streamflow in the Yellow River basin.