Supplementary Material s18

Supplementary material The supplementary material contains additional five figures and two tables.

Fig. A1 shows that uncertainty range increase with the time for changes in annual average discharge, seasonal high flow, and daily peak discharge in 21st century relative to 1981–2010. Fig. A2 shows that the WATCH data captures spatial patterns of temperature and precipitation in the upper Yangtze basin very well with a spatial correlation with the observation-based patterns higher than 0.90. Fig. A3 presents results of additional calibration and validation (step 2) of four hydrological models driven by observed climate data for the upper Yangtze (see Discussion). The results are quite good: the Nash-Sutcliffe efficiency of observed and simulated daily discharge from HBV, SWAT, SWIM and VIC reaches 0.81, 0.81, 0.73, 0.75 in the calibration period, and 0.78, 0.80, 0.73, 0.74 in the validation period, respectively. Percent bias (PBIAS) between observed and simulated flows for each of four models is 6.8%, 1.1%, 9.2%, -9.3% in the calibration period, and 7.0%, 3.6%, 5.1%, -6.5% in the validation period, respectively. Fig. A4 compares the long-term average monthly dynamics of discharge for the historical period based on two calibration/validation steps: 1) using the WATCH climate data, and 2) using observed climate data. The same GCMs bias-corrected to WATCH data were used in both cases to drive hydrological models. It is shown that the GCMs driven outputs in the historical period match very well with the WATCH driven results (Fig. A4a), since GCMs were bias-corrected to WATCH, but the GCMs driven outputs corresponding to step 2) are obviously lower than the observed climate driven results (Fig.A4b), because the WATCH and the bias-corrected to WATCH GCMs underestimate precipitation in the upper Yangtze. The comparison of relative changes in the long-term average monthly discharge at the end-century relative to the reference period based on WATCH data (step 1) and observed climate (step 2) calibrations is shown in Fig. A5. Fig. A5a is related to step 1 calibration, and Fig. A5b – to step 2 calibration. It is evident from this Figure that the relative changes in discharge based on two calibration/validation steps are quite similar, though the spreads are slightly larger in simulations based on the observed climate (Fig. A5b). Tables A1 and A2 present some additional results related to peak discharge. In 85% of all cases it is projected that the 100-year return period of peak discharge during 1981–2010 will be shortened in the 21st century; the 100-year event will become less than 50-year event in 73% cases. The increasing frequency of 100 year return level is more obvious at the end-century than at the mid- century.

Fig. A1: Time series of relative changes (related to 1986–2005) in annual averaged discharge (a), seasonal high flow (b) and peak discharge (c) for the upper Yangtze. The thick lines denote ensemble means of historical (black line) and future simulation (colored lines) under the RCP 2.6 and 8.5 scenarios, the thin lines denote individual model simulations. Fig. A2: Comparison of observed temperature and precipitation patterns with those based on the WATCH reanalysis data for 1971–2001 in the upper Yangtze. Fig. A3: Comparison of calibration and validation runs in 1971–1980 (a) and 1981–1990 (b) by HBV, SWAT, SWIM and VIC using in-situ observed climate data. Fig. A4: Comparison of the long-term average monthly dynamics of discharge simulated by ensemble of HBV, SWAT, SWIM and VIC based on WATCH calibration/validation (step 1, a), and based on observed climate calibration/validation (step 2, b) in the historical period. In addition to validation runs (WATCH and Obs in a and b), the GCM-driven simulations based on these two calibration/validations steps for the historical period are shown in both cases (a and b). Fig. A5: Comparison of relative changes in monthly discharge at the end-century relative to the reference period based on WATCH (a) and observed (b) climate calibration/validation. Thick lines denote means of the changes by multi model projections under the RCP 2.6 and 8.5 scenarios, and shades denote spreads simulated by all individual model combinations. Projection SWI HBV SWAT VIC period GCMs\HMs M GFDL 44 130 310 110 Had 7 21 33 19 2036-2065 IPSL 208 53 35 245 MIROC 10 12 17 36 Nor 27 56 43 47 GFDL 13 22 22 23 Had 3 6 8 30 2070-2099 IPSL 43 29 17 110 MIROC 7 11 10 17 Nor 26 83 62 56 (unit: year)

Table A1: Return period of peak discharge in the mid-century (2036–2065) and the end-century (2070–2099) corresponding to 100-year events in the reference period (1981–2010) under the RCP 4.5 scenario in the upper Yangtze estimated by Generalized Logistic Distribution. Projection HBV SWAT SWIM VIC period GCMs\HMs GFDL 17.0% -1.9% -7.5% -0.92% Had 27.4% 11.4% 8.6% 16.21% 2036-2065 IPSL -6.0% 7.7% 12.9% -9.70% MIROC 27.5% 20.4% 12.6% 13.18% Nor 17.0% 4.5% 6.9% 10.85% GFDL 11.6% 31.3% 20.8% 39.4% Had 40.8% 32.3% 41.6% 30.9% 2070-2099 IPSL 9.6% 14.6% 18.7% -1.1% MIROC 49.7% 22.1% 20.7% 26.8% Nor 11.6% 1.2% 2.7% 6.0%

Table A2: Percentage changes of 100 year peak discharge in the mid-century (2036–2065) and the end-century (2070–2099) relative to the reference period (1981–2010) under the RCP 4.5 scenario in the upper Yangtze.