1 Attribution of growing season evapotranspiration variability 2 considering snowmelt and vegetation changes in the arid alpine 3 basins 4 Tingting Ningabc, Zhi Lid, Qi Fengac* , Zongxing Liac and Yanyan Qinb 5 aKey Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, 6 Chinese Academy of Sciences, Lanzhou, 730000, China 7 bKey Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of 8 Sciences, Lanzhou 730000, China 9 cQilian Mountains Eco-environment Research Center in Gansu Province, Lanzhou, 730000, China 10 dCollege of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi, 712100, China 11 * Correspondence to: Qi Feng (
[email protected] ) 12 1 / 50 13 Abstract: Previous studies have successfully applied variance decomposition 14 frameworks based on the Budyko equations to determine the relative contribution of 15 variability in precipitation, potential evapotranspiration (E0), and total water storage 2 16 changes (∆S) to evapotranspiration variance (휎퐸푇) on different time-scales; however, 17 the effects of snowmelt (Qm) and vegetation (M) changes have not been incorporated 18 into this framework in snow-dependent basins. Taking the arid alpine basins in the 19 Qilian Mountains in northwest China as the study area, we extended the Budyko 2 20 framework to decompose the growing season 휎퐸푇 into the temporal variance and 21 covariance of rainfall (R), E0, ∆S, Qm, and M. The results indicate that the incorporation 22 of Qm could improve the performance of the Budyko framework on a monthly scale; 2 23 휎퐸푇 was primarily controlled by the R variance with a mean contribution of 63%, 24 followed by the coupled R and M (24.3%) and then the coupled R and E0 (14.1%).