Attribution of growing season evapotranspiration variability considering snowmelt and vegetation changes in the arid alpine basins

[摘要] Previous studies have successfully applied variance decomposition frameworks based on the Budyko equations to determine the relative contribution of variability in precipitation, potential evapotranspiration ( E 0 ), and total water storage changes ( Δ S ) to evapotranspiration variance ( σ ET 2 ) on different timescales; however, the effects of snowmelt ( Q m ) and vegetation ( M ) changes have not been incorporated into this framework in snow-dependent basins. Taking the arid alpine basins in the Qilian Mountains in northwest China as the study area, we extended the Budyko framework to decompose the growing season σ ET 2 into the temporal variance and covariance of rainfall ( R ), E 0 , Δ S , Q m , and M . The results indicate that the incorporation of Q m could improve the performance of the Budyko framework on a monthly scale; σ ET 2 was primarily controlled by the R variance with a mean contribution of 63 %, followed by the coupled R and M (24.3 %) and then the coupled R and E 0 (14.1 %). The effects of M variance or Q m variance cannot be ignored because they contribute 4.3 % and 1.8 % of σ ET 2 , respectively. By contrast, the interaction of some coupled factors adversely affected σ ET 2 , and the out-of-phase seasonality between R and Q m had the largest effect ( − 7.6 %). Our methodology and these findings are helpful for quantitatively assessing and understanding hydrological responses to climate and vegetation changes in snow-dependent regions on a finer timescale.

[学科分类] 妇产科学