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

Ning, Tingting; Li, Zhi; Feng, Qi; Li, Zongxing; Qin, Yanyan

Previous studies have successfully applied variance decomposition frameworks based on the Budyko equations to determine the relative contribution of variability in precipitation, potential evapotranspiration (inline-formulaE0), and total water storage changes (inline-formulaΔS) to evapotranspiration variance (inline-formula M3inlinescrollmathml italic σ normal ET normal 2 19pt17ptsvg-formulamathimgf919296b3dc1e4a3924335dcd5e440a4 hess-25-3455-2021-ie00001.svg19pt17pthess-25-3455-2021-ie00001.png ) on different timescales; however, the effects of snowmelt (inline-formulaQm) and vegetation (inline-formulaM) 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 inline-formula M6inlinescrollmathml italic σ normal ET normal 2 19pt17ptsvg-formulamathimg60916bb4ce29d2c36970618be6b96751 hess-25-3455-2021-ie00002.svg19pt17pthess-25-3455-2021-ie00002.png into the temporal variance and covariance of rainfall (inline-formulaR), inline-formulaE0, inline-formulaΔS,Qm, and inline-formulaM. The results indicate that the incorporation of inline-formulaQm could improve the performance of the Budyko framework on a monthly scale; inline-formula M12inlinescrollmathml italic σ normal ET normal 2 19pt17ptsvg-formulamathimg24ef8de89516f8a142e9409e65a26619 hess-25-3455-2021-ie00003.svg19pt17pthess-25-3455-2021-ie00003.png was primarily controlled by the inline-formulaR variance with a mean contribution of 63 %, followed by the coupled inline-formulaR and inline-formulaM (24.3 %) and then the coupled inline-formulaR and inline-formulaE0 (14.1 %). The effects of inline-formulaM variance or inline-formulaQm variance cannot be ignored because they contribute 4.3 % and 1.8 % of inline-formula M20inlinescrollmathml italic σ normal ET normal 2 19pt17ptsvg-formulamathimgcf66821c06e5ec80c7cc252a8a91c69e hess-25-3455-2021-ie00004.svg19pt17pthess-25-3455-2021-ie00004.png , respectively. By contrast, the interaction of some coupled factors adversely affected inline-formula M21inlinescrollmathml italic σ normal ET normal 2 19pt17ptsvg-formulamathimg4a0568c88a48dab56f75c92bde9784f6 hess-25-3455-2021-ie00005.svg19pt17pthess-25-3455-2021-ie00005.png , and the out-of-phase seasonality between inline-formulaR and inline-formulaQm had the largest effect (inline-formula−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.



Ning, Tingting / Li, Zhi / Feng, Qi / et al: Attribution of growing season evapotranspiration variability considering snowmelt and vegetation changes in the arid alpine basins. 2021. Copernicus Publications.


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