Moisture conditions are limiting evapotranspiration changes of alpine
mountains of Qilian Mountains
Abstract
Changes in evapotranspiration and its response to control variables are
crucial for understanding water balance and climate change in
high-altitude areas. Environmental changes will inevitably disturb
regional water cycles and water balance, especially in the high-altitude
alpine regions of the Qilian Mountains. To better understand the
variation of evapotranspiration at different altitudes in the
high-altitude region of the Qilian Mountains and the applicability of
the model and its response to environmental factors, we measured the
variation of actual evapotranspiration at three altitude gradients using
meteorological stations and automatic observation of continuous data
with a weighing-type micro-lysimeter at three altitude gradients of 3797
m, 4250 m, and 4303 m in the Shaliu River basin of the Qilian Mountains
during the growing season from June 2020 to October 2022 in our
research. Using ten models to calculate the variation of reference
evapotranspiration, and fitting them to the actual evapotranspiration,
we selected the most suitable model. The results showed that the
cumulative total evapotranspiration during the growing season in our
study period was 1974.556 mm, 2203.066 mm, and 2201.393 mm,
respectively, with intra-annual fluctuations consistent across the three
elevation gradients. The value of evapotranspiration in August showed
the highest at the monthly scale of 4.809 mm·day -1
and a bimodal variation at the daily scale with peaks at 10:00 and
15:00. The model of Dalton simulations showed the best results with the
lowest analysis of residuals (RA), root mean square error (RMSE), and
percentage error (PE), which had values of 3.291 mm·day
-1, 3.994 mm·day -1, and 0.692%,
and the values of R 2 between simulated and measured
values of 0.622, 0.609, and 0.420. Water balance results showed that a
portion of evapotranspiration in the study area originated from deep
soil moisture. Partial Least Squares Regression (PLSR) analysis and
enhanced regression tree model results indicated that precipitation was
the most important variable, with Variable Importance in Projection
(VIP) scores of 2.079 and a relative contribution to evapotranspiration
of 52.6%. Overall, moisture conditions and precipitation were important
factors limiting evapotranspiration variation in our research area. Our
findings have implications for future climate change conditions. This
conclusion is important for future water budget details in alpine
mountains under climate change.