Spatiotemporal variations in evapotranspiration and its influencing factors in the semiarid Hailar river basin, Northern China

Wang, Libo; Wang, Guoqiang; Xue, Baolin; Yinglan, A; Fang, Qingqing; Shrestha, Sangam

doi:10.1016/j.envres.2022.113275

Cited by 9 publications

(5 citation statements)

References 42 publications

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“…Our study only analyzed two driving factors for ET a , namely temperature and precipitation. Although previous studies have confirmed that these two factors exert a significant impact on ET a [72,73], the changes in ET are also influenced by other factors. These include other meteorological factors, terrain factors, vegetation coverage, and human activities.…”

Section: Limitations and Future Prospectsmentioning

confidence: 87%

Spatiotemporal Characteristics of Actual Evapotranspiration Changes and Their Climatic Causes in China

Dai,

Chen,

Cui

et al. 2023

Remote Sensing

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As the main expenditure item in water balance, evapotranspiration has an important impact on the surface ecosystem. Assessing the impact of changes in meteorological elements on evapotranspiration is essential to identify the spatiotemporal heterogeneity of hydrographic responses to climate changes. Based on the actual evapotranspiration (ETa) product (GPR-ET) generated by Gaussian process regression (GPR), as well as temperature and precipitation datasets, our study employed various statistical analysis methods, including geographic detector, the center of gravity migration model, spatial variation coefficients, and partial differential models, to investigate the spatiotemporal variation in ETa in China from 2000 to 2018. The analysis covered future trends in ETa changes and the contribution of meteorological factors. Our results showed that the ETa in northwest China had stronger spatial heterogeneity and the mean value was generally lower than that in the southeast. But the center of gravity of ETa was shifting towards the northwest. In most areas, the future trend was expected to be inconsistent with the current stage. ETa in the regions of north and west was mainly driven by precipitation, while its increase in southeast China was largely attributed to temperature. In addition to spatial variations, the joint enhancement effect of temperature and precipitation on ETa exists. According to the contribution analysis, precipitation contributed more to the change in ETa than temperature. These findings have enhanced our comprehension of the contribution of climate variability to ETa changes, providing scientific proof for the optimization apportion of future water resources.

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Section: Limitations and Future Prospectsmentioning

confidence: 87%

Spatiotemporal Characteristics of Actual Evapotranspiration Changes and Their Climatic Causes in China

Dai,

Chen,

Cui

et al. 2023

Remote Sensing

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“…During this period, plant growth entered the late stage and scrub plants started to lose their leaves (Xu et al, 2021), and plant photosynthesis and respiration gradually decreased, which resulting in a significant decrease in the contribution of plant transpiration to evapotranspiration. At the same time, the relative humidity of the atmosphere was low (Tang & Tang, 2021; Wang, Wang, Liu, et al, 2022; Wang, Wang, Xue, et al, 2022), which facilitated the evaporation of soil water and a significant increase in the contribution of soil evaporation to evapotranspiration. In comparison to semi‐shaded aspect, the percentage of plant transpiration on semi‐sunny aspect was slightly higher during this period, which was related to the relatively later leafing of scrub plants for the better light conditions and the relatively stronger plant transpiration on semi‐sunny aspect.…”

Section: Discussionmentioning

confidence: 99%

“…The influence of meteorological elements on local evapotranspiration is more obvious. Relevant studies showed that the main meteorological elements affecting evapotranspiration were precipitation, temperature, relative humidity, wind speed and solar radiation, and so forth (Ju et al, 2022; Li & Yu, 2020; Tang & Tang, 2021; Wang, Wang, Liu, et al, 2022; Wang, Wang, Xue, et al, 2022). Precipitation is one of the most important factors affecting on evapotranspiration change, especially in arid and semi‐arid areas where precipitation is a key variable affecting evapotranspiration by increasing soil water content and promoting plant growth (Jin et al, 2017; Li et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

Evapotranspiration variation of soil‐plant‐atmosphere continuum in subalpine scrubland of Qilian Mountains in China

Yu,

Jia,

Zhang

et al. 2024

Hydrological Processes

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The water cycle in the soil‐plant‐atmosphere continuum is an important element of hydrological and ecological studies, and differences in the composition characteristics of hydrogen and oxygen stable isotopes in different water bodies can indicate water cycling processes. In this study, hydrogen and oxygen isotopes of precipitation, soil water and plant water samples had been collected in the subalpine scrubland of the Qilian Mountains from May to October 2019. The Craig‐Gordon model, the isotopic steady‐state (ISS) assumption, the Keeling Plot model and the two‐source mixing model were used to analyse the stable isotope compositions of different water bodies, the stable isotope characteristics of water vapour of soil evaporation and plant transpiration and the variation of evapotranspiration in the SPAC of the subalpine scrubland. The results showed that plant transpiration (FT) contributed 87.28% and 86.95% to evapotranspiration and soil evaporation (FE) contributed 12.72% and 13.05% to evapotranspiration in the growing season on semi‐sunny and semi‐shaded aspects, respectively, indicating that evapotranspiration in the subalpine scrubland mainly came from the transpiration of scrubland plants. In the early of the growing season (May–June), due to the rapid expansion of plant leaves, the contribution of transpiration to evapotranspiration was at a high level, which intensified transpiration and led to a gradual increase of the transpiration contribution. In the middle of the growing season (July–August), owing to better conditions of rain and heat that made plants grow vigorously, plant transpiration made the highest contribution to evapotranspiration more than 90%, which caused to an overwhelming contribution of plant transpiration to evapotranspiration. In the later of growing season (September to October), the contribution of plant transpiration to evapotranspiration decreased significantly while that of soil evaporation increased, which was because plant photosynthesis and respiration gradually declined for losing their leaves of scrub plants and the relative atmospheric humidity was lower.

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“…Among such methods, the eddy covariance (EC) technique is generally considered the most accurate method for measuring ET [12], and many studies have used ET measurements obtained at flux stations as a basis to evaluate the reliability of other models [13]. The second way to obtain ET is through simulations, including remote sensing estimations, model simulations, and assimilations [14]. Such models are based on specific physical mechanisms with good spatial continuity and wide coverage.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Framework for Simulating Actual Evapotranspiration in Data-Deficient Areas: A Case Study of the Inner Mongolia Section of the Yellow River Basin

Jiang

Wang

et al. 2023

Remote Sensing

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Evapotranspiration (ET) plays an import role in transferring water and converting energy in the land‒atmosphere system. Accurately estimating ET is crucial for understanding global climate change, ecological environmental problems, the water cycle, and hydrological processes. Machine learning (ML) algorithms have been considered as a promising method for estimating ET in recent years. However, due to the limitations associated with the spatial–temporal resolution of the flux tower data commonly used as the target set in ML algorithms, the ability of ML to discover the inherent laws within the data is reduced. In this study, a hybrid framework was established to simulate ET in data-deficient areas. ET simulation results of a coupled model comprising the Budyko function and complementary principle (BC2021) were used as the target set of the random forest model, instead of using the flux station observation data. By combining meteorological and hydrological data, the monthly ET of the Inner Mongolia section of the Yellow River Basin (IMSYRB) was simulated from 1982 to 2020, and good results were obtained (R2 = 0.94, MAE = 3.82 mm/mon, RMSE = 5.07 mm/mon). Furthermore, the temporal and spatial variations in ET and the influencing factors were analysed. In the past 40 years, annual ET in the IMSYRB ranged between 241.38 mm and 326.37 mm, showing a fluctuating growth trend (slope = 0.80 mm/yr), and the summer ET accounted for the highest proportion in the year. Spatially, ET in the IMSYRB showed a regular distribution of high ET in the eastern region and low ET in the western area. The high ET value areas gradually expanded from east to west over time, and the area increased continuously, with the largest increase observed in the 1980s. Temperature, precipitation, and normalized difference vegetation index (NDVI) were found to be the most important factors affecting ET in the region and play a positive role in promoting ET changes. These results provide an excellent example of long-term and large-scale accurate ET simulations in an area with sparse flux stations.

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Spatiotemporal variations in evapotranspiration and its influencing factors in the semiarid Hailar river basin, Northern China

Cited by 9 publications

References 42 publications

Spatiotemporal Characteristics of Actual Evapotranspiration Changes and Their Climatic Causes in China

Spatiotemporal Characteristics of Actual Evapotranspiration Changes and Their Climatic Causes in China

Evapotranspiration variation of soil‐plant‐atmosphere continuum in subalpine scrubland of Qilian Mountains in China

A Hybrid Framework for Simulating Actual Evapotranspiration in Data-Deficient Areas: A Case Study of the Inner Mongolia Section of the Yellow River Basin

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