2023
DOI: 10.1007/s40333-023-0001-z
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Biocrust-induced partitioning of soil water between grass and shrub in a desert steppe of Northwest China

Abstract: Maintaining the stability of exotic sand-binding shrub has become a large challenge in arid and semi-arid grassland ecosystems in northern China. We investigated two kinds of shrublands with different BSCs (biological soil crusts) cover in desert steppe in Northwest China to characterize the water sources of shrub (Caragana intermedia Kuang et H. C. Fu) and grass (Artemisia scoparia Waldst. et Kit.) by stable 18 O isotopic. Our results showed that both shrublands were subject to persistent soil water deficienc… Show more

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“…Quantitative assessment of the soil-atmosphere transformation processes using remotely sensed data provides a better understanding of the relationship between crop growth and water resource management [12]. The effectiveness of spatiotemporal engineering of land surface evapotranspiration and irrigation water consumption in the Yanqi Basin at the farmland scale was evaluated using MODIS remote sensing data and HTEM (hybrid dual-source scheme and trapezoid framework-based evapotranspiration model) [13] modeling of this region [14]. In that study, remote sensing was used to identify the area of arable land [15], compensating for the limitations of statistical data that can only be counted at the county and city levels, as well as the problem of data accuracy, making the results more rapid and accurate.…”
Section: Introductionmentioning
confidence: 99%
“…Quantitative assessment of the soil-atmosphere transformation processes using remotely sensed data provides a better understanding of the relationship between crop growth and water resource management [12]. The effectiveness of spatiotemporal engineering of land surface evapotranspiration and irrigation water consumption in the Yanqi Basin at the farmland scale was evaluated using MODIS remote sensing data and HTEM (hybrid dual-source scheme and trapezoid framework-based evapotranspiration model) [13] modeling of this region [14]. In that study, remote sensing was used to identify the area of arable land [15], compensating for the limitations of statistical data that can only be counted at the county and city levels, as well as the problem of data accuracy, making the results more rapid and accurate.…”
Section: Introductionmentioning
confidence: 99%