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Using surface energy balance model to analyze evapotranspiration and soil salinity in the Manasi River Basin

Authors :
PENG Zicheng
YANG Xiaohu
YANG Haichang
ZHANG Fenghua
LIN Weiping
LI Juan
LI Haiyao
Source :
Guan'gai paishui xuebao, Vol 43, Iss 12, Pp 106-112 (2024)
Publication Year :
2024
Publisher :
Science Press, 2024.

Abstract

【Objective】 Evaluating evapotranspiration and soil salinization is critical for soil and water management but challenging on large scales. This paper investigates the feasibility of using remote sensing technologies and meteorological data to estimate evapotranspiration and soil salinization in irrigated areas. 【Method】 The study was conducted in the Manasi River Basin in Northeastern China. It was based on the Surface Energy Balance System (SEBS) model, using the Landsat-8 remote sensing data and field sampling to estimate spatial distribution of both evapotranspiration and soil salinity in the studied area. 【Result】 ① The normalized vegetation index (R2 = 0.644 8), surface specific emissivity (R2 = 0.637 7), and surface temperature (R2 = 0.558 3) all showed a strong correlation with soil salinity, while surface albedo (R2 = 0.198 6) had a weaker correlation with soil salinity. ② Daily evapotranspiration (ET) in the Manasi River Basin ranged from 0.024 to 5.403 mm, with an average of 3.866 mm. ET decreased from the Southern irrigation area to the Northern Gobi region. ③ ET values less than 3.60 mm/d were associated with non-saline and moderate saline soils. For areas with ET between 3.60 mm/d and 4.05 mm/d, moderate soil salinity dominated. For areas with ET exceeding 4.05 mm/d, the proportion of severe soil salinity increased significantly. 【Conclusion】 Using remotely sensed satellite imagery, the SEBS model provides an accurate, high-resolution estimate of evapotranspiration in terrestrial systems. The evapotranspiration was positively correlated with soil salinity in the Manasi River Basin. These results can help improve land and water management in the region.

Details

Language :
Chinese
ISSN :
16723317
Volume :
43
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Guan'gai paishui xuebao
Publication Type :
Academic Journal
Accession number :
edsdoj.03c12d85acd147bfa376b21d76471fb9
Document Type :
article
Full Text :
https://doi.org/10.13522/j.cnki.ggps.2024154