Estimation and validation of high-resolution evapotranspiration products for an arid river basin using multi-source remote sensing data
文献类型：期刊论文
| 作者 | Xiao, Jing4,5; Sun, Fubao2,3,4,5; Wang, Tingting2; Wang, Hong2 |
| 刊名 | AGRICULTURAL WATER MANAGEMENT
 |
| 出版日期 | 2024-06-01 |
| 卷号 | 298页码:108864 |
| 关键词 | Surface energy balance model Spatiotemporal evapotranspiration pattern Landsat images Uncertainty |
| DOI | 10.1016/j.agwat.2024.108864 |
| 产权排序 | 4 |
| 文献子类 | Article |
| 英文摘要 | Accurate estimation of evapotranspiration (ET) at high spatial resolution is crucial for drought monitoring and water resources management, but currently available remote sensing ET products generally have coarse spatial resolution (>= 1000 m). To estimate ET at a high spatial resolution, Landsat images, Global Land Surface Satellite (GLASS), Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological forcing data were integrated, and the surface energy balance (SEBS) model was employed to calculate the 16 -day average ET at 30 m resolution for China ' s Tarim River Basin, spanning from 2009 to 2018. The results indicated that the average 16day ET estimates correlated well with ground observations for land and water surfaces (root mean square error (RMSE) for land = 0.92 mm day - 1 , RMSE for water = 1.63 mm day - 1 , mean bias for land = 0.3 mm day - 1 , mean bias for water = 0.52 mm day - 1 ). Cross validation with GLASS, ETMonitor, and Penman-Monteith-Leuning (PML_V2) ET datasets revealed an overall increasing trend for all four products (PML_V2 = 6.277 mm year - 1 , GLASS = 2.185 mm year -1 , ETMonitor = 3.258 mm year - 1 , SEBS = 1.441 mm year - 1 ), demonstrating good spatial consistency. The consistent increasing pixels were primarily distributed in the northern, southwestern, and southeastern mountainous regions, accounting for 22.8%, while 0.29% of the consistent decreasing pixels were mainly concentrated in the central desert and mountain -front oasis areas. Inconsistent pixels accounted for 76.9%, with 2.34% of the inconsistent decreasing pixels exhibiting a scattered distribution, while 37.28% of the inconsistent increasing pixels were mainly found in the central desert and some oasis areas. Furthermore, SEBS ET trend analysis indicated that the oasis area experienced more pronounced changes than the mountainous and desert areas during the 2009 - 2018 period. The SEBS ET estimated in this study can provide high -precision data support and a reference for future research on the water resources management. |
| WOS关键词 | SURFACE-ENERGY-BALANCE ; AREA INDEX ESTIMATION ; WACMOS-ET PROJECT ; LATENT-HEAT FLUX ; TARIM RIVER ; GLOBAL EVAPOTRANSPIRATION ; TERRESTRIAL EVAPOTRANSPIRATION ; IMPROVING EVAPOTRANSPIRATION ; SPATIOTEMPORAL FUSION ; HEIHE RIVER |
| WOS研究方向 | Agriculture ; Water Resources |
| WOS记录号 | WOS:001241852500001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/205333]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Sun, Fubao; Wang, Tingting |
| 作者单位 | 1.Datun Rd 11, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Akesu Natl Stn Observat & Res Oasis Agroecosyst, Akesu 843017, Xinjiang, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xiao, Jing,Sun, Fubao,Wang, Tingting,et al. Estimation and validation of high-resolution evapotranspiration products for an arid river basin using multi-source remote sensing data[J]. AGRICULTURAL WATER MANAGEMENT,2024,298:108864. |
| APA | Xiao, Jing,Sun, Fubao,Wang, Tingting,&Wang, Hong.(2024).Estimation and validation of high-resolution evapotranspiration products for an arid river basin using multi-source remote sensing data.AGRICULTURAL WATER MANAGEMENT,298,108864. |
| MLA | Xiao, Jing,et al."Estimation and validation of high-resolution evapotranspiration products for an arid river basin using multi-source remote sensing data".AGRICULTURAL WATER MANAGEMENT 298(2024):108864. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。