IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v298y2024ics0378377424001999.html
   My bibliography  Save this article

Estimation and validation of high-resolution evapotranspiration products for an arid river basin using multi-source remote sensing data

Author

Listed:
  • Xiao, Jing
  • Sun, Fubao
  • Wang, Tingting
  • Wang, Hong

Abstract

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 16-day 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.

Suggested Citation

  • 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, Elsevier, vol. 298(C).
    • Handle: RePEc:eee:agiwat:v:298:y:2024:i:c:s0378377424001999
    DOI: 10.1016/j.agwat.2024.108864
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377424001999
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2024.108864?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xue, Jingyuan & Bali, Khaled M. & Light, Sarah & Hessels, Tim & Kisekka, Isaya, 2020. "Evaluation of remote sensing-based evapotranspiration models against surface renewal in almonds, tomatoes and maize," Agricultural Water Management, Elsevier, vol. 238(C).
    2. Xu, Hailiang & Ye, Mao & Li, Jimei, 2008. "The water transfer effects on agricultural development in the lower Tarim River, Xinjiang of China," Agricultural Water Management, Elsevier, vol. 95(1), pages 59-68, January.
    3. Yu, Yang & Yu, Ruide & Chen, Xi & Yu, Guoan & Gan, Miao & Disse, Markus, 2017. "Agricultural water allocation strategies along the oasis of Tarim River in Northwest China," Agricultural Water Management, Elsevier, vol. 187(C), pages 24-36.
    4. Meng Zhao & Geruo A & Yanlan Liu & Alexandra G. Konings, 2022. "Evapotranspiration frequently increases during droughts," Nature Climate Change, Nature, vol. 12(11), pages 1024-1030, November.
    5. Yash Agrawal & Manoranjan Kumar & Supriya Ananthakrishnan & Gopalakrishnan Kumarapuram, 2022. "Evapotranspiration Modeling Using Different Tree Based Ensembled Machine Learning Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(3), pages 1025-1042, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peddinti, Srinivasa Rao & Kisekka, Isaya, 2022. "Estimation of turbulent fluxes over almond orchards using high-resolution aerial imagery with one and two-source energy balance models," Agricultural Water Management, Elsevier, vol. 269(C).
    2. Wu, Hao & Xu, Min & Peng, Zhuoyue & Chen, Xiaoping, 2022. "Quantifying the potential impacts of meltwater on cotton yields in the Tarim River Basin, Central Asia," Agricultural Water Management, Elsevier, vol. 269(C).
    3. Yan, Haofang & Li, Mi & Zhang, Chuan & Zhang, Jianyun & Wang, Guoqing & Yu, Jianjun & Ma, Jiamin & Zhao, Shuang, 2022. "Comparison of evapotranspiration upscaling methods from instantaneous to daytime scale for tea and wheat in southeast China," Agricultural Water Management, Elsevier, vol. 264(C).
    4. Xue, Jingyuan & Fulton, Allan & Kisekka, Isaya, 2021. "Evaluating the role of remote sensing-based energy balance models in improving site-specific irrigation management for young walnut orchards," Agricultural Water Management, Elsevier, vol. 256(C).
    5. Yan, Dong & Chen, Lin & Sun, Huaiwei & Liao, Weihong & Chen, Haorui & Wei, Guanghui & Zhang, Wenxin & Tuo, Ye, 2022. "Allocation of ecological water rights considering ecological networks in arid watersheds: A framework and case study of Tarim River basin," Agricultural Water Management, Elsevier, vol. 267(C).
    6. Shaochun Huang & Valentina Krysanova & Jianqing Zhai & Buda Su, 2015. "Impact of Intensive Irrigation Activities on River Discharge Under Agricultural Scenarios in the Semi-Arid Aksu River Basin, Northwest China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(3), pages 945-959, February.
    7. Qi Liu & Yi Liu & Jie Niu & Dongwei Gui & Bill X. Hu, 2022. "Prediction of the Irrigation Area Carrying Capacity in the Tarim River Basin under Climate Change," Agriculture, MDPI, vol. 12(5), pages 1-14, April.
    8. Bretreger, David & Yeo, In-Young & Hancock, Greg, 2022. "Quantifying irrigation water use with remote sensing: Soil water deficit modelling with uncertain soil parameters," Agricultural Water Management, Elsevier, vol. 260(C).
    9. Xiyi Wang & Shuzhen Peng & Hongbo Ling & Hailiang Xu & Tingting Ma, 2019. "Do Ecosystem Service Value Increase and Environmental Quality Improve due to Large–Scale Ecological Water Conveyance in an Arid Region of China?," Sustainability, MDPI, vol. 11(23), pages 1-18, November.
    10. Fenghua Zhang & Munir Hanjra & Fan Hua & Yunqiao Shu & Yuyi Li, 2014. "Analysis of climate variability in the Manas River Valley, North-Western China (1956–2006)," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 19(7), pages 1091-1107, October.
    11. Jayashree T R & NV Subba Reddy & U Dinesh Acharya, 2023. "Modeling Daily Reference Evapotranspiration from Climate Variables: Assessment of Bagging and Boosting Regression Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1013-1032, February.
    12. Dilip Kumar Roy & Tapash Kumar Sarkar & Sujit Kumar Biswas & Bithin Datta, 2023. "Generalized Daily Reference Evapotranspiration Models Based on a Hybrid Optimization Algorithm Tuned Fuzzy Tree Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 193-218, January.
    13. Bin Guo & Weihong Li & Jinyun Guo & Chuanfa Chen, 2015. "Risk Assessment of Regional Irrigation Water Demand and Supply in an Arid Inland River Basin of Northwestern China," Sustainability, MDPI, vol. 7(9), pages 1-16, September.
    14. Yu, Yang & Yu, Ruide & Chen, Xi & Yu, Guoan & Gan, Miao & Disse, Markus, 2017. "Agricultural water allocation strategies along the oasis of Tarim River in Northwest China," Agricultural Water Management, Elsevier, vol. 187(C), pages 24-36.
    15. He, Ruyan & Jin, Yufang & Jiang, Jinbao & Xu, Meng & Jia, Sen, 2022. "Sensitivity of METRIC-based tree crop evapotranspiration estimation to meteorology, land surface parameters and domain size," Agricultural Water Management, Elsevier, vol. 271(C).
    16. Jinyao Lin & Qitong Chen, 2023. "Analyzing and Simulating the Influence of a Water Conveyance Project on Land Use Conditions in the Tarim River Region," Land, MDPI, vol. 12(11), pages 1-16, November.
    17. Hertzog, Thomas & Poussin, Jean-Christophe & Tangara, Bréhima & Kouriba, Indé & Jamin, Jean-Yves, 2014. "A role playing game to address future water management issues in a large irrigated system: Experience from Mali," Agricultural Water Management, Elsevier, vol. 137(C), pages 1-14.
    18. Hao, Pengyu & Di, Liping & Guo, Liying, 2022. "Estimation of crop evapotranspiration from MODIS data by combining random forest and trapezoidal models," Agricultural Water Management, Elsevier, vol. 259(C).
    19. Xinqin Gu & Li Yao & Lifeng Wu, 2023. "Prediction of Water Carbon Fluxes and Emission Causes in Rice Paddies Using Two Tree-Based Ensemble Algorithms," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
    20. Linker, Raphael & Kisekka, Isaya, 2022. "Concurrent data assimilation and model-based optimization of irrigation scheduling," Agricultural Water Management, Elsevier, vol. 274(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:298:y:2024:i:c:s0378377424001999. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.