IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i18p13904-d1242906.html
   My bibliography  Save this article

Spatiotemporal Variation of Evapotranspiration and Its Driving Factors in the Urumqi River Basin

Author

Listed:
  • Kamila Ablikim

    (Institute of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
    Xinjiang Key Laboratory of Lake Environment and Resources in Arid Zone, Xinjiang Normal University, Urumqi 830054, China)

  • Han Yang

    (Institute of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
    Xinjiang Key Laboratory of Lake Environment and Resources in Arid Zone, Xinjiang Normal University, Urumqi 830054, China)

  • Azimatjan Mamattursun

    (Institute of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
    Xinjiang Key Laboratory of Lake Environment and Resources in Arid Zone, Xinjiang Normal University, Urumqi 830054, China)

Abstract

Evapotranspiration (ET) is a key indicator of arid and semi-arid ecosystem processes and hydrological cycles. The study of basin-scale ET characteristics and drivers can provide a better understanding of regional water balance and energy cycles. This study used the Pixel Information Expert Engine platform based on MODIS (MOD16A2) data to extract the separate spatial and temporal characteristics of interannual and seasonal ET in the Urumqi River Basin in Xinjiang, China, over a 20-year period, from 2000 to 2020, and to analyze the influence of land-use data and altitude on ET in the basin. The average interannual ET in the watershed has had an increasing trend over the past two decades, varying from 126.57 mm to 247.66 mm, with the maximum ET in July and the minimum in December. On the seasonal scale, the ET trend is greatest in summer, followed by spring, and it is the least in winter. Spatially, the surface ET in the Urumqi River Basin is generally high in the upstream area and low in the downstream area, with the average multi-year ET throughout the basin falling within the range of 22.74–479.33 mm. The average ET for each type of land use showed that forest land had the highest ET and unused land the lowest. Analysis found that the effect of altitude on ET was more pronounced, with a significant increase in ET as altitude increases. Analysis of the drivers of ET change from 2000 to 2020 using the Optimal Parameters-based Geographical Detector model (OPGD) showed that the natural factors that had the greatest influence were, in descending order, temperature > vegetation cover > precipitation. Among the interacting factors, vegetation index with temperature, elevation, and precipitation and land use with elevation had a relatively greater influence on ET in the basin, and the effects of interacting factors were all greater than those of single factors.

Suggested Citation

  • Kamila Ablikim & Han Yang & Azimatjan Mamattursun, 2023. "Spatiotemporal Variation of Evapotranspiration and Its Driving Factors in the Urumqi River Basin," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13904-:d:1242906
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/18/13904/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/18/13904/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiuliang Yuan & Jie Bai, 2018. "Future Projected Changes in Local Evapotranspiration Coupled with Temperature and Precipitation Variation," Sustainability, MDPI, vol. 10(9), pages 1-14, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammet Omer Dis, 2023. "A New Approach for Completing Missing Data Series in Pan Evaporation Using Multi-Meteorologic Phenomena," Sustainability, MDPI, vol. 15(21), pages 1-16, November.
    2. Tonghui Yu & Xuan Huang & Shanshan Jia & Xufeng Cui, 2023. "Unveiling the Spatio-Temporal Evolution and Key Drivers for Urban Green High-Quality Development: A Comparative Analysis of China’s Five Major Urban Agglomerations," Land, MDPI, vol. 12(11), pages 1-25, October.

    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. Yang Wang & Shuai Zhang & Xueer Chang, 2020. "Evapotranspiration Estimation Based on Remote Sensing and the SEBAL Model in the Bosten Lake Basin of China," Sustainability, MDPI, vol. 12(18), pages 1-17, September.

    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:gam:jsusta:v:15:y:2023:i:18:p:13904-:d:1242906. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.