IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12792-d935696.html
   My bibliography  Save this article

Low-Altitude Remote Sensing Inversion of River Flow in Ungauged Basins

Author

Listed:
  • Mingtong Zhou

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China)

  • Yuchuan Guo

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China)

  • Ning Wang

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China)

  • Xuan Wei

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China)

  • Yunbao Bai

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China)

  • Huijing Wang

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China)

Abstract

Runoff is closely related to human production, the regional environment, and hydrological characteristics. It is also an important basis for water cycle research and regional water resource development and management. However, obtaining hydrological information for uninformed river sections is complicated by harsh environments, limited transportation, sparse populations, and a low density of hydrological observation stations in the inland arid zone. Here, low-altitude remote sensing technology was introduced to combine riverbed characteristics through unmanned aerial vehicle (UAV) inversion with classical hydraulic equations for ungauged basins in the middle and lower reaches of the Keriya River, northwest China, and investigate the applicability of this method on wide and shallow riverbeds of inland rivers. The results indicated that the estimated average error of the low-altitude remote sensing flow was 8.49% (ranging 3.26–17.00%), with a root mean square error (RMSE) of 0.59 m 3 ·s −1 across the six selected river sections, suggesting that this method has some applicability in the study area. Simultaneously, a method for estimating river flow based on the water surface width– and water depth–flow relationship curves for each section was proposed whereas the precise relationships were selected based on actual section attributes to provide a new method for obtaining runoff data in small- and medium-scale river areas where information is lacking.

Suggested Citation

  • Mingtong Zhou & Yuchuan Guo & Ning Wang & Xuan Wei & Yunbao Bai & Huijing Wang, 2022. "Low-Altitude Remote Sensing Inversion of River Flow in Ungauged Basins," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12792-:d:935696
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12792/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/19/12792/
    Download Restriction: no
    ---><---

    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:14:y:2022:i:19:p:12792-:d:935696. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.