IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v39y2025i2d10.1007_s11269-024-03992-9.html
   My bibliography  Save this article

Evaluation of Sentinel-1 Satellite-based Soil Moisture Products for Runoff Modelling with Karst Formation Characteristics

Author

Listed:
  • Hanggar Ganara Mawandha

    (Universitas Gadjah Mada)

  • Afinafghani Duta Pratama

    (Universitas Gadjah Mada)

  • M. Ramadhan Al Ghifari

    (Universitas Gadjah Mada)

  • Nasywa Hanin Hanifah

    (Universitas Gadjah Mada)

  • Issiami Nursafa

    (Universitas Gadjah Mada)

  • Prieskarinda Lestari

    (Universitas Gadjah Mada)

  • Satoru Oishi

    (Kobe University)

Abstract

High soil moisture levels reduce the soil’s ability to absorb rainfall, leading to increased surface runoff. In karst regions, the presence of underground channels and conduits means that water can quickly move through the subsurface. High soil moisture can lead to accelerated groundwater flow through these karst features. Increased subsurface flow might result in delayed but intense surface flooding. Recently, remote sensing technology has demonstrated considerable potential for the assessment of soil moisture conditions. This research aims to identify the soil moisture characteristics in karst formations for runoff estimation based on remote sensing imagery obtained from the Sentinel-1 satellite. The soil moisture was calculated by the TOPP equation based on the soil dielectric value obtained from the Dubois model. By employing a variety of land use types and soil moisture data obtained from the Sentinel-1 satellite, Curve Number (CN) values were generated and subsequently utilized to estimate runoff. The remaining biases in the estimation were attributable to factors such as dense shade, land slope, and cloud cover. Based on the extracted vertical transmit-vertical receive polarization in Sentinel-1 A for karst regions, soil moisture was calculated as 0.055 cm3/cm3. The model produces real-time Curve Number-based Soil Moisture data that can be integrated with a rainfall runoff model utilizing the SCS-CN, so-called CN-SM model. The runoff estimate gives a difference of 0.052 m³/s greater then the observed runoff value. As a result of these findings, soil moisture monitoring is essential for determining CN values accurately for runoff estimates.

Suggested Citation

  • Hanggar Ganara Mawandha & Afinafghani Duta Pratama & M. Ramadhan Al Ghifari & Nasywa Hanin Hanifah & Issiami Nursafa & Prieskarinda Lestari & Satoru Oishi, 2025. "Evaluation of Sentinel-1 Satellite-based Soil Moisture Products for Runoff Modelling with Karst Formation Characteristics," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(2), pages 821-846, January.
    • Handle: RePEc:spr:waterr:v:39:y:2025:i:2:d:10.1007_s11269-024-03992-9
    DOI: 10.1007/s11269-024-03992-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-024-03992-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-024-03992-9?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.

    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:spr:waterr:v:39:y:2025:i:2:d:10.1007_s11269-024-03992-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.