Author
Listed:
- Noory, Hamideh
- Khoshsima, Morteza
- Tsunekawa, Atsushi
- Tsubo, Mitsuru
- Haregeweyn, Nigussie
- Pashapour, Salar
Abstract
Efficient use of water and irrigation management are essential to sustain irrigated agriculture in drylands, where water resources are limited. Because of the high cost and difficulties of operation and maintenance of in situ instrumentation over irrigated fields, fine-scale monitoring of soil moisture (SM) based on remote sensing and a simulation model may be a practical way to inform irrigation practices. We herein propose a method for integration of low-cost, available, multi-source data, including field data (crop, soil, and weather) and high-resolution satellite data (Sentinel-2 and Landsat-8) into a soil–water–atmosphere–plant (SWAP) model to provide daily, accurate surface- and root-zone SM at the field scale that can inform optimal management of irrigation water. Specifically, effective soil parameters and crop growth in the SWAP model were parameterized and updated using satellite-based surface SM and leaf area index data obtained using inverse modeling and assimilation techniques. We applied and evaluated the developed method for the surface- and root-zone SM estimates using the measured SM over 13 marked locations in six study fields in Iran with two crop types, wheat and maize. The proposed method showed promising results at all marked locations, study fields, study crops, crop growth stages, and monitored soil depths and layers. The root mean square errors (RMSEs) and coefficients of determination (R2 values) were < 0.032 cm3 cm−3 and 0.52–0.95, respectively. The results showed that the type of irrigation system had a direct effect on the SM estimated with the proposed method. The proposed method could improve the spatiotemporal resolution of surface and root-zone SM monitoring via simulation of daily root-zone SM at a spatial resolution of 10 m. This method may enable the development of precise irrigation systems that optimize water allocations and conserve limited water resources at the field scale.
Suggested Citation
Noory, Hamideh & Khoshsima, Morteza & Tsunekawa, Atsushi & Tsubo, Mitsuru & Haregeweyn, Nigussie & Pashapour, Salar, 2025.
"Developing a method for root-zone soil moisture monitoring at the field scale using remote sensing and simulation modeling,"
Agricultural Water Management, Elsevier, vol. 308(C).
Handle:
RePEc:eee:agiwat:v:308:y:2025:i:c:s0378377424005997
DOI: 10.1016/j.agwat.2024.109263
Download full text from publisher
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:eee:agiwat:v:308:y:2025:i:c:s0378377424005997. 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: 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.