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Root Zone Soil Moisture Assessment at the Farm Scale Using Remote Sensing and Water Balance Models

Author

Listed:
  • Thanaporn Supriyasilp

    (Department of Civil Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Teerawat Suwanlertcharoen

    (Geo-Informatics and Space Technology Development Agency (Public Organization), Bangkok 10210, Thailand)

  • Nudnicha Pongput

    (Department of Environmental Science, Faculty of Environment, Kasetsart University, Bangkok 10900, Thailand)

  • Kobkiat Pongput

    (Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand)

Abstract

Water resource planning and management necessitates understanding soil moisture changes with depth in the root zone at the farm scale. For measuring soil moisture, remote sensing methods have been relatively successful. Soil moisture is estimated from image data, using in situ moisture and an empirical scattering model via regression fit analysis. However, in situ sensor data are prone to misinterpretations, requiring verification. Herein, we aimed at investigating the application of soil moisture from the water balance model towards verification of in situ soil moisture sensor data before in situ data was assessed for its relationship with remote sensing data. In situ soil moisture sensor data was obtained at 10 and 30 cm, and CROPWAT8.0 furnished root zone soil moisture data. The correlation between the in situ soil moisture at 10 and 30 cm was 0.78; the correlation between the soil moisture from CROPWAT8.0 and the in situ soil moisture were 0.64 and 0.62 at 10 and 30 cm, respectively. The R 2 between Sentinel-1 backscatter coefficients and in situ moisture were 0.74 and 0.68 at each depth, respectively. Therefore, the water balance model could verify sensor results before assessing in situ soil moisture data for relationship with remote sensing data.

Suggested Citation

  • Thanaporn Supriyasilp & Teerawat Suwanlertcharoen & Nudnicha Pongput & Kobkiat Pongput, 2022. "Root Zone Soil Moisture Assessment at the Farm Scale Using Remote Sensing and Water Balance Models," Sustainability, MDPI, vol. 14(3), pages 1-15, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1123-:d:728273
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    Cited by:

    1. Jingtian Ma & Yang Liu & Jiaying Liu & Guosong Fei & Ziwu Fan, 2023. "Modeling and Pilot-Scale Experiment of Hydrodynamic Regulation to Improve the Water Quality of a Plain Urban River Network: A Case Study of Changzhou, China," Sustainability, MDPI, vol. 15(7), pages 1-18, March.

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