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Evaluation of single crop coefficient curves derived from Landsat satellite images for major crops in Iran

Author

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  • Mokhtari, Ali
  • Noory, Hamideh
  • Vazifedoust, Majid
  • Palouj, Mojtaba
  • Bakhtiari, Atousa
  • Barikani, Elham
  • Zabihi Afrooz, Ramezan Ali
  • Fereydooni, Fatemeh
  • Sadeghi Naeni, Ali
  • Pourshakouri, Farrokh
  • Badiehneshin, Alireza
  • Afrasiabian, Yasamin

Abstract

Improving the accuracy of single crop coefficient (Kc) for major crops at regional scales would significantly result in optimizing the consumption of agriculture water. In this study, a new approach is applied to generate Kc curves from satellite images based on the Priestley-Taylor equation. The equation mainly consists of shortwave radiation and thermal terms. Therefore in order to meet the equation’s requirements, the Landsat optical data was considered as the essential satellite-based input of the approach, yet thermal data was obtained from the MODIS imagery which was primarily downscaled using the TsHARP algorithm to fit the 30 m spatial resolution of Landsat; therefore, in this study the method is referred to as the MultiSensor Data Fusion for potential EvapoTranspiration calculation (MSDF-ET). The Kc trends were first evaluated for annual crops (forage maize, sugar beet, wheat, and barley) in two different regions (the Qazvin and Tehran-Karaj plains) using field observation data of Leaf Area Index (LAI). The method was then applied to the major crops in 31 selected plains with three different climatic conditions in Iran. Climatic conditions were categorized into cold (North West region), arid (Central region), and warm and humid (South West region). Eventually, crop water requirements (CWR) in different regions were compared considering long-term air temperature, wind, and relative humidity (RH) variations. Evaluation of the method in the Qazvin and Tehran-Karaj plains showed promising results. The Kc trend varied according to the LAI and temperature variability. Crop growth duration and especially Kc curves were successfully extracted using remotely sensed data in the studied areas. CWR in the zone with higher values of air temperature, notably in warm seasons, was higher in comparison with other climatic zones. Also lengths of the growing seasons were shorter. In conclusion, surface and groundwater resources management would be improved as the result of taking satellite data into account for Kc and subsequently CWR calculations.

Suggested Citation

  • Mokhtari, Ali & Noory, Hamideh & Vazifedoust, Majid & Palouj, Mojtaba & Bakhtiari, Atousa & Barikani, Elham & Zabihi Afrooz, Ramezan Ali & Fereydooni, Fatemeh & Sadeghi Naeni, Ali & Pourshakouri, Farr, 2019. "Evaluation of single crop coefficient curves derived from Landsat satellite images for major crops in Iran," Agricultural Water Management, Elsevier, vol. 218(C), pages 234-249.
    • Handle: RePEc:eee:agiwat:v:218:y:2019:i:c:p:234-249
    DOI: 10.1016/j.agwat.2019.03.024
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    References listed on IDEAS

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    1. González-Dugo, M.P. & Escuin, S. & Cano, F. & Cifuentes, V. & Padilla, F.L.M. & Tirado, J.L. & Oyonarte, N. & Fernández, P. & Mateos, L., 2013. "Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. II. Application on basin scale," Agricultural Water Management, Elsevier, vol. 125(C), pages 92-104.
    2. Mokhtari, Ali & Noory, Hamideh & Vazifedoust, Majid & Bahrami, Mahdi, 2018. "Estimating net irrigation requirement of winter wheat using model- and satellite-based single and basal crop coefficients," Agricultural Water Management, Elsevier, vol. 208(C), pages 95-106.
    3. Lian, Jinjiao & Huang, Mingbin, 2016. "Comparison of three remote sensing based models to estimate evapotranspiration in an oasis-desert region," Agricultural Water Management, Elsevier, vol. 165(C), pages 153-162.
    4. Gonzalez-Dugo, M.P. & Mateos, L., 2008. "Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops," Agricultural Water Management, Elsevier, vol. 95(1), pages 48-58, January.
    5. Allen, Richard G. & Pereira, Luis S. & Howell, Terry A. & Jensen, Marvin E., 2011. "Evapotranspiration information reporting: I. Factors governing measurement accuracy," Agricultural Water Management, Elsevier, vol. 98(6), pages 899-920, April.
    6. Mateos, L. & González-Dugo, M.P. & Testi, L. & Villalobos, F.J., 2013. "Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. I. Method validation," Agricultural Water Management, Elsevier, vol. 125(C), pages 81-91.
    7. Alireza Sharifi & Yagob Dinpashoh, 2014. "Sensitivity Analysis of the Penman-Monteith reference Crop Evapotranspiration to Climatic Variables in Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5465-5476, December.
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    2. Alexandris, Stavros & Proutsos, Nikolaos, 2020. "How significant is the effect of the surface characteristics on the Reference Evapotranspiration estimates?," Agricultural Water Management, Elsevier, vol. 237(C).

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