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Mapping crop evapotranspiration by integrating vegetation indices into a soil water balance model

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  • Consoli, S.
  • Vanella, D.

Abstract

The approach combines the basal crop coefficient (Kcb) derived from vegetation indices (VIs) with the daily soil water balance, as proposed in the FAO-56 paper, to estimate daily crop evapotranspiration (ETc) rates of orange trees. The reliability of the approach to detect water stress was also assessed. VIs were simultaneously retrieved from Worldview 2 imagery and hyper-spectral data collected in the field for comparison. ETc estimated were analysed at the light of independent measurements of the same fluxes by an eddy covariance (EC) system located in the study area. The soil water depletion in the root zone of the crop simulated by the model was also validated by using an in situ soil water monitoring. Average overestimate of daily ETc of 6% was obtained from the proposed approach with respect to EC measurements, evidencing a quite satisfactory agreement between data. The model also detected several periods of light stress for the crop under study, corresponding to an increase of the root zone water deficit matching quite well the in situ soil water monitoring. The overall outcomes of this study showed that the FAO-56 approach with remote sensing-derived basal crop coefficient can have the potential to be applied for estimating crop water requirements and enhancing water management strategies in agricultural contexts.

Suggested Citation

  • Consoli, S. & Vanella, D., 2014. "Mapping crop evapotranspiration by integrating vegetation indices into a soil water balance model," Agricultural Water Management, Elsevier, vol. 143(C), pages 71-81.
    • Handle: RePEc:eee:agiwat:v:143:y:2014:i:c:p:71-81
    DOI: 10.1016/j.agwat.2014.06.012
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    6. Consoli, Simona & D'Urso, Guido & Toscano, Attilio, 2006. "Remote sensing to estimate ET-fluxes and the performance of an irrigation district in southern Italy," Agricultural Water Management, Elsevier, vol. 81(3), pages 295-314, March.
    7. Campos, Isidro & Neale, Christopher M.U. & Calera, Alfonso & Balbontín, Claudio & González-Piqueras, Jose, 2010. "Assessing satellite-based basal crop coefficients for irrigated grapes (Vitis vinifera L.)," Agricultural Water Management, Elsevier, vol. 98(1), pages 45-54, December.
    8. Er-Raki, S. & Chehbouni, A. & Guemouria, N. & Duchemin, B. & Ezzahar, J. & Hadria, R., 2007. "Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region," Agricultural Water Management, Elsevier, vol. 87(1), pages 41-54, January.
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    4. Awada, Hassan & Di Prima, Simone & Sirca, Costantino & Giadrossich, Filippo & Marras, Serena & Spano, Donatella & Pirastru, Mario, 2022. "A remote sensing and modeling integrated approach for constructing continuous time series of daily actual evapotranspiration," Agricultural Water Management, Elsevier, vol. 260(C).
    5. Mahmoud, Shereif H. & Gan, Thian Yew, 2019. "Irrigation water management in arid regions of Middle East: Assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data," Agricultural Water Management, Elsevier, vol. 212(C), pages 35-47.
    6. Consoli, S. & Licciardello, F. & Vanella, D. & Pasotti, L. & Villani, G. & Tomei, F., 2016. "Testing the water balance model criteria using TDR measurements, micrometeorological data and satellite-based information," Agricultural Water Management, Elsevier, vol. 170(C), pages 68-80.
    7. Rallo, G. & Paço, T.A. & Paredes, P. & Puig-Sirera, À. & Massai, R. & Provenzano, G. & Pereira, L.S., 2021. "Updated single and dual crop coefficients for tree and vine fruit crops," Agricultural Water Management, Elsevier, vol. 250(C).
    8. Aishajiang Aili & Xu Hailiang & Abdul Waheed & Zhao Wanyu & Xu Qiao & Zhao Xinfeng & Zhang Peng, 2024. "The Dynamics of Vegetation Evapotranspiration and Its Response to Surface Meteorological Factors in the Altay Mountains, Northwest China," Sustainability, MDPI, vol. 16(19), pages 1-19, October.
    9. Pôças, I. & Calera, A. & Campos, I. & Cunha, M., 2020. "Remote sensing for estimating and mapping single and basal crop coefficientes: A review on spectral vegetation indices approaches," Agricultural Water Management, Elsevier, vol. 233(C).
    10. Solgi, Shahin & Ahmadi, Seyed Hamid & Seidel, Sabine Julia, 2023. "Remote sensing of canopy water status of the irrigated winter wheat fields and the paired anomaly analyses on the spectral vegetation indices and grain yields," Agricultural Water Management, Elsevier, vol. 280(C).
    11. Carpintero, E. & Mateos, L. & Andreu, A. & González-Dugo, M.P., 2020. "Effect of the differences in spectral response of Mediterranean tree canopies on the estimation of evapotranspiration using vegetation index-based crop coefficients," Agricultural Water Management, Elsevier, vol. 238(C).
    12. Singh, Ajay, 2016. "Managing the water resources problems of irrigated agriculture through geospatial techniques: An overview," Agricultural Water Management, Elsevier, vol. 174(C), pages 2-10.
    13. Longo-Minnolo, G. & Vanella, D. & Consoli, S. & Intrigliolo, D.S. & Ramírez-Cuesta, J.M., 2020. "Integrating forecast meteorological data into the ArcDualKc model for estimating spatially distributed evapotranspiration rates of a citrus orchard," Agricultural Water Management, Elsevier, vol. 231(C).
    14. Singh, Ajay, 2019. "Poor-drainage-induced salinization of agricultural lands: Management through structural measures," Land Use Policy, Elsevier, vol. 82(C), pages 457-463.

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