Agriculture, Forestry and Fisheries

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Evapotranspiration and Water Stress Estimation from TIR and SWIR Bands

Received: 25 October 2014    Accepted: 10 November 2014    Published: 17 November 2014
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Abstract

The World agriculture depends on water availability; thus, a successful water management system would assure food for the World. For several decades, the scientific community has developed methods to support water management. These models include the estimates of the main water loss in the system, i.e. the evapotranspiration (ET). In turn, the satellite technology encouraged the development of new models to monitor large regions. In this work, we present a modified ET estimation adapting the F parameter introduced by Venturini et al., in 2008. Additionally, a new simple index to estimate water stress (WS) for different types of surfaces, is also presented. The relative evaporation represented by F is derived from the soil moisture condition following the formulation of Barton and computed from the surface reflectance in the shortwave infrared bands (SWIR). The new ET and WS equations are applicable, with different satellite datasets, to any remote region since they are based on universal relationships. The preliminary results show errors of about 11% in ET. In general, the new WS index would have values of approximately 0.8 for a dry surface and 0.4 for a wet surface.

DOI 10.11648/j.aff.s.2014030601.16
Published in Agriculture, Forestry and Fisheries (Volume 3, Issue 6-1, November 2014)

This article belongs to the Special Issue Agriculture Ecosystems and Environment

Page(s) 36-45
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Evapotranspiration, Water Stress, Remote Sensing, TIR, SWIR

References
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Author Information
  • Centro de Estudios Hidro Ambientales, Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral, C. C. 217, Santa Fe, (3000) Argentina

  • Centro de Estudios Hidro Ambientales, Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral, C. C. 217, Santa Fe, (3000) Argentina

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  • APA Style

    Girolimetto Daniela, Venturini Virginia. (2014). Evapotranspiration and Water Stress Estimation from TIR and SWIR Bands. Agriculture, Forestry and Fisheries, 3(6-1), 36-45. https://doi.org/10.11648/j.aff.s.2014030601.16

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    ACS Style

    Girolimetto Daniela; Venturini Virginia. Evapotranspiration and Water Stress Estimation from TIR and SWIR Bands. Agric. For. Fish. 2014, 3(6-1), 36-45. doi: 10.11648/j.aff.s.2014030601.16

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    AMA Style

    Girolimetto Daniela, Venturini Virginia. Evapotranspiration and Water Stress Estimation from TIR and SWIR Bands. Agric For Fish. 2014;3(6-1):36-45. doi: 10.11648/j.aff.s.2014030601.16

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  • @article{10.11648/j.aff.s.2014030601.16,
      author = {Girolimetto Daniela and Venturini Virginia},
      title = {Evapotranspiration and Water Stress Estimation from TIR and SWIR Bands},
      journal = {Agriculture, Forestry and Fisheries},
      volume = {3},
      number = {6-1},
      pages = {36-45},
      doi = {10.11648/j.aff.s.2014030601.16},
      url = {https://doi.org/10.11648/j.aff.s.2014030601.16},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.aff.s.2014030601.16},
      abstract = {The World agriculture depends on water availability; thus, a successful water management system would assure food for the World. For several decades, the scientific community has developed methods to support water management. These models include the estimates of the main water loss in the system, i.e. the evapotranspiration (ET). In turn, the satellite technology encouraged the development of new models to monitor large regions. In this work, we present a modified ET estimation adapting the F parameter introduced by Venturini et al., in 2008. Additionally, a new simple index to estimate water stress (WS) for different types of surfaces, is also presented. The relative evaporation represented by F is derived from the soil moisture condition following the formulation of Barton and computed from the surface reflectance in the shortwave infrared bands (SWIR). The new ET and WS equations are applicable, with different satellite datasets, to any remote region since they are based on universal relationships. The preliminary results show errors of about 11% in ET. In general, the new WS index would have values of approximately 0.8 for a dry surface and 0.4 for a wet surface.},
     year = {2014}
    }
    

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  • TY  - JOUR
    T1  - Evapotranspiration and Water Stress Estimation from TIR and SWIR Bands
    AU  - Girolimetto Daniela
    AU  - Venturini Virginia
    Y1  - 2014/11/17
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    N1  - https://doi.org/10.11648/j.aff.s.2014030601.16
    DO  - 10.11648/j.aff.s.2014030601.16
    T2  - Agriculture, Forestry and Fisheries
    JF  - Agriculture, Forestry and Fisheries
    JO  - Agriculture, Forestry and Fisheries
    SP  - 36
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    PB  - Science Publishing Group
    SN  - 2328-5648
    UR  - https://doi.org/10.11648/j.aff.s.2014030601.16
    AB  - The World agriculture depends on water availability; thus, a successful water management system would assure food for the World. For several decades, the scientific community has developed methods to support water management. These models include the estimates of the main water loss in the system, i.e. the evapotranspiration (ET). In turn, the satellite technology encouraged the development of new models to monitor large regions. In this work, we present a modified ET estimation adapting the F parameter introduced by Venturini et al., in 2008. Additionally, a new simple index to estimate water stress (WS) for different types of surfaces, is also presented. The relative evaporation represented by F is derived from the soil moisture condition following the formulation of Barton and computed from the surface reflectance in the shortwave infrared bands (SWIR). The new ET and WS equations are applicable, with different satellite datasets, to any remote region since they are based on universal relationships. The preliminary results show errors of about 11% in ET. In general, the new WS index would have values of approximately 0.8 for a dry surface and 0.4 for a wet surface.
    VL  - 3
    IS  - 6-1
    ER  - 

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