IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v289y2023ics0378377423003876.html
   My bibliography  Save this article

A double two-sources energy-water balance model for improving evapotranspiration estimates and irrigation management in fruit trees fields

Author

Listed:
  • Corbari, Chiara
  • Paciolla, Nicola
  • Rossi, Greta
  • Mancini, Marco

Abstract

Improving the use of water in irrigated agriculture is meaningful in a period of increasing water scarcity conditions. A more accurate estimate of evapotranspiration (ET) and its components thus becomes fundamental to better quantify the irrigation water volumes. Many existing models, based on different remote sensing data, provide daily estimates of latent heat flux (LE) from correlation between net radiation and instantaneous estimates of LE, computed as residual component of the energy balance equation or from a correlation of land surface temperature (LST) with vegetation indices., However, they mainly lack of solutions which are continuous in time (e.g. hourly), independent from satellite LST availability and a simultaneous estimation of soil moisture. Addressing this gap, a double two-sources energy-water balance model (FEST‐2×2‐EWB) is developed based on the decoupling of both water and energy fluxes between the bare soil or grass interrow and the trees rows. This novel parameterization approach enables the differentiation of water uptake from the root zone, which varies between tall trees and grass, considering the dynamics of soil moisture (SM) in the superficial and deep layers. Additionally, it provides partitioned values for transpiration and evaporation. The new model has been evaluated in two irrigated trees fields in the North of Italy, a walnut trees field from 2019 to 2021 and a pear trees field, for the year 2022. Results of the study showcased a root-mean-square-error (RMSE) of about 55 W m− 2 and a bias of about 40 W m− 2 for hourly latent and sensible heat fluxes when compared to the eddy covariance stations located in the fields, while a RMSE of 2 °C (bias of 1.5 °C) for LST and of 0.04 for SM. The FEST‐2×2‐EWB model significantly enhances the accuracy of ET simulation in fruits trees areas in respect to the original one source and one-layer version of the same model. Finally, the application of an irrigation optimization strategy with this new model, allowed to demonstrate its potentiality in water saving (about 90 mm in a year) in respect to farmers applied irrigation, and with a difference of about 60 mm between using the double two-sources model and single source one.

Suggested Citation

  • Corbari, Chiara & Paciolla, Nicola & Rossi, Greta & Mancini, Marco, 2023. "A double two-sources energy-water balance model for improving evapotranspiration estimates and irrigation management in fruit trees fields," Agricultural Water Management, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:agiwat:v:289:y:2023:i:c:s0378377423003876
    DOI: 10.1016/j.agwat.2023.108522
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377423003876
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2023.108522?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alexandratos, Nikos & Bruinsma, Jelle, 2012. "World agriculture towards 2030/2050: the 2012 revision," ESA Working Papers 288998, Food and Agriculture Organization of the United Nations, Agricultural Development Economics Division (ESA).
    2. Bastiaanssen, Wim G. M. & Molden, David J. & Makin, Ian W., 2000. "Remote sensing for irrigated agriculture: examples from research and possible applications," Agricultural Water Management, Elsevier, vol. 46(2), pages 137-155, December.
    3. Corbari, Chiara & Salerno, Raffaele & Ceppi, Alessandro & Telesca, Vito & Mancini, Marco, 2019. "Smart irrigation forecast using satellite LANDSAT data and meteo-hydrological modeling," Agricultural Water Management, Elsevier, vol. 212(C), pages 283-294.
    4. Vuolo, Francesco & D’Urso, Guido & De Michele, Carlo & Bianchi, Biagio & Cutting, Michael, 2015. "Satellite-based irrigation advisory services: A common tool for different experiences from Europe to Australia," Agricultural Water Management, Elsevier, vol. 147(C), pages 82-95.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Corbari, Chiara & Gabrieli, Davide & Furlan, Lorenzo & Furlanetto, Jacopo & Skokovic, Drazen & Sobrino, Josè & Morari, Francesco, 2024. "Optimizing variable rate irrigation using model and satellite-based dynamic prescription maps," Agricultural Water Management, Elsevier, vol. 299(C).
    2. Ascui, Francisco & Ball, Alex & Kahn, Lewis & Rowe, James, 2021. "Is operationalising natural capital risk assessment practicable?," Ecosystem Services, Elsevier, vol. 52(C).
    3. Achoja, Felix Odemero & Enujeke, Emmanuel Chukudinife & Ogisi, Oraye Dicta & Overehirha, Rebecca Tega, 2020. "Multinomial Regression Analysis of Yam (Dioscorea Spp.) Consumers' Preferences and Varietal Diversification Pattern in Nigeria," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society (AESS), vol. 10(02), January.
    4. Bipul Neupane & Teerayut Horanont & Nguyen Duy Hung, 2019. "Deep learning based banana plant detection and counting using high-resolution red-green-blue (RGB) images collected from unmanned aerial vehicle (UAV)," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-22, October.
    5. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
    6. Bonfante, A. & Monaco, E. & Manna, P. & De Mascellis, R. & Basile, A. & Buonanno, M. & Cantilena, G. & Esposito, A. & Tedeschi, A. & De Michele, C. & Belfiore, O. & Catapano, I. & Ludeno, G. & Salinas, 2019. "LCIS DSS—An irrigation supporting system for water use efficiency improvement in precision agriculture: A maize case study," Agricultural Systems, Elsevier, vol. 176(C).
    7. James J Elser & Timothy J Elser & Stephen R Carpenter & William A Brock, 2014. "Regime Shift in Fertilizer Commodities Indicates More Turbulence Ahead for Food Security," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-7, May.
    8. Ying-Jung Chen & Joseph McFadden & Keith Clarke & Dar Roberts, 2015. "Measuring Spatio-temporal Trends in Residential Landscape Irrigation Extent and Rate in Los Angeles, California Using SPOT-5 Satellite Imagery," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5749-5763, December.
    9. Vogel, Everton & Martinelli, Gabrielli & Artuzo, Felipe Dalzotto, 2021. "Environmental and economic performance of paddy field-based crop-livestock systems in Southern Brazil," Agricultural Systems, Elsevier, vol. 190(C).
    10. Kik, M.C. & Claassen, G.D.H. & Meuwissen, M.P.M. & Smit, A.B. & Saatkamp, H.W., 2021. "Actor analysis for sustainable soil management – A case study from the Netherlands," Land Use Policy, Elsevier, vol. 107(C).
    11. Jovanovic, N. & Pereira, L.S. & Paredes, P. & Pôças, I. & Cantore, V. & Todorovic, M., 2020. "A review of strategies, methods and technologies to reduce non-beneficial consumptive water use on farms considering the FAO56 methods," Agricultural Water Management, Elsevier, vol. 239(C).
    12. repec:ags:ijag24:346816 is not listed on IDEAS
    13. Mounir Amdaoud, 2019. "Ressources naturelles, innovation et développement économique : vers une nouvelle approche," CEPN Working Papers 2019-06, Centre d'Economie de l'Université de Paris Nord.
    14. Imran Ali Lakhiar & Haofang Yan & Chuan Zhang & Guoqing Wang & Bin He & Beibei Hao & Yujing Han & Biyu Wang & Rongxuan Bao & Tabinda Naz Syed & Junaid Nawaz Chauhdary & Md. Rakibuzzaman, 2024. "A Review of Precision Irrigation Water-Saving Technology under Changing Climate for Enhancing Water Use Efficiency, Crop Yield, and Environmental Footprints," Agriculture, MDPI, vol. 14(7), pages 1-40, July.
    15. Victor Nechifor & Matthew Winning, 2017. "The impacts of higher CO2 concentrations over global crop production and irrigation water requirements," EcoMod2017 10487, EcoMod.
    16. Bircol, Guilherme Augusto Carminato & Souza, Marcelo Pereira de & Fontes, Aurélio Teodoro & Chiarello, Adriano Garcia & Ranieri, Victor Eduardo Lima, 2018. "Planning by the rules: A fair chance for the environment in a land-use conflict area," Land Use Policy, Elsevier, vol. 76(C), pages 103-112.
    17. Maurer, Rainer, 2023. "Comparing the effect of different agricultural land-use systems on biodiversity," Land Use Policy, Elsevier, vol. 134(C).
    18. Fayaz Ahmad Lone & M. Imran Ganaie & Showkat A. Ganaie & M. Shafi Bhat & Javeed Ahmad Rather, 2023. "Drivers of agricultural land-use change in Kashmir valley - an application of mixed method approach," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-20, December.
    19. Pogue, Sarah J. & Kröbel, Roland & Janzen, H. Henry & Alemu, Aklilu W. & Beauchemin, Karen A. & Little, Shannan & Iravani, Majid & de Souza, Danielle Maia & McAllister, Tim A., 2020. "A social-ecological systems approach for the assessment of ecosystem services from beef production in the Canadian prairie," Ecosystem Services, Elsevier, vol. 45(C).
    20. Anna‐Katharina Hornidge & Lisa Oberkircher & Bernhard Tischbein & Gunther Schorcht & Anik Bhaduri & Ahmad M. Manschadi, 2011. "Reconceptualizing water management in Khorezm, Uzbekistan," Natural Resources Forum, Blackwell Publishing, vol. 35(4), pages 251-268, November.
    21. Järnberg, Linn & Enfors Kautsky, Elin & Dagerskog, Linus & Olsson, Per, 2018. "Green niche actors navigating an opaque opportunity context: Prospects for a sustainable transformation of Ethiopian agriculture," Land Use Policy, Elsevier, vol. 71(C), pages 409-421.

    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:289:y:2023:i:c:s0378377423003876. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.