IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i5p385-d542724.html
   My bibliography  Save this article

A Novel Approach for the Simulation of Reference Evapotranspiration and Its Partitioning

Author

Listed:
  • Pei Wang

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Jingjing Ma

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Juanjuan Ma

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Haitao Sun

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Qi Chen

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

Abstract

To estimate the irrigation volume required for agriculture and improve water resources utilization efficiency, it is essential to obtain an estimate of reference evapotranspiration (ET 0 ) and its components (e.g., reference transpiration, T 0 and reference soil evaporation, E 0 ). This study updated a soil-plant-atmosphere continuum (SPAC) evapotranspiration model and its associated components to obtain a reference-based SPAC model of reference evapotranspiration (R-SPAC), and it applied the model to an agricultural ecosystem. Model simulations of mean hourly ET 0 were benchmarked against those of the Penman-Monteith method by the Food and Agriculture Organization (FAO-PM) throughout the growing season. The resulting good correlation obtained (R 2 = 0.96, agreement index, I = 0.98, root-mean-square deviation (RMSD) = 0.05 mm h −1 ) validated the accuracy of the R-SPAC model. Sensitivity analysis was used to explore uncertainties and errors for ET 0 , T 0 , and E 0 caused by input variables. The results showed that net radiation and shortwave radiation at the study site were the main drivers of ET 0 for both the FAO-PM and R-SPAC models. The study showed that the proposed R-SPAC model can be used for predicting ET 0 and for exploring interactions between climate, crop type, and soil in determining evapotranspiration under various future environment conditions.

Suggested Citation

  • Pei Wang & Jingjing Ma & Juanjuan Ma & Haitao Sun & Qi Chen, 2021. "A Novel Approach for the Simulation of Reference Evapotranspiration and Its Partitioning," Agriculture, MDPI, vol. 11(5), pages 1-12, April.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:5:p:385-:d:542724
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/5/385/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/11/5/385/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Tianxin & Melton, Forrest S. & Pôças, Isabel & Johnson, Lee F. & Thao, Touyee & Post, Kirk & Cassel-Sharma, Florence, 2021. "Evaluation of crop coefficient and evapotranspiration data for sugar beets from landsat surface reflectances using micrometeorological measurements and weighing lysimetry," Agricultural Water Management, Elsevier, vol. 244(C).
    2. Pereira, L.S. & Paredes, P. & Melton, F. & Johnson, L. & Wang, T. & López-Urrea, R. & Cancela, J.J. & Allen, R.G., 2020. "Prediction of crop coefficients from fraction of ground cover and height. Background and validation using ground and remote sensing data," Agricultural Water Management, Elsevier, vol. 241(C).
    3. Pei Wang & Tsutomu Yamanaka & Guo Yu Qiu, 2012. "Causes of decreased reference evapotranspiration and pan evaporation in the Jinghe River catchment, northern China," Environment Systems and Decisions, Springer, vol. 32(1), pages 1-10, March.
    4. 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).
    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. Pereira, L.S. & Paredes, P. & Melton, F. & Johnson, L. & Mota, M. & Wang, T., 2021. "Prediction of crop coefficients from fraction of ground cover and height: Practical application to vegetable, field and fruit crops with focus on parameterization," Agricultural Water Management, Elsevier, vol. 252(C).
    2. 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).
    3. Wang, Tianxin & Melton, Forrest S. & Pôças, Isabel & Johnson, Lee F. & Thao, Touyee & Post, Kirk & Cassel-Sharma, Florence, 2021. "Evaluation of crop coefficient and evapotranspiration data for sugar beets from landsat surface reflectances using micrometeorological measurements and weighing lysimetry," Agricultural Water Management, Elsevier, vol. 244(C).
    4. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).
    5. Shao, Guomin & Han, Wenting & Zhang, Huihui & Zhang, Liyuan & Wang, Yi & Zhang, Yu, 2023. "Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods," Agricultural Water Management, Elsevier, vol. 276(C).
    6. Zhang, Yu & Han, Wenting & Zhang, Huihui & Niu, Xiaotao & Shao, Guomin, 2023. "Evaluating maize evapotranspiration using high-resolution UAV-based imagery and FAO-56 dual crop coefficient approach," Agricultural Water Management, Elsevier, vol. 275(C).
    7. Pereira, L.S. & Paredes, P. & López-Urrea, R. & Hunsaker, D.J. & Mota, M. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for vegetable crops, an update of FAO56 crop water requirements approach," Agricultural Water Management, Elsevier, vol. 243(C).
    8. 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).
    9. Darouich, Hanaa & Karfoul, Razan & Ramos, Tiago B. & Moustafa, Ali & Shaheen, Baraa & Pereira, Luis S., 2021. "Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region," Agricultural Water Management, Elsevier, vol. 255(C).
    10. Williams, Larry E. & Levin, Alexander D. & Fidelibus, Matthew W., 2022. "Crop coefficients (Kc) developed from canopy shaded area in California vineyards," Agricultural Water Management, Elsevier, vol. 271(C).
    11. Liu, Meihan & Paredes, Paula & Shi, Haibin & Ramos, Tiago B. & Dou, Xu & Dai, Liping & Pereira, Luis S., 2022. "Impacts of a shallow saline water table on maize evapotranspiration and groundwater contribution using static water table lysimeters and the dual Kc water balance model SIMDualKc," Agricultural Water Management, Elsevier, vol. 273(C).
    12. Shao, Guomin & Han, Wenting & Zhang, Huihui & Liu, Shouyang & Wang, Yi & Zhang, Liyuan & Cui, Xin, 2021. "Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices," Agricultural Water Management, Elsevier, vol. 252(C).
    13. Salgado, Ramiro & Mateos, Luciano, 2021. "Evaluation of different methods of estimating ET for the performance assessment of irrigation schemes," Agricultural Water Management, Elsevier, vol. 243(C).
    14. Elshikha, Diaa Eldin M. & Hunsaker, Douglas J. & Waller, Peter M. & Thorp, Kelly R. & Dierig, David & Wang, Guangyao & Cruz, Von Mark V. & Katterman, Matthew E. & Bronson, Kevin F. & Wall, Gerard W. &, 2022. "Estimation of direct-seeded guayule cover, crop coefficient, and yield using UAS-based multispectral and RGB data," Agricultural Water Management, Elsevier, vol. 265(C).
    15. Christian Mera-Parra & Fernando Oñate-Valdivieso & Priscilla Massa-Sánchez & Pablo Ochoa-Cueva, 2021. "Establishment of the Baseline for the IWRM in the Ecuadorian Andean Basins: Land Use Change, Water Recharge, Meteorological Forecast and Hydrological Modeling," Land, MDPI, vol. 10(5), pages 1-18, May.
    16. Ramos, Tiago B. & Oliveira, Ana R. & Darouich, Hanaa & Gonçalves, Maria C. & Martínez-Moreno, Francisco J. & Rodríguez, Mario Ramos & Vanderlinden, Karl & Farzamian, Mohammad, 2023. "Field-scale assessment of soil water dynamics using distributed modeling and electromagnetic conductivity imaging," Agricultural Water Management, Elsevier, vol. 288(C).
    17. Paredes, Paula & Trigo, Isabel & de Bruin, Henk & Simões, Nuno & Pereira, Luis S., 2021. "Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products," Agricultural Water Management, Elsevier, vol. 248(C).
    18. Ramírez-Cuesta, J.M. & Intrigliolo, D.S. & Lorite, I.J. & Moreno, M.A. & Vanella, D. & Ballesteros, R. & Hernández-López, D. & Buesa, I., 2023. "Determining grapevine water use under different sustainable agronomic practices using METRIC-UAV surface energy balance model," Agricultural Water Management, Elsevier, vol. 281(C).
    19. Malik, Anurag & Jamei, Mehdi & Ali, Mumtaz & Prasad, Ramendra & Karbasi, Masoud & Yaseen, Zaher Mundher, 2022. "Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection," Agricultural Water Management, Elsevier, vol. 272(C).
    20. Ouaadi, Nadia & Jarlan, Lionel & Khabba, Saïd & Le Page, Michel & Chakir, Adnane & Er-Raki, Salah & Frison, Pierre-Louis, 2023. "Are the C-band backscattering coefficient and interferometric coherence suitable substitutes of NDVI for the monitoring of the FAO-56 crop coefficient?," Agricultural Water Management, Elsevier, vol. 282(C).

    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:gam:jagris:v:11:y:2021:i:5:p:385-:d:542724. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.