IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v217y2019icp346-355.html
   My bibliography  Save this article

Batch-processing of AquaCrop plug-in for rainfed maize using satellite derived Fractional Vegetation Cover data

Author

Listed:
  • Mohamed Sallah, Abdoul-Hamid
  • Tychon, Bernard
  • Piccard, Isabelle
  • Gobin, Anne
  • Van Hoolst, Roel
  • Djaby, Bakary
  • Wellens, Joost

Abstract

Coupling crop growth models and remote sensing data has shown great potential to improve crop yield and biomass forecasting. However, few such applications are used at field level. In this study, the plug-in version of AquaCrop, a water driven model initially designed for conditions in which water is the limiting factor in crop production, was adapted to assess maize in Belgium. Field campaigns were organised in 2015, 2016 and 2017, during which ground measurements were collected. At field level and under rainfed conditions, above ground total dry biomass and field management information (crop density, planting dates, biomass measurements etc.) was collected. Green fractional vegetation cover (fCover) data were retrieved from high spatial and temporal satellite images (DMC-2/ DEIMOS-1 and Sentinel-2). Maximum canopy cover and emergence date were derived from the time series and assimilated into AquaCrop. The model was calibrated with the 2015–2016 dataset and validated with 2017 data. The root mean square error (RMSE) for the biomass assessment was 0.7 ton/ha and the R² reached 0.85. The R² between the canopy cover simulated by the model and the remotely sensed fCover ranged from 0.76–0.98 in most of the cases. To simultaneously run and evaluate the ensemble of field-level simulations, a semi-automated R-environment was developed. This robust and automated approach offers vast potential for large-scale field-level yield assessments for temperate as well as tropical conditions.

Suggested Citation

  • Mohamed Sallah, Abdoul-Hamid & Tychon, Bernard & Piccard, Isabelle & Gobin, Anne & Van Hoolst, Roel & Djaby, Bakary & Wellens, Joost, 2019. "Batch-processing of AquaCrop plug-in for rainfed maize using satellite derived Fractional Vegetation Cover data," Agricultural Water Management, Elsevier, vol. 217(C), pages 346-355.
    • Handle: RePEc:eee:agiwat:v:217:y:2019:i:c:p:346-355
    DOI: 10.1016/j.agwat.2019.03.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377418315117
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2019.03.016?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. Abedinpour, M. & Sarangi, A. & Rajput, T.B.S. & Singh, Man & Pathak, H. & Ahmad, T., 2012. "Performance evaluation of AquaCrop model for maize crop in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 110(C), pages 55-66.
    2. Wellens, Joost & Raes, Dirk & Traore, Farid & Denis, Antoine & Djaby, Bakary & Tychon, Bernard, 2013. "Performance assessment of the FAO AquaCrop model for irrigated cabbage on farmer plots in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 127(C), pages 40-47.
    3. Trombetta, Andrea & Iacobellis, Vito & Tarantino, Eufemia & Gentile, Francesco, 2016. "Calibration of the AquaCrop model for winter wheat using MODIS LAI images," Agricultural Water Management, Elsevier, vol. 164(P2), pages 304-316.
    4. Andarzian, B. & Bannayan, M. & Steduto, P. & Mazraeh, H. & Barati, M.E. & Barati, M.A. & Rahnama, A., 2011. "Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran," Agricultural Water Management, Elsevier, vol. 100(1), pages 1-8.
    5. Zhao, Yanxia & Chen, Sining & Shen, Shuanghe, 2013. "Assimilating remote sensing information with crop model using Ensemble Kalman Filter for improving LAI monitoring and yield estimation," Ecological Modelling, Elsevier, vol. 270(C), pages 30-42.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alvar-Beltrán, Jorge & Saturnin, Coulibaly & Grégoire, Baki & Camacho, Jose Luís & Dao, Abdalla & Migraine, Jean Baptiste & Marta, Anna Dalla, 2023. "Using AquaCrop as a decision-support tool for improved irrigation management in the Sahel region," Agricultural Water Management, Elsevier, vol. 287(C).
    2. Liu, Xiao & Yang, Dawen, 2021. "Irrigation schedule analysis and optimization under the different combination of P and ET0 using a spatially distributed crop model," Agricultural Water Management, Elsevier, vol. 256(C).
    3. Ewa Panek-Chwastyk & Ceren Nisanur Ozbilge & Katarzyna Dąbrowska-Zielińska & Konrad Wróblewski, 2024. "Assessment of Grassland Biomass Prediction Using AquaCrop Model: Integrating Sentinel-2 Data and Ground Measurements in Wielkopolska and Podlasie Regions, Poland," Agriculture, MDPI, vol. 14(6), pages 1-16, May.
    4. Tsakmakis, I.D. & Gikas, G.D. & Sylaios, G.K., 2021. "Integration of Sentinel-derived NDVI to reduce uncertainties in the operational field monitoring of maize," Agricultural Water Management, Elsevier, vol. 255(C).

    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. López-Urrea, R. & Domínguez, A. & Pardo, J.J. & Montoya, F. & García-Vila, M. & Martínez-Romero, A., 2020. "Parameterization and comparison of the AquaCrop and MOPECO models for a high-yielding barley cultivar under different irrigation levels," Agricultural Water Management, Elsevier, vol. 230(C).
    2. Razzaghi, Fatemeh & Zhou, Zhenjiang & Andersen, Mathias N. & Plauborg, Finn, 2017. "Simulation of potato yield in temperate condition by the AquaCrop model," Agricultural Water Management, Elsevier, vol. 191(C), pages 113-123.
    3. Wang, Youzhi & Guo, Shanshan & Yue, Qing & Mao, Xiaomin & Guo, Ping, 2021. "Distributed AquaCrop simulation-nonlinear multi-objective dependent-chance programming for irrigation water resources management under uncertainty," Agricultural Water Management, Elsevier, vol. 247(C).
    4. Seyed Ahmadi & Elnaz Mosallaeepour & Ali Kamgar-Haghighi & Ali Sepaskhah, 2015. "Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2837-2853, June.
    5. Ran, Hui & Kang, Shaozhong & Li, Fusheng & Du, Taisheng & Tong, Ling & Li, Sien & Ding, Risheng & Zhang, Xiaotao, 2018. "Parameterization of the AquaCrop model for full and deficit irrigated maize for seed production in arid Northwest China," Agricultural Water Management, Elsevier, vol. 203(C), pages 438-450.
    6. Iqbal, M. Anjum & Shen, Yanjun & Stricevic, Ruzica & Pei, Hongwei & Sun, Hongyoung & Amiri, Ebrahim & Penas, Angel & del Rio, Sara, 2014. "Evaluation of the FAO AquaCrop model for winter wheat on the North China Plain under deficit irrigation from field experiment to regional yield simulation," Agricultural Water Management, Elsevier, vol. 135(C), pages 61-72.
    7. Sandhu, Rupinder & Irmak, Suat, 2019. "Performance of AquaCrop model in simulating maize growth, yield, and evapotranspiration under rainfed, limited and full irrigation," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    8. Toumi, J. & Er-Raki, S. & Ezzahar, J. & Khabba, S. & Jarlan, L. & Chehbouni, A., 2016. "Performance assessment of AquaCrop model for estimating evapotranspiration, soil water content and grain yield of winter wheat in Tensift Al Haouz (Morocco): Application to irrigation management," Agricultural Water Management, Elsevier, vol. 163(C), pages 219-235.
    9. Wellens, Joost & Raes, Dirk & Traore, Farid & Denis, Antoine & Djaby, Bakary & Tychon, Bernard, 2013. "Performance assessment of the FAO AquaCrop model for irrigated cabbage on farmer plots in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 127(C), pages 40-47.
    10. Mustafa, S.M.T. & Vanuytrecht, E. & Huysmans, M., 2017. "Combined deficit irrigation and soil fertility management on different soil textures to improve wheat yield in drought-prone Bangladesh," Agricultural Water Management, Elsevier, vol. 191(C), pages 124-137.
    11. Ćosić, Marija & Stričević, Ružica & Djurović, Nevenka & Moravčević, Djordje & Pavlović, Miloš & Todorović, Mladen, 2017. "Predicting biomass and yield of sweet pepper grown with and without plastic film mulching under different water supply and weather conditions," Agricultural Water Management, Elsevier, vol. 188(C), pages 91-100.
    12. Tinashe Lindel Dirwai & Aidan Senzanje & Tafadzwanashe Mabhaudhi, 2021. "Calibration and Evaluation of the FAO AquaCrop Model for Canola ( Brassica napus ) under Varied Moistube Irrigation Regimes," Agriculture, MDPI, vol. 11(5), pages 1-18, May.
    13. Alvar-Beltrán, Jorge & Saturnin, Coulibaly & Grégoire, Baki & Camacho, Jose Luís & Dao, Abdalla & Migraine, Jean Baptiste & Marta, Anna Dalla, 2023. "Using AquaCrop as a decision-support tool for improved irrigation management in the Sahel region," Agricultural Water Management, Elsevier, vol. 287(C).
    14. Wu, Zhangsheng & Li, Yue & Wang, Rong & Xu, Xu & Ren, Dongyang & Huang, Quanzhong & Xiong, Yunwu & Huang, Guanhua, 2023. "Evaluation of irrigation water saving and salinity control practices of maize and sunflower in the upper Yellow River basin with an agro-hydrological model based method," Agricultural Water Management, Elsevier, vol. 278(C).
    15. Yunfeng Li & Quanqing Feng & Dongwei Li & Mingfa Li & Huifeng Ning & Qisheng Han & Abdoul Kader Mounkaila Hamani & Yang Gao & Jingsheng Sun, 2022. "Water-Salt Thresholds of Cotton ( Gossypium hirsutum L.) under Film Drip Irrigation in Arid Saline-Alkali Area," Agriculture, MDPI, vol. 12(11), pages 1-21, October.
    16. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    17. Giorgio Baiamonte & Mario Minacapilli & Giuseppina Crescimanno, 2020. "Effects of Biochar on Irrigation Management and Water Use Efficiency for Three Different Crops in a Desert Sandy Soil," Sustainability, MDPI, vol. 12(18), pages 1-19, September.
    18. Kondwani Msowoya & Kaveh Madani & Rahman Davtalab & Ali Mirchi & Jay R. Lund, 2016. "Climate Change Impacts on Maize Production in the Warm Heart of Africa," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5299-5312, November.
    19. Katerji, Nader & Campi, Pasquale & Mastrorilli, Marcello, 2013. "Productivity, evapotranspiration, and water use efficiency of corn and tomato crops simulated by AquaCrop under contrasting water stress conditions in the Mediterranean region," Agricultural Water Management, Elsevier, vol. 130(C), pages 14-26.
    20. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(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:eee:agiwat:v:217:y:2019:i:c:p:346-355. 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.