IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i5p1466-d212520.html
   My bibliography  Save this article

Assessing the Performance of the WOFOST Model in Simulating Jujube Fruit Tree Growth under Different Irrigation Regimes

Author

Listed:
  • Tiecheng Bai

    (College of Information Engineering, Tarim University, Akaer 843300, China
    TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, Liège University, Passage des Déportés, 2, 5030 Gembloux, Belgium)

  • Nannan Zhang

    (College of Information Engineering, Tarim University, Akaer 843300, China)

  • Youqi Chen

    (Institute of Agricultural Resources and Regional Planning of CAAS, No. 12 Zhongguancun South St., Haidian District, Beijing 100081, China)

  • Benoit Mercatoris

    (TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, Liège University, Passage des Déportés, 2, 5030 Gembloux, Belgium)

Abstract

Cropping system models are widely employed to evaluate plant water requirements and growth situations. However, these models rarely focus on growth studies of perennial fruit trees. The aim of this study was to evaluate the performance of the WOFOST (WOrld FOod STudies) model in simulating jujube fruit tree growth under different irrigation treatments. The model was calibrated on data obtained from full irrigation treatments in 2016 and 2017. The model was validated on four deficit percentages (60%, 70%, 80%, and 90%) and one full irrigation treatment from 2016 to 2018. Calibrated R 2 and RMSE values of simulated versus measured soil moisture content, excluding samples on the day of irrigation and first day after irrigation, reached 0.94 and 0.005 cm 3 cm −3 . The model reproduced growth dynamics of the total biomass and leaf area index, with a validated R 2 = 0.967 and RMSE = 0.915 t ha −1 , and R 2 = 0.962 and RMSE = 0.160 m 2 m −2 , respectively. The model also showed good global performance, with R 2 = 0.86 and RMSE = 0.51 t ha −1 , as well as good local agreement (R 2 ≥ 0.8 ) and prediction accuracy (RMSE ≤ 0.62 t ha −1 ) for each growth season. Furthermore, 90% of full irrigation can be recommended to achieve a balance between jujube yields and water savings (average decline ratio of yield ≤ 3.8%).

Suggested Citation

  • Tiecheng Bai & Nannan Zhang & Youqi Chen & Benoit Mercatoris, 2019. "Assessing the Performance of the WOFOST Model in Simulating Jujube Fruit Tree Growth under Different Irrigation Regimes," Sustainability, MDPI, vol. 11(5), pages 1-16, March.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:5:p:1466-:d:212520
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/5/1466/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/5/1466/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aggarwal, P.K. & Banerjee, B. & Daryaei, M.G. & Bhatia, A. & Bala, A. & Rani, S. & Chander, S. & Pathak, H. & Kalra, N., 2006. "InfoCrop: A dynamic simulation model for the assessment of crop yields, losses due to pests, and environmental impact of agro-ecosystems in tropical environments. II. Performance of the model," Agricultural Systems, Elsevier, vol. 89(1), pages 47-67, July.
    2. 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.
    3. Abi Saab, Marie Therese & Todorovic, Mladen & Albrizio, Rossella, 2015. "Comparing AquaCrop and CropSyst models in simulating barley growth and yield under different water and nitrogen regimes. Does calibration year influence the performance of crop growth models?," Agricultural Water Management, Elsevier, vol. 147(C), pages 21-33.
    4. Confalonieri, Roberto & Acutis, Marco & Bellocchi, Gianni & Donatelli, Marcello, 2009. "Multi-metric evaluation of the models WARM, CropSyst, and WOFOST for rice," Ecological Modelling, Elsevier, vol. 220(11), pages 1395-1410.
    5. Supit, I. & van Diepen, C.A. & de Wit, A.J.W. & Kabat, P. & Baruth, B. & Ludwig, F., 2010. "Recent changes in the climatic yield potential of various crops in Europe," Agricultural Systems, Elsevier, vol. 103(9), pages 683-694, November.
    6. Geerts, S. & Raes, D. & Garcia, M., 2010. "Using AquaCrop to derive deficit irrigation schedules," Agricultural Water Management, Elsevier, vol. 98(1), pages 213-216, December.
    7. Aggarwal, P.K. & Kalra, N. & Chander, S. & Pathak, H., 2006. "InfoCrop: A dynamic simulation model for the assessment of crop yields, losses due to pests, and environmental impact of agro-ecosystems in tropical environments. I. Model description," Agricultural Systems, Elsevier, vol. 89(1), pages 1-25, July.
    8. de Wit, Allard & Boogaard, Hendrik & Fumagalli, Davide & Janssen, Sander & Knapen, Rob & van Kraalingen, Daniel & Supit, Iwan & van der Wijngaart, Raymond & van Diepen, Kees, 2019. "25 years of the WOFOST cropping systems model," Agricultural Systems, Elsevier, vol. 168(C), pages 154-167.
    9. Bussay, Attila & van der Velde, Marijn & Fumagalli, Davide & Seguini, Lorenzo, 2015. "Improving operational maize yield forecasting in Hungary," Agricultural Systems, Elsevier, vol. 141(C), pages 94-106.
    10. Ceglar, A. & van der Wijngaart, R. & de Wit, A. & Lecerf, R. & Boogaard, H. & Seguini, L. & van den Berg, M. & Toreti, A. & Zampieri, M. & Fumagalli, D. & Baruth, B., 2019. "Improving WOFOST model to simulate winter wheat phenology in Europe: Evaluation and effects on yield," Agricultural Systems, Elsevier, vol. 168(C), pages 168-180.
    11. Chen, Chao & Wang, Enli & Yu, Qiang, 2010. "Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain," Agricultural Water Management, Elsevier, vol. 97(8), pages 1175-1184, August.
    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. Bai, Tiecheng & Zhang, Nannan & Wang, Tao & Wang, Desheng & Yu, Caili & Meng, Wenbo & Fei, Hao & Chen, Rengu & Li, Yanhui & Zhou, Baoping, 2021. "Simulating on the effects of irrigation on jujube tree growth, evapotranspiration and water use based on crop growth model," Agricultural Water Management, Elsevier, vol. 243(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. Cheng, Minghui & Wang, Haidong & Fan, Junliang & Xiang, Youzhen & Liu, Xiaoqiang & Liao, Zhenqi & Abdelghany, Ahmed Elsayed & Zhang, Fucang & Li, Zhijun, 2022. "Evaluation of AquaCrop model for greenhouse cherry tomato with plastic film mulch under various water and nitrogen supplies," Agricultural Water Management, Elsevier, vol. 274(C).
    2. M. Sujithra & Subhash Chander, 2013. "Simulation of rice brown planthopper, Nilaparvata lugens (Stal.) population and crop-pest interactions to assess climate change impact," Climatic Change, Springer, vol. 121(2), pages 331-347, November.
    3. 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.
    4. 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.
    5. Paresh B. Shirsath & Vinay Kumar Sehgal & Pramod K. Aggarwal, 2020. "Downscaling Regional Crop Yields to Local Scale Using Remote Sensing," Agriculture, MDPI, vol. 10(3), pages 1-14, March.
    6. Kattarkandi Byjesh & Soora Kumar & Pramod Aggarwal, 2010. "Simulating impacts, potential adaptation and vulnerability of maize to climate change in India," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(5), pages 413-431, June.
    7. Fargue-Lelièvre, A. & Le Cœur, D. & Baudry, J., 2011. "Integrating farming techniques in an ecological matrix model: Implementation on the primrose (Primula vulgaris)," Ecological Modelling, Elsevier, vol. 222(4), pages 1002-1015.
    8. Trnka, M. & Muška, F. & Semerádová, D. & Dubrovský, M. & Kocmánková, E. & Žalud, Z., 2007. "European Corn Borer life stage model: Regional estimates of pest development and spatial distribution under present and future climate," Ecological Modelling, Elsevier, vol. 207(2), pages 61-84.
    9. Nana, E. & Corbari, C. & Bocchiola, D., 2014. "A model for crop yield and water footprint assessment: Study of maize in the Po valley," Agricultural Systems, Elsevier, vol. 127(C), pages 139-149.
    10. Zhu, Xiufang & Xu, Kun & Liu, Ying & Guo, Rui & Chen, Lingyi, 2021. "Assessing the vulnerability and risk of maize to drought in China based on the AquaCrop model," Agricultural Systems, Elsevier, vol. 189(C).
    11. Bocchiola, D. & Brunetti, L. & Soncini, A. & Polinelli, F. & Gianinetto, M., 2019. "Impact of climate change on agricultural productivity and food security in the Himalayas: A case study in Nepal," Agricultural Systems, Elsevier, vol. 171(C), pages 113-125.
    12. Sulav Paudel & Lalit P. Sah & Mukti Devkota & Vijaya Poudyal & P.V. Vara Prasad & Manuel R. Reyes, 2020. "Conservation Agriculture and Integrated Pest Management Practices Improve Yield and Income while Reducing Labor, Pests, Diseases and Chemical Pesticide Use in Smallholder Vegetable Farms in Nepal," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
    13. 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).
    14. Singh, P. & Aggarwal, P. K. & Bhatia, V. S. & Murty, M. V. R. & Pala, M. & Oweis, T. & Benli, B. & Rao, K. P. C. & Wani, S. P., 2009. "Yield gap analysis: modelling of achievable yields at farm level," IWMI Books, Reports H041995, International Water Management Institute.
    15. Selvaraj Krishnan & Subhash Chander, 2015. "Simulation of climatic change impact on crop-pest interactions: a case study of rice pink stem borer Sesamia inferens (Walker)," Climatic Change, Springer, vol. 131(2), pages 259-272, July.
    16. K. Viswanath & P. Sinha & S. Naresh Kumar & Taru Sharma & Shalini Saxena & Shweta Panjwani & H. Pathak & Shalu Mishra Shukla, 2017. "Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario," Climatic Change, Springer, vol. 142(1), pages 155-167, May.
    17. 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.
    18. A. Mukherjee & A. K. S. Huda, 2018. "Assessment of climate variability and trend on wheat productivity in West Bengal, India: crop growth simulation approach," Climatic Change, Springer, vol. 147(1), pages 235-252, March.
    19. Kalra, Naveen & Chakraborty, Debashis & Ramesh Kumar, P. & Jolly, Monica & Sharma, P.K., 2007. "An approach to bridging yield gaps, combining response to water and other resource inputs for wheat in northern India, using research trials and farmers' fields data," Agricultural Water Management, Elsevier, vol. 93(1-2), pages 54-64, October.
    20. 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.

    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:jsusta:v:11:y:2019:i:5:p:1466-:d:212520. 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.