IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v95y2008i7p776-786.html
   My bibliography  Save this article

Evaluation of CERES-Wheat and CropSyst models for water-nitrogen interactions in wheat crop

Author

Listed:
  • Singh, Anil Kumar
  • Tripathy, Rojalin
  • Chopra, Usha Kiran

Abstract

Crop simulation models can provide an alternative, less time-consuming and inexpensive means of determining the optimum crop N and irrigation requirements under varied soil and climatic conditions. In this context, two dynamic mechanistic models (CERES (Crop Environment REsource Synthesis)-Wheat and CropSyst (Cropping Systems Simulation Model)) were validated for predicting growth and yield of wheat (Triticum aestivum L) under different nitrogen and water management conditions. Their potential as N and water management tool was evaluated for New Delhi representing semi-arid irrigated ecosystems in the Indo-Gangetic Plains. The field experiment was carried out on a silty clay loam soil at the Research Farm of the Indian Agricultural Research Institute, New Delhi, India during 2000-2001 to collect the input data for the calibration and validation of both the models on wheat crop (variety HD 2687). The models were evaluated for three water regimes [I4 (4 irrigations within the growing season), I3 (3 irrigations within the growing season) and I2 (2 irrigations within the growing season)] and five N treatments (N0, N60, N90, N120 and N150). Both the models were calibrated using data obtained from the treatments receiving maximum nitrogen and irrigations, i.e., N150 and I4 treatments. The models were then validated against other water and nitrogen treatments. For performance evaluation, in addition to coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE) and Wilmot's index of agreement (IoA) were estimated. Both CERES-Wheat and CropSyst provided very satisfactory estimates for the emergence, flowering and physiological maturity dates. For CERES-Wheat overall prediction (pooled result of the three water regimes) of grain yield was satisfactory with significant R2 values (0.88). The model, however, under estimated the biomass under all water regimes and N levels except for N0 level, under which biomass was overpredicted. CropSyst predicted yield and biomass of wheat more closely than CERES-Wheat. The combined RMSE for the three water regimes between predicted and observed grain yield was 0.36 mg ha-1 for CropSyst as compared to 0.63 mg ha-1 for CERES-Wheat. Similarly, RMSE between observed and predicted biomass by CropSyst was 1.27 mg ha-1 as compared to 1.94 mg ha-1 between observed and predicted biomass by CERES-Wheat. Wilmot's index of agreement (IoA) also indicated that CropSyst model is more appropriate than CERES-Wheat in predicting growth and yield of wheat under different N and irrigation application situations in this study.

Suggested Citation

  • Singh, Anil Kumar & Tripathy, Rojalin & Chopra, Usha Kiran, 2008. "Evaluation of CERES-Wheat and CropSyst models for water-nitrogen interactions in wheat crop," Agricultural Water Management, Elsevier, vol. 95(7), pages 776-786, July.
    • Handle: RePEc:eee:agiwat:v:95:y:2008:i:7:p:776-786
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378-3774(08)00052-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Hunt, L. A. & White, J. W. & Hoogenboom, G., 2001. "Agronomic data: advances in documentation and protocols for exchange and use," Agricultural Systems, Elsevier, vol. 70(2-3), pages 477-492.
    2. Paz, J. O. & Batchelor, W. D. & Babcock, B. A. & Colvin, T. S. & Logsdon, S. D. & Kaspar, T. C. & Karlen, D. L., 1999. "Model-based technique to determine variable rate nitrogen for corn," Agricultural Systems, Elsevier, vol. 61(1), pages 69-75, July.
    3. Timsina, J. & Humphreys, E., 2006. "Performance of CERES-Rice and CERES-Wheat models in rice-wheat systems: A review," Agricultural Systems, Elsevier, vol. 90(1-3), pages 5-31, October.
    4. Stockle, Claudio O. & Martin, Steve A. & Campbell, Gaylon S., 1994. "CropSyst, a cropping systems simulation model: Water/nitrogen budgets and crop yield," Agricultural Systems, Elsevier, vol. 46(3), pages 335-359.
    5. Pala, M. & Stockle, C. O. & Harris, H. C., 1996. "Simulation of durum wheat (Triticum turgidum ssp. durum) growth under different water and nitrogen regimes in a mediterranean environment using CropSyst," Agricultural Systems, Elsevier, vol. 51(2), pages 147-163, June.
    6. Kovacs, G. J. & Nemeth, T. & Ritchie, J. T., 1995. "Testing simulation models for the assessment of crop production and nitrate leaching in Hungary," Agricultural Systems, Elsevier, vol. 49(4), pages 385-397.
    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. 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.
    2. Wang, Xiangping & Huang, Guanhua & Yang, Jingsong & Huang, Quanzhong & Liu, Haijun & Yu, Lipeng, 2015. "An assessment of irrigation practices: Sprinkler irrigation of winter wheat in the North China Plain," Agricultural Water Management, Elsevier, vol. 159(C), pages 197-208.
    3. Samiha Ouda & Tahany Noreldin & Juan José Alarcón & Ragab Ragab & Gianluca Caruso & Agnieszka Sekara & Magdi T. Abdelhamid, 2021. "Response of Spring Wheat ( Triticum aestivum ) to Deficit Irrigation Management under the Semi-Arid Environment of Egypt: Field and Modeling Study," Agriculture, MDPI, vol. 11(2), pages 1-13, January.
    4. Shen, Hongzheng & Wang, Yue & Jiang, Kongtao & Li, Shilei & Huang, Donghua & Wu, Jiujiang & Wang, Yongqiang & Wang, Yangren & Ma, Xiaoyi, 2022. "Simulation modeling for effective management of irrigation water for winter wheat," Agricultural Water Management, Elsevier, vol. 269(C).
    5. Tavakoli, Ali Reza & Mahdavi Moghadam, Mehran & Sepaskhah, Ali Reza, 2015. "Evaluation of the AquaCrop model for barley production under deficit irrigation and rainfed condition in Iran," Agricultural Water Management, Elsevier, vol. 161(C), pages 136-146.
    6. Houda Mazhoud & Fraj Chemak & Hatem Belhouchette & Roza Chenoune, 2022. "A Bio-Economic Model for Improving Irrigated Durum Wheat Performance and Regional Profits under Mediterranean Conditions," Agriculture, MDPI, vol. 12(5), pages 1-25, April.
    7. A. Madani & A. Shirani-Rad & A. Pazoki & G. Nourmohammadi & R. Zarghami & A. Mokhtassi-Bidgoli, 2010. "The impact of source or sink limitations on yield formation of winter wheat (Triticum aestivum L.) due to post-anthesis water and nitrogen deficiencies," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 56(5), pages 218-227.
    8. Aftab Wajid & Khalid Hussain & Ayesha Ilyas & Muhammad Habib-ur-Rahman & Qamar Shakil & Gerrit Hoogenboom, 2021. "Crop Models: Important Tools in Decision Support System to Manage Wheat Production under Vulnerable Environments," Agriculture, MDPI, vol. 11(11), pages 1-22, November.
    9. Patel, Jignesh & Bhatt, Chetan, 2015. "A CommonKADS Model Framework for Web Based Agricultural Decision Support System," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 5(4), pages 1-8, January.
    10. Anshuman Gunawat & Devesh Sharma & Aditya Sharma & Swatantra Kumar Dubey, 2022. "Assessment of climate change impact and potential adaptation measures on wheat yield using the DSSAT model in the semi-arid environment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 2077-2096, March.
    11. Mavromatis, T., 2016. "Spatial resolution effects on crop yield forecasts: An application to rainfed wheat yield in north Greece with CERES-Wheat," Agricultural Systems, Elsevier, vol. 143(C), pages 38-48.
    12. You, Yang & Wang, Yakun & Fan, Xiaodong & Dai, Qin & Yang, Guang & Wang, Wene & Chen, Dianyu & Hu, Xiaotao, 2024. "Progress in joint application of crop models and hydrological models," Agricultural Water Management, Elsevier, vol. 295(C).
    13. 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.

    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. Paleari, Livia & Movedi, Ermes & Zoli, Michele & Burato, Andrea & Cecconi, Irene & Errahouly, Jabir & Pecollo, Eleonora & Sorvillo, Carla & Confalonieri, Roberto, 2021. "Sensitivity analysis using Morris: Just screening or an effective ranking method?," Ecological Modelling, Elsevier, vol. 455(C).
    2. Benli, B. & Pala, M. & Stockle, C. & Oweis, T., 2007. "Assessment of winter wheat production under early sowing with supplemental irrigation in a cold highland environment using CropSyst simulation model," Agricultural Water Management, Elsevier, vol. 93(1-2), pages 45-53, October.
    3. Montoya, F. & Camargo, D. & Domínguez, A. & Ortega, J.F. & Córcoles, J.I., 2018. "Parametrization of Cropsyst model for the simulation of a potato crop in a Mediterranean environment," Agricultural Water Management, Elsevier, vol. 203(C), pages 297-310.
    4. 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.
    5. Kropff, M. J. & Bouma, J. & Jones, J. W., 2001. "Systems approaches for the design of sustainable agro-ecosystems," Agricultural Systems, Elsevier, vol. 70(2-3), pages 369-393.
    6. Garrison, M. V. & Batchelor, W. D. & Kanwar, R. S. & Ritchie, J. T., 1999. "Evaluation of the CERES-Maize water and nitrogen balances under tile-drained conditions," Agricultural Systems, Elsevier, vol. 62(3), pages 189-200, December.
    7. Kaur, Harsimran & Huggins, David R. & Carlson, Bryan & Stockle, Claudio & Nelson, Roger, 2022. "Dryland fallow vs flex-cropping decisions in inland Pacific Northwest of USA," Agricultural Systems, Elsevier, vol. 201(C).
    8. Anar, Mohammad J. & Lin, Zhulu & Hoogenboom, Gerrit & Shelia, Vakhtang & Batchelor, William D. & Teboh, Jasper M. & Ostlie, Michael & Schatz, Blaine G. & Khan, Mohamed, 2019. "Modeling growth, development and yield of Sugarbeet using DSSAT," Agricultural Systems, Elsevier, vol. 169(C), pages 58-70.
    9. Pannkuk, C. D. & Stockle, C. O. & Papendick, R. I., 1998. "Evaluating CropSyst simulations of wheat management in a wheat-fallow region of the US pacific northwest," Agricultural Systems, Elsevier, vol. 57(2), pages 121-134, June.
    10. Gupta, Rishabh & Mishra, Ashok, 2019. "Climate change induced impact and uncertainty of rice yield of agro-ecological zones of India," Agricultural Systems, Elsevier, vol. 173(C), pages 1-11.
    11. 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.
    12. Mompremier, R. & Her, Y. & Hoogenboom, G. & Migliaccio, K. & Muñoz-Carpena, R. & Brym, Z. & Colbert, R.W. & Jeune, W., 2021. "Modeling the response of dry bean yield to irrigation water availability controlled by watershed hydrology," Agricultural Water Management, Elsevier, vol. 243(C).
    13. Garcia y Garcia, Axel & Guerra, Larry C. & Hoogenboom, Gerrit, 2008. "Impact of generated solar radiation on simulated crop growth and yield," Ecological Modelling, Elsevier, vol. 210(3), pages 312-326.
    14. Badini, Oumarou & Stockle, Claudio O. & Jones, Jim W. & Nelson, Roger & Kodio, Amadou & Keita, Moussa, 2007. "A simulation-based analysis of productivity and soil carbon in response to time-controlled rotational grazing in the West African Sahel region," Agricultural Systems, Elsevier, vol. 94(1), pages 87-96, April.
    15. Pala, M. & Stockle, C. O. & Harris, H. C., 1996. "Simulation of durum wheat (Triticum turgidum ssp. durum) growth under different water and nitrogen regimes in a mediterranean environment using CropSyst," Agricultural Systems, Elsevier, vol. 51(2), pages 147-163, June.
    16. Anshuman Gunawat & Devesh Sharma & Aditya Sharma & Swatantra Kumar Dubey, 2022. "Assessment of climate change impact and potential adaptation measures on wheat yield using the DSSAT model in the semi-arid environment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 2077-2096, March.
    17. Tahiri, Adel Zeggaf & Anyoji, H. & Yasuda, H., 2006. "Fixed and variable light extinction coefficients for estimating plant transpiration and soil evaporation under irrigated maize," Agricultural Water Management, Elsevier, vol. 84(1-2), pages 186-192, July.
    18. Cabelguenne, M. & Debaeke, P. & Bouniols, A., 1999. "EPICphase, a version of the EPIC model simulating the effects of water and nitrogen stress on biomass and yield, taking account of developmental stages: validation on maize, sunflower, sorghum, soybea," Agricultural Systems, Elsevier, vol. 60(3), pages 175-196, June.
    19. Adam, M. & Wery, J. & Leffelaar, P.A. & Ewert, F. & Corbeels, M. & Van Keulen, H., 2013. "A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth," Ecological Modelling, Elsevier, vol. 250(C), pages 258-268.
    20. Perez, Carlos & Roncoli, Carla & Neely, Constance & Steiner, Jean L., 2007. "Can carbon sequestration markets benefit low-income producers in semi-arid Africa? Potentials and challenges," Agricultural Systems, Elsevier, vol. 94(1), pages 2-12, April.

    More about this item

    Statistics

    Access and download statistics

    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:95:y:2008:i:7:p:776-786. 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.