IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v207y2007i2p243-250.html
   My bibliography  Save this article

Modeling field-scale N mineralization in Coastal Plain soils (USA)

Author

Listed:
  • Zubillaga, M. Mercedes
  • Cabrera, Miguel L.
  • Kissel, David E.
  • Rema, John A.

Abstract

A tool to estimate the amount of net N mineralized under field conditions would be useful to adjust N fertilizer rates. A simulation model of soil N may be useful to develop such estimates, but must first be evaluated under the conditions in which it will be used. In this work, we implemented the N subroutine of CERES-N in Stella 6.0 modeling software to simulate net N mineralized from soil organic matter and cotton residues at three locations in a Coastal Plain field of south Georgia. The model was first calibrated with laboratory data of net N mineralized from an incubation study of cotton leaves and stems, and then used to simulate net N mineralized at three field locations. The calibrated model underestimated net N mineralized at two of the field locations by 45% and 56%, respectively. This underestimation was apparently caused by an underestimation of N mineralized from soil organic matter. To explore possible reasons for the underestimation, we collected soil samples monthly for 1 year to measure potentially mineralizable N at the three field locations, and used the data to modify the rate of soil organic matter mineralization throughout the year according to a sinusoidal wave. Simulated values of net N mineralized with this modification were within the 95% confidence interval for field-measured values. These results suggest that further research should be conducted to study the dynamics of the microbial population and microfauna present in soil, which may be partially responsible for seasonal changes in N mineralization rates.

Suggested Citation

  • Zubillaga, M. Mercedes & Cabrera, Miguel L. & Kissel, David E. & Rema, John A., 2007. "Modeling field-scale N mineralization in Coastal Plain soils (USA)," Ecological Modelling, Elsevier, vol. 207(2), pages 243-250.
  • Handle: RePEc:eee:ecomod:v:207:y:2007:i:2:p:243-250
    DOI: 10.1016/j.ecolmodel.2007.05.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380007002761
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2007.05.025?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. 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.
    2. Booltink, H. W. G. & van Alphen, B. J. & Batchelor, W. D. & Paz, J. O. & Stoorvogel, J. J. & Vargas, R., 2001. "Tools for optimizing management of spatially-variable fields," Agricultural Systems, Elsevier, vol. 70(2-3), pages 445-476.
    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. 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.
    2. 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.
    3. Utset, Angel & Velicia, Herminio & del Rio, Blanca & Morillo, Rodrigo & Centeno, Jose Antonio & Martinez, Juan Carlos, 2007. "Calibrating and validating an agrohydrological model to simulate sugarbeet water use under mediterranean conditions," Agricultural Water Management, Elsevier, vol. 94(1-3), pages 11-21, December.
    4. 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).
    5. Kadiyala, M.D.M. & Jones, J.W. & Mylavarapu, R.S. & Li, Y.C. & Reddy, M.D., 2015. "Identifying irrigation and nitrogen best management practices for aerobic rice–maize cropping system for semi-arid tropics using CERES-rice and maize models," Agricultural Water Management, Elsevier, vol. 149(C), pages 23-32.
    6. Timsina, J. & Buresh, R.J. & Dobermann, A. & Dixon, J. (ed.), 2011. "Rice-maize systems in Asia: current situation and potential," IRRI Books, International Rice Research Institute (IRRI), number 164490.
    7. Kothari, Kritika & Ale, Srinivasulu & Bordovsky, James P. & Thorp, Kelly R. & Porter, Dana O. & Munster, Clyde L., 2019. "Simulation of efficient irrigation management strategies for grain sorghum production over different climate variability classes," Agricultural Systems, Elsevier, vol. 170(C), pages 49-62.
    8. Timsina, Jagadish & Dutta, Sudarshan & Devkota, Krishna Prasad & Chakraborty, Somsubhra & Neupane, Ram Krishna & Bishta, Sudarshan & Amgain, Lal Prasad & Singh, Vinod K. & Islam, Saiful & Majumdar, Ka, 2021. "Improved nutrient management in cereals using Nutrient Expert and machine learning tools: Productivity, profitability and nutrient use efficiency," Agricultural Systems, Elsevier, vol. 192(C).
    9. Wenting Yan & Wenting Jiang & Xiaori Han & Wei Hua & Jinfeng Yang & Peiyu Luo, 2020. "Simulating and Predicting Crop Yield and Soil Fertility under Climate Change with Fertilizer Management in Northeast China Based on the Decision Support System for Agrotechnology Transfer Model," Sustainability, MDPI, vol. 12(6), pages 1-20, March.
    10. Zhang, Yuxi & Walker, Jeffrey P. & Pauwels, Valentijn R.N., 2022. "Assimilation of wheat and soil states for improved yield prediction: The APSIM-EnKF framework," Agricultural Systems, Elsevier, vol. 201(C).
    11. Melpomeni Nikou & Theodoros Mavromatis, 2023. "Demonstrating the Use of the Yield-Gap Concept on Crop Model Calibration in Data-Poor Regions: An Application to CERES-Wheat Crop Model in Greece," Land, MDPI, vol. 12(7), pages 1-19, July.
    12. Langensiepen, M. & Hanus, H. & Schoop, P. & Gräsle, W., 2008. "Validating CERES-wheat under North-German environmental conditions," Agricultural Systems, Elsevier, vol. 97(1-2), pages 34-47, April.
    13. Jing, Qi & Keulen, Herman van & Hengsdijk, Huib, 2010. "Modeling biomass, nitrogen and water dynamics in rice-wheat rotations," Agricultural Systems, Elsevier, vol. 103(7), pages 433-443, September.
    14. Xuan Yang & Zhan Tian & Laixiang Sun & Baode Chen & Francesco N. Tubiello & Yinlong Xu, 2017. "The impacts of increased heat stress events on wheat yield under climate change in China," Climatic Change, Springer, vol. 140(3), pages 605-620, February.
    15. 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.
    16. Zhao, Jie & Zhang, Xuepeng & Yang, Yadong & Zang, Huadong & Yan, Peng & Meki, Manyowa N. & Doro, Luca & Sui, Peng & Jeong, Jaehak & Zeng, Zhaohai, 2021. "Alternative cropping systems for groundwater irrigation sustainability in the North China Plain," Agricultural Water Management, Elsevier, vol. 250(C).
    17. Confalonieri, Roberto & Bregaglio, Simone & Acutis, Marco, 2016. "Quantifying uncertainty in crop model predictions due to the uncertainty in the observations used for calibration," Ecological Modelling, Elsevier, vol. 328(C), pages 72-77.
    18. 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.
    19. Prem Woli & Joel Paz, 2014. "Crop Management Effects on the Energy and Carbon Balances of Maize Stover-Based Ethanol Production," Energies, MDPI, vol. 8(1), pages 1-26, December.
    20. Yusuke Toda & Hitomi Wakatsuki & Toru Aoike & Hiromi Kajiya-Kanegae & Masanori Yamasaki & Takuma Yoshioka & Kaworu Ebana & Takeshi Hayashi & Hiroshi Nakagawa & Toshihiro Hasegawa & Hiroyoshi Iwata, 2020. "Predicting biomass of rice with intermediate traits: Modeling method combining crop growth models and genomic prediction models," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-21, June.

    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:ecomod:v:207:y:2007:i:2:p:243-250. 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.journals.elsevier.com/ecological-modelling .

    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.