IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v88y2006i2-3p451-471.html
   My bibliography  Save this article

Evaluating uncertainty introduced to process-based simulation model estimates by alternative sources of meteorological data

Author

Listed:
  • Rivington, M.
  • Matthews, K.B.
  • Bellocchi, G.
  • Buchan, K.

Abstract

No abstract is available for this item.

Suggested Citation

  • Rivington, M. & Matthews, K.B. & Bellocchi, G. & Buchan, K., 2006. "Evaluating uncertainty introduced to process-based simulation model estimates by alternative sources of meteorological data," Agricultural Systems, Elsevier, vol. 88(2-3), pages 451-471, June.
  • Handle: RePEc:eee:agisys:v:88:y:2006:i:2-3:p:451-471
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308-521X(05)00123-X
    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. Xie, Yun & Kiniry, James R. & Williams, Jimmy R., 2003. "The ALMANAC model's sensitivity to input variables," Agricultural Systems, Elsevier, vol. 78(1), pages 1-16, October.
    2. Nonhebel, Sanderine, 1994. "The effects of use of average instead of daily weather data in crop growth simulation models," Agricultural Systems, Elsevier, vol. 44(4), pages 377-396.
    3. Aggarwal, P. K., 1995. "Uncertainties in crop, soil and weather inputs used in growth models: Implications for simulated outputs and their applications," Agricultural Systems, Elsevier, vol. 48(3), pages 361-384.
    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. Rahimikhoob, Ali, 2010. "Estimating global solar radiation using artificial neural network and air temperature data in a semi-arid environment," Renewable Energy, Elsevier, vol. 35(9), pages 2131-2135.
    2. İ. Esra Büyüktahtakın & Robert G. Haight, 2018. "A review of operations research models in invasive species management: state of the art, challenges, and future directions," Annals of Operations Research, Springer, vol. 271(2), pages 357-403, December.
    3. Rivington, M. & Matthews, K.B. & Buchan, K. & Miller, D.G. & Bellocchi, G. & Russell, G., 2013. "Climate change impacts and adaptation scope for agriculture indicated by agro-meteorological metrics," Agricultural Systems, Elsevier, vol. 114(C), pages 15-31.
    4. Deo, Ravinesh C. & Wen, Xiaohu & Qi, Feng, 2016. "A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset," Applied Energy, Elsevier, vol. 168(C), pages 568-593.
    5. 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.

    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. 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.
    2. Mooney, Sian & Antle, John M. & Capalbo, Susan Marie & Paustian, Keith H., 2003. "Incorporating Uncertainty In Integrated Assessment Modeling," 2003 Annual meeting, July 27-30, Montreal, Canada 22225, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. 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.
    4. Richard Petritsch & Hubert Hasenauer, 2014. "Climate input parameters for real-time online risk assessment," 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. 70(3), pages 1749-1762, February.
    5. Wang, Zhiqiang & Ye, Li & Jiang, Jingyi & Fan, Yida & Zhang, Xiaoran, 2022. "Review of application of EPIC crop growth model," Ecological Modelling, Elsevier, vol. 467(C).
    6. Hartkamp, A. D. & White, J. W. & Hoogenboom, G., 2003. "Comparison of three weather generators for crop modeling: a case study for subtropical environments," Agricultural Systems, Elsevier, vol. 76(2), pages 539-560, May.
    7. Bandaru, Varaprasad, 2022. "Climate data induced uncertainties in simulated carbon fluxes under corn and soybean systems," Agricultural Systems, Elsevier, vol. 196(C).
    8. Behnam Ababaei, 2014. "Are Weather Generators Robust Tools to Study Daily Reference Evapotranspiration and Irrigation Requirement?," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 915-932, March.
    9. Wu, Renye & Lawes, Roger & Oliver, Yvette & Fletcher, Andrew & Chen, Chao, 2019. "How well do we need to estimate plant-available water capacity to simulate water-limited yield potential?," Agricultural Water Management, Elsevier, vol. 212(C), pages 441-447.
    10. Hijmans, R. J. & Condori, B. & Carrillo, R. & Kropff, M. J., 2003. "A quantitative and constraint-specific method to assess the potential impact of new agricultural technology: the case of frost resistant potato for the Altiplano (Peru and Bolivia)," Agricultural Systems, Elsevier, vol. 76(3), pages 895-911, June.
    11. Daniel Wallach & Linda O. Mearns & Alex C. Ruane & Reimund P. Rötter & Senthold Asseng, 2016. "Lessons from climate modeling on the design and use of ensembles for crop modeling," Climatic Change, Springer, vol. 139(3), pages 551-564, December.
    12. Bert, Federico E. & Laciana, Carlos E. & Podesta, Guillermo P. & Satorre, Emilio H. & Menendez, Angel N., 2007. "Sensitivity of CERES-Maize simulated yields to uncertainty in soil properties and daily solar radiation," Agricultural Systems, Elsevier, vol. 94(2), pages 141-150, May.
    13. Utset, Angel & Borroto, Matilde, 2001. "A modeling-GIS approach for assessing irrigation effects on soil salinisation under global warming conditions," Agricultural Water Management, Elsevier, vol. 50(1), pages 53-63, August.
    14. Mondaca-Duarte, F.D. & Reyes-Lastiri, D. & Heinen, M. & van Henten, E.J. & van Mourik, S., 2023. "Visualization of uncertain leaching fraction and drought exposure as a function of irrigation dosage and frequency," Agricultural Water Management, Elsevier, vol. 283(C).
    15. Capa-Morocho, Mirian & Ines, Amor V.M. & Baethgen, Walter E. & Rodríguez-Fonseca, Belén & Han, Eunjin & Ruiz-Ramos, Margarita, 2016. "Crop yield outlooks in the Iberian Peninsula: Connecting seasonal climate forecasts with crop simulation models," Agricultural Systems, Elsevier, vol. 149(C), pages 75-87.
    16. Zhao, Gang & Bryan, Brett A. & Song, Xiaodong, 2014. "Sensitivity and uncertainty analysis of the APSIM-wheat model: Interactions between cultivar, environmental, and management parameters," Ecological Modelling, Elsevier, vol. 279(C), pages 1-11.
    17. Szulczewski, Wieslaw & Zyromski, Andrzej & Biniak-Pieróg, Malgorzata & Machowczyk, Anna, 2010. "Modelling of the effect of dry periods on yielding of spring barley," Agricultural Water Management, Elsevier, vol. 97(5), pages 587-595, May.
    18. Park, S.J. & Hwang, C.S. & Vlek, P.L.G., 2005. "Comparison of adaptive techniques to predict crop yield response under varying soil and land management conditions," Agricultural Systems, Elsevier, vol. 85(1), pages 59-81, July.

    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:agisys:v:88:y:2006:i:2-3:p:451-471. 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/agsy .

    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.