IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v260y2013icp62-76.html
   My bibliography  Save this article

Development, uncertainty and sensitivity analysis of the simple SALUS crop model in DSSAT

Author

Listed:
  • Dzotsi, K.A.
  • Basso, B.
  • Jones, J.W.

Abstract

Simplified approaches to modeling crop growth and development have recently received more attention due to increased interest in applying crop models at large scales for various agricultural assessments. In this study, we integrated the simple version of SALUS (System Approach to Land Use Sustainability) crop model in the widely-used Decision Support System for Agrotechnology Transfer (DSSAT) to enhance the capability of DSSAT to simulate additional crops without requiring detailed parameterization. An uncertainty and sensitivity analysis was conducted using the integrated DSSAT-simple SALUS model to assess the variability in model outputs and crop parameter ranking in response to uncertainties associated with crop parameters required by the model. The influence of year, production level, and location on the effect of crop parameter uncertainty was also investigated.

Suggested Citation

  • Dzotsi, K.A. & Basso, B. & Jones, J.W., 2013. "Development, uncertainty and sensitivity analysis of the simple SALUS crop model in DSSAT," Ecological Modelling, Elsevier, vol. 260(C), pages 62-76.
    • Handle: RePEc:eee:ecomod:v:260:y:2013:i:c:p:62-76
    DOI: 10.1016/j.ecolmodel.2013.03.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380013001749
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2013.03.017?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. Confalonieri, R. & Bellocchi, G. & Bregaglio, S. & Donatelli, M. & Acutis, M., 2010. "Comparison of sensitivity analysis techniques: A case study with the rice model WARM," Ecological Modelling, Elsevier, vol. 221(16), pages 1897-1906.
    2. Adam, M. & Van Bussel, L.G.J. & Leffelaar, P.A. & Van Keulen, H. & Ewert, F., 2011. "Effects of modelling detail on simulated potential crop yields under a wide range of climatic conditions," Ecological Modelling, Elsevier, vol. 222(1), pages 131-143.
    3. Fye, R. E. & Reddy, V. R. & Baker, D. N., 1984. "The validation of GOSSYM: Part 1--Arizona conditions," Agricultural Systems, Elsevier, vol. 14(2), pages 85-105.
    4. Kiniry, James R. & Williams, J. R. & Gassman, Philip W. & Debacke, P., 1992. "General, Process-Oriented Model for Two Competing Plant Species (A)," Staff General Research Papers Archive 483, Iowa State University, Department of Economics.
    5. Stehfest, Elke & Heistermann, Maik & Priess, Joerg A. & Ojima, Dennis S. & Alcamo, Joseph, 2007. "Simulation of global crop production with the ecosystem model DayCent," Ecological Modelling, Elsevier, vol. 209(2), pages 203-219.
    6. Kiniry, James R. & Major, D. J. & Izarralde, R. C. & Williams, J. R. & Gassman, Philip W. & Morrison, M. & Bergentine, R. & Zentner, R. P., 1995. "Epic Model Parameters for Cereal, Oilseed, and Forage Crops in the Northern Great Plains Region," Staff General Research Papers Archive 894, Iowa State University, Department of Economics.
    7. Reddy, V. R. & Baker, D. N., 1988. "Estimation of parameters for the cotton simulation model GOSSYM: Cultivar differences," Agricultural Systems, Elsevier, vol. 26(2), pages 111-122.
    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. Seidel, S.J. & Barfus, K. & Gaiser, T. & Nguyen, T.H. & Lazarovitch, N., 2019. "The influence of climate variability, soil and sowing date on simulation-based crop coefficient curves and irrigation water demand," Agricultural Water Management, Elsevier, vol. 221(C), pages 73-83.
    2. Huang, Jingyi & Hartemink, Alfred E. & Kucharik, Christopher J., 2021. "Soil-dependent responses of US crop yields to climate variability and depth to groundwater," Agricultural Systems, Elsevier, vol. 190(C).
    3. Dzotsi, K.A. & Basso, B. & Jones, J.W., 2015. "Parameter and uncertainty estimation for maize, peanut and cotton using the SALUS crop model," Agricultural Systems, Elsevier, vol. 135(C), pages 31-47.
    4. Thornton, Philip K. & Whitbread, Anthony & Baedeker, Tobias & Cairns, Jill & Claessens, Lieven & Baethgen, Walter & Bunn, Christian & Friedmann, Michael & Giller, Ken E. & Herrero, Mario & Howden, Mar, 2018. "A framework for priority-setting in climate smart agriculture research," Agricultural Systems, Elsevier, vol. 167(C), pages 161-175.
    5. Lin Liu & Bruno Basso, 2020. "Linking field survey with crop modeling to forecast maize yield in smallholder farmers’ fields in Tanzania," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(3), pages 537-548, June.
    6. Liu, Lin & Basso, Bruno, 2017. "Spatial evaluation of maize yield in Malawi," Agricultural Systems, Elsevier, vol. 157(C), pages 185-192.
    7. Xenia Specka & Claas Nendel & Ralf Wieland, 2019. "Temporal Sensitivity Analysis of the MONICA Model: Application of Two Global Approaches to Analyze the Dynamics of Parameter Sensitivity," Agriculture, MDPI, vol. 9(2), pages 1-29, February.
    8. 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.

    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. Dzotsi, K.A. & Basso, B. & Jones, J.W., 2015. "Parameter and uncertainty estimation for maize, peanut and cotton using the SALUS crop model," Agricultural Systems, Elsevier, vol. 135(C), pages 31-47.
    2. Ascough II, J.C. & Andales, A.A. & Sherrod, L.A. & McMaster, G.S. & Hansen, N.C. & DeJonge, K.C. & Fathelrahman, E.M. & Ahuja, L.R. & Peterson, G.A. & Hoag, D.L., 2010. "Simulating landscape catena effects in no-till dryland agroecosystems using GPFARM," Agricultural Systems, Elsevier, vol. 103(8), pages 569-584, October.
    3. Tatsumi, Kenichi, 2016. "Effects of automatic multi-objective optimization of crop models on corn yield reproducibility in the U.S.A," Ecological Modelling, Elsevier, vol. 322(C), pages 124-137.
    4. Francisco A. Buendia-Hernandez & Maria J. Ortiz Bevia & Francisco J. Alvarez-Garcia & Antonio Ruizde Elvira, 2022. "Sensitivity of a Dynamic Model of Air Traffic Emissions to Technological and Environmental Factors," IJERPH, MDPI, vol. 19(22), pages 1-17, November.
    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.
    6. Kanapaux, William & Kiker, Gregory A., 2013. "Development and testing of an object-oriented model for adaptively managing human disturbance of least tern (Sternula antillarum) nesting habitat," Ecological Modelling, Elsevier, vol. 268(C), pages 64-77.
    7. Zhao, Xin & Calvin, Katherine & Patel, Pralit & Abigail, Snyder & Wise, Marshall & Waldhoff, Stephanie & Hejazi, Mohamad & Edmonds, James, 2021. "Impacts of interannual climate and biophysical variability on global agriculture markets," Conference papers 333245, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    8. 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.
    9. Čerkasova, Natalja & White, Michael & Arnold, Jeffrey & Bieger, Katrin & Allen, Peter & Gao, Jungang & Gambone, Marilyn & Meki, Manyowa & Kiniry, James & Gassman, Philip W., 2023. "Field scale SWAT+ modeling of corn and soybean yields for the contiguous United States: National Agroecosystem Model Development," Agricultural Systems, Elsevier, vol. 210(C).
    10. Chauhdary, Junaid Nawaz & Bakhsh, Allah & Engel, Bernard A. & Ragab, Ragab, 2019. "Improving corn production by adopting efficient fertigation practices: Experimental and modeling approach," Agricultural Water Management, Elsevier, vol. 221(C), pages 449-461.
    11. 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.
    12. 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.
    13. DeJonge, Kendall C. & Ascough, James C. & Ahmadi, Mehdi & Andales, Allan A. & Arabi, Mazdak, 2012. "Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments," Ecological Modelling, Elsevier, vol. 231(C), pages 113-125.
    14. Dennis Junior Choruma & Frank Chukwuzuoke Akamagwuna & Nelson Oghenekaro Odume, 2022. "Simulating the Impacts of Climate Change on Maize Yields Using EPIC: A Case Study in the Eastern Cape Province of South Africa," Agriculture, MDPI, vol. 12(6), pages 1-24, May.
    15. Yang, Jia & Ren, Wei & Ouyang, Ying & Feng, Gary & Tao, Bo & Granger, Joshua J. & Poudel, Krishna P., 2019. "Projection of 21st century irrigation water requirement across the Lower Mississippi Alluvial Valley," Agricultural Water Management, Elsevier, vol. 217(C), pages 60-72.
    16. Fritz, Steffen & See, Linda & Bayas, Juan Carlos Laso & Waldner, François & Jacques, Damien & Becker-Reshef, Inbal & Whitcraft, Alyssa & Baruth, Bettina & Bonifacio, Rogerio & Crutchfield, Jim & Rembo, 2019. "A comparison of global agricultural monitoring systems and current gaps," Agricultural Systems, Elsevier, vol. 168(C), pages 258-272.
    17. Luoman Pu & Shuwen Zhang & Jiuchun Yang & Liping Chang & Shuting Bai, 2019. "Spatio-Temporal Dynamics of Maize Potential Yield and Yield Gaps in Northeast China from 1990 to 2015," IJERPH, MDPI, vol. 16(7), pages 1-18, April.
    18. Kiniry, James R. & Bean, Brent & Xie, Yun & Chen, Pei-yu, 2004. "Maize yield potential: critical processes and simulation modeling in a high-yielding environment," Agricultural Systems, Elsevier, vol. 82(1), pages 45-56, October.
    19. Paleari, Livia & Confalonieri, Roberto, 2016. "Sensitivity analysis of a sensitivity analysis: We are likely overlooking the impact of distributional assumptions," Ecological Modelling, Elsevier, vol. 340(C), pages 57-63.
    20. Cheng, Kun & Ogle, Stephen M. & Parton, William J. & Pan, Genxing, 2013. "Predicting methanogenesis from rice paddies using the DAYCENT ecosystem model," Ecological Modelling, Elsevier, vol. 261, pages 19-31.

    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:260:y:2013:i:c:p:62-76. 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.