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Evaluation of three simulation approaches for assessing yield of rainfed sunflower in a Mediterranean environment for climate change impact modelling

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  • J. García-López
  • Ignacio Lorite
  • R. García-Ruiz
  • J. Domínguez

Abstract

The determination of the impact of climate change on crop yield at a regional scale requires the development of new modelling methodologies able to generate accurate yield estimates with reduced available data. In this study, different simulation approaches for assessing yield have been evaluated. In addition to two well-known models (AquaCrop and Stewart function), a methodological proposal considering a simplified approach using an empirical model (SOM) has been included in the analysis. This empirical model was calibrated using rainfed sunflower experimental field data from three sites located in Andalusia, southern Spain, and validated using two additional locations, providing very satisfactory results compared with the other models with higher data requirements. Thus, only requiring weather data (accumulated rainfall from the beginning of the season fixed on September 1st, and maximum temperature during flowering) the approach accurately described the temporal and spatial yield variability observed (RMSE = 391 kg ha −1 ). The satisfactory results for assessing yield of sunflower under semi-arid conditions obtained in this study demonstrate the utility of empirical approaches with few data requirements, providing an excellent decision tool for climate change impact analyses at a regional scale, where available data is very limited. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • J. García-López & Ignacio Lorite & R. García-Ruiz & J. Domínguez, 2014. "Evaluation of three simulation approaches for assessing yield of rainfed sunflower in a Mediterranean environment for climate change impact modelling," Climatic Change, Springer, vol. 124(1), pages 147-162, May.
    • Handle: RePEc:spr:climat:v:124:y:2014:i:1:p:147-162
    DOI: 10.1007/s10584-014-1067-6
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    References listed on IDEAS

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    1. Rinaldi, Michele & Losavio, Nicola & Flagella, Zina, 2003. "Evaluation and application of the OILCROP-SUN model for sunflower in southern Italy," Agricultural Systems, Elsevier, vol. 78(1), pages 17-30, October.
    2. Hansen, J. W. & Jones, J. W., 2000. "Scaling-up crop models for climate variability applications," Agricultural Systems, Elsevier, vol. 65(1), pages 43-72, July.
    3. M. Moriondo & C. Giannakopoulos & M. Bindi, 2011. "Climate change impact assessment: the role of climate extremes in crop yield simulation," Climatic Change, Springer, vol. 104(3), pages 679-701, February.
    4. Daniel Urban & Michael Roberts & Wolfram Schlenker & David Lobell, 2012. "Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields," Climatic Change, Springer, vol. 112(2), pages 525-533, May.
    5. Katerji, N. & van Hoorn, J. W. & Hamdy, A. & Mastrorilli, M. & Karam, F., 1998. "Salinity and drought, a comparison of their effects on the relationship between yield and evapotranspiration," Agricultural Water Management, Elsevier, vol. 36(1), pages 45-54, February.
    6. 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.
    7. Raes, Dirk & Geerts, Sam & Kipkorir, Emmanuel & Wellens, Joost & Sahli, Ali, 2006. "Simulation of yield decline as a result of water stress with a robust soil water balance model," Agricultural Water Management, Elsevier, vol. 81(3), pages 335-357, March.
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    Cited by:

    1. Hussain, Mubshar & Farooq, Shahid & Hasan, Waseem & Ul-Allah, Sami & Tanveer, Mohsin & Farooq, Muhammad & Nawaz, Ahmad, 2018. "Drought stress in sunflower: Physiological effects and its management through breeding and agronomic alternatives," Agricultural Water Management, Elsevier, vol. 201(C), pages 152-166.
    2. Zhao Chen & Xv Liu & Junpeng Niu & Wennan Zhou & Tian Zhao & Wenbo Jiang & Jian Cui & Robert Kallenbach & Quanzhen Wang, 2019. "Optimizing irrigation and nitrogen fertilization for seed yield in western wheatgrass [Pascopyrum smithii (Rydb.) Á. Löve] using a large multi-factorial field design," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-21, June.
    3. Na Liu & Wenhao Feng & Hongyuan Zhang & Fangdi Chang & Jing Wang & Yuyi Li & Huancheng Pang, 2023. "If Sand Interlayer Acts Better than Straw Interlayer for Saline Soil Amelioration? A Three-Year Field Experiment," Sustainability, MDPI, vol. 15(6), pages 1-13, March.
    4. Cabezas, J.M. & Ruiz-Ramos, M. & Soriano, M.A. & Santos, C. & Gabaldón-Leal, C. & Lorite, I.J., 2021. "Impact of climate change on economic components of Mediterranean olive orchards," Agricultural Water Management, Elsevier, vol. 248(C).
    5. Cabezas, J.M. & Ruiz-Ramos, M. & Soriano, M.A. & Gabaldón-Leal, C. & Santos, C. & Lorite, I.J., 2020. "Identifying adaptation strategies to climate change for Mediterranean olive orchards using impact response surfaces," Agricultural Systems, Elsevier, vol. 185(C).
    6. García-López, J. & García-Ruiz, R. & Domínguez, J. & Lorite, I.J., 2019. "Improving the sustainability of farming systems under semi-arid conditions by enhancing crop management," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    7. Dhouib, M. & Zitouna-Chebbi, R. & Prévot, L. & Molénat, J. & Mekki, I. & Jacob, F., 2022. "Multicriteria evaluation of the AquaCrop crop model in a hilly rainfed Mediterranean agrosystem," Agricultural Water Management, Elsevier, vol. 273(C).
    8. García-López, J. & Lorite, I.J. & García-Ruiz, R. & Ordoñez, R. & Dominguez, J., 2016. "Yield response of sunflower to irrigation and fertilization under semi-arid conditions," Agricultural Water Management, Elsevier, vol. 176(C), pages 151-162.

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