IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v103y2010i9p656-665.html
   My bibliography  Save this article

Regional simulation of maize production in tropical savanna fallow systems as affected by fallow availability

Author

Listed:
  • Gaiser, Thomas
  • Judex, Michael
  • Hiepe, Claudia
  • Kuhn, Arnim

Abstract

Upscaling of crop models from the field scale to the national or global scale is being used as a widespread method to make large-scale assessments of global change impacts on crop yields and agricultural production. In spite of the fact that soil fertility restoration and crop performance in many developing countries with low-input agriculture rely strongly on fallow duration and management, there are only few approaches which take into account the effect of fallowing on crop yields at the regional scale. The objectives of this study were to evaluate the sensitivity of maize yield simulations with the Environmental Policy Integrated Climate (EPIC) model to fallow availability at the field and regional scale and (2) to present a novel approach to derive a model-based estimate of the average fallow availability within a typical catchment of the sub-humid savanna zone of West Africa. Therefore, the EPIC model has been validated at the field scale and then incorporated into a spatial database covering a typical catchment within the sub-humid savanna zone of West Africa with 121 sub-basins. Maize-fallow rotations have been simulated within 2556 quasi-homogenous spatial units and then aggregated to the 10 districts within the catchment assuming three different scenarios of fallow availability: 100% of the bush-grass savanna area is available and used in fallow-crop rotations (FU100), 50% of the bush-grass savanna area is available and used in fallow-crop rotations (FU50) and 25% of the bush-grass savanna area is available and used in fallow-crop rotations (FU25). A new aggregation procedure has been developed which is based on changes in the frequency of fallow-cropland classes within the sub-basins to render the simulation results in the spatial database sensitive to changes in fallow availability. Comparison of the average simulated grain yield with the mean yield over the catchment shows that the simulations overestimate maize yields by 62%, 44% and 15% for scenario FU100, FU50 and FU25, respectively. The best agreement between simulated and observed crop yields at the district scale was found when using the assumption that 25% of the savanna is available as fallow land under the present cropping patterns, which corresponds to a fallow-cropland ratio of 0.9. Comparison with farm surveys shows that the combination of remote sensing and dynamic crop modelling with yield observations provides realistic estimates of effective fallow use at the regional scale.

Suggested Citation

  • Gaiser, Thomas & Judex, Michael & Hiepe, Claudia & Kuhn, Arnim, 2010. "Regional simulation of maize production in tropical savanna fallow systems as affected by fallow availability," Agricultural Systems, Elsevier, vol. 103(9), pages 656-665, November.
  • Handle: RePEc:eee:agisys:v:103:y:2010:i:9:p:656-665
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308-521X(10)00100-9
    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. Hartkamp, A. D. & White, J. W. & Rossing, W. A. H. & van Ittersum, M. K. & Bakker, E. J. & Rabbinge, R., 2004. "Regional application of a cropping systems simulation model: crop residue retention in maize production systems of Jalisco, Mexico," Agricultural Systems, Elsevier, vol. 82(2), pages 117-138, November.
    2. Manlay, Raphael J. & Ickowicz, Alexandre & Masse, Dominique & Floret, Christian & Richard, Didier & Feller, Christian, 2004. "Spatial carbon, nitrogen and phosphorus budget of a village in the West African savanna--I. Element pools and structure of a mixed-farming system," Agricultural Systems, Elsevier, vol. 79(1), pages 55-81, January.
    3. Babcock, Bruce A. & Campbell, Todd & Gassman, Philip W. & Hurley, Terrance M. & Mitchell, Paul D. & Otake, Toshitsugu & Siemers, Mark & Wu, JunJie, 1998. "RAPS 1997: Agricultural and Environmental Outlook," Staff General Research Papers Archive 1158, Iowa State University, Department of Economics.
    4. Gaiser, Thomas & Stahr, Karl & Billen, Norbert & Mohammad, Mohammad Abdel-Razek, 2008. "Modeling carbon sequestration under zero tillage at the regional scale. I. The effect of soil erosion," Ecological Modelling, Elsevier, vol. 218(1), pages 110-120.
    5. Liu, Junguo & Williams, Jimmy R. & Zehnder, Alexander J.B. & Yang, Hong, 2007. "GEPIC - modelling wheat yield and crop water productivity with high resolution on a global scale," Agricultural Systems, Elsevier, vol. 94(2), pages 478-493, May.
    6. Philip W. Gassman & Jimmy R. Williams & Verel W. Benson & R. César Izaurralde & Larry M. Hauck & C. Allan Jones & Jay D. Atwood & James Kiniry & Joan D. Flowers, 2005. "Historical Development and Applications of the EPIC and APEX Models," Center for Agricultural and Rural Development (CARD) Publications 05-wp397, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    7. Gassman, Philip W. & Wu, JunJie & Mitchell, Paul D. & Babcock, Bruce A. & Hurley, Terrance M. & Chung, S. W., 1998. "Impact of U.S. Agricultural Policy on Regional Nitrogen Losses [Poster Papers]," Staff General Research Papers Archive 1186, Iowa State University, Department of Economics.
    8. Bernardos, J. N. & Viglizzo, E. F. & Jouvet, V. & Lertora, F. A. & Pordomingo, A. J. & Cid, F. D., 2001. "The use of EPIC model to study the agroecological change during 93 years of farming transformation in the Argentine pampas," Agricultural Systems, Elsevier, vol. 69(3), pages 215-234, September.
    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. Folberth, Christian & Yang, Hong & Gaiser, Thomas & Abbaspour, Karim C. & Schulin, Rainer, 2013. "Modeling maize yield responses to improvement in nutrient, water and cultivar inputs in sub-Saharan Africa," Agricultural Systems, Elsevier, vol. 119(C), pages 22-34.
    2. Webber, Heidi & Gaiser, Thomas & Ewert, Frank, 2014. "What role can crop models play in supporting climate change adaptation decisions to enhance food security in Sub-Saharan Africa?," Agricultural Systems, Elsevier, vol. 127(C), pages 161-177.
    3. Sierra, Jorge & Causeret, François & Chopin, Pierre, 2017. "A framework coupling farm typology and biophysical modelling to assess the impact of vegetable crop-based systems on soil carbon stocks. Application in the Caribbean," Agricultural Systems, Elsevier, vol. 153(C), pages 172-180.
    4. Srivastava, Amit Kumar & Mboh, Cho Miltin & Gaiser, Thomas & Webber, Heidi & Ewert, Frank, 2016. "Effect of sowing date distributions on simulation of maize yields at regional scale – A case study in Central Ghana, West Africa," Agricultural Systems, Elsevier, vol. 147(C), pages 10-23.

    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. Liu, Junguo & Williams, Jimmy R. & Zehnder, Alexander J.B. & Yang, Hong, 2007. "GEPIC - modelling wheat yield and crop water productivity with high resolution on a global scale," Agricultural Systems, Elsevier, vol. 94(2), pages 478-493, May.
    2. 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).
    3. Dong Jiang & Shuai Chen & Mengmeng Hao & Jingying Fu & Fangyu Ding, 2018. "Assessing the Sustainable Development of Bioenergy from Cassava within “Water-Energy-Food” Nexus Framework in China," Sustainability, MDPI, vol. 10(7), pages 1-17, June.
    4. Xun Zhang & Jingying Fu & Gang Lin & Dong Jiang & Xiaoxi Yan, 2017. "Switchgrass-Based Bioethanol Productivity and Potential Environmental Impact from Marginal Lands in China," Energies, MDPI, vol. 10(2), pages 1-15, February.
    5. Scheierling, Susanne M. & Treguer, David O. & Booker, James F. & Decker, Elisabeth, 2014. "How to assess agricultural water productivity ? looking for water in the agricultural productivity and efficiency literature," Policy Research Working Paper Series 6982, The World Bank.
    6. Mitchell, Paul David, 1999. "The theory and practice of green insurance: insurance to encourage the adoption of corn rootworm IPM," ISU General Staff Papers 1999010108000013154, Iowa State University, Department of Economics.
    7. María Jesús Beltrán & Esther Velázquez, 2011. "Del metabolismo social al metabolismo hídrico," Documentos de Trabajo de la Asociación de Economía Ecológica en España 01_2011, Asociación de Economía Ecológica en España.
    8. JunJie Wu & Richard M. Adams & Catherine L. Kling & Katsuya Tanaka, 2003. "Assessing the Costs and Environmental Consequences of Agricultural Land Use Changes: A Site-Specific, Policy-Scale Modeling Approach," Center for Agricultural and Rural Development (CARD) Publications 03-wp330, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    9. Sheng, Meiling & Liu, Junzhi & Zhu, A-Xing & Rossiter, David G. & Zhu, Liming & Peng, Guoqiang, 2018. "Evaluation of CLM-Crop for maize growth simulation over Northeast China," Ecological Modelling, Elsevier, vol. 377(C), pages 26-34.
    10. Tomaz, Alexandra & Palma, José Ferro & Ramos, Tiago & Costa, Maria Natividade & Rosa, Elizabete & Santos, Marta & Boteta, Luís & Dôres, José & Patanita, Manuel, 2021. "Yield, technological quality and water footprints of wheat under Mediterranean climate conditions: A field experiment to evaluate the effects of irrigation and nitrogen fertilization strategies," Agricultural Water Management, Elsevier, vol. 258(C).
    11. Luxon Nhamo & James Magidi & Adolph Nyamugama & Alistair D. Clulow & Mbulisi Sibanda & Vimbayi G. P. Chimonyo & Tafadzwanashe Mabhaudhi, 2020. "Prospects of Improving Agricultural and Water Productivity through Unmanned Aerial Vehicles," Agriculture, MDPI, vol. 10(7), pages 1-18, July.
    12. Sierra, Jorge & Causeret, François & Chopin, Pierre, 2017. "A framework coupling farm typology and biophysical modelling to assess the impact of vegetable crop-based systems on soil carbon stocks. Application in the Caribbean," Agricultural Systems, Elsevier, vol. 153(C), pages 172-180.
    13. 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.
    14. Billen, Norbert & Röder, Clara & Gaiser, Thomas & Stahr, Karl, 2009. "Carbon sequestration in soils of SW-Germany as affected by agricultural management—Calibration of the EPIC model for regional simulations," Ecological Modelling, Elsevier, vol. 220(1), pages 71-80.
    15. Belem, Mahamadou & Manlay, Raphaël J. & Müller, Jean-Pierre & Chotte, Jean-Luc, 2011. "CaTMAS: A multi-agent model for simulating the dynamics of carbon resources of West African villages," Ecological Modelling, Elsevier, vol. 222(20), pages 3651-3661.
    16. Mahamadou Belem & Sansa Youl & Raphael Manlay & Bruno Barbier & Christophe Lepage, 2000. "MIROT: A multi-Agent System Model for the Simulation of the Dynamics of Carbon Resources of West-African Village Territories," Regional and Urban Modeling 283600008, EcoMod.
    17. Huang, Jing & Ridoutt, Bradley G. & Thorp, Kelly R. & Wang, Xuechun & Lan, Kang & Liao, Jun & Tao, Xu & Wu, Caiyan & Huang, Jianliang & Chen, Fu & Scherer, Laura, 2019. "Water-scarcity footprints and water productivities indicate unsustainable wheat production in China," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    18. Chul-Hee Lim & Yuyoung Choi & Moonil Kim & Soo Jeong Lee & Christian Folberth & Woo-Kyun Lee, 2018. "Spatially Explicit Assessment of Agricultural Water Equilibrium in the Korean Peninsula," Sustainability, MDPI, vol. 10(1), pages 1-17, January.
    19. Abolpour, Behrouz, 2018. "Realistic evaluation of crop water productivity for sustainable farming of wheat in Kamin Region, Fars Province, Iran," Agricultural Water Management, Elsevier, vol. 195(C), pages 94-103.
    20. Chul-Hee Lim & Seung Hee Kim & Yuyoung Choi & Menas C. Kafatos & Woo-Kyun Lee, 2017. "Estimation of the Virtual Water Content of Main Crops on the Korean Peninsula Using Multiple Regional Climate Models and Evapotranspiration Methods," Sustainability, MDPI, vol. 9(7), pages 1-17, July.

    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:103:y:2010:i:9:p:656-665. 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.