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


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


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

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    References listed on IDEAS

    1. repec:eee:ecomod:v:218:y:2008:i:1:p:110-120 is not listed on IDEAS
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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.
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    1. repec:eee:agisys:v:153:y:2017:i:c:p:172-180 is not listed on IDEAS
    2. 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.
    3. 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.
    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.
    5. Amit Kumar Srivastava & Thomas Gaiser & Frank Ewert, 2016. "Climate change impact and potential adaptation strategies under alternate climate scenarios for yam production in the sub-humid savannah zone of West Africa," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(6), pages 955-968, August.


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