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A conceptual modelling framework for simulating the impact of soil degradation on maize yield in data-sparse regions of the tropics

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  • Adiku, Samuel G.K.
  • MacCarthy, Dilys S.
  • Kumahor, Samuel K.

Abstract

The harsh environmental conditions and poor management of agricultural fields in many parts of the tropics lead to rapid soil degradation and low crop yields, once native lands are converted to agriculture. The assessment and management of degraded fields is constrained by the low resource availability to support field data collection. Crop simulation models offer tools for assessing the degradation problem and support improved management decisions. Though a host of comprehensive crop models have been published, their wide-scale application in the tropics, especially as decision support tools continues to lag, largely due to the types and fine-scale data requirements for model execution, which are often lacking in the tropical regions. In this paper, we present a simple modelling framework that is capable of simulating the impact of soil degradation on maize yields using field-scale agriculture data. The major departure of this new modelling framework is the description of erosion in terms of soil depth loss instead of soil mass loss. The framework, which was developed from an assembly of relevant theory and equations in the published literature is designed to address the data paucity challenges often encountered in many tropical regions. The model was programmed in Excel and tested against published observed maize yields for situations where the maize was grown on simulated eroded soils of varying severity and nitrogen application rates. The model simulated well the decline in maize yields with increased erosion severity and varying nitrogen application rates (R2 = 0.79, nRMSE = 28% and Willmott d-index = 0.95). It is concluded that the model, though simple, provided a framework for assessing maize yield response to varied soil degradation conditions.

Suggested Citation

  • Adiku, Samuel G.K. & MacCarthy, Dilys S. & Kumahor, Samuel K., 2021. "A conceptual modelling framework for simulating the impact of soil degradation on maize yield in data-sparse regions of the tropics," Ecological Modelling, Elsevier, vol. 448(C).
  • Handle: RePEc:eee:ecomod:v:448:y:2021:i:c:s030438002100096x
    DOI: 10.1016/j.ecolmodel.2021.109525
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    References listed on IDEAS

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    1. Dzotsi, K.A. & Jones, J.W. & Adiku, S.G.K. & Naab, J.B. & Singh, U. & Porter, C.H. & Gijsman, A.J., 2010. "Modeling soil and plant phosphorus within DSSAT," Ecological Modelling, Elsevier, vol. 221(23), pages 2839-2849.
    2. Rodriguez, Andres F. & Gerber, Stefan & Daroub, Samira H., 2020. "Modeling soil subsidence in a subtropical drained peatland. The case of the everglades agricultural Area," Ecological Modelling, Elsevier, vol. 415(C).
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    4. Jalota, S.K. & Singh, Sukhvinder & Chahal, G.B.S. & Ray, S.S. & Panigraghy, S. & Bhupinder-Singh & Singh, K.B., 2010. "Soil texture, climate and management effects on plant growth, grain yield and water use by rainfed maize-wheat cropping system: Field and simulation study," Agricultural Water Management, Elsevier, vol. 97(1), pages 83-90, January.
    5. Blaney, Harry F. & Criddle, Wayne D., 1962. "Determining Consumptive Use and Irrigation Water Requirements," Technical Bulletins 171000, United States Department of Agriculture, Economic Research Service.
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    1. Liao, Kaihua & Lv, Ligang & Lai, Xiaoming & Zhu, Qing, 2021. "Toward a framework for the multimodel ensemble prediction of soil nitrogen losses," Ecological Modelling, Elsevier, vol. 456(C).

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