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An Approach for Simulating Soil Loss from an Agro-Ecosystem Using Multi-Agent Simulation: A Case Study for Semi-Arid Ghana

Author

Listed:
  • Biola K. Badmos

    (Civil Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
    West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL), KNUST, Kumasi, Ghana)

  • Sampson K. Agodzo

    (Agricultural Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana)

  • Grace B. Villamor

    (Center for Development Research, University of Bonn, 53113 Bonn, Germany)

  • Samuel N. Odai

    (Civil Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
    West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL), KNUST, Kumasi, Ghana)

Abstract

Soil loss is not limited to change from forest or woodland to other land uses/covers. It may occur when there is agricultural land-use/cover modification or conversion. Soil loss may influence loss of carbon from the soil, hence implication on greenhouse gas emission. Changing land use could be considered actually or potentially successful in adapting to climate change, or may be considered maladaptation if it creates environmental degradation. In semi-arid northern Ghana, changing agricultural practices have been identified amongst other climate variability and climate change adaptation measures. Similarly, some of the policies aimed at improving farm household resilience toward climate change impact might necessitate land use change. The heterogeneity of farm household (agents) cannot be ignored when addressing land use/cover change issues, especially when livelihood is dependent on land. This paper therefore presents an approach for simulating soil loss from an agro-ecosystem using multi-agent simulation (MAS). We adapted a universal soil loss equation as a soil loss sub-model in the Vea-LUDAS model (a MAS model). Furthermore, for a 20-year simulation period, we presented the impact of agricultural land-use adaptation strategy (maize cultivation credit i.e. , maize credit scenario) on soil loss and compared it with the baseline scenario i.e. , business-as-usual. Adoption of maize as influenced by maize cultivation credit significantly influenced agricultural land-use change in the study area. Although there was no significant difference in the soil loss under the tested scenarios, the incorporation of human decision-making in a temporal manner allowed us to view patterns that cannot be seen in single step modeling. The study shows that opening up cropland on soil with a high erosion risk has implications for soil loss. Hence, effective measures should be put in place to prevent the opening up of lands that have high erosion risk.

Suggested Citation

  • Biola K. Badmos & Sampson K. Agodzo & Grace B. Villamor & Samuel N. Odai, 2015. "An Approach for Simulating Soil Loss from an Agro-Ecosystem Using Multi-Agent Simulation: A Case Study for Semi-Arid Ghana," Land, MDPI, vol. 4(3), pages 1-20, July.
    • Handle: RePEc:gam:jlands:v:4:y:2015:i:3:p:607-626:d:53186
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    References listed on IDEAS

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    1. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    2. Muaz Niazi & Amir Hussain, 2011. "Agent-based computing from multi-agent systems to agent-based models: a visual survey," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 479-499, November.
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    Cited by:

    1. Roslan Zainal Abidin & Mohd Amirul Mahamud & Mohd Fazly Yusof & Nor Azazi Zakaria & Mohd Aminur Rashid Mohd Amiruddin Arumugam, 2021. "Determination of Cover Management and Soil Loss Risk Mapping by Sub-Districts and River Catchments of Cameron Highlands Malaysia," Land, MDPI, vol. 10(11), pages 1-15, November.
    2. Mwambo, Francis Molua & Fürst, Christine & Nyarko, Benjamin K. & Borgemeister, Christian & Martius, Christopher, 2020. "Maize production and environmental costs: Resource evaluation and strategic land use planning for food security in northern Ghana by means of coupled emergy and data envelopment analysis," Land Use Policy, Elsevier, vol. 95(C).
    3. Kleemann, Janina & Celio, Enrico & Fürst, Christine, 2018. "Reprint of “Validation approaches of an expert-based Bayesian Belief Network in northern Ghana, West Africa”," Ecological Modelling, Elsevier, vol. 371(C), pages 101-118.
    4. Ulfia A. Lenfers & Julius Weyl & Thomas Clemen, 2018. "Firewood Collection in South Africa: Adaptive Behavior in Social-Ecological Models," Land, MDPI, vol. 7(3), pages 1-17, August.
    5. James D. A. Millington & John Wainwright, 2016. "Comparative Approaches for Innovation in Agent-Based Modelling of Landscape Change," Land, MDPI, vol. 5(2), pages 1-4, May.
    6. Amadou, Mahamadou L. & Villamor, Grace B. & Kyei-Baffour, Nicholas, 2018. "Simulating agricultural land-use adaptation decisions to climate change: An empirical agent-based modelling in northern Ghana," Agricultural Systems, Elsevier, vol. 166(C), pages 196-209.
    7. Biola K. Badmos & Ademola A. Adenle & Sampson K. Agodzo & Grace B. Villamor & Daniel K. Asare-Kyei & Laouali M. Amadou & Samuel N. Odai, 2018. "Micro-level social vulnerability assessment towards climate change adaptation in semi-arid Ghana, West Africa," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(5), pages 2261-2279, October.
    8. Mohd Amirul Mahamud & Noor Aida Saad & Roslan Zainal Abidin & Mohd Fazly Yusof & Nor Azazi Zakaria & Mohd Aminur Rashid Mohd Amiruddin Arumugam & Safari Mat Desa & Md. Nasir Md. Noh, 2021. "Determination of Cover and Land Management Factors for Soil Loss Prediction in Cameron Highlands, Malaysia," Agriculture, MDPI, vol. 12(1), pages 1-11, December.
    9. Chia-Fa Chi & Shiau-Yun Lu & Willow Hallgren & Daniel Ware & Rodger Tomlinson, 2021. "Role of Spatial Analysis in Avoiding Climate Change Maladaptation: A Systematic Review," Sustainability, MDPI, vol. 13(6), pages 1-22, March.

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