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Multi-objective land use allocation modelling for prioritizing climate-smart agricultural interventions

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  • Dunnett, A.
  • Shirsath, P.B.
  • Aggarwal, P.K.
  • Thornton, P.
  • Joshi, P.K.
  • Pal, B.D.
  • Khatri-Chhetri, A.
  • Ghosh, J.

Abstract

Climate-smart interventions in agriculture have varying costs and environmental and economic impacts. Their implementation requires appropriate investment decisions by policy makers that are relevant for current as well as future scenarios of agro-ecology, climate and economic development. Decision support tools are therefore needed to assist different stakeholders to prioritize and hence implement appropriate strategic interventions. These interventions transform agriculture ecosystems to climate-resilient, adaptive and efficient. This paper outlines the mathematical modelling framework of one such, the Climate Smart Agricultural Prioritization (CSAP) toolkit. This toolkit employs a dynamic, spatially-explicit multi-objective optimization model to explore a range of agricultural growth pathways coupled with climate-adaptation strategies to meet agricultural development and environmental goals. The toolkit consists of three major components: (i) land evaluation including assessment of resource availability, land suitability, yield and input-output estimation for all promising crop production practices and technologies for key agro-ecological units; (ii) formulation of scenarios based on policy views and development plans; and (iii) land-use optimization in the form of linear programming models. Climate change and socio-economic drivers condition the land evaluation, technological input-output relations, and specification of optimization objectives that define modelled scenarios. By integrating detailed bottom-up biophysical, climate impact and agricultural-emissions models, CSAP is capable of supporting multi-objective analysis of agricultural production goals in relation to food self-sufficiency, incomes, employment and mitigation targets, thus supporting a wide range of analyses ranging from food security assessment to environmental impact assessment to preparation of climate smart development plans.

Suggested Citation

  • Dunnett, A. & Shirsath, P.B. & Aggarwal, P.K. & Thornton, P. & Joshi, P.K. & Pal, B.D. & Khatri-Chhetri, A. & Ghosh, J., 2018. "Multi-objective land use allocation modelling for prioritizing climate-smart agricultural interventions," Ecological Modelling, Elsevier, vol. 381(C), pages 23-35.
    • Handle: RePEc:eee:ecomod:v:381:y:2018:i:c:p:23-35
    DOI: 10.1016/j.ecolmodel.2018.04.008
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    Cited by:

    1. Iyappan, Karunya & Babu, Suresh Chandra, 2018. "Building resilient food systems: An analytical review," IFPRI discussion papers 1758, International Food Policy Research Institute (IFPRI).
    2. Deo, Aniket & Shirsath, Paresh B. & Aggarwal, Pramod K., 2024. "Identifying resource-conscious and low-carbon agricultural development pathways through land use modelling," Land Use Policy, Elsevier, vol. 143(C).
    3. Nikouei, Alireza & Asgharipour, Mohammad Reza & Marzban, Zahra, 2022. "Modeling land allocation to produce crops under economic and environmental goals in Iran: a multi-objective programming approach," Ecological Modelling, Elsevier, vol. 471(C).
    4. Pietro De Marinis & Paolo Stefano Ferrario & Guido Sali & Giulio Senes, 2022. "The Rapid and Participatory Assessment of Land Suitability in Development Cooperation," Sustainability, MDPI, vol. 14(20), pages 1-24, October.
    5. Chandio, Abbas Ali & Ozdemir, Dicle & Jiang, Yuansheng, 2023. "Modelling the impact of climate change and advanced agricultural technologies on grain output: Recent evidence from China," Ecological Modelling, Elsevier, vol. 485(C).
    6. Min Chen & Songhao Shang & Wei Li, 2020. "Integrated Modeling Approach for Sustainable Land-Water-Food Nexus Management," Agriculture, MDPI, vol. 10(4), pages 1-19, April.
    7. Chandio, Abbas Ali & Dash, Devi Prasad & Nathaniel, Solomon Prince & Sargani, Ghulam Raza & Jiang, Yuansheng, 2023. "Mitigation pathways towards climate change: Modelling the impact of climatological factors on wheat production in top six regions of China," Ecological Modelling, Elsevier, vol. 481(C).
    8. Thornton, Philip K. & Whitbread, Anthony & Baedeker, Tobias & Cairns, Jill & Claessens, Lieven & Baethgen, Walter & Bunn, Christian & Friedmann, Michael & Giller, Ken E. & Herrero, Mario & Howden, Mar, 2018. "A framework for priority-setting in climate smart agriculture research," Agricultural Systems, Elsevier, vol. 167(C), pages 161-175.
    9. Alexis Rampa & Yiorgos Gadanakis & Gillian Rose, 2020. "Land Reform in the Era of Global Warming—Can Land Reforms Help Agriculture Be Climate-Smart?," Land, MDPI, vol. 9(12), pages 1-24, November.
    10. Paresh B. Shirsath & Pramod K. Aggarwal, 2021. "Trade-Offs between Agricultural Production, GHG Emissions and Income in a Changing Climate, Technology, and Food Demand Scenario," Sustainability, MDPI, vol. 13(6), pages 1-13, March.
    11. De Marinis, Pietro & Sali, Guido, 2020. "Participatory analytic hierarchy process for resource allocation in agricultural development projects," Evaluation and Program Planning, Elsevier, vol. 80(C).
    12. Prasun K. Gangopadhyay & Arun Khatri-Chhetri & Paresh B. Shirsath & Pramod K. Aggarwal, 2019. "Spatial targeting of ICT-based weather and agro-advisory services for climate risk management in agriculture," Climatic Change, Springer, vol. 154(1), pages 241-256, May.

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