...
首页> 外文期刊>Ecological Modelling >Multi-objective land use allocation modelling for prioritizing climate-smart agricultural interventions
【24h】

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

机译:用于优先级气候智能农业干预措施的多目标土地利用分配建模

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

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.
机译:农业气候智能干预措施具有不同的成本和环境和经济影响。他们的实施要求由与当前的政策制定者以及农业生态,气候和经济发展的未来情景相关的政策制定者进行适当的投资决策。因此,需要决策支持工具来帮助不同的利益相关者优先考虑,从而实施适当的战略干预措施。这些干预措施将农业生态系统转变为气候弹性,适应性和高效。本文概述了一个如此,气候智能农业优先级(CSAP)工具包的数学建模框架。该工具包采用动态,空间明确的多目标优化模型,以探索与气候适应策略相加的一系列农业增长途径,以满足农业发展和环境目标。该工具包由三个主要组成部分组成:(i)土地评估,包括评估资源可用性,土地适用性,产量和投入产出估计,所有有前景的作物生产实践和关键农业生态单位技术的技术; (ii)基于政策意见和发展计划的情景制定; (iii)线性规划模型形式的土地利用优化。气候变化和社会经济司机条件土地评估,技术投入产出关系和定义建模方案的优化目标规范。通过整合详细的自下而上的生物物理,气候影响和农业排放模式,CSAP能够支持与食品自给自足,收入,就业和缓解目标相关的农业生产目标的多目标分析,从而支持各种各样的从粮食安全评估到环境影响评估的分析,为制定气候智能发展计划的环境影响评估。

著录项

  • 来源
    《Ecological Modelling》 |2018年第2018期|共13页
  • 作者单位

    CGIAR Res Program Climate Change Agr &

    Food Secur New Delhi 110012 India;

    Inamat Maize &

    Wheat Improvement Ctr CIMMYT BISA CGIAR Res Program Climate Change Agr &

    Food Secur New Delhi 110012 India;

    Inamat Maize &

    Wheat Improvement Ctr CIMMYT BISA CGIAR Res Program Climate Change Agr &

    Food Secur New Delhi 110012 India;

    Int Livestock Res Inst CGIAR Res Program Climate Change Agr &

    Food Secur POB 30709 Nairobi 00100 Kenya;

    Int Food Policy Res Inst IFPRI South Asia New Delhi 110012 India;

    Int Food Policy Res Inst IFPRI South Asia New Delhi 110012 India;

    Inamat Maize &

    Wheat Improvement Ctr CIMMYT BISA CGIAR Res Program Climate Change Agr &

    Food Secur New Delhi 110012 India;

    Int Food Policy Res Inst IFPRI South Asia New Delhi 110012 India;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 环境生物学;
  • 关键词

    Climate-smart agriculture; Optimization; Adaptation; Mitigation; Prioritization; Climate change;

    机译:气候智能农业;优化;适应;缓解;优先级;气候变化;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号