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

dc.creatorDunnett, A.
dc.creatorShirsath, P.B.
dc.creatorAggarwal, P.K.
dc.creatorThornton, P.K.
dc.creatorJoshi, P.K.
dc.creatorPal, B.D.
dc.creatorKhatri-Chhetri, A.
dc.creatorGhosh, J.
dc.date2018-05-29T19:04:26Z
dc.date2018-05-29T19:04:26Z
dc.date2018
dc.date.accessioned2023-07-17T20:02:43Z
dc.date.available2023-07-17T20:02:43Z
dc.identifier0304-3800 (Print)
dc.identifierhttps://hdl.handle.net/10883/19491
dc.identifier10.1016/j.ecolmodel.2018.04.008
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7511383
dc.descriptionClimate-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.
dc.description23-35
dc.formatPDF
dc.languageEnglish
dc.publisherElsevier
dc.relationhttps://ars.els-cdn.com/content/image/1-s2.0-S030438001830125X-mmc1.docx
dc.rightsCIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
dc.rightsOpen Access
dc.source381
dc.sourceEcological Modelling
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectOptimization
dc.subjectCLIMATE-SMART AGRICULTURE
dc.subjectCLIMATE CHANGE
dc.subjectADAPTATION
dc.subjectPRIORITIZATION
dc.subjectMITIGATION
dc.titleMulti-objective land use allocation modelling for prioritizing climate-smart agricultural interventions
dc.typeArticle
dc.coverageAmsterdam, Netherlands


Este ítem pertenece a la siguiente institución