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    Producing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change
    (Amsterdam [u.a.] : Elsevier Science, 2019) Warren, R.F.; Edwards, N.R.; Babonneau, F.; Bacon, P.M.; Dietrich, J.P.; Ford, R.W.; Garthwaite, P.; Gerten, D.; Goswami, S.; Haurie, A.; Hiscock, K.; Holden, P.B.; Hyde, M.R.; Joshi, S.R.; Kanudia, A.; Labriet, M.; Leimbach, M.; Oyebamiji, O.K.; Osborn, T.; Pizzileo, B.; Popp, A.; Price, J.; Riley, G.D.; Schaphoff, S.; Slavin, P.; Vielle, M.; Wallace, C.
    We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI_E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. Some of the coupled models have been made available for use at a secure and user-friendly web portal. © 2018 The Authors
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    To what extent is climate change adaptation a novel challenge for agricultural modellers?
    (Amsterdam [u.a.] : Elsevier Science, 2019) Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.J.; Lauwers, L.; Özkan Gülzari, Ş.; Reidsma, P.; Rolinski, S.; Ruiz-Ramos, M.; Sandars, D.L.; Sándor, R.; Schönhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Schönhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Eory, V.
    Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. © 2019 The Authors
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    Water-saving agriculture can deliver deep water cuts for China
    (Amsterdam [u.a.] : Elsevier Science, 2019) Huang, Guorui; Hoekstra, Arjen Y.; Krol, Maarten S.; Jägermeyr, Jonas; Galindo, Alejandro; Yu, Chaoqing; Wang, Ranran
    China is working hard to reconcile growing demands for freshwater with already oversubscribed renewable water resources. However, the knowledge essential for setting and achieving the intended water consumption cuts remains limited. Here we show that on-farm water management interventions such as improved irrigation and soil management practices for maize cultivation can lead to substantial water consumption reductions, by a simulated total of 28–46 % (7–14 billion m3/year) nationally, with or without the impacts of climate change. The water consumption cut is equivalent to 16–31 % of the ultimate capacity of the South-North Water Transfer Project. Much of the reduction is achievable at the populous and water-stressed North China Plain and Northeast China. Meanwhile, the interventions can increase maize production by an estimated 7–15 %, meeting 22–28 % of demand increase projected for 2050. The water management and food production improvements obtained are crucial for achieving multiple Sustainable Development Goals (SDGs) related to water, land, and food in China and far beyond. © 2019 The Authors