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Global estimation of crop productivity and the impacts of global warming by GIS and EPIC integration

机译:GIS和EPIC集成对作物产量和全球变暖影响的全球估计

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摘要

In this paper, a new methodology for global estimation of crop productivity is proposed. This methodology integrates Erosion Productivity Impact Calculator (EPIC) model with Geographic Information System (GIS) and Inference Engine (IE) technique. EPIC was developed by USDA to analyze the relationship between soil erosion and agricultural productivity just at field level. With the integration of GIS, EPIC can be extended to the application of global or regional level. In this integration, IE is developed to determine possible crop combinations, the optimum starting and ending dates of growth cycle for each crop type and grid cell, in order to ensure best possible crop yields for both rain-fed and irrigated conditions. A case of global crop productivity estimation is tested with GIS-based EPIC in 2000. National averages are computed to be comparable to yields in FAO statistics. The comparison indicates that the GIS-based EPIC is able to simulate crop productivity at global level. In addition, with the global climate change data provided by the Intergovernment Panel on Climate Change (IPCC) from the first version of the Canadian Global Coupled Model (CGCM1), GIS-based EPIC is run for scenarios of future climate in the year of 2010, 2020, 2030, 2040, and 2050 to predict the effects of global warming on main crop yields. Results show the global warming will be harmful for most of the countries, and an efficient adaptation to alternative climates tends to reduce the damages. (C) 2003 Elsevier Science B.V. All rights reserved. [References: 38]
机译:在本文中,提出了一种新的全球农作物生产力估算方法。该方法论将侵蚀生产力影响计算器(EPIC)模型与地理信息系统(GIS)和推理引擎(IE)技术集成在一起。 EPIC是由美国农业部(USDA)开发的,用于在田间水平分析土壤侵蚀与农业生产力之间的关系。通过集成GIS,EPIC可以扩展到全球或区域级别的应用。通过这种集成,开发了IE,以确定可能的作物组合,每种作物类型和网格单元的最佳生长周期的开始和结束日期,以确保在雨育和灌溉条件下均能获得最佳的作物产量。 2000年,使用基于GIS的EPIC对全球作物生产力估算的一个案例进行了测试。计算得出的全国平均值与粮农组织统计数据中的产量可比。比较表明,基于GIS的EPIC能够在全球范围内模拟作物生产力。此外,根据政府间气候变化专门委员会(IPCC)提供的第一版加拿大全球耦合模型(CGCM1)的全球气候变化数据,基于GIS的EPIC将用于2010年的未来气候情景,2020、2030、2040和2050年,以预测全球变暖对主要农作物产量的影响。结果表明,全球变暖对大多数国家都是有害的,对替代气候的有效适应往往会减少损害。 (C)2003 Elsevier Science B.V.保留所有权利。 [参考:38]

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