| 基于FCS及EPIC模型的未来情境下作物空间竞争模拟 |
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| 引用本文： | 何英彬,高明杰,周振亚,张 晴,韦文珊,陈学渊,刘 洋.基于FCS及EPIC模型的未来情境下作物空间竞争模拟[J].农业工程学报,2015,31(13):171-177. |
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| 作者姓名： | 何英彬 高明杰 周振亚 张 晴 韦文珊 陈学渊 刘 洋 |
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| 作者单位： | 1. 中国农业科学院农业资源与农业区划研究所，北京 100081; 2. 天津工业大学管理学院，天津 300387;,1. 中国农业科学院农业资源与农业区划研究所，北京 100081;,1. 中国农业科学院农业资源与农业区划研究所，北京 100081;,1. 中国农业科学院农业资源与农业区划研究所，北京 100081;,1. 中国农业科学院农业资源与农业区划研究所，北京 100081;,1. 中国农业科学院农业资源与农业区划研究所，北京 100081;,1. 中国农业科学院农业资源与农业区划研究所，北京 100081; |
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| 基金项目： | 国家自然科学基金青年基金（41001049） |
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| 摘 要： | 该文模拟了未来2030年气候变化和社会经济情景下东北地区粮食作物玉米、水稻和大豆空间竞争情况,并将竞争结果空间化,以期为相关研究和农业区域布局政策制定提供参考。该文设置A2C1D1(IPCCA2 CO2排放气候变化情景、农民无打工收益、3种作物政府收购价格翻一番)、A2C1D2(IPCCA2 CO2排放气候变化情景、农民无打工收益、3种作物政府价格翻二番)、B2C2D1(IPCC B2 CO2排放气候变化情景、农民无打工收益、3种作物政府收购价格翻一番)和B2C2D2(IPCC B2 CO2排放气候变化情景、农民无打工收益、3种作物政府价格翻二番)等4种IPCC气体排放气候变化和社会经济混合情景,与2009年3种作物空间竞争结果比较,可以得到如下结论:1)在A2C1D1情景下,玉米面积所占粮食作物农田面积比例由82.3%下降到77.36%,大豆由7.7%上涨至8.93%,水稻则由10%上涨到13.71%,空间上,玉米在小兴安岭与嫩江平原区之间的过渡地带及辽宁省腹地水系较为发达地区的周边地区有所减少,而大豆在小兴安岭与嫩江平原区之间的过渡地带,水稻在辽宁省腹地辽河平原面积相应有所增加;2)在A2C1D2情景下,玉米面积比例由82.3%下降到75.56%,而大豆由7.7%上涨至9.52%,水稻则由10%上涨至14.92%,空间上,这一情景的变化与A2C1D1非常相似;3)在B2C2D1情景下,玉米所占面积比例由82.3%上升到84.16%,而大豆由7.7%下降至7.27%,水稻由10%则下降到8.57%,空间上,玉米面积在小兴安岭与嫩江平原区之间的过渡地带和辽宁水系较为丰富的腹地地区,大豆种植区在小兴安岭与嫩江平原区之间的过渡地出现萎缩,而水稻在辽宁腹地种植面积逐渐减少,这一现象与A2C1D1和A2C1D2相反;4)在B2收购价格翻两番的情景下,玉米所占面积比例由82.3%下降到80.06%,而大豆由7.7%上升至9.01%,而水稻由10%则上涨到10.93%,空间上分布没有明显变化。从指导实际生产的角度分析,在中国经济发展呈现新常态特征的情况下,2030年B2C2D1和B2C2D2的情景预测可能更加符合实际情况,从农产品相对平衡发展的角度出发,收购价格无差别化提高2倍对于优化农产品布局更加有利。
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| 关 键 词： | 作物 遥感 模型 粮食作物 空间竞争 FCS模型 EPIC模型 未来情景 |
| 收稿时间： | 1/5/2015 12:00:00 AM |
| 修稿时间： | 2015/5/23 0:00:00 |
Simulation on crops spatial competition based on FCS and EPIC models under future scenarios |
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| He Yingbin,Gao Mingjie,Zhou Zheny,Zhang Qing,Wei Wenshan,Chen Xueyuan and Liu Yang.Simulation on crops spatial competition based on FCS and EPIC models under future scenarios[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(13):171-177. |
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| Authors: | He Yingbin Gao Mingjie Zhou Zheny Zhang Qing Wei Wenshan Chen Xueyuan and Liu Yang |
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| Institution: | 1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 2. The Management School of Tianjin Polytechnic University, Tianji 300387, China;,1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;,1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;,1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;,1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;,1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China; and 1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China; |
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| Abstract: | Abstract: In this paper, the Northeast China including the 3 provinces of Heilongjiang, Liaoning and Jilin was regarded as study area where maize, rice and soybean were main food crops. Simulation of spatial competition of the 3 crops under 4 future combined scenarios of IPCC CO2 emission and socio-economic development (urbanization rate and governmental purchasing price for food crops) was conducted for the year of 2030 by application of the FCS (farmer crop selection) model () and EPIC (environmental policy integrated climate) model. The 4 final scenarios were A2C1D1, A2C1D2, B2C2D1 and B2C2D2. A2C1D1 represented a combination scenario by IPCC A2 option, farmers having no income when going to city to do temporary work and prices for food crop purchased by government doubling. A2C1D2 meant a combination scenario by IPCC A2 option, farmers having no income when going to city to do temporary work and prices for food crop purchased by government quadrupling. B2C2D1 was a combination scenario by IPCC B2 option, farmers having income when going to city to do temporary work and prices for food crop purchased by government doubling. B2C2D2 denoted a combination scenario by IPCC B2 option, farmers having income when going to city to do temporary work and prices for food crop purchased by government quadrupling. In comparison with simulation results in 2009, the conclusions were: 1) For the first scenario of A2C1D1, percentage of maize acreage to total arable land decreased to 77.36% from 82.3%, and meanwhile there was an increase from 7.7% and 10% to 8.93% and 13.71% for soybean and paddy rice, respectively; spatially, maize acreage declined in the fringe areas between the Lesser Xing'an Mountain and the Haerbin Plain, but in the Liaohe Plain acreages of soybean and rice went up respectively. 2) For the second scenario of A2C1D2, percentage of maize acreage to total arable land decreased to 75.56% and meanwhile that of soybean and paddy rice increased to 9.52% and 14.92%, respectively; spatially the change was very similar to that of the scenario of A2C1D1. 3) For the third scenario of B2C2D1, due to a little bit higher urbanization rate than present and present purchasing price by government doubling, percentage of maize acreage to total arable land increased to 84.16%, and meanwhile soybean and paddy rice increased to 9.52% and 14.92%, respectively; maize acreage rose in the fringe areas between the Lesser Xing'an Mountain and the Haerbin Plain, while in the Liaohe Plain acreages of soybean and rice went down respectively, which was contrary to that of the A2C1D1scenario. 4) For the fourth scenario of IPCC B2C2D2, due to a little bit higher urbanization rate than present and present purchasing price by government quadrupling, percentage of maize acreage to total food crops acreage decreased to 80.06%, and meanwhile soybean and paddy rice increased to 9.01% and 10.93%, respectively. There was not obvious change in space. Since 2030 is not far from present, there are not very dramatic changes of food crops in space for all the 4 scenarios. We also don't consider extreme events' effect on spatial competition of food crops because cognition and judge of farmers will not be influenced by that. In terms of present practical situation in China, we deduce the scenarios of B2C2D1 and B2C2D2 maybe more accord with reality. Moreover, B2C2D2 will be more beneficial to optimizing agricultural layout. |
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| Keywords: | crops remote sensing models food crop spatial competition FCS model EPIC model future scenario |
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