| 基于MIV-BP型的喀斯特地区水资源安全影响因素分析 |
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| 引用本文： | 刘丽颖,官冬杰,杨清伟,苏维词.基于MIV-BP型的喀斯特地区水资源安全影响因素分析[J].水土保持通报,2017,37(5):128-134. |
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| 作者姓名： | 刘丽颖 官冬杰 杨清伟 苏维词 |
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| 作者单位： | 1. 重庆交通大学河海学院,重庆400074;重庆工商大学数学与统计学院,重庆400067;2. 重庆交通大学建筑与城市规划学院,重庆,400074;3. 重庆交通大学河海学院,重庆,400074;4. 重庆师范大学地理与旅游学院,重庆400047;贵州科学院山地资源研究所,贵州贵阳550001 |
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| 基金项目： | 国家科技计划项目“喀斯特地下水赋存条件及监测技术研究”（2014BAB03B01）；国家社科基金后期资助项目（16FJY010）；贵州喀斯特山区水资源环境系统服务功能创新科技人才团队”（黔科合人才团队[2014]4014）；重庆工商大学2015年校级科研项目（670101577） |
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| 摘 要： | 目的]分析喀斯特地区水资源安全的影响因素及其影响趋势,提出促进喀斯特地区水资源安全的措施与建议。方法]采用贵州省近10a的数据,建立BP型网络模型计算平均影响值(mean impact value,MIV),对其影响因素进行实证分析。结果]地下水供水比例、工业用水率、水资源利用率、人均粮食产量以及产水模数是水资源安全的阻碍因素。其中产水模数的影响程度呈现波动中逐年递减趋势,其余4个阻碍因素影响程度均显示逐年增强;工业固废综合利用率、工业废水排放达标率、中度以上石漠化面积比、单位GDP需水量以及地下水开发利用程度共同构成了水资源安全的驱动因素。从时间顺序来看,单位GDP需水量和地下水开发利用程度的影响趋于稳定,中度以上石漠化面积比因子对水资源安全影响越来越显著。工业废水排放达标率的影响逐年减弱,而工业固废综合利用率的影响情况波动比较大。结论]模型计算表明,MIV-BP模型在喀斯特地区水资源安全影响因素研究方面具有一定的现实可行性。
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| 关 键 词： | 喀斯特地区 水资源安全 MIV BP神经网络 影响因素 |
| 收稿时间： | 2017/2/8 0:00:00 |
| 修稿时间： | 2017/3/12 0:00:00 |
Influence Factors of Water Resource Security in Karst Area Based on MIV-BP Model |
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| LIU Liying,GUAN Dongjie,YANG Qingwei and SU Weici.Influence Factors of Water Resource Security in Karst Area Based on MIV-BP Model[J].Bulletin of Soil and Water Conservation,2017,37(5):128-134. |
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| Authors: | LIU Liying GUAN Dongjie YANG Qingwei and SU Weici |
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| Institution: | College of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing 400074, China;College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, China,College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing 400074, China,College of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing 400074, China and College of Geography and Tourism, Chongqing Normal University, Chongqing 400047, China;Institute of Mountain Resources, Guizhou Academy of Sciences, Guiyang, Guizhou 550001, China |
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| Abstract: | Objective] This paper illustrated the influencing factors of water resource security and its evolution trend aimed to put forward some suggestions about the water resource security in Karst area.Methods] Based on the data of Guizhou Province in the past ten years, this paper established a BP network model and applied the mean impact value(MIV) algorithm method to analyze the influencing factors of the water resource security in Karst area.Results] The groundwater supply ratio, the industrial water use proportion, water use efficiency, per capital grain yield and water yield modulus were the obstacles to the development of water resources system. The influencing degree of water yield modulus was decreasing year by year, while the other four factors showed increasing trends. Comprehensive utilization rate of industrial solid waste, the attainment rate of the industrial waste water, the ratio of moderate rocky desertification area, water requirement per-unit GDP and exploitation degree of groundwater were the driving factors. In chronological order, the influence of water requirement of per-unit GDP and exploitation degree of groundwater were stable, while the ratio of moderate rocky desertification area was more and more pronounced. The impact of the attainment rate of the industrial waste water decreased year by year, while comprehensive utilization rate of industrial solid waste fluctuated greatly.Conclusion] The MIV-BP model is feasible in studying influencing factors of water resource security in karst area. |
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| Keywords: | karst area water resource security MIV BP neural network influence factors |
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