江淮分水岭地区水资源承载力系统结构模型评价
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  • 英文篇名:Evaluation on water resources carrying capacity in Jianghuai watershed based on system structure model
  • 作者:邢菊 ; 周亮广 ; 金菊良 ; 程启鹏
  • 英文作者:XING Ju;ZHOU Liangguang;JIN Juliang;CHENG Qipeng;College of Geographic Information and Tourism, Chuzhou University;School of Civil Engineering, Hefei University of Technology;
  • 关键词:水资源承载力 ; 环境承载能力 ; 环境保护 ; 水资源保护 ; 系统结构模型 ; 水资源超载 ; 江淮分水岭
  • 英文关键词:water resource carrying capacity;;environment carrying capacity;;environment protection;;water resource protection;;system structure model;;water resources overload;;Jianghuai watershed
  • 中文刊名:RIVE
  • 英文刊名:Yangtze River
  • 机构:滁州学院地理信息与旅游学院;合肥工业大学土木与水利工程学院;
  • 出版日期:2019-07-28
  • 出版单位:人民长江
  • 年:2019
  • 期:v.50;No.656
  • 基金:国家重点研发计划项目“水资源承载力评价方法及全国县域承载评价”(2016YFC0401303);; 安徽省高校人文社会科学重点研究基地项目“江淮分水岭地区旱涝风险评估”(SK2015A176)
  • 语种:中文;
  • 页:RIVE201907018
  • 页数:8
  • CN:07
  • ISSN:42-1202/TV
  • 分类号:114-120+126
摘要
江淮分水岭地区是安徽省重要的粮油畜禽生产基地,但区域土壤不肥,易旱缺水。基于江淮分水岭地区水资源现状,从"水环境-社会经济-生态环境"复合系统出发,依据水资源支撑力、水资源压力、水资源承载调控力3个子系统在水资源承载过程中的相互作用,建立了区域水资源承载力系统结构模型,用于对江淮分水岭地区水资源承载力进行评价分析。研究表明:在保障生态用水与生活用水前提下,当前该区域水资源承载力总体处于可载状态,但时空差异明显。时间尺度上,2005~2015年间,区域单位GDP综合用水量大幅减少,水资源所承载的经济总量呈现明显的上升趋势;区域降水量和水资源可利用量年际变化较大,可承载的人口规模波动趋势明显。空间尺度上,各市间水资源可承载的经济总量与可承载的人口规模差异极大,可承载的经济总量上合肥最大,淮南最小;可承载的人口规模上六安最大,淮南同样为最小,合肥次之。水资源承载潜力上六安>巢湖>滁州>合肥>淮南;在各市的水资源承载状态中,合肥在研究期内有4 a处于超载状态,超载范围在9.87%~31.46%,超载率最高年份为2008年,淮南各年均处于超载状态,平均超载率为59.79%,2010年超载率最高达70.18%,区域化水资源问题趋于严重。水资源可承载的人口规模与区域降水量大小显著相关,用水效率的提高及产业结构的合理性调整可降低单位GDP综合用水量,大大提高水资源承载能力。根据研究结果,建议各市应根据水资源承载力实际状况,提高用水效率,合理调整产业结构,促进区域水资源与社会经济协调发展。
        Jianghuai watershed area is one of the most important bases of grain, oil, domestic animals and poultry in Anhui Province, however the soil in the region is less fertile and prone to drought. Based on the status of water resources in the region, and starting from the complex system of "water environment, social economy and ecological environment", we built a system structure model regarding regional water resources carrying capacity based on the interaction of three subsystems, i.e. water resources supporting capacity, water resources pressure and water resources regulation ability, and we used it to evaluate the Jianghuai watershed area. The results show that under the premise of ensuring ecological and domestic water use, the carrying capacity of water resources in the region is in an under-loading state, with obvious spatial and temporal differences. In terms of time scale, the integrated water consumption for per unit of GDP reduced drastically from year 2005 to 2015, while the total economic volume experienced a noted increase. Annual regional precipitation and water resources availability vary a lot from year to year. The carrying capacity of population fluctuates significantly. In terms of spatial scale, there are great differences between cities in the economic amount and population size of water resources, Hefei city has the largest economic capacity, while Huainan city has the smallest. Liuan city has the largest population capacity while Huainan city has the smallest, followed by Hefei city. The ranking of water resources carrying capacity from the largest to the smallest is Liuan, Chaohu, Chuzhou, Hefei, Huainan. Hefei city was in overload state in 4 years during the study period, ranging from 9.87% to 31.46%, with the highest overload rate appeared in 2008. Meanwhile, Huainan city was in overload state for the whole ten years, with an average overload rate of 59.79%, and it went up to its highest in 2010 at 70.18%, indicating that the problem of regional water resources was getting serious. The population carrying capacity is significantly related to the regional precipitation. The improvement of water use efficiency and the rational adjustment of industrial structure can reduce the integrated water consumption for unit GDP and greatly increase water resources carrying capacity. According to the results, each city should improve water use efficiency, adjust industrial structure and promote the coordinated development of water resources and social economy in the region.
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