鄱阳湖生态经济区低碳经济发展模式

从鄱阳湖生态经济区发展低碳经济的优、劣势分析入手,对低碳经济概念内涵分析的基础上,提出了鄱阳湖生态经济区低碳经济发展的4个模式：能源科技创新模式、生产体系改进模式、产业结构优化模式和低碳消费驱动模式。研究认为：优化能源供需结构,提高能源利用效率是鄱阳湖生态经济区发展低碳经济的重要途径。发展新型生产体系,推动产业结构升级是鄱阳湖生态经济区建设的核心任务。推进企业技术创新,培育低碳产业群落是鄱阳湖生态经济区建设的核心动力。引导公众绿色消费,提倡低碳生活方式是鄱阳湖生态经济区低碳发展的必然趋势。加强环境保护力度,发挥森林碳汇潜力是鄱阳湖生态经济区发展低碳经济的明显优势。     

鄱阳湖生态经济区城镇体系空间结构演变

合理有序的空间结构可以助推区域实现空间效益最大化。借助GIS空间分析技术,采用"自下而上"的城市等级及腹地划分方法以及社会网络分析方法,从城市等级、腹地、网络3个角度对鄱阳湖生态经济区城镇体系空间结构演变特征进行研究。结果表明:鄱阳湖生态经济区城镇体系等级结构特征明显;南昌、九江周边区域空间邻近效应显著;城镇网络的"核心-边缘"结构特征趋向明显;南昌市对东部区域辐射能力持续偏弱;城市等级划分出现中心城市等级与行政级别"错位耦合"的现象;城市腹地划分"边界效应"明显。     

基于能值的鄱阳湖生态经济区耕地利用集约度时空差异分析

以鄱阳湖生态经济区为例, 采用能值形态从投入指标测度耕地的利用集约度, 系统分析了研究区2000-2009 年间耕地的劳动力集约度、机械化集约度、化肥集约度、农药集约度和地膜集约度的时序特征, 然后以这5 种投入能值为基准对研究区耕地利用集约度的整体特征及其时空差异进行分析。结果表明:① 10 年间, 鄱阳湖生态经济区耕地利用集约度呈指数增加, 其中农业机械集约度的比重最大, 达到了99.50%以上, 且逐年上升, 农业机械化成为研究区农业发展的基本趋势;② 耕地属于高度集约利用和低度集约利用的县(市) 最多, 属于精细利用和粗放利用的县(市) 最少;③ 鄱阳湖生态经济区可划分为东部耕地精细利用区、中东部耕地低度集约利用区、中部耕地高度集约利用区、南部和北部耕地中度集约利用区5 个区;④ 耕地利用集约度与社会经济发展水平相协调的县(市) 逐年增加, 社会经济发展水平对当地耕地集约利用水平影响越来越明显。     

建设林业血防工程 推进鄱阳湖生态经济区建设

都昌县位于鄱阳湖北岸,居南昌、九江、景德镇金三角的中心地带,全县现有土地总面积2669.5km^2,其中陆地面积1279.2km^2,占全县面积的47.9%,水域面积1390.3km^2,占52.1%,耕地面积35572hm^2,其中水田22312hm^2,     

生态脆弱性评价方法评述

生态环境的脆弱性分析及评估是制定可持续发展的区域发展规划的重要前提,是当前环境资源领域研究的重要问题之一,近年来在地理学和生态学研究中广泛应用。通过回顾中国生态脆弱性研究中对生态环境脆弱性的定义与理解,对比分析常用的评价指标体系和方法,得出主要评价方法的特点及适用条件。并结合国外的发展方向、应用及中国的实际情况,指出了目前国内生态环境脆弱性研究中存在的问题及其发展趋势。     

基于土地退化的甘肃省生态脆弱性评价研究

生态脆弱性评价是区域生态综合评价的重要内容和生态规划的重要依据。采用甘肃省最主要和普遍的土地退化指标:土地沙漠化、土壤侵蚀（水蚀）、土壤盐渍化3项指标,以县为单元,对全省进行生态脆弱性综合评价。省内土地沙漠化和土壤盐渍化主要发生在河西地区,土壤侵蚀（水蚀）主要发生在中东部和南部地区。生态脆弱性综合评价结果为:全省发生土地退化的81个县(市、区),强度脆弱2个,高度脆弱4个,中度脆弱26个,轻度脆弱30个,微度脆弱19个。生态脆弱性呈现由南到北增加的趋势。     

青藏高原高寒区生态脆弱性评价

在分析青藏高原高寒生态系统形成机制的基础上,构筑了3个层次、10个指标的脆弱性评价指标体系,系统评估了青藏高原生态脆弱性及其区域差异。研究结果表明：青藏高原中、重度以上脆弱区的面积较大,占区域总面积的74．79％。微度、轻度脆弱区主要分布在雅鲁藏布江大拐弯处、藏东南海拔3000m以下的山地、祁连山南坡的西北段和昆仑山北...     

基于SRP概念模型的祁连山地区生态脆弱性评价

基于生态敏感性-生态恢复力-生态压力度(SRP)概念模型,从地形、气候、植被和社会经济因子选取8个评价指标,利用遥感和GIS技术,采用主成分分析方法求取权重,对祁连山地区启动水源涵养区生态环境保护和综合治理规划研究前后近10 a的生态脆弱性程度进行系统、定量地评估,旨在揭示生态脆弱性的分布特征、时空演变及动因,为区域生态保护、资源利用和可持续发展提供参考。结果表明:(1)从研究区生态脆弱性分布来看,祁连山地区主要以轻度和重度脆弱为主,脆弱性程度从西北向东南地区逐渐减弱,西北地区植被覆盖度小,海拔高,生态环境较为恶劣是导致脆弱性程度较高的原因;(2)祁连山地区3期生态脆弱程度呈逐渐下降趋势,综合指数分别为3.307、3.118和3.103;2005年生态脆弱性较高,极度脆弱面积为28 610 km²,2010年下降为11 723 km²,2015年降低为6 174 km²,极度脆弱面积逐渐减少;(3)从祁连山地区生态脆弱性演变动因来看,8个指标对生态脆弱性影响均较为显著,但在不同的时间影响程度各不相同,2005—2015年...     

博斯腾湖湿地生态脆弱性评价研究

通过对博斯腾湖流域的水资源及其湿地现状分析,采取了定性与定量相结合的方法,对博斯腾湖湿地进行了评价。评价中依据湿地生态特性及演化规律建立评价指标体系,利用层次分析法(AHP)确定指标权重,利用综合指数法计算出湿地的脆弱度。结果显示博斯腾湖湿地生态系统为中度脆弱,在此基础上探讨了博斯腾湖湿地生态脆弱性的成因。指出人类活动通过叠加在自然变化背景上的影响程度日趋增强成为该区湿地生态环境的主导性脆弱因子。     

吉林省生态经济区竞争力评价

吉林省依据其社会、经济和生态环境的现状,提出了生态省建设的战略决策,以提高综合竞争力,实现可持续发展。本文在阐述吉林生态省和区域生态经济竞争力内涵的基础上,从经济发展、生态环境、社会进步三个方面,创建了评价指标体系和评价方法,评价了吉林省9个地级区的生态经济竞争力。结合吉林省生态经济区划图,得出结论:中部生态经济竞争力最强,东部和东中部次之,西部最弱。最后根据评价结果提出了参考建议。     

鄱阳湖区洪灾风险与农户脆弱性分析

This paper quantitatively explores farmers' vulnerability to flood in the Poyang Lake Region (PLR) with the supports of GIS spatial functions. The analysis consists of three major steps,which is based on the spatial unit of township. Firstly,the spatial extent and charac-teristics of flood risk areas were determined using a digital elevation model (DEM) derived from the 1:50,000 topographic map. Secondly,for each of the township,six indices indicating the economic activities of local farmers were calculated. These indices are: rural population proportion,cultivated land proportion,GDP per unit area,employment proportion of primary industry,net rural income per capita and agricultural income proportion. These six indices were then normalized and used for later vulnerability assessment. Thirdly,the normalized indices (as GIS data layers) were overlaid with the flood risk areas to produce the risk coeffi-cient for each township and to calculate the overall vulnerability for each township. The analysis results show that in the PLR there are high flood risk areas where the farmers' livings are seriously influenced or threatened. About 55.56% of the total 180 townships in the flood risk areas have a high degree of flood vulnerability. The townships under flood risk are mainly distributed in the areas around the Poyang Lake and the areas along the "five rivers".     

Landscape Changes and Increasing Flood Frequency in China's Poyang Lake Region*

Jiangxi Province in southeastern China contains Poyang Lake, the largest freshwater lake in China. Poyang Lake and the lower sections of the major Jiangxi rivers flowing into the lake often flood during the early summer months. Floodwater can be several meters above the surrounding lowlands during the most severe flood events. Levees at the margins of Poyang Lake and along the Jiangxi rivers provide flood protection for about 10 million people. The number of severe floods in this region has increased rapidly during the past few decades, resulting in catastrophic levee failures. The three factors likely responsible for the increasing frequency of severe floods are (1) land reclamation and levee construction and (2) lake sedimentation, both of which reduce lake volume, and (3) increasing Changjiang water level, which slows Poyang Lake drainage.     

Landscape Changes and Increasing Flood Frequency in China's Poyang Lake Region*

Abstract

Jiangxi Province in southeastern China contains Poyang Lake, the largest freshwater lake in China. Poyang Lake and the lower sections of the major Jiangxi rivers flowing into the lake often flood during the early summer months. Floodwater can be several meters above the surrounding lowlands during the most severe flood events. Levees at the margins of Poyang Lake and along the Jiangxi rivers provide flood protection for about 10 million people. The number of severe floods in this region has increased rapidly during the past few decades, resulting in catastrophic levee failures. The three factors likely responsible for the increasing frequency of severe floods are (1) land reclamation and levee construction and (2) lake sedimentation, both of which reduce lake volume, and (3) increasing Changjiang water level, which slows Poyang Lake drainage.     

Farmers&rsquo|vulnerability to flood risk: A case study in the Poyang Lake Region

This paper quantitatively explores farmers’ vulnerability to flood in the Poyang Lake Region (PLR) with the supports of GIS spatial functions. The analysis consists of three major steps, which is based on the spatial unit of township. Firstly, the spatial extent and charac-teristics of flood risk areas were determined using a digital elevation model (DEM) derived from the 1:50,000 topographic map. Secondly, for each of the township, six indices indicating the economic activities of local farmers were calculated. These indices are: rural population proportion, cultivated land proportion, GDP per unit area, employment proportion of primary industry, net rural income per capita and agricultural income proportion. These six indices were then normalized and used for later vulnerability assessment. Thirdly, the normalized indices (as GIS data layers) were overlaid with the flood risk areas to produce the risk coeffi-cient for each township and to calculate the overall vulnerability for each township. The analysis results show that in the PLR there are high flood risk areas where the farmers’ livings are seriously influenced or threatened. About 55.56% of the total 180 townships in the flood risk areas have a high degree of flood vulnerability. The townships under flood risk are mainly distributed in the areas around the Poyang Lake and the areas along the “five rivers”.     

鄱阳湖湿地管理现状及对策分析

近年来鄱阳湖湿地利用与保护取得了一定的发展和成效,但随着鄱阳湖生态经济区建设不断深入,湿地利用与保护依然面临着诸多问题。为了维护湿地系统生态平衡、保护湿地功能和湿地生物多样性,实现湿地资源的可持续利用,坚持生态优先、做到适度利用、统一行政执法、加强科技创新、推进公众参与等是非常重要的应对策略。     

鄱阳湖区洪灾风险与农户脆弱性分析

运用1:5 万DEM 地形数据对鄱阳湖区洪涝灾害风险区区域范围及空间分布进行了分析。在此基础上, 以乡镇为基本研究单元, 选取乡村人口比重、耕地面积比重为洪灾风险暴露分析指标, 选取单位面积生产总值、农民人均纯收入、第一产业从业人员比重、农业收入占农村经济总收入比重等为农户洪灾应对能力分析指标, 并引入了不同洪水水位特征值的影响系数, 对鄱阳湖区农户洪灾脆弱性程度进行了定量研究。结果表明, 鄱阳湖洪灾风险区面积广、影响深, 农户对洪涝灾害总体上存在着较高的脆弱性; 在所涉及的180 个乡镇中, 农户脆弱度高于平均值的有100 个, 占到乡镇数55.56%。脆弱度最高的乡镇主要集中在滨湖地带及五河干流沿岸地区, 而脆弱度较低的乡镇则主要分布在湖区各县城关镇所在区域。     

鄱阳湖水位变化的复合驱动机制

基于对鄱阳湖开放水文系统特点和影响因素的深入分析,通过构建一组联合的神经网络模型,定量辨识了包括湖盆地形变化、三峡工程作用、长江流域气候变化等因素对湖泊水位变化的影响分量、时空差异及其发展趋势,并对其作用机制进行了探讨。结果表明：相对于1980—1999年,2003—2014年鄱阳湖湖盆地形变化、三峡工程运行、长江流域气候变化和其他人类活动对湖泊水位降低的平均贡献率分别为50%、18%和32%。由于影响机制的不同,湖泊水位对这3个驱动因子的响应表现出明显的时空差异。冬、春季节湖泊水位降低主要由湖盆地形变化引起,而夏、秋季节的水位降低则主要归因于长江流域气候变化及其他人类活动的综合影响。湖盆地形变化对湖泊水位的影响在湖区都昌站附近最为突出,并且该影响仍呈长期增加趋势。三峡工程引起的湖泊水位变化在湖口处最大,向南部湖区逐渐减弱,其长期变化趋势日渐稳定。长江流域气候变化及其他人类活动的作用值得特别注意,该影响年际间波动较大,在某些年份里（如2006年、2011年）可成为湖泊水位降低的主导因素,但年际变化趋势不明显。     

Effect of Three Gorges Dam on Poyang Lake water level at daily scale based on machine learning

Lake water level is an essential indicator of environmental changes caused by natural and human factors. The water level of Poyang Lake, the largest freshwater lake in China,has exhibited a dramatic variation for the past few years, especially after the completion of the Three Gorges Dam(TGD). However, there is a lack of more accurate assessment of the effect of the TGD on the Poyang Lake water level(PLWL) at finer temporal scales(e.g., the daily scale). Here, we used three machine learning models, namely, an Artificial Neural Network(ANN), a Nonlinear Autoregressive model with eXogenous input(NARX), and a Gated Recurrent Unit(GRU), to simulate the daily lake level during 2003–2016. We found that machine learning models with historical memory(i.e., the GRU model) are more suitable for simulating the PLWL under the influence of the TGD. The GRU-based results show that the lake level is significantly affected by the TGD regulation in the different operation stages and in different periods. Although the TGD has had a slight but not very significant impact on the yearly decline of the PLWL, the blocking or releasing of water at the TGD at certain moments has caused large changes in the lake level. This machine-learning-based study sheds light on the interactions between Poyang Lake and the Yangtze River regulated by the TGD.