洞庭湖区滩地及稻田洼地资源分布研究

Research on Beach and Paddy Depression Resource Distribution of Dongting Lake Region

洞庭湖是我国第二大淡水湖,也是承接湘、资、沅、澧四水和吞吐长江洪道调蓄型湖泊。随着三峡的建成,以及全球气候的变化,湖区受到洪水及干旱季节交替变化,呈现涨水为湖,落水为洲的变化规律,稻田洼地及滩地的面积伴随着改变。但是对于其时空分布规律、与水位变化的关系及资源总量没有确切的数据。而系统地掌握其演替规律,对洞庭湖生态经济区的建设与发展意义重大。因此,本研究利用 1996—2016 年的 18 期 Landsat TM 遥感影像数据,提取三峡建成前后,洞庭湖区滩地及稻田洼地面积,结合城陵矶水文及气象数据,分析洞庭湖区水面、水陆交错带滩地及稻田洼地资源的时空演变规律。结果显示:湖区滩地平均面积为 21.93×10^(4)hm^(2),空间上呈聚集型分布与湖堤内、湖岸带及三口四水的河堤内,三峡蓄水前(23.27×10^(4)hm^(2))较蓄水后(21.26×10^(4)hm^(2))减幅达 8.62%,面积东洞庭(12.43×10^(4)hm^(2))>南洞庭(5.71×10^(4)hm^(2))>西洞庭(3.80×10^(4)hm^(2)),与行政区划面积正相关,年际变化与湖区水位变化呈负相关的变化规律;稻田洼地平均面积为 4.75×10^(4)hm^(2),空间上呈随机且较均匀斑块分布于湖区围湖造田后形成的堤垸及三口四水冲积而成的湖盆地内,远离湖心的区域,蓄水前(5.14×10^(4)hm^(2))较蓄水后(4.56×10^(4)hm^(2))减幅达 11.34%,面积岳阳市(2.29×10^(4)hm^(2))>常德市(1.61×10^(4)hm^(2))>益阳市(0.85×10^(4)hm^(2))。各县级行政区划的滩地及稻田洼地在三峡建成前后减幅明显;采用 Pearson 相关性分析及主成分分析可知,影响滩地及稻田洼地分布因子可分为 2 个主成分,第一主成分为“枯水期”性状,包括冬季月平均温度、冬季水位、冬季降雨量、稻田洼地面积及冬季流量等指标;第二主成分可称“丰水期”性状,包括夏季月平均温度、夏季流量、夏季水位、滩地面积、夏季降雨量等指标,构建的分析模型较可靠,能为湖区滩地及稻田洼地综合利用提供较好的理论基础。

Dongting Lake is the second largest freshwater lake in China.It is also a regulating and storage lake that receives the four rivers (Xiangjiang River,Zijiang River,Yuanjiang River and Lishui River) of Hunan,and it also is the flood channel of the Yangtze River.With the completion of the Three Gorges and the change of global climate,Dongting Lake area is subject to alternating change of flood and drought seasons,showing the change law that the rising water is a lake and the falling water is a continent,and the area of paddy depression and beach is changing with it.However,there is no exact data on its temporal and spatial distribution law,its relationship with water level change and the total amount of resources.The systematic grasp of its succession law is of great significance to the construction and development of Dongting Lake Ecological Economic Zone.Therefore,this study uses the 18 periods of Landsat TM remote sensing image data from 1996 to 2016 to extract the area of beach and paddy depression in Dongting Lake area before and after the completion of the Three Gorges.Combined with the hydrological and meteorological data of Chenglingji,this study analyzes the temporal and spatial evolution law of water surface,water land ecotone beach and paddy depression resources in Dongting Lake area.The results show that the average area of beach in the lake area is 21.93 × 10hm^(2),spatially concentrated,distributed in the lake embankment,the lake bank zone and the river embankment with three ports and four waters,before the impoundment of the Three Gorges (23.27×10^(4)hm^(2)) after impoundment (21.26×10^(4)hm^(2)),with a decrease of 8.62%,East Dongting (12.43×10^(4)hm^(2)) > South Dongting (5.71×10~4hm^(2)) > West Dongting (3.80×10^(4)hm^(2)),which is positively correlated with the area of administrative division,and the interannual change is negatively correlated with the change of water level in the lake area;The average area of paddy depression is 4.75×10^(4)hm^(2),randomly and evenly distributed in space,patches are distributed in the embankment formed after land reclamation in the lake area and the lake basin formed by the alluvium of three ports and four rivers,far away from the center of the lake,before impoundment (5.14×10^(4)hm^(2)) after impoundment (4.56×10^(4)hm^(2)),a decrease of 11.34%,Yueyang City (2.29×10^(4)hm^(2)) >Changde City (1.61×10^(4)hm^(2)) > Yiyang City (0.85×10^(4)hm^(2)) in sequence.Before and after the completion of the Three Gorges project,the beach and paddy depression in the county-level administrative divisions decreased significantly;According to Pearson correlation analysis and principal component analysis,the factors affecting the distribution of beach and paddy depression can be divided into two principal components.The first principal component is the characteristics of “Dry Season”,including monthly average temperature in winter,water level in winter,rainfall in winter,area of paddy depression and flow in winter;The second principal component can be called “Wet Season” character,including summer monthly average temperature,summer flow,summer water level,beach area,summer rainfall and other indicators.The analysis model is more reliable and can provide a better theoretical basis for the comprehensive utilization of lake beach and paddy field depression.