敦煌西湖自然保护区湿地演化与驱动因子分析

发布时间：2018-04-09 22:02

本文选题：湿地演变　切入点：驱动因子　出处：《中国水利水电科学研究院》2015年硕士论文

【摘要】：湿地是地球表面的特殊自然综合体,它对内陆干旱地区的生态环境具有重要的意义。受自然和人文因素的影响,湿地在结构及功能上不断变化。近年来,随着大规模土地开发以及全球变暖引起的气候变化,我国湿地退化有加剧的趋势。研究湿地的演变规律,分析湿地演变的驱动机制,确认湿地各类驱动因子对湿地演变的影响程度,判断湿地的演变趋势,对保护湿地生态环境,促进区域社会经济可持续发展,具有重要指导作用。本研究从自然和人文两方面驱动因子出发,结合遥感影像数据对湿地演化进行分析。分析过程从湿地演化规律、湿地演化趋势、湿地各驱动因子的贡献程度等角度出发,系统分析了内陆湿地演化与其驱动因子之间的关系,并以敦煌西湖保护区湿地为例进行了应用。主要研究结果如下：(1)选取甘肃西北部的敦煌西湖国家级自然保护区为研究对象,利用遥感影像分别对西湖湿地年内非冰封期的湿地水体分布和多年的湿地范围演变进行了解译。对湿地年内水体变化的分析表明,湿地水源来源于地下水(泉水溢出),湿地水体的分布与保护区内的地下水动态有密切关系。湿地分布区,春季因气温较低,潜水蒸发强度低,地下水水位处于高水位,泉水溢出量大,湿地因泉水补给而能保持较大的面积；到夏季气温升高,蒸发强烈,地下水水位下降,泉水溢出量衰减,导致湿地水体范围萎缩；到秋季后,地下水水位逐步抬升,湿地水体也缓慢扩展。对湿地多年演化的分析表明,在1980～2013年间,保护区湿地面积从1.72×104 hm2减少到0.99×104 hm2,湿地退化趋势明显。同时,受保护区东部城市发展的影响,湿地还有着整体向西南缓慢移动的趋势。(2)为分析湿地演化的各驱动因子对湿地演变的影响,本文从自然和人文两方面分析了每个驱动因子与湿地演化间的关系。分析表明,在自然因子中,气温的升高会加剧湿地的退化；径流量的变化并未对湿地的退化产生显著影响；冰川面积的变化会通过影响地下水的变化来影响湿地的补给,而积雪则会通过产生径流来影响湿地上游的径流量；地下水位的持续下降造成湿地主要补给水源的减少,加速了湿地的退化。在人文因子中,人口和国内生产总值的增加使社会对水资源的需求不断增大,耕地面积的扩大导致灌溉用水量的增加,这都加剧了湿地的退化。(3)在湿地演化的自然驱动因子中,冰川面积变化和高山冰雪融水对湿地的补给具有重要作用。本文利用π定理分析了冰川面积变化与气候条件间的关系,通过将冰川面积与径流量的变化对比发现二者间有较好的相关性。然后用融雪径流模型(SRM模型)对保护区上游的冰雪融水进行了模拟。同时考虑到雪盖数据对SRM模拟精度的影响较大,在对雪盖数据进行遥感解译的基础上,利用π定理对雪盖变化和气候因素变化规律进行了分析,建立了雪盖面积变化函数。然后利用该函数计算得到逐日的雪盖数据,并带入到SRM模型中再次进行模拟,结果显示模拟精度由0.84提高到了0.92,表明π定理有助于SRM模型模拟精度的提高。(4)在对湿地演化进行单因子分析的基础上,利用投影寻踪方法对湿地和各因子的演变过程进行分析,得到各因子的投影向量。投影向量的计算结果显示,在选取的湿地演化因子中,耕地面积、地下水位、冰川面积、人口等因子的向量值最大,即其对湿地演变的贡献值最大。根据投影向量最后计算出1980～2013年间各年的最佳投影值,据此来判断各个年份湿地的退化程度,结果显示在1980～2013年间有25个年份湿地处于快速退化的状态,7个年份处于严重退化状态。(5)利用灰色系统理论对湿地演变的预测表明,在考虑未来的敦煌市水资源规划中将压缩耕地面积至2.41×104 hm2。利用GM(1,2)模型对西湖湿地未来10年变化的预测显示,10年后湿地面积将减少至0.92×104 hm2,同时沙地、戈壁将稍有增加,湿地迅速退化的趋势逐渐变缓。
[Abstract]:Wetland is a special natural complex of the earth's surface, it has important significance to the ecological environment. The inland arid areas affected by natural and human factors, the wetland changes in the structure and function. In recent years, with the large-scale land development and climate change caused by global warming, China's wetlands have exacerbated the trend. The study of the evolution of wetlands, wetland evolution analysis of driving mechanism, various driving factors confirm wetland on wetland evolution, evolution trend of wetland, the wetland ecological environment protection, promote regional economic and social sustainable development, has important guiding role. This study from two aspects of natural and human driving factors of remote sensing the image data of wetland evolution were analyzed. The analysis process from the evolution of wetland, wetland wetland evolution trend, each driving factor contribution degree angle And systematic analysis of inland wetland evolution and its driving factor relationship between, and to Dunhuang wetland conservation area in West Lake as an example of the application. The main results are as follows: (1) Dunhuang West Lake national selection of Northwest Gansu nature reserve as the research object, using the remote sensing images respectively on distribution and range of wetland wetland water for many years West Lake wetland frozen period of years of non evolution are interpreted. Analysis of the changes of water in wetland indicated that wetland water comes from groundwater (water overflow), there is a close relationship between wetland water distribution and protection zone of underground water dynamic. Wetland area in spring, due to low temperatures, phreatic evaporation is low. The groundwater level in high water level, water overflow volume, wetlands due to spring water supply and to maintain a larger area; the summer temperatures rise, evaporation, groundwater level drop, water spillage The range of water attenuation, which causes the wetland atrophy; to fall, the groundwater level gradually lifted, wetland water slowly expanded. According to the analysis of the evolution of wetland for many years, in 1980~2013 years, the wetland area from 1.72 * 104 hm2 reduced to 0.99 * 104 Hm2, wetland degradation trend obviously. At the same time, the protected area of Eastern influence the development of the city, there is a whole wetland to the southwest of slow moving trend. (2) the evolution of the driving influence factor analysis of wetland on wetland evolution, this paper analyzes the relationship between each factor and driving the wetland evolution from the two aspects of natural and human. The results show that, in the natural factors, the temperature rise will be degraded intensified wetland; runoff change did not have a significant impact on wetland degradation; changes in glacier area will be affected by the change of wetland effect of groundwater recharge, and will be produced by snow The runoff to influence the runoff in the upper reaches of the wetland; the underground water level continues to decline due to the reduction of wetland mainly supply water, accelerate the wetland degradation. In human factors, the increase of population and GDP of the social demand for water resources is increasing, the expansion of cultivated area caused by the increasing demand for irrigation, which intensified the wetland degradation. (3) in the evolution of wetland natural driving factors, changes in glacier area and mountain snow melt water supply to the wetland plays an important role. This paper analyzes the relationship between the theorem of glacier area change and climatic conditions of the glacier area between the two there is a good correlation between discovery and comparison the runoff. Then the snowmelt runoff model (SRM model) to protect the area of upper reaches of meltwater is simulated. Considering the influence of snow cover data on precision of SRM is large, in the Based on the interpretation of remote sensing data of snow cover, changes of snow cover and climate change factors were analyzed by using the theorem is established. Then the function changes of snow cover area is calculated by using the data of daily snow cover function, and brought into the SRM model again in the simulation, the results show that the simulation precision is improved from 0.84 to 0.92. The theorem shows that SRM model is helpful to the improvement of simulation accuracy. (4) in the wetland evolution based on single factor analysis, it analyzes the evolution of wetland and the factors by using the projection pursuit method, projection vector of each factor. The calculation results show the projection vector, in the evolution of selected wetland factors and the area of cultivated land, underground water, glacier area, population factor vector maximum, i.e. the maximum contribution to the evolution of wetland. According to the projection vector and finally calculate 1980~2013 years each year The best projection value to judge the degree of degradation of wetland each year, results showed that in 1980~2013 years there are 25 years in the rapid degradation of the wetland, the 7 year is in the serious degraded state. (5) to predict the evolution of wetland based on grey system theory shows that in the future will consider the Dunhuang city water resources planning land compression area to 2.41 * 104 hm2. by GM (1,2) prediction model of West Lake wetland in the next 10 years change showed that after 10 years the wetland area will be reduced to 0.92 * 104 hm2 at the same time, sandy, Gobi will be increased slightly, the wetland quickly back trend gradually slow.

【学位授予单位】：中国水利水电科学研究院
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X36

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