基于RS与GIS的典型流域岩溶潜流带空间分布特征研究

发布时间：2018-11-28 16:49

【摘要】：岩溶潜流带是在岩溶裂隙发育区,地表水与地下水混合交互的区域,承担着重要的生态保护作用。我国岩溶潜流带分布广泛,但由于对其研究不足,加上保护措施不到位,使得岩溶潜流带的污染日益加重,严重威胁着水质以及周围生态系统的健康。开展岩溶前潜流带相关研究迫在眉睫,首要任务是进行岩溶潜流带的分布特征研究,对于后续岩溶潜流带机理、运移规律方面的研究具有重要的指导意义。本文在分析岩溶潜流带的基本特征和识别途径的基础上,根据岩溶潜流带分布区域地表响应特征,将RS及GIS技术应用于岩溶潜流带分布的识别分析。选取济南岩溶水分布典型流域三川流域(即锦绣川、锦云川、锦阳川,合称“三川”)作为研究区,在分析该流域地理位置、地形地貌以及水文地质等基本概况的基础上,分别采用遥感光谱分类分别叠加DWT模型、LWP模型、GgLWP模型的方法识别岩溶潜流带的潜在分布范围。选择丰水期(2015年9月)与枯水期(2016年3月)两个季节的高分一号遥感影像数据进行遥感预处理,采用监督分类法对遥感影像进行土地利用类型解译,结合生物量指标的变化特征,将岩溶潜流带分布区划分为高、中、低3个等级。基于GIS分别建立3种湿度模型,包括:DWT模型、LWP模型、GgLWP模型,然后分别与遥感光谱分类结果叠加分析,划分出岩溶潜流带潜在分布等级。根据根据野外植被调查及岩溶潜流带生物采样结果验证遥感光谱分类分别叠加DWT模型、LWP模型、GgLWP模型识别岩溶潜流带潜在分布结果的准确率。结果表明:遥感光谱分类叠加LWP模型的方法具有较高的可信度,能够较准确反映岩溶潜流带的分布情况。遥感光谱分类叠加LWP模型识别岩溶潜流带潜分布高、中、低3个等级的可信度分别达到86.5%、61.7%、78.3%。高、中、低3个等级占研究区面积的比例分别为10.3%、31.9%、57.8%。岩溶潜流带较多分布于河流、水库河床、河岸缓冲带、泉水出露区等。其中,东部发育程度较高,西部地区发育程度较低。东部卧虎山水库地区岩溶潜流带分布范围最广,西部锦绣川上游流域分布范围最小。三条主干河流中锦阳川流域岩溶潜流带的分布范围最大,其次为锦绣川流域,锦云川流域分布范围最小。基于遥感光谱分类叠加LWP模型对岩溶潜流带潜在分布等级的识别结果,分析了岩溶潜流带形成的空间基础条件,采用变异函数法揭示岩溶潜流带分布等级的空间演变规律,结果表明:岩溶潜流带分布等级在东-西方向上的空间变异尺度最大,西北-东南方向次之,东北-西南方向上的空间变异尺度最小,岩溶潜流带空间分布的主要变异方向在东-西方向。根据遥感解译与空间分析结果,采用相关分析的方法,探讨了岩溶潜流带空间变异性的影响因素,结果表明:分析岩溶潜流带的分布与NDVI、NDWI以及地形坡度均存在相关性,高NDVI、NDWI地区且经历干旱时期后能保持相对高NDVI、NDWI值的地区,存在岩溶潜流带的可能性越大,岩溶潜流带的分布等级比其他地区高;坡度越大存在岩溶潜流带的可能性也越大,则岩溶潜流带的分布等级越高。
[Abstract]:The karst undercurrent zone is an area of mixed interaction between surface water and ground water in the development area of karst fissure. The distribution of the karst undercurrent zone in our country is widespread, but due to the insufficient research, the protection measures are not in place, so that the pollution of the karst undercurrent zone is increasing, and the health of the water quality and the surrounding ecological system is seriously threatened. It is urgent to carry out the related research of the pre-karst undercurrent zone, and the first task is to study the distribution characteristics of the karst undercurrent zone, which is of great significance to the research of the follow-up karst undercurrent belt mechanism and the migration law. Based on the analysis of the basic characteristics and the identification methods of the karst undercurrent zone, the RS and GIS technology is applied to the identification and analysis of the distribution of the karst undercurrent zone according to the surface response characteristics of the distribution area of the karst undercurrent zone. Based on the analysis of the geographical location of the river basin, the terrain and the landform, and the hydrogeology and other basic general conditions, the three-Sichuan basin of the typical water distribution of the karst water in Jinan (i.e., Jinxiu, Jinyun, Jinyang, and the third Sichuan) is selected as the research area. The potential distribution range of the karst undercurrent zone is identified by means of the remote sensing spectrum classification, the DWT model, the LWP model and the GgLWP model, respectively. the remote sensing pre-processing is carried out on the high-score-1 remote sensing image data of the two seasons in the high-water period (September 2015) and the dry season (March 2016), The distribution area of the karst undercurrent zone is divided into high, medium and low 3 grades. Three kinds of humidity models are set up based on GIS, including: DWT model, LWP model, GgLWP model, and then with the remote sensing spectrum classification result, the potential distribution grade of the karst undercurrent zone is divided. According to the field vegetation survey and the biological sampling results of the karst undercurrent zone, the accuracy of the potential distribution results of the karst undercurrent zone is identified by the superposition of the DWT model, the LWP model and the GgLWP model, respectively. The results show that the method of the remote sensing spectrum classification and superposition of the LWP model has high reliability and can accurately reflect the distribution of the karst undercurrent zone. The classification of the remote sensing spectrum and the superposition of the LWP model to identify the high, middle and low three levels of the karst undercurrent zone has reached 86.5%, 61.7%, 78.3%, respectively. The proportion of the area of the study area was 10.3%, 31.9% and 55.7%, respectively. The karst undercurrent zone is more distributed in the river, the reservoir bed, the river bank buffer zone, the spring water outlet area and the like. Among them, the development of the east is high, and the development of the western region is low. The distribution range of the karst undercurrent zone is the most and the distribution range of the upper reaches of the western Jinxiu River is the smallest. In the three main rivers, the distribution range of the karst undercurrent zone in the Jinyang-chuan river basin is the largest, the second is the Jinxiu River basin, and the distribution range of the Jinyangchuan river basin is the smallest. Based on the recognition results of the potential distribution grade of the karst undercurrent zone based on the remote sensing spectrum classification and superposition of the LWP model, the spatial basic condition of the formation of the karst undercurrent zone is analyzed, and the spatial evolution law of the distribution grade of the karst undercurrent zone is revealed by using the variation function method, and the results show that: The spatial variation scale in the east-west direction is the largest, the northwest-southeast direction is the second, the spatial variation scale in the northeast-southwest direction is the smallest, and the main variation direction of the spatial distribution of the karst undercurrent zone is in the east-west direction. Based on the results of the remote sensing interpretation and the spatial analysis, the influence factors of the spatial variability of the karst undercurrent zone are discussed by the method of correlation analysis. The results show that the distribution of the karst undercurrent zone is related to the NDVI, NDWI and the terrain slope, and the high NDVI, In the NDWI area and after the period of drought, the area with relatively high NDVI and NDWI value can be maintained. The higher the probability of the karst undercurrent zone, the higher the distribution grade of the karst undercurrent zone, and the higher the probability of the karst undercurrent zone, the higher the distribution grade of the karst undercurrent zone.
【学位授予单位】：济南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P641.134

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