【摘要】：巖溶潛流帶是在巖溶裂隙發(fā)育區(qū),地表水與地下水混合交互的區(qū)域,承擔(dān)著重要的生態(tài)保護(hù)作用。我國(guó)巖溶潛流帶分布廣泛,但由于對(duì)其研究不足,加上保護(hù)措施不到位,使得巖溶潛流帶的污染日益加重,嚴(yán)重威脅著水質(zhì)以及周圍生態(tài)系統(tǒng)的健康。開展巖溶前潛流帶相關(guān)研究迫在眉睫,首要任務(wù)是進(jìn)行巖溶潛流帶的分布特征研究,對(duì)于后續(xù)巖溶潛流帶機(jī)理、運(yùn)移規(guī)律方面的研究具有重要的指導(dǎo)意義。本文在分析巖溶潛流帶的基本特征和識(shí)別途徑的基礎(chǔ)上,根據(jù)巖溶潛流帶分布區(qū)域地表響應(yīng)特征,將RS及GIS技術(shù)應(yīng)用于巖溶潛流帶分布的識(shí)別分析。選取濟(jì)南巖溶水分布典型流域三川流域(即錦繡川、錦云川、錦陽川,合稱“三川”)作為研究區(qū),在分析該流域地理位置、地形地貌以及水文地質(zhì)等基本概況的基礎(chǔ)上,分別采用遙感光譜分類分別疊加DWT模型、LWP模型、GgLWP模型的方法識(shí)別巖溶潛流帶的潛在分布范圍。選擇豐水期(2015年9月)與枯水期(2016年3月)兩個(gè)季節(jié)的高分一號(hào)遙感影像數(shù)據(jù)進(jìn)行遙感預(yù)處理,采用監(jiān)督分類法對(duì)遙感影像進(jìn)行土地利用類型解譯,結(jié)合生物量指標(biāo)的變化特征,將巖溶潛流帶分布區(qū)劃分為高、中、低3個(gè)等級(jí)�；贕IS分別建立3種濕度模型,包括:DWT模型、LWP模型、GgLWP模型,然后分別與遙感光譜分類結(jié)果疊加分析,劃分出巖溶潛流帶潛在分布等級(jí)。根據(jù)根據(jù)野外植被調(diào)查及巖溶潛流帶生物采樣結(jié)果驗(yàn)證遙感光譜分類分別疊加DWT模型、LWP模型、GgLWP模型識(shí)別巖溶潛流帶潛在分布結(jié)果的準(zhǔn)確率。結(jié)果表明:遙感光譜分類疊加LWP模型的方法具有較高的可信度,能夠較準(zhǔn)確反映巖溶潛流帶的分布情況。遙感光譜分類疊加LWP模型識(shí)別巖溶潛流帶潛分布高、中、低3個(gè)等級(jí)的可信度分別達(dá)到86.5%、61.7%、78.3%。高、中、低3個(gè)等級(jí)占研究區(qū)面積的比例分別為10.3%、31.9%、57.8%。巖溶潛流帶較多分布于河流、水庫河床、河岸緩沖帶、泉水出露區(qū)等。其中,東部發(fā)育程度較高,西部地區(qū)發(fā)育程度較低。東部臥虎山水庫地區(qū)巖溶潛流帶分布范圍最廣,西部錦繡川上游流域分布范圍最小。三條主干河流中錦陽川流域巖溶潛流帶的分布范圍最大,其次為錦繡川流域,錦云川流域分布范圍最小�；谶b感光譜分類疊加LWP模型對(duì)巖溶潛流帶潛在分布等級(jí)的識(shí)別結(jié)果,分析了巖溶潛流帶形成的空間基礎(chǔ)條件,采用變異函數(shù)法揭示巖溶潛流帶分布等級(jí)的空間演變規(guī)律,結(jié)果表明:巖溶潛流帶分布等級(jí)在東-西方向上的空間變異尺度最大,西北-東南方向次之,東北-西南方向上的空間變異尺度最小,巖溶潛流帶空間分布的主要變異方向在東-西方向。根據(jù)遙感解譯與空間分析結(jié)果,采用相關(guān)分析的方法,探討了巖溶潛流帶空間變異性的影響因素,結(jié)果表明:分析巖溶潛流帶的分布與NDVI、NDWI以及地形坡度均存在相關(guān)性,高NDVI、NDWI地區(qū)且經(jīng)歷干旱時(shí)期后能保持相對(duì)高NDVI、NDWI值的地區(qū),存在巖溶潛流帶的可能性越大,巖溶潛流帶的分布等級(jí)比其他地區(qū)高;坡度越大存在巖溶潛流帶的可能性也越大,則巖溶潛流帶的分布等級(jí)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.
【學(xué)位授予單位】：濟(jì)南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P641.134

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