【摘要】：數(shù)字高程模型(DEM)作為重要的空間數(shù)據(jù),已經(jīng)被廣泛應(yīng)用于諸多領(lǐng)域。在流域數(shù)字化的背景下,利用DEM自動(dòng)提取流域特征已成為水文學(xué)研究的重點(diǎn)。流域特征是水文模擬及流域管理等研究的基礎(chǔ)性數(shù)據(jù),能否準(zhǔn)確快速的獲去,直接關(guān)系到這些研究的精度和效率。近年來隨著3S技術(shù)的不斷發(fā)展及DEM精度和獲取速度的不斷提高,流域特征提取研究得到進(jìn)一步發(fā)展,涌現(xiàn)出了許多新理論和新方法。 本文系統(tǒng)概括的介紹了數(shù)字高程模型的相關(guān)知識(shí),回顧了基于DEM提取流域特征的國內(nèi)外研究進(jìn)展,介紹了流域特征的基本概念,探討了基于DEM提取流域特征的算法基礎(chǔ)及方法；以三川河流域?yàn)槔?利用先進(jìn)的GIS技術(shù),實(shí)現(xiàn)了流域特征的自動(dòng)提取,分析了提取結(jié)果的精度；對(duì)整體流域進(jìn)行分割并對(duì)子流域進(jìn)行了分類。 研究成果有： (1)提取的地形因子較好的吻合流域?qū)嶋H情況,表明提取算法和應(yīng)用的工具是成熟有效的。結(jié)果表明：流域內(nèi)地形平均坡度為13.34。,河源地區(qū)較河谷地區(qū)要大,坡度大致隨著地形高程的不斷降低而降低；河谷和殘?jiān)吹貐^(qū)坡度變化微小,溝壑區(qū)變化較大；坡向變率清楚的表征了流域內(nèi)山脊線和山谷線的分布情況；坡向在8個(gè)方向上的分布較均勻；由曲率特征值可知流域內(nèi)河谷區(qū)地形平坦,非河谷區(qū)溝壑縱橫凹凸交替。 (2)提取河網(wǎng)的步驟包括：DEM的預(yù)處理、格網(wǎng)流向判定、匯流累計(jì)量計(jì)算、最佳臨界閥值確定、柵格河網(wǎng)生成、柵格河網(wǎng)矢量化及河網(wǎng)的修正和平滑。提出通過匯流累計(jì)閥值與河網(wǎng)密度相關(guān)關(guān)系來確定最佳臨界閥值的新方法,經(jīng)反復(fù)試驗(yàn)表明閥值為6500時(shí),提取的河網(wǎng)最符合實(shí)際情況,同時(shí)說明此方法是可行的。 (3)基于提取的柵格河網(wǎng)及格網(wǎng)流向數(shù)據(jù),將整體流域分割成52個(gè)子流域,并實(shí)現(xiàn)了子流域編碼及可視化顯示。選取流域面積、河網(wǎng)密度及流域形狀系數(shù)作為子流域分類因子。采用分層分類法,構(gòu)建了8類型分類標(biāo)準(zhǔn)體系,完成子流域分類。分類結(jié)果表明：子流域以狹長型小流域、狹長型大中流域及卵形低河網(wǎng)密度小流域?yàn)橹?流域整體河網(wǎng)密度大,易形成陡漲陡落的洪水,另外地形破碎植被稀疏,水土流失嚴(yán)重。
[Abstract]:As an important spatial data, digital elevation model (DEM) has been widely used in many fields. In the background of watershed digitization, automatic extraction of watershed features by using DEM has become the focus of hydrology research. Watershed characteristics are the basic data of hydrological simulation and watershed management, and the accuracy and efficiency of these studies are directly related to the accuracy and efficiency of these studies. In recent years, with the development of 3s technology and the improvement of DEM precision and acquisition speed, the research of watershed feature extraction has been further developed, and many new theories and methods have emerged. This paper systematically introduces the relevant knowledge of digital elevation model, reviews the research progress of extracting watershed features based on DEM at home and abroad, introduces the basic concepts of watershed features, and discusses the algorithm basis and method of extracting watershed features based on DEM. Taking Sanchuan River Basin as an example, the automatic extraction of watershed features is realized by using advanced GIS technology, and the accuracy of the extraction results is analyzed, and the whole watershed is divided and the sub-watershed is classified. The results are as follows: (1) the extracted terrain factors are in good agreement with the actual situation of the watershed, which indicates that the extraction algorithm and the applied tools are mature and effective. The results show that the average slope of the river basin is 13.34. The slope of the river source area is larger than that of the river valley area, and the slope degree decreases with the decreasing of the topographic elevation, the slope of the valley and residual source area changes slightly, and the gully area changes greatly. The distribution of ridge line and valley line in the watershed is clearly represented by the slope direction change rate; the distribution of slope direction is more uniform in eight directions; according to the curvature characteristic value, the terrain of valley area is flat, and the valley in non-valley area alternates with longitudinal and transverse concave and concave convex. (2) the steps of extracting river network include preprocessing of: Dem, determination of grid flow direction, calculation of accumulative amount of confluence, determination of optimal critical threshold, generation of grid network, vectorization of grid river network and modification and smoothing of river network. A new method is proposed to determine the optimal critical threshold value by the correlation between the cumulative threshold value and the density of the river network. The repeated tests show that the extracted river network is the most suitable for the actual situation when the threshold value is 6500, and it is also shown that this method is feasible. (3) based on the grid network flow data, the whole watershed is divided into 52 subbasins, and the subbasin coding and visualization are realized. Watershed area, river network density and watershed shape coefficient are selected as subwatershed classification factors. By using stratified classification method, 8 types classification standard system was constructed to complete subbasin classification. The classification results show that the subbasin is dominated by narrow and narrow small watershed, long and narrow large and medium watershed and small valley with low density of oval river network. The whole river network of the basin is dense and easy to form flood with steep rise and steep fall, in addition, the topographic vegetation is sparse. Soil erosion is serious.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：P208

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李晶;張征;朱建剛;牟向玉;劉淑春;羅柳紅;;基于DEM的太湖流域水文特征提取[J];環(huán)境科學(xué)與管理;2009年05期

2 朱金兆，吳斌，，畢華興;地理信息系統(tǒng)在黃土高原小流域分類中的應(yīng)用[J];北京林業(yè)大學(xué)學(xué)報(bào);1994年03期

3 李勤超;李宏偉;孟嬋媛;;基于DEM提取水域特征的一種算法實(shí)現(xiàn)[J];測(cè)繪科學(xué);2007年01期

4 朱慶,趙杰,鐘正,眭海剛;基于規(guī)則格網(wǎng)DEM的地形特征提取算法[J];測(cè)繪學(xué)報(bào);2004年01期

5 劉學(xué)軍,龔健雅,周啟鳴,湯國安;基于DEM坡度坡向算法精度的分析研究[J];測(cè)繪學(xué)報(bào);2004年03期

6 李麗,郝振純;基于DEM的流域特征提取綜述[J];地球科學(xué)進(jìn)展;2003年02期

7 許捍衛(wèi);何江;佘遠(yuǎn)見;;基于DEM與遙感信息的秦淮河流域數(shù)字水系提取方法[J];河海大學(xué)學(xué)報(bào)(自然科學(xué)版);2008年04期

8 強(qiáng)曉煥,元昌安;基于DEM的坡度算法分析及精度探討[J];南昌工程學(xué)院學(xué)報(bào);2005年02期

9 張勇傳,王乘;數(shù)字流域——數(shù)字地球的一個(gè)重要區(qū)域?qū)哟蝃J];水電能源科學(xué);2001年03期

10 孫友波,宮輝力,趙文吉,趙寶奎;基于DEM的數(shù)字河網(wǎng)生成方法的淺議[J];首都師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2005年02期

本文編號(hào)：2258079