基于数字高程模型的混合流向算法
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摘要
从数字高程模型提取的汇水网络和汇水区等信息是分布式水文模型及应用分析的基础参数,基于地表汇水模拟的算法是提取该类信息的主要方法,其中,水流方向的确定对提取结果有着直接的影响。单流向算法因其易于实现、易于确定上游汇水区等特性,得到了广泛应用,然而单流向算法在坡度平缓区域会产生不自然的平行径流,能模拟地表水流分散径流特点的多流向算法可以在一定程度上避免此问题,但多流向算法使得不同区域的汇水单元可能存在交叉。本文结合两类流向算法各自的优点和适用性,设计实现了一种混合流向算法,以期在不同的地形条件下模拟得到更加合理的水流分配。首先,使用基于模板的形态检测方法,在给定阈值的基础上,对数字地形进行了分类,DEM被划分为山谷、山脊、鞍部、缓坡和陡坡5类。对陡坡、山谷和山脊区域运用单流向算法;对缓坡和鞍部区域采用多流向算法确定径流方向并进行水量分配。本文选取了黄土地貌和中低山丘陵的两个流域作为研究区,利用并采用了30m和90m两个分辨率的DEM。本文研究将混合流向算法与现有其他算法的结果进行比较。相比于多流向算法,该算法结果中的分散效应受到明显的抑制,相比于单流向算法,非自然的平行径流也大幅减少。同时,混合流向算法在较大分辨率DEM上(30m)改进效果更加明显。
Hydrological information extracted from digital elevation models(DEMs)is the basis of distributed hydrological models.Algorithms determining water flow direction over terrain surface are basis for extracting hydrological information from the DEM.Flow direction and accumulation distributions have a direct effect on catchment area.Single flow direction algorithm is widely used because of its easiness to implement and to track upstream catchment areas.However,the single flow direction(SFD)algorithms tend to produce unnatural parallel flow paths in gentle slope areas.Therefore,multiple flow direction(MFD)algorithms have been proposed to calculate water flow directions.However,MFD algorithms create overlap upstream boundaries of watersheds.Considering applicability of SFD and MFD algorithms,a hybrid approach is proposed to calculate a more reasonable distribution of water under different terrain conditions.First,a template-based terrain classification algorithm is applied to the given DEM which is categorized into five classes:valleys,ridges,passes,gentle slope area and steep slope area with a slope threshold value.A single flow direction algorithm is applied to steep slope,valley and ridge area.A multiple flow direction algorithm is used to determine water flow directions in the gentle slope and passes area.In this paper,two small watersheds in the Linfen Basin of the Loess Plateau and the Sichuan Basin in the Yangtze River Basin were selected as study areas.SRTM DEMs of 30 mand 90 m are used in experiments.The results of hybrid flow direction algorithm are compared with the results of typical SFD and MFD algorithms.The divergent effect is apparently suppressed compared to multi-flow direction algorithms.The occurrence of unnatural parallel drainage lines is decreased compared to the results of single flow direction algorithms.And improvements of hybrid flow direction on DEMs of 30 mis better than 90 mdatasets.
Hydrological information extracted from digital elevation models(DEMs)is the basis of distributed hydrological models.Algorithms determining water flow direction over terrain surface are basis for extracting hydrological information from the DEM.Flow direction and accumulation distributions have a direct effect on catchment area.Single flow direction algorithm is widely used because of its easiness to implement and to track upstream catchment areas.However,the single flow direction(SFD)algorithms tend to produce unnatural parallel flow paths in gentle slope areas.Therefore,multiple flow direction(MFD)algorithms have been proposed to calculate water flow directions.However,MFD algorithms create overlap upstream boundaries of watersheds.Considering applicability of SFD and MFD algorithms,a hybrid approach is proposed to calculate a more reasonable distribution of water under different terrain conditions.First,a template-based terrain classification algorithm is applied to the given DEM which is categorized into five classes:valleys,ridges,passes,gentle slope area and steep slope area with a slope threshold value.A single flow direction algorithm is applied to steep slope,valley and ridge area.A multiple flow direction algorithm is used to determine water flow directions in the gentle slope and passes area.In this paper,two small watersheds in the Linfen Basin of the Loess Plateau and the Sichuan Basin in the Yangtze River Basin were selected as study areas.SRTM DEMs of 30 mand 90 m are used in experiments.The results of hybrid flow direction algorithm are compared with the results of typical SFD and MFD algorithms.The divergent effect is apparently suppressed compared to multi-flow direction algorithms.The occurrence of unnatural parallel drainage lines is decreased compared to the results of single flow direction algorithms.And improvements of hybrid flow direction on DEMs of 30 mis better than 90 mdatasets.
引文
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[22]张尧,樊红,李玉娥.一种基于等高线的地形特征线提取方法[J].测绘学报,2013,42(4):574-580.ZHANG Yao,FAN Hong,LI Yu'e.A Method of Terrain Feature Extraction Based on Contour[J].Acta Geodaetica et Cartographica Sinica,2013,42(4):574-580.
[23]刘学军,晋蓓,王彦芳.DEM流径算法的相似性分析[J].地理研究,2008,27(6):1347-1357.LIU Xuejun,JIN Bei,WANG Yanfang.Similarity Analysis of Flow Route Algorithms for Extracting Drainage Network from Grid-based Terrain Model[J].Geographical Research,2008,27(6):1347-1357.
[24]JENSON S K,DOMINGUE J O.Extracting Topographic Structure from Digital Elevation Data for Geographic Information System Analysis[J].Photogrammetric Engineering and Remote Sensing,1988,54(11):1593-1600.
[25]李辉,陈晓玲,张利华,等.基于三方向搜索的DEM中洼地处理方法[J].水科学进展,2009,20(4):473-479.LI Hui,CHEN Xiaoling,ZHANG Lihua,et al.Depression Removal Method for Grid DEM Based on Three-direction Search[J].Advances in Water Science,2009,20(4):473-479.
[2]O'CALLAGHAN J F,MARK D M.The Extraction of Drainage Networks from Digital Elevation Data[J].Computer Vision,Graphics,and Image Processing,1984,28(3):323-344.
[3]FAIRFIELD J,LEYMARIE P.Drainage Networks from Grid Digital Elevation Models[J].Water Resources Research,1991,27(5):709-717.
[4]PAIK K.Global Search Algorithm for Nondispersive Flow Path Extraction[J].Journal of Geophysical Research:Earth Surface,2008,113(F4):F04001.
[5]SHIN S,PAIK K.An Improved Method for Single Flow Direction Calculation in Grid Digital Elevation Models[J].Hydrological Processes,2017,31(8):1650-1661.
[6]ZHOU Qiming,PILESJP,CHEN Yumin.Estimating Surface Flow Paths on a Digital Elevation Model Using a Triangular Facet Network[J].Water Resources Research,2011,47(7):W07522.
[7]FREEMAN T G.Calculating Catchment Area with Divergent Flow Based on a Regular Grid[J].Computers&Geosciences,1991,17(3):413-422.
[8]QUINN P,BEVEN K,CHEVALLIER P,et al.The Prediction of Hillslope Flow Paths for Distributed Hydrological Modelling Using Digital Terrain Models[J].Hydrological Processes,1991,5(1):59-79.
[9]QUINN P F,BEVEN K J,LAMB R.The in(a/tan/β)Index:How to Calculate It and How to Use It within the Topmodel Framework[J].Hydrological Processes,1995,9(2):161-182.
[10]PILESJP,ZHOU Qiming,HARRIE L.Estimating Flow Distribution over Digital Elevation Models Using a Formbased Algorithm[J].Geographic Information Sciences:A Journal of the Association of Chinese Professionals in Geographic Information Systems,1998,4(1-2):44-51.
[11]秦承志,李宝林,朱阿兴,等.水流分配策略随下坡坡度变化的多流向算法[J].水科学进展,2006,17(4):450-456.QIN Chengzhi,LI Baolin,ZHU Axing,et al.Multiple Flow Direction Algorithm with Flow Partition Scheme Based on Downslope Gradient[J].Advances in Water Science,2006,17(4):450-456.
[12]GALLANT J C,WILSON J P.Primary Topographic Attributes[M]∥WILSON J P,GALLANT J C.Terrain Analysis:Principles and Applications.New York:John Wiley&Sons,2000:51-85.
[13]张占阳,郑红梅,郭新成,等.局部曲面正切曲率与流线曲率的水流路径算法[J].测绘科学,2013,38(2):122-124.ZHANG Zhanyang,ZHENG Hongmei,GUO Xincheng,et al.Flow Paths Algorithm Based on Tangential Curvature and Flow-path Curvature of Partial Surface[J].Science of Surveying and Mapping,2013,38(2):122-124.
[14]XIONG Liyang,TANG Guoan,YAN Shijiang,et al.Landformoriented Flow-routing Algorithm for the Dual-structure Loess Terrain Based on Digital Elevation Models[J].Hydrological Processes,2014,28(4):1756-1766.
[15]JOHNSTON E G,ROSENFELD A.Digital Detection of Pits,Peaks,Ridges,and Ravines[J].IEEE Transactions on Systems,Man,and Cybernetics,1975,SMC-5(4):472-480.
[16]LINDSAY J B.Sensitivity of Channel Mapping Techniques to Uncertainty in Digital Elevation Data[J].International Journal of Geographical Information Science,2006,20(6):669-692.
[17]JASIEWICZ J,STEPINSKI T F.Geomorphons—A Pattern Recognition Approach to Classification and Mapping of Landforms[J].Geomorphology,2013,182:147-156.
[18]BURROUGH P A,VAN GAANS P F M,MACMILLAN R A.High-resolution Landform Classification Using Fuzzy Kmeans[J].Fuzzy Sets and Systems,2000,113(1):37-52.
[19]DRGUL,BLASCHKE T.Automated Classification of Landform Elements Using Object-based Image Analysis[J].Geomorphology,2006,81(3-4):330-344.
[20]DRGUL,MINR J,CSILLIK O,et al.Land-surface Segmentation to Delineate Elementary Forms from Digital Elevation Models[C]∥Proceedings of Geomorphometry2013.Nanjing:[s.n.],2013:61-64.
[21]闾国年,钱亚东,陈钟明.基于栅格数字高程模型自动提取黄土地貌沟沿线技术研究[J].地理科学,1998,18(6):567-573.LU Guonian,QIAN Yadong,CHEN Zhongming.Study of Automated Extraction of Shoulder Line of Valley from Grid Digital Elevation Data[J].Scientia Geographica Sinica,1998,18(6):567-573.
[22]张尧,樊红,李玉娥.一种基于等高线的地形特征线提取方法[J].测绘学报,2013,42(4):574-580.ZHANG Yao,FAN Hong,LI Yu'e.A Method of Terrain Feature Extraction Based on Contour[J].Acta Geodaetica et Cartographica Sinica,2013,42(4):574-580.
[23]刘学军,晋蓓,王彦芳.DEM流径算法的相似性分析[J].地理研究,2008,27(6):1347-1357.LIU Xuejun,JIN Bei,WANG Yanfang.Similarity Analysis of Flow Route Algorithms for Extracting Drainage Network from Grid-based Terrain Model[J].Geographical Research,2008,27(6):1347-1357.
[24]JENSON S K,DOMINGUE J O.Extracting Topographic Structure from Digital Elevation Data for Geographic Information System Analysis[J].Photogrammetric Engineering and Remote Sensing,1988,54(11):1593-1600.
[25]李辉,陈晓玲,张利华,等.基于三方向搜索的DEM中洼地处理方法[J].水科学进展,2009,20(4):473-479.LI Hui,CHEN Xiaoling,ZHANG Lihua,et al.Depression Removal Method for Grid DEM Based on Three-direction Search[J].Advances in Water Science,2009,20(4):473-479.