栅格流向算法在山丘区水系提取中的应用评价
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摘要
流向算法对于流域特征提取和分布式水文模型研究起着关键作用。选取3个研究区(夺底沟、姜湾、杜家湾研究区),使用30 m分辨率DEM数据,从集水面积灰度图、集水面积累积频率分布、相对差系数、实际效果以及运行时间5方面对目前常用的6种流向算法(D8、D8-LTD、rwflood、MFD、Dinf和MDinf)进行的对比分析结果显示,不同算法之间的相似性存在着较大差异;多流向算法还原河道的准确性优于单流向算法,rwflood算法准确性最差;不同流向算法运行时间差距明显,流向算法的选取应综合考虑精度与速率需求。
The flow direction algorithm plays a key role in watershed feature extraction and distributed hydrological model research. Three research areas( Dingdigou, Jiangwan and Dujiawan research area) are selected, and six flow direction algorithms( D8, D8-LTD, rwflood, MFD, Dinf and MDinf) are compared and analyzed from five aspects of water collection area gray map, catchment area cumulative frequency distribution, relative difference coefficient, actual effect and running time by using 30 m-resolution DEM data. The results show that,( a) the similarity between different algorithms is quite different;( b) the accuracy of multi-flow algorithm for reducing river is better than that of single-flow algorithm, and the accuracy of rwflood algorithm is the worst; and( c) the running time difference of different flow algorithms is obvious. The selection of flow direction algorithm should take into account the requirements on accuracy and running rate.
The flow direction algorithm plays a key role in watershed feature extraction and distributed hydrological model research. Three research areas( Dingdigou, Jiangwan and Dujiawan research area) are selected, and six flow direction algorithms( D8, D8-LTD, rwflood, MFD, Dinf and MDinf) are compared and analyzed from five aspects of water collection area gray map, catchment area cumulative frequency distribution, relative difference coefficient, actual effect and running time by using 30 m-resolution DEM data. The results show that,( a) the similarity between different algorithms is quite different;( b) the accuracy of multi-flow algorithm for reducing river is better than that of single-flow algorithm, and the accuracy of rwflood algorithm is the worst; and( c) the running time difference of different flow algorithms is obvious. The selection of flow direction algorithm should take into account the requirements on accuracy and running rate.
引文
[1] ORLANDINI S, MORETTI G. Determination of surface flow paths from gridded elevation data[J]. Water Resources Research,2009,45(3):150-164.
[2] JULIEN P Y, SAGHAFIAN B, OGDEN F L. Raster-based hydrologic modeling of spatially-varied surface runoff[J]. Journal of the American Water Resources Association,1995,31(3):523-536.
[3] HAN X L, LIU J T, MITRA S, et al. Selection of optimal scales for soil depth prediction on headwater hillslopes:A modeling approach[J]. Catena,2018(163):257-275.
[4] TUCKER G E, LANCASTER S T, GASPARINI N M, et al. An object-oriented framework for distributed hydrologic and geomorphic modeling using triangulated irregular networks[J]. Computers&Geosciences,2001,27(8):959-973.
[5] HOOSHYAR M, WANG D B, KIM S, et al. Valley and channel networks extraction based on local topographic curvature and k-means clustering of contours[J]. Water Resources Research,2016,52(10):8081-8102.
[6] YAN Y Z, TANG J, PILESJP. A combined algorithm for automated drainage network extraction from Digital Elevation Models[J]. Hydrological Processes,2018,32(10):1322-1333.
[7] 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.
[8]何灿灿,徐翠玲,宋敦江.基于Arcpy自动提取清涧河流域水系特征[J].水力发电,2017,43(3):30-33.
[9]张维,杨昕,汤国安,等.基于DEM的平缓地区水系提取和流域分割的流向算法分析[J].测绘科学,2012,37(2):94-96.
[10] O'CALLAGHAN J F, MARK D M. The extraction of drainage networks from digital elevation data[J]. Computer Vision Graphics&Image Processing,1984,28(3):323-344.
[11] ORLANDINI S, MORETTI G, FRANCHINI M, et al. Path-based methods for the determination of nondispersive drainage directions in grid-based digital elevation models[J]. Water Resources Research,2003,39(6):1144.
[12] MAGALHES S V, ANDRADE M V, FRANKLIN R W, et al. A linear time algorithm to compute the drainage network on grid terrains[J]. Journal of Hydroinformatics,2014,16(6):1227-1234.
[13] 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.
[14] TARBOTON D G. A new method for the determination of flow directions and upslope areas in grid digital elevation models[J]. Water Resources Research,1997,33(2):662-670.
[15] SEIBERT J, MCGLYNN B L. A new triangular multiple flow direction algorithm for computing upslope areas from gridded digital elevation models[J]. Water Resources Research, 2007, 43(4):306-320.
[16]李宗梅,魏锦旺,满旺,等.基于D8算法和Dinf算法的水系提取研究[J].水资源与水工程学报,2016,27(5):42-45.
[17]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(6):125-135.
[18] LIU Yonghe, ZHANG Wanchang, XU Jingwen. Another fast and simple DEM depression-filling algorithm based on priority queue structure[J]. Atmospheric&Oceanic Science Letters,2009,2(4):214-219.
[19] SU Cheng, YU Weibin, FENG Cunjun, et al. An efficient algorithm for calculating drainage accumulation in digital elevation models based on the basin tree index[J]. IEEE Geoscience and Remote Sensing Letters,2015,12(2):424-428.
[2] JULIEN P Y, SAGHAFIAN B, OGDEN F L. Raster-based hydrologic modeling of spatially-varied surface runoff[J]. Journal of the American Water Resources Association,1995,31(3):523-536.
[3] HAN X L, LIU J T, MITRA S, et al. Selection of optimal scales for soil depth prediction on headwater hillslopes:A modeling approach[J]. Catena,2018(163):257-275.
[4] TUCKER G E, LANCASTER S T, GASPARINI N M, et al. An object-oriented framework for distributed hydrologic and geomorphic modeling using triangulated irregular networks[J]. Computers&Geosciences,2001,27(8):959-973.
[5] HOOSHYAR M, WANG D B, KIM S, et al. Valley and channel networks extraction based on local topographic curvature and k-means clustering of contours[J]. Water Resources Research,2016,52(10):8081-8102.
[6] YAN Y Z, TANG J, PILESJP. A combined algorithm for automated drainage network extraction from Digital Elevation Models[J]. Hydrological Processes,2018,32(10):1322-1333.
[7] 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.
[8]何灿灿,徐翠玲,宋敦江.基于Arcpy自动提取清涧河流域水系特征[J].水力发电,2017,43(3):30-33.
[9]张维,杨昕,汤国安,等.基于DEM的平缓地区水系提取和流域分割的流向算法分析[J].测绘科学,2012,37(2):94-96.
[10] O'CALLAGHAN J F, MARK D M. The extraction of drainage networks from digital elevation data[J]. Computer Vision Graphics&Image Processing,1984,28(3):323-344.
[11] ORLANDINI S, MORETTI G, FRANCHINI M, et al. Path-based methods for the determination of nondispersive drainage directions in grid-based digital elevation models[J]. Water Resources Research,2003,39(6):1144.
[12] MAGALHES S V, ANDRADE M V, FRANKLIN R W, et al. A linear time algorithm to compute the drainage network on grid terrains[J]. Journal of Hydroinformatics,2014,16(6):1227-1234.
[13] 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.
[14] TARBOTON D G. A new method for the determination of flow directions and upslope areas in grid digital elevation models[J]. Water Resources Research,1997,33(2):662-670.
[15] SEIBERT J, MCGLYNN B L. A new triangular multiple flow direction algorithm for computing upslope areas from gridded digital elevation models[J]. Water Resources Research, 2007, 43(4):306-320.
[16]李宗梅,魏锦旺,满旺,等.基于D8算法和Dinf算法的水系提取研究[J].水资源与水工程学报,2016,27(5):42-45.
[17]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(6):125-135.
[18] LIU Yonghe, ZHANG Wanchang, XU Jingwen. Another fast and simple DEM depression-filling algorithm based on priority queue structure[J]. Atmospheric&Oceanic Science Letters,2009,2(4):214-219.
[19] SU Cheng, YU Weibin, FENG Cunjun, et al. An efficient algorithm for calculating drainage accumulation in digital elevation models based on the basin tree index[J]. IEEE Geoscience and Remote Sensing Letters,2015,12(2):424-428.
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