基于数字高程模型的混合流向算法

doi:10.11947/j.AGCS.2018.20170614

测绘学报 ›› 2018, Vol. 47 ›› Issue (5): 683-691.doi: 10.11947/j.AGCS.2018.20170614

• 中国测绘地理信息学会2017年青年优秀论文 • 上一篇下一篇

基于数字高程模型的混合流向算法

夏誉玲^1,3, 李小娟^1,5, 王涛^2,4

1. 首都师范大学北京市成像技术高精尖创新中心, 北京 100094;
2. 首都师范大学地球空间信息科学与技术国际化示范学院, 北京 100048;
3. 首都师范大学资源环境与旅游学院, 北京 100048;
4. 首都师范大学三维信息获取与应用教育部重点实验室, 北京 100048;
5. 首都师范大学水资源安全北京实验室, 北京 100048

收稿日期:2017-12-20 修回日期:2018-01-31 出版日期:2018-05-20 发布日期:2018-06-01
通讯作者: 王涛 E-mail:wangt@cnu.edu.cn
作者简介:夏誉玲(1991-),女,博士生,研究方向为地理信息空间模拟。E-mail:2160901012@cnu.edu.cn
基金资助:
国家自然科学基金（41671403）；国家重点研发计划（2017YFC0406006）；北京市教委科技计划（SQKM201710028013）

A Hybrid Flow Direction Algorithm for Water Routing on DEMs

XIA Yuling^1,3, LI Xiaojuan^1,5, WANG Tao^2,4

1. Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100094, China;
2. College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China;
3. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China;
4. Key Lab of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China;
5. Water Resources Security Beijing Laboratory, Capital Normal University, Beijing 100048, China

Received:2017-12-20 Revised:2018-01-31 Online:2018-05-20 Published:2018-06-01
Supported by:
The National Natural Science Foundation of China (No.41671403);The National Key Research and Development Program of China (No.2017YFC0406006);The Science Foundation of Beijing Municipal Education Commission (No.SQKM201710028013)

摘要/Abstract

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30 m和90 m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（30 m）改进效果更加明显。

关键词: 数字高程模型, 流向, 汇水面积, 混合流向算法, 地理信息系统

Abstract: 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 m and 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 m is better than 90 m datasets.

Key words: DEM, water flow direction algorithm, total catchment area, hybrid flow direction algorithm, geographic Information System

中图分类号:

P208

夏誉玲, 李小娟, 王涛. 基于数字高程模型的混合流向算法[J]. 测绘学报, 2018, 47(5): 683-691.

XIA Yuling, LI Xiaojuan, WANG Tao. A Hybrid Flow Direction Algorithm for Water Routing on DEMs[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(5): 683-691.

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基于数字高程模型的混合流向算法

A Hybrid Flow Direction Algorithm for Water Routing on DEMs

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