一种采用SRTM DEM重构河床数字地形的方法

doi:10.12082/dqxxkx.2021.190811

地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (3): 385-394.doi: 10.12082/dqxxkx.2021.190811

• 地球信息科学理论与方法 • 上一篇下一篇

一种采用SRTM DEM重构河床数字地形的方法

孔乔¹(), 韩露²^,³, 刘兴坡¹^,³^,⁴, 丁永生¹^,⁴^,^*(), 王一帆¹

1.上海海事大学海洋科学与工程学院,上海 201306
2.上海河口海岸科学研究中心,上海 201201
3.河口海岸交通行业重点实验室,上海, 201201
4.上海海事大学持久性有毒物质国际联合研究中心,上海 201306

收稿日期:2019-12-29 修回日期:2020-03-22 出版日期:2021-03-25 发布日期:2021-05-25
通讯作者: 丁永生 E-mail:qiao199571218@163.com;ysding@shmtu.edu.cn
作者简介:孔乔（1995- ）,男,山东曲阜人,硕士生,主要从事水文水资源研究。E-mail: qiao199571218@163.com
基金资助:
2018年河口海岸交通行业重点实验室开放课题(KLECE201802)

Methodology of Digital Riverbed Reconstruction based on SRTM DEM Data

KONG Qiao¹(), HAN Lu²^,³, Liu Xingpo¹^,³^,⁴, DING Yongsheng¹^,⁴^,^*(), WANG Yifan¹

1. College of Ocean Science & Engineering, Shanghai Maritime University, Shanghai 201306, China
2. Estuarine & Coastal Science Research Center, Shanghai 201201, China
3. Key Laboratory of Estuarine & Coastal Project, Ministry of Transport, Shanghai 201201, China
4. International Joint Research Center for Persistent Toxic Substance(IJRC-PTS), Shanghai Maritime University, Shanghai 201306, China

Received:2019-12-29 Revised:2020-03-22 Online:2021-03-25 Published:2021-05-25
Contact: DING Yongsheng E-mail:qiao199571218@163.com;ysding@shmtu.edu.cn
Supported by:
2018 Open Project of Key Laboratory of Estuarine & Coastal Transportation Industry(KLECE201802)

摘要/Abstract

摘要：

数字高程模型（DEM）包含的信息常作为重要的水文水动力研究基础数据,但是由于公共源DEM数据精度不能完整表达河床地形,所以无法应用于河流泛洪分析等研究工作。因此,本研究开展了基于DEM数据构建数字河床的工作,首先对提取的纵向河网高程数据引入了强局部加权回归算法进行平滑处理以消除畸点;然后以河面要素文件为掩膜,采用反距离加权方法进行横向的空间插值得到3D数字化河面;最后结合河面高程与河深数据完成河床的整体构建。本研究以SRTM DEM为数据地形基础,以位于我国吉林省永吉县境内的温德河为研究实例,对其下游局部区域内的河段重构了矩形、梯形和V型 3种河床断面数字地形。为评价重构数据的合理性,分别对所得到的数字河面进行等值线分析;对河床构建前后DEM水文分析提取的河网进行河道偏移量计算;对构建的地形数据进行河流水动力模拟应用分析,结果表明：① 应用反距离加权插值可以很好地实现河网高程向河面高程的横向延展;② 基于河床重构DEM数据的水文分析误差得到了很好地消除;③ 本研究的重构数据在河流分析中具有较好地应用性和可靠性。

关键词: DEM, 河床, 平滑, 重构, 插值, 水文分析, 河流分析

Abstract:

Digital Elevation Model (DEM) plays an important role in hydrodynamic researches as an essential data. The resolution of DEM data from public sources is usually not able to depict the riverbed topography. Hence, they cannot be applied to the research work such as river flood analysis. This study carries out the work of digital riverbed construction based on DEM data. Firstly, the longitudinal river network elevation derived from a DEM is smoothed by introducing robust locally weighted regression algorithm to eliminate the abnormal elevation values. Secondly, the cross-sectional interpolation based on the inverse distance weighted method is carried out with the river surface polygon as the mask to acquire the 3D digital river surface. Finally, the overall construction of the riverbed is completed by combining the river surface elevation and river depth data. Based on SRTM DEM, this study took Wende River in Yongji County of Jilin Province as a research example, and constructed three types of digital terrain of riverbed section, i.e., rectangular, trapezoid, and V-shaped, respectively. In order to evaluate the rationality of the data reconstruction, the contour analysis was performed on the obtained digital river surface, and the channel offset of river network extracted from DEM hydrological analyses before and after riverbed reconstruction was also calculated. We finally analyzed the river hydraulic simulation results. Our results show that: (1) the application of inverse distance weighted interpolation can well complete the two-dimensional extension of river network elevation to river surface elevation; (2) the error of hydrological analysis based on reconstructed DEM of riverbed topography was well eliminated; and (3) the reconstruction data in this paper had good applicability and reliability.

Key words: DEM, riverbed, smoothing, reconstruction, interpolation, hydrological analysis, river analysis

孔乔, 韩露, 刘兴坡, 丁永生, 王一帆. 一种采用SRTM DEM重构河床数字地形的方法[J]. 地球信息科学学报, 2021, 23(3): 385-394.DOI:10.12082/dqxxkx.2021.190811

KONG Qiao, HAN Lu, Liu Xingpo, DING Yongsheng, WANG Yifan. Methodology of Digital Riverbed Reconstruction based on SRTM DEM Data[J]. Journal of Geo-information Science, 2021, 23(3): 385-394.DOI:10.12082/dqxxkx.2021.190811

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数据名称	数据来源	数据格式	投影系统	坐标系
SRTM1 DEM	美国地质调查局（https:// www.usgs.gov/）	GeoTIFF	Universal Transverse Mercator projecting（UTM, Zone 52N）	World Geodetic System 1984（WGS84）
河面矢量数据	国家地理信息公共服务平台天地图（https://www.tianditu.gov.cn/）	Shape
河网矢量数据	OSM开放数据源（https://www.openstreetmap.org/）	Shape

特征点编码	原始DEM	矩形河床融合DEM	梯形河床融合DEM	V形河床融合DEM
1	80.90	16.11	0.31	0.26
2	35.97	5.66	0.06	0.16
3	30.30	4.73	2.16	0.15
4	47.31	1.88	1.17	0.02
5	68.61	6.83	0.09	0.38
6	516.65	32.81	9.93	1.36
7	277.69	33.90	22.78	20.89
8	12.13	26.58	12.38	12.10
9	52.96	31.92	21.87	24.16
10	278.79	28.97	16.15	0.00
平均偏移量	140.13	18.94	8.69	5.95
总体方差	24 404.66	156.74	76.05	81.49
总体标准差	156.22	12.52	8.72	9.03

点位编码	A	B	C	D	E
坐标	（126°29′57″E,43°40′29″N）	（126°29′21″E,43°39′56″N）	（126°27′58″E,43°38′33″N）	（126°27′39″E,43°39′16″N）	（126°30′13″E,43°39′32″N）
水深/m	2.07	2.39	3.07	1.98	0.54
水面高程/m	215.04	218.22	225.31	223.84	223.73
流速/m.s^-1	1.83	1.55	0.59	1.02	0.52

一种采用SRTM DEM重构河床数字地形的方法

Methodology of Digital Riverbed Reconstruction based on SRTM DEM Data

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