DEM在湖泊水文变化研究中的应用进展

doi:10.12082/dqxxkx.2020.190538

地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (7): 1510-1521.doi: 10.12082/dqxxkx.2020.190538

• 地理空间分析综合应用 • 上一篇下一篇

DEM在湖泊水文变化研究中的应用进展

罗竹¹^,²(), 刘凯², 张春亢¹, 邓心远³, 马荣华², 宋春桥²^,^*()

1.贵州大学矿业学院,贵阳 550025;
2.中国科学院南京地理与湖泊研究所中国科学院流域地理学重点实验室,南京 210008;
3.南京信息工程大学遥感与测绘工程学院,南京 210044

收稿日期:2019-09-23 修回日期:2020-02-27 出版日期:2020-07-25 发布日期:2020-09-25
通讯作者: 宋春桥 E-mail:m15761635597_1@163.com;cqsong@niglas.ac.cn
作者简介:罗竹（1994— ）,女,贵州贵阳人,硕士生,主要从事环境遥感与数字地形分析研究。E-mail:m15761635597_1@163.com
基金资助:
中国科学院战略性先导科技专项子课题(XDA23100102);国家自然科学基金项目(41801321);国家重点研发计划重点专项课题(2018YFD1100101);国家自然科学基金项目(41701464)

Progress of the DEM Application for Studying Lake Hydrologic Dynamics

LUO Zhu¹^,²(), LIU Kai², ZHANG Chunkang¹, DENG Xinyuan³, MA Ronghua², SONG Chunqiao²^,^*()

1. Mining College, Guizhou University, Guiyang 550025, China;
2. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
3. School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China

Received:2019-09-23 Revised:2020-02-27 Online:2020-07-25 Published:2020-09-25
Contact: SONG Chunqiao E-mail:m15761635597_1@163.com;cqsong@niglas.ac.cn
Supported by:
Strategic Priority Research Program of the Chinese Academy of Sciences(XDA23100102);National natural science foundation of China(41801321);Key project of national key research and development plan(2018YFD1100101);National natural science foundation of China(41701464)

摘要/Abstract

摘要：

在全球变化背景下,湖泊水文的动态变化不仅是评估和预测气候与环境变化的重要指示剂,同时对社会可持续发展、水资源的开发与利用、生态文明建设等产生重要影响。湖泊水文的动态变化受到湖滨及湖底地形的控制,数字高程模型（DEM）成为湖泊水文研究的重要数据源。随着遥测技术的发展,高分辨率、区域/全球大尺度DEM数据的获取手段快速发展、数据源不断丰富,DEM对推动湖泊水文动态研究进展起到了关键作用。本文首先基于Web of Science平台对DEM在湖泊水文动态研究中的相关文献进行了分析,阐述了该主题现有研究在发文时间、发文数量增减态势、研究区域与热点地区、文献所涉及的DEM数据等方面的特点。接着,围绕着DEM在湖泊水文动态的研究中4个主要方向：湖泊水域变化、湖泊水位变化、湖泊水量变化、湖泊水文灾害情势,重点总结：DEM与其他遥感观测平台、实地观测及模型模拟等多源数据的融合策略,数字地形分析与水文学分析、遥感影像分析等方法的集成策略,以及DEM数据不确定性等对湖泊水文变化研究的影响。最后,本文论述了目前DEM在湖泊水文研究中存在的关键问题,并结合技术发展趋势和研究热点问题,提出了可能的解决路径和未来的研究前景。

关键词: DEM, 湖泊水文, 动态变化, 气候变化, 湖盆地形, 湖泊水域, 湖泊水位, 湖泊水量

Abstract:

：The dynamics of lake hydrology is not only an important indicator for assessing and predicting climate change, but also poses important impacts on the sustainable development of regional society, the utilization of water resources, and the construction of ecological civilization. The changes of lakes are controlled by the topography of lakeside and underwater bathymetry. Hence, the topographic information is essential to quantify the lake variations. With the development of remote sensing technology, the methods for high-resolution data acquisition at large scale have been improved largely. Currently, DEM has been widely used in the studies of lake hydrology. This study collected the related literatures based on Web of Science platform, with a quantitative analysis in terms of published time, study area and adopted datasets. Then, the research literature can be categorized in four main fields including: Lake water extent change, lake water level change, lake water volume change and lake hydrological disaster. To take full advantages of DEM, three aspects of efforts should be further paid, specifically in (1) integrating DEM with multiple other sources including remote sensing images, satellite altimetry and hydrological observations, (2) developing state-of-artdata fusion strategy by integrating digital terrain analysis and hydrological analysis, and (3) improving the performances of DEM data in resolution and accuracy for lake hydrology study. Finally, this paper discusses the key problems of DEM in lake hydrology research, and puts forward possible solutions and research prospective based on the development trend of technology and hot issues.

Key words: DEM, lake hydrology, dynamic change, climate change, lake bathymetry, lake water areas, lake water level, lake water storage

罗竹, 刘凯, 张春亢, 邓心远, 马荣华, 宋春桥. DEM在湖泊水文变化研究中的应用进展[J]. 地球信息科学学报, 2020, 22(7): 1510-1521.DOI:10.12082/dqxxkx.2020.190538

LUO Zhu, LIU Kai, ZHANG Chunkang, DENG Xinyuan, MA Ronghua, SONG Chunqiao. Progress of the DEM Application for Studying Lake Hydrologic Dynamics[J]. Journal of Geo-information Science, 2020, 22(7): 1510-1521.DOI:10.12082/dqxxkx.2020.190538

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数据名称	覆盖	获取原理	测量时间	主要数据版本	数据处理	发布机构	下载地址	发布时间	分辨率/m
SRTM DEM	56°S~60° N	SAR-C 波段	2000.02	SRTM V.1	未编辑	USGS	http://earthexplorer.usgs.gov	2003	90
				SRTM V4.1	填补空洞,对水体进行了处理	CGIAR	http://srtm.csi.cgiar.org/srtmdata/	2008	90
				SRTM V.3	采用ASTER DEMs、GMTED2010、NED作为辅助数据源填补空洞、提高分辨率和精度,对水体进行了处理	NASA、USGS	https://dwtkns.com/srtm30m/	2015	30
SRTM X-SAR DEM	56°S~60° N	SAR-X 波段	2000.02	SRTM X-SAR DEM	未编辑	DLR	https://download.geoservice.dlr.de/SRTM_XSAR/#download	2010	30
ASTER DEM	83°S~83° N	光学传感器	2000—2011	ASTER GDEM V.1	230万张影像立体测图自动化处理	METI、NASA	https://gdemdl.aster.jspacesystems.or.jp/	2009	90
			2000—2013	ASTER GDEM V.2	提高精度、分辨率及水体的准确性,减少人工误差	METI、NASA		2011	30
			2000—2013	ASTER GDEM V.3	填补空洞,使用新的全球水体数据处理水体,减少水域异常	METI、NASA		2019	30
AW3D DEM	60°S~60° N	光学传感器	2006—2011	ALOS AW3D 30 V.1.0	300万张影像立体测图自动化处理	JAXAEORC	https://www.eorc.jaxa.jp/ALOS/en/aw3d30/	2016	30
AW3D DEM	60°S~60° N	光学传感器	2006—2011	ALOS AW3D 30 V.2.2	填补空洞,对数据质量差的区域进行修补,对海岸线进行了更新	JAXAEORC	https://www.eorc.jaxa.jp/ALOS/en/aw3d30/	2019	30
TanDEM-X	全球	SAR-X 波段	2010—2015	TanDEM-X 90	未编辑	DLR	https://download.geoservice.dlr.de/TDM90	2018	90

DEM在湖泊水文变化研究中的应用进展

Progress of the DEM Application for Studying Lake Hydrologic Dynamics

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