Advertisement

An Automatic Method for Drainage Basin Spatial Range Delineation Using DEMs

  • Xinming Li
  • Ding Li
  • Chengzhi Qin
  • A.-Xing Zhu
  • Lin YangEmail author
Conference paper
  • 28 Downloads
Part of the Environmental Science and Engineering book series (ESE)

Abstract

Basin spatial range data is widely used in hydrological, ecological and environmental fields, and is an important basic geographic data. At present, it is not very convenient to obtain the spatial data of the basin. The generation of spatial range of river basin needs some professional knowledge. The process is not highly automated. With the development of intelligent geoscience calculation and the emergence of more application requirements, it is of great significance to realize the intelligent retrieval of basin spatial data. In this paper, the method of automatic watershed spatial range determination is proposed. The method modifies the related steps manually operated now in the existing watershed algorithm. A set of automatic processing flow is designed, according to vector data, DEM data is automatically cut and drainage outlet position is automatically determined. The automatic generation of basin range data from vector data is realized, which overcomes the previous cumbersome shortage of spatial range data acquisition.

Keywords

River basin Automatic conversion Spatial range 

Notes

Acknowledgements

This study is supported by the National Natural Science Foundation of China (Project No. 41971054; 41471178; 41530749)

References

  1. Huang Y, Vardossy A (2014) Improving the transferability of hydrological model parameters under changing conditions. In: EGU general assembly conferenceGoogle Scholar
  2. Jenson K, Dominique FO (1988) Extracting topographic structure from digital elevation data for geographical information system analysis. Photogram Eng Remote Sens 54(11):1593–1600Google Scholar
  3. Jing L, Zheng Z, Jiangang Z, Xiangyu M (2009) Hydrological feature extraction of Taihu Lake basin based on DEM. Environ Sci Manag 34(05):138–142Google Scholar
  4. Matsuura T, Aniya M (2012) Automated segmentation of hillslope profiles across ridges and valleys using a digital elevation model. Geomorphology 177–178:167–177CrossRefGoogle Scholar
  5. O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Comput Vis Graph Image Process 28:323–344CrossRefGoogle Scholar
  6. Pelletier JD (2013) A robust, two-parameter method for the extraction of drainage networks from high-resolution digital elevation models (DEMs): evaluation using synthetic and real-world DEMs. Water Resour Res 49(1):75–89CrossRefGoogle Scholar
  7. Tribe AS (1992) Automated recognition of valley lines and drainage networks from grid digital elevation models: a review and a new method. J Hydrol 139(1–4):263–293CrossRefGoogle Scholar
  8. Xiaomeng S, Jianyun Z, Chesheng Z, Jiufu L (2013) Research progress of digital watershed feature extraction based on DEM. Prog Geogr Sci 32(01):31–40Google Scholar
  9. Yang D, Koike T, Tanizawa H (2004) Application of a distributed hydrological model and weather radar observations for flood management in the upper Tone River of Japan. Journal 18(16):3119–3132Google Scholar
  10. Yoeli P (1984) Computer-assisted determination of the valley and ridge lines of digital terrain models. Int Yearb Cartogr 24:197–205Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Xinming Li
    • 1
    • 2
  • Ding Li
    • 1
    • 2
  • Chengzhi Qin
    • 1
    • 2
  • A.-Xing Zhu
    • 1
    • 3
  • Lin Yang
    • 4
    Email author
  1. 1.State Key Laboratory of Resources and Environmental Information SystemInstitute of Geographical Sciences and Natural Resources Research, CASBeijingChina
  2. 2.College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
  3. 3.Key Laboratory of Virtual Geographic Environment, Ministry of EducationNanjing Normal UniversityNanjingChina
  4. 4.School of Geography and Ocean ScienceNanjing UniversityNanjingChina

Personalised recommendations