Volume 9, Issue 18 (1-2019)                   jwmr 2019, 9(18): 260-270 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Komaki C B, Ahmadi H, Mombeni M, Ahmad Yousefi S, Mostafavi N. (2019). Comparison of Automatic Extraction of Sediment Delivery of Watershed and Traditional Method in Geographic Information System (Case Study: Yekechenar Watershed –Golestan Province) . jwmr. 9(18), 260-270. doi:10.29252/jwmr.9.18.260
URL: http://jwmr.sanru.ac.ir/article-1-797-en.html
Gorgan University of Agricultural Sciences and Natural Resources
Abstract:   (3039 Views)

Determining the sediment delivery rate and watershed delineation is among the first stage in environmental research, especially in water erosion estimation. The determining the accurate boundary of watershed is important for the hydrological and morphologic characteristics of watersheds. The study aims to present an automatic extraction model of watershed delineation and calculate sediment delivery rate. The traditional method of determining the watershed delineation, and subsequently, calculating sediment delivery rate is performed manually that using a topographic map, the boundary of the watershed is determined and main flow length is calculated. However, nowadays due to the advancement of digital analytical spatial-based methods in GIS software, automatic delineation of watershed is feasible. For this purpose, the errors of digital elevation model are removed. After calculating the flow direction, and flow accumulation, watershed boundaries can be determined having pourpoints. Then, sediment delivery rate is calculated by local height of watershed, its perimeter, and flow length. In this research, the digital elevation models of ASTER-DEM and SRTM-DEM are utilized to design watershed delineation model and to evaluate the overall accuracy and the correspondence of them, so the border of watershed is delineated using Google map, which is used as a ground truth. The findings of this study show the automatic extraction of watershed boundary and calculation of sediment delivery rate do not have significant differences with traditional mothed. So that, the overall accuracy and Kappa index of the watershed boundary based on ASTER-DEM are 93 percent and 0.92, respectively, and their values for the watershed boundary based on SRTM-DEM are 94.3 percent and 0.94, respectively. The correlation coefficient (r2) of calculated sediment delivery rate based on SRTM-DEM is 0.98 and its value based on ASTER-DEM is 0.95.
 

Full-Text [PDF 1198 kb]   (842 Downloads)    
Type of Study: Research | Subject: Special
Received: 2017/04/25 | Revised: 2019/01/21 | Accepted: 2017/06/12 | Published: 2019/01/21

References
1. Afsari, R. and J. Ghodousi. 2011. The Assessment of various methods of sediment delivery rate (SDR) in different climatic conditions (case study: watersheds of Markazi Province, Iran). Natural Geography, 4(12): 107-18 (In Persian).
2. Ahmadi, H., A. Das, M. Pourtaheri, C.B. Komaki and H. Khairy. 2014. Redefining the watershed line and stream networks via digital resources and topographic map using GIS and remote sensing (case study: the Neka River Watershed). Natural Hazards, 72(2): 711-722. [DOI:10.1007/s11069-014-1031-9]
3. Alavipanah, S. K. and C.B. Komaki. 2007. The study of spectral separability information classes of lut desert using satellite data. Geography Researches, 38(3): 13-28 (In Persian).
4. Bera, A.K., V. Singh, N. Bankar, S. S. Salunkhe and J.R. Sharma. 2013. Watershed delineation in Flat Terrain of Thar Desert Region in North West India - a semi-automated approach using DEM. Journal of the Indian Society of Remote Sensing, 41(1): 187-199. [DOI:10.1007/s12524-013-0308-x]
5. Chang, C.L. 2009. The impact of watershed delineation on hydrology and water quality simulation. Environmental Monitoring and Assessment, 148(1-4): 159-65. [DOI:10.1007/s10661-007-0147-8]
6. De Rosa, P., C. Cencetti and A. Fredduzzi. 2016. A GRASS Tool for the Sediment Delivery Ratio Mapping. PeerJ Preprints 4, https://doi.org/10.7287/peerj.preprints.2227v2 [DOI:10.7287/peerj.preprints.2227v2.]
7. DeMers, Michael N. 2009. GIS for Dummies. Hoboken, NJ: Wiley. 348 pp.
8. Gopinath, G., T.V. Swetha and M.K. Ashitha. 2014. Automated extraction of watershed boundary and drainage network from SRTM and comparison with survey of India Toposheet. Arabian Journal of Geosciences, 7(7): 2625-2632. [DOI:10.1007/s12517-013-0919-0]
9. Haralick, R.M. and G.L. Kelly. 1969. Pattern recognition with measurement space and spatial clustering for multiple images. Proceedings of the IEEE, 57(4): 654-65. [DOI:10.1109/PROC.1969.7020]
10. Khosravi, K., A. Safari. M. Habibnejad Roshan and N. Mahmoudi. 2012. Evaluation of soil erosion and sediment yield estimation various empirical model by observation values (Case Study: Babolroud Watershed, Mazandaran Province). Environmental Erosion Researches, 1(4): 33-53 (In Persian).
11. Lockhart, J.J. 1991. A comparison of manual and automated methods for delimiting watersheds for use with GRASS/GIS software. DTIC Document. USACERL Technical Report N-91/34. 1-31pp. US US Army Corps of Engineers, Construction Engineering Research Laboratory.
12. Nasri, M. and A. Najafi. 2015. Determining of mathematical relationships sediment delivery rate and watershed factors. Natural Ecosystems of Iran, 6(2): 1-12 (In Persian).
13. O'Banion, R., I. Alameddine, A. Gronewold and K. Reckhow. 2008. PyLIDEM: A Python-Based Tool to Delineate Coastal Watersheds Using LIDAR Data. AGU Fall Meeting Abstracts 1 (December): San Francisco, CA.
14. O'Callaghan, J.F. and D.M. Mark. 1984. The extraction of drainage networks from digital elevation data. Computer Vision, Graphics, and Image Processing, 28(3): 323-344. [DOI:10.1016/S0734-189X(84)80011-0]
15. Pratt, W.K. 2007. Digital Image Processing PIKS Scientific Inside. 4th ed. Hoboken, NJ: Wiley. 812 pp. Wiley-Interscience. Hoboken, N.J.
16. Pryde, J.K., J. Osorio, M.L. Wolfe, C. Heatwole, B. Benham and A. Cardenas. 2016. Comparison of watershed boundaries derived from SRTM and ASTER digital elevation datasets and from a digitized topographic map. 1-10 pp. An ASABE Meeting Presentation, Minnesota, USA.
17. Rahman, M.M., D.S. Arya and N.K. Goel. 2010. Limitation of 90 m SRTM DEM in drainage network delineation using D8 Method-a case study in Flat Terrain of Bangladesh. Applied Geomatics, 2(2): 49-58. [DOI:10.1007/s12518-010-0020-2]
18. Rostami, N. 2009. Selection of Best Model of SDR estimation in Illam dam. M.Sc. Thesis, Keraj: Tehran University (In Persian).
19. Vigiak, O., L. Borselli, L.T.H. Newham, J. McInnes and A.M. Roberts. 2012. Comparison of conceptual landscape metrics to define hillslope-scale sediment delivery ratio. Geomorphology, 138(1): 74-88. [DOI:10.1016/j.geomorph.2011.08.026]
20. Wang, Yu-Hsiang. 2010. Tutorial: Image Segmentation. National Taiwan University, Taipei, 1-36.
21. Zhou, W. and W.U. Bingfang. 2008. Assessment of soil erosion and sediment delivery ratio using remote sensing and GIS: A case study of Upstream Chaobaihe River Catchment, North China. International Journal of Sediment Research, 23(2): 167-73. [DOI:10.1016/S1001-6279(08)60016-5]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Watershed Management Research

Designed & Developed by : Yektaweb