Effect of DEM data resolution on low relief region sub-watershed boundaries delineating using of SWAT model and DEM derived from CARTOSAT-1 (IRS-P5), SRTM and ASTER
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Abstract
Watersheds are natural integrators of hydrological, biological, and geological processes and as such require an integrated approach to data analysis and modeling, which usually starts delineating accurately a polygon vector layer of watershed boundaries as input. In that way, Garrah sub-watershed in Shahjahanpur district of U.P., India, had been isolated with the objective of evaluate the accuracy of sub-watershed boundaries derived from three different sources: One was delineated by 2.6 m resolution CARTOSAT-1 DEM (IRS-P5) and other two were derived from a 30 m ASTER DEM and a 90 m SRTM DEM, using the Soil and Water Assessment Tool (SWAT) model. In this analysis we found that the accuracy of CARTOSAT-1 DEM is so best for accurate delineation of a sub-watershed in the management of the watershed, and the coarse spatial resolution SRTM DEM (90 m) performed much better and significantly than the high spatial resolution ASTER DEM (30 m) it’s cause of the errors in the ASTER DEM, map algebra was used to define where the “Fill” tool had filled the sinks finding that the errors in the stream network occurred where some especially large fills had occurred. Not only the visual interpretation of the produces figures indicate the SRTM DEM delineated sub-watershed as relatively more accurate from ASTER DEM delineated sub-watershed boundaries, also statistics for the SRTM DEM elevation turned in significantly higher than that of the ASTER DEM. Overall SRTM DEMs offer more precise elevations while, ASTER DEMs offer more details. Therefore, the accuracy of the sub-watershed delineation depends on the first place on the accuracy of the DEM.
Article Details
Article Details
ASTER, CARTOSAT-1, DEM, GIS, SRTM and SWAT
Arnold, J.G., Williams, J.R. and Maidment, D. R. (1998). Large area hydrologic modeling and assessment part I: model development. J. of the American Water Resources Association, 34:73-89.
Baker, M.E. and Weller, D. E. (2006). Comparison of automated watershed delineations: effects on land cover areas, percentages and relationships to nutrient discharge. Photogrammetric Engineering and Remote Sensing, 72:159-168.
Bhang, K. J. and Schwartz, F.W. (2008). Limitations in the Hydrologic Applications of C-Band SRTM DEMs in Low-Relief Settings. IEEE Geoscience and Remote Sensing Letters, 5:497-501.
DeVencia, K., Walker, S. and Zhang, B. (2007). New approaches to generating and processing high resolution elevation data with imagery. ‘Proceedings of Photogrammetric week 2007, Stuttgart, Germany’, 297-308.
Rawat, K.S., Mishra, A.K. and Tripathi, V.K. (2013). Hydro-morphometrical analyses of sub-himalyan region in relation to small hydro-electric power. Arabian Journal of Geosciences. 6(8): 2889-2899.
Egels, Y. and Kasser, M. (1998). Monuments historiques levers photogrammétriques. Digital Photogrammetry, Revue Géomètre, 3:41-43.
Estrada, R.D. and Posner, J. (2001). The Watershed as an organizing principle for research and development: An evaluation of experience in the Andean Ecoregion. Mountain Research and Development, 21:123-127.
Gianinetto, M. and Fassi, F. (2008). Alidation of cartosat-1 dtm generation for the salon de provence test site. International Society of Photogrmatry and Remote Sensing, 37:1374.
Gianinetto, M. (2008). Automatic digital terrain model generation using cartosat-1 stereo images. Sensor Review, 28:299-310.
Grohmann, G., Kroenung, G. and Strebeck, J. (2006). filling SRTM voids: The delta surface fill method. Photogrammetric Engineering and Remote Sensing, 72: 213–216.
Hasan, A., Pilesjö, P. and Persson, A. (2011). The use of LiDAR as a data source for digital elevation models DEM resolution versus accuracy and estimated slope, drainage area and wetness in northern peatlands. Hydrology and Earth System Sciences, discussion paper
Hall, O., Falorni, G. and Bras, R. L. (2005). Characterization and quantification of data voids in the shuttle Radar topography mission data, IEEE Geoscience and Remote Sensing Letter, 2:177-181.
Jenson, S. K., Domingue, J. O. (1988). Extracting topographic structure from digital elevation data for geographic information system analysis. Photogrammetric Engineering and Remote Sensing, 54:593-1600.
Krishna, M.Y.V.N., Srinivasa, R.S., Prakasa, R.R.S. and Jayaraman, V. (2008). Analysis of dem generated using catosat-1 stereo data over Mausanne Les Alpiles. International Society of Photogrmatry and Remote Sensing, 37:1343-1348.
Knisel, W.G. (1980). USDA - Agricultural research service, Washington DC. Cons. Res Rpt 26:643.
Lindsay, J. B., Rothwell, J. J., Helen, D. (2008). Mapping outlet points used for watershed delineation onto DEMderived stream networks. Water Resources Research, 44:12-20.
Luedeling, E., Siebertb, S. and Buerkerta, A. (2007). Filling the voids in the SRTM elevation model-A TIN-based delta surface approach. International Society of Photogrmatry and Remote Sensing, 62:283-294.
Maidment, D. (1999). Environmental systems research institute, available online at http:/ Icampus.esri.coml courses/hydrolgy IwatShdhy.
Marks, D., Dozier, J. and Frew, J. (1984). Automated basin delineation from digital elevation data. Geo-Processing, 2:299-311.
Rabus, B., Eineder, M. and Bamler, R. (2003). The shuttle radar topography mission-a new class of digital elevation models acquired by spaceborne radar. Photogrammetry and Remote Sensing, 57:241-262.
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