Skip to main content

Comparison of different digital elevation models for drainage morphometric parameters: a case study from South India

Arabian Journal of Geosciences volume 13, Article number: 1050 (2020) Cite this article

Abstract

With a plethora of digital elevation models (DEM) available for elevation extraction and catchment morphometric analysis, it is essential to compare and investigate their accuracy and parameter uncertainty derived from them. To serve that purpose, in this study, we have compared the DEMs of different resolution obtained from Shuttle Radar Topography Mission (SRTM), CARTOSAT, and topographic maps (1:25000) in terms of vertical accuracy and morphometric parameters. The investigation was performed on a sub-basin of Champavathi River which is located in Andhra Pradesh, the southern part of India. The vertical accuracy of the DEMs was estimated using elevation from about 1180 points obtained from the Differential Global Positioning System (DGPS) survey. The morphometric analysis showed that the basin is elongated with low relief ratio, mild/rolling slopes, and medium drainage density, and the results were comparable from different DEM sources indicating that most of the morphometric parameters were not significantly dependent on the scale and source of the DEM. Further, vertical accuracy estimation showed that the CARTOSAT DEMs (10 m and 30 m) have a lower root mean square error (4.53 m and 5.89 m) when compared with the SRTM DEMs (6.11 m and 7.19 m).

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  • Abdeta GC, Tesemma AB, Tura AL, Atlabachew GH (2020) Morphometric analysis for prioritizing sub-watersheds and management planning and practices in Gidabo Basin, Southern Rift Valley of Ethiopia. Appl Water Sci 10:1–15

    Article  Google Scholar 

  • Abdulkareem JH, Pradhan B, Sulaiman WNA, Jamil NR (2018) Quantification of runoff as influenced by morphometric characteristics in a rural complex catchment. Earth Syst Environ 2:145–162

    Article  Google Scholar 

  • Agarwal KK, Prakash C, Ali SN, Jahan N (2012) Morphometric analysis of the Ladhiya and Lohawati river basins, Kumaun Lesser Himalaya, India. Z Geomorphol 56:201–224

    Article  Google Scholar 

  • Aher PD, Adinarayana J, Gorantiwar SD (2014) Quantification of morphometric characterization and prioritization for management planning in semi-arid tropics of India: a remote sensing and GIS approach. J Hydrol 511:850–860. https://doi.org/10.1016/j.jhydrol.2014.02.028

    Article  Google Scholar 

  • Ajibade L, Ifabiyi L, Iroye K, Ogunteru S (2010) Morphometric analysis of Ogunpa and Ogbere drainage basins, Ibadan, Nigeria. Ethiop J Environ Stud Manag 3:1–19. https://doi.org/10.4314/ejesm.v3i1.54392

    Article  Google Scholar 

  • Altaf F, Meraj G, Romshoo SA (2013) Morphometric analysis to infer hydrological behaviour of Lidder watershed, Western Himalaya, India. Geogr J 2013:1–14. https://doi.org/10.1155/2013/178021

    Article  Google Scholar 

  • Aouragh MH, Essahlaoui A (2018) A TOPSIS approach-based morphometric analysis for sub-watersheds prioritization of high Oum Er-Rbia basin, Morocco. Spat Inf Res 26:187–202. https://doi.org/10.1007/s41324-018-0169-z

    Article  Google Scholar 

  • Arabameri A, Pradhan B, Pourghasemi HR, Rezaei K (2018) Identification of erosion-prone areas using different multi-criteria decision-making techniques and gis. Geomatics Nat Hazards Risk 9:1129–1155. https://doi.org/10.1080/19475705.2018.1513084

    Article  Google Scholar 

  • Arabameri A, Tiefenbacher JP, Blaschke T, Pradhan B, Bui DT (2020) Morphometric analysis for soil erosion susceptibility mapping using novel gis-based ensemble model. Remote Sens 12:1–24. https://doi.org/10.3390/rs12050874

  • Bajabaa S, Masoud M, Al-Amri N (2014) Flash flood hazard mapping based on quantitative hydrology, geomorphology and GIS techniques (case study of Wadi Al Lith, Saudi Arabia). Arab J Geosci 7(6):2469–2481. https://doi.org/10.1007/s12517-013-0941-2

  • Balasubramanian A, Duraisamy K, Thirumalaisamy S, Krishnaraj S, Yatheendradasan RK (2017) Prioritization of subwatersheds based on quantitative morphometric analysis in lower Bhavani basin, Tamil Nadu, India using DEM and GIS techniques. Arab J Geosci 10:1–18. https://doi.org/10.1007/s12517-017-3312-6

  • Banerjee A, Singh P, Pratap K (2017) Morphometric evaluation of Swarnrekha watershed, Madhya Pradesh, India: an integrated GIS-based approach. Appl Water Sci 7:1807–1815. https://doi.org/10.1007/s13201-015-0354-3

    Article  Google Scholar 

  • Burrough PA, McDonnell R, McDonnell RA, Lloyd CD (2015) Principles of geographical information systems. Oxford university press

  • Caraballo-Arias NA, Conoscenti C, Di Stefano C, Ferro V (2014) Testing GIS-morphometric analysis of some Sicilian badlands. Catena 113:370–376. https://doi.org/10.1016/j.catena.2013.08.021

    Article  Google Scholar 

  • Chopra R, Dhiman RD, Sharma PK (2005) Morphometric analysis of sub-watersheds in Gurdaspur district, Punjab using remote sensing and GIS techniques. J Indian Soc Remote Sens 33:531–539. https://doi.org/10.1007/BF02990738

    Article  Google Scholar 

  • Chorley RJ (1969) Water, earth, and man. A synthesis of hydrology, geomorphology, and socio-economic geography. Water, earth, and man. A synthesis of hydrology, geomorphology, and socio-economic geography

  • Chow VT (1964) Handbook of applied hydrology

  • Cook AJ, Murray T, Luckman A, Vaughan DG (2012) A new 100-m digital elevation model of the antarctic peninsula derived from ASTER Global DEM: methods and accuracy assessment. Earth Syst Sci Data 4:129–142. https://doi.org/10.5194/essd-4-129-2012

    Article  Google Scholar 

  • Das S, Patel PP, Sengupta S (2016) Evaluation of different digital elevation models for analyzing drainage morphometric parameters in a mountainous terrain: a case study of the Supin–Upper Tons Basin, Indian Himalayas. Springerplus 5:1–38. https://doi.org/10.1186/s40064-016-3207-0

    Article  Google Scholar 

  • Dikpal RL, Renuka Prasad TJ, Satish K (2017) Evaluation of morphometric parameters derived from Cartosat-1 DEM using remote sensing and GIS techniques for Budigere Amanikere watershed, Dakshina Pinakini Basin, Karnataka, India. Appl Water Sci 7:4399–4414. https://doi.org/10.1007/s13201-017-0585-6

  • Dodov B, Foufoula-Georgiou E (2005) Fluvial processes and streamflow variability: Interplay in the scale-frequency continuum and implications for scaling. Water Resour Res 41:1–18. https://doi.org/10.1029/2004WR003408

    Article  Google Scholar 

  • Esper Angillieri MY (2008) Morphometric analysis of Colangüil river basin and flash flood hazard, San Juan, Argentina. Environ Geol 55:107–111. https://doi.org/10.1007/s00254-007-0969-2

    Article  Google Scholar 

  • Fairfield J, Leymarie P (1991) Drainage networks from grid digital elevation models. Water Resour Res 27(5):709–717. https://doi.org/10.1029/90WR02658

    Article  Google Scholar 

  • Farhan Y (2017) Morphometric assessment of Wadi Wala watershed, Southern Jordan Using ASTER (DEM) and GIS. J Geogr Inf Syst 09:158–190. https://doi.org/10.4236/jgis.2017.92011

    Article  Google Scholar 

  • Farr TG, Kobrick M (2000) Shuttle radar topography mission produces a wealth of data. EOS Trans Am Geophys Union 81:583. https://doi.org/10.1029/EO081i048p00583

    Article  Google Scholar 

  • Farr TG, Rosen PA, Caro E, Crippen R, Duren R, Hensley S, Kobrick M, Paller M, Rodriguez E, Roth L, Seal D (2007) The Shuttle Radar Topography Mission. Rev Geophys 45:2

    Article  Google Scholar 

  • Giusti EV, Schneider WJ (1965) The distribution of branches in river networks. US Government Printing Office

  • Gopinath G, Ambili GK, Gregory SJ, Anusha CK (2015) Drought risk mapping of south-western state in the Indian peninsula - a web based application. J Environ Manag 161:453–459. https://doi.org/10.1016/j.jenvman.2014.12.040

    Article  Google Scholar 

  • Gopinath G, Ramisha N, Nair AG, Jesiya NP (2018) Spatial characters of a tropical river basin, south-west coast of India. In Hydrologic modeling (pp. 641–657). Springer, Singapore. https://doi.org/10.1007/978-981-10-5801-1_44

  • Grohmann CH, Riccomini C, Alves FM (2007) SRTM-based morphotectonic analysis of the Poços de Caldas Alkaline Massif, southeastern Brazil. Comput Geosci 33:10–19. https://doi.org/10.1016/j.cageo.2006.05.002

    Article  Google Scholar 

  • Gruber A, Wessel B, Huber M, Roth A (2012) Operational TanDEM-X DEM calibration and first validation results. ISPRS J Photogramm Remote Sens 73:39–49. https://doi.org/10.1016/j.isprsjprs.2012.06.002

    Article  Google Scholar 

  • Hirt C, Filmer MS, Featherstone WE (2010) Comparison and validation of the recent freely available ASTER-GDEM ver1, SRTM ver4.1 and GEODATA DEM-9 s ver3 digital elevation models over Australia. Aust J Earth Sci 57:337–347. https://doi.org/10.1080/08120091003677553

    Article  Google Scholar 

  • Hlaing KT, Haruyama S, Aye MM (2008) Using GIS-based distributed soil loss modeling and morphometric nalysis to prioritize watershed for soil conservation in Bago river basin of Lower Myanmar. Front Earth Sci China 2:465–478. https://doi.org/10.1007/s11707-008-0048-3

    Article  Google Scholar 

  • Horton RE (1932) Drainage-basin characteristics. EOS Trans Am Geophys Union 13:350–361. https://doi.org/10.1029/TR013i001p00350

    Article  Google Scholar 

  • Horton RE (1945) Erosional development of streams and their drainage density: hydrophysical approach to quantitative geomorphology. Geol Soc Amer Bull 56:275–370

  • Hosseinzadeh SR (2011) Drainage network analysis, comparis of Digital Elevation Model (DEM) from ASTER with high resolution satellite image and areal photographs. International Journal of Environmental Science and Development 2(3):194. https://doi.org/10.7763/IJESD.2011.V2.123

  • Jacques PD, Salvador ED, Rô M, Grohmann CH, Nummer AR (2014) Application of morphometry in neotectonic studies at the eastern edge of the Paraná Basin, Santa Catarina State, Brazil. Geomorphology 213:13–23. https://doi.org/10.1016/j.geomorph.2013.12.037

    Article  Google Scholar 

  • Jain SK, Singh RD, Seth SM (2000) Design flood estimation using GIS supported GIUH approach. Water Resour Manag 14:369–376. https://doi.org/10.1023/A:1011147623014

    Article  Google Scholar 

  • Javed A, Khanday MY, Ahmed R (2009) Prioritization of sub-watersheds based on morphometric and land use analysis using Remote Sensing and GIS techniques. J Indian Soc Remote Sens 37:261–274. https://doi.org/10.1007/s12524-009-0016-8

    Article  Google Scholar 

  • Jenson SK, Domingue JO (1988) Extracting topographic structure from digital elevation data for geographic information system analysis. Photogramm Eng Remote Sens 54(11):1593–1600

    Google Scholar 

  • Jothimani M, Dawit Z, Mulualem W (2020) Flood Susceptibility modeling of Megech River Catchment, Lake Tana Basin, North Western Ethiopia, using morphometric analysis. Earth Syst Environ. https://doi.org/10.1007/s41748-020-00173-7

  • Kaplan ED, Hegarty CJ (2006) Understanding GPS: principles and applications. Artech House :379–380

  • Kannan R, Venkateswaran S, Vijay Prabhu M, Sankar K (2018) Drainage morphometric analysis of the Nagavathi watershed, Cauvery river basin in Dharmapuri district, Tamil Nadu, India using SRTM data and GIS. Data Br 19:2420–2426. https://doi.org/10.1016/j.dib.2018.07.016

  • Kasi V, Yeditha PK, Rathinasamy M, Pinninti R, Landa SR, Sangamreddi C, Agarwal A, Radha PRD (2020) A novel method to improve vertical accuracy of CARTOSAT DEM using machine learning models. Earth Sci Inf. https://doi.org/10.1007/s12145-020-00494-1

  • Korup O (2005) Geomorphic imprint of landslides on alpine river systems, southwest New Zealand. Earth Surf Process Landf 30:783–800. https://doi.org/10.1002/esp.1171

    Article  Google Scholar 

  • Lindsay JB, Evans MG (2008) The influence of elevation error on the morphometrics of channel networks extracted from DEMs and the implications for hydrological modelling. Hydrol Process 22:1588–1603. https://doi.org/10.1002/hyp.6728

    Article  Google Scholar 

  • Luo W, Harlin JM (2003) A theoretical travel time based on watershed hypsometry. J Am Water Resour Assoc 39:785–792. https://doi.org/10.1111/j.1752-1688.2003.tb04405.x

    Article  Google Scholar 

  • Maheswaran R, Khosa R, Gosain AK, Lahari S, Sinha SK, Chahar BR, Dhanya CT (2016) Regional scale groundwater modelling study for Ganga River basin. J Hydrol 541:727–741. https://doi.org/10.1016/j.jhydrol.2016.07.029

    Article  Google Scholar 

  • Masoud MH (2016) Geoinformatics application for assessing the morphometric characteristics’ effect on hydrological response at watershed (casestudy of Wadi Qanunah, Saudi Arabia). Arab J Geosci 9:1–22. https://doi.org/10.1007/s12517-015-2300-y

  • Melton MA (1957) An analysis of the relations among elements of climate, surface properties, and geomorphology, Dept. Geol. Columbia Univ. Tech. Rep. 11, Proj. NR 389–042, Off. of Nav. Res., New York

  • Mesa LM (2006) Morphometric analysis of a subtropical Andean basin (Tucumán, Argentina). Environ Geol 50:1235–1242. https://doi.org/10.1007/s00254-006-0297-y

    Article  Google Scholar 

  • Miller VC (1953) Quantitative geomorphic study of drainage basin characteristics in the Clinch Mountain area, Virginia and Tennessee. Technical report (Columbia University. Department of Geology); no. 3

  • Morisawa ME (1962) Quantitative geomorphology of some watersheds in the Appalachian Plateau. Geol Soc Am Bull 73(9):1025–1046

    Article  Google Scholar 

  • Mueller JE (1968) An introduction to the hydraulic and topographic sinuosity indexes. Ann Assoc Am Geogr 58(2):371–385

  • Mukherjee S, Joshi PK, Mukherjee S, Ghosh A, Garg RD, Mukhopadhyay A (2013) Evaluation of vertical accuracy of open source Digital Elevation Model (DEM). Int J Appl Earth Obs Geoinf 21:205–217. https://doi.org/10.1016/j.jag.2012.09.004

    Article  Google Scholar 

  • Nag SK (1998) Morphometric analysis using remote sensing techniques in the Chaka sub-basin. J Indian Soc Remote Sens 26:70–76

    Article  Google Scholar 

  • Nitheshnirmal S, Thilagaraj P, Rahaman SA, Jegankumar R (2019) Erosion risk assessment through morphometric indices for prioritisation of Arjuna watershed using ALOS-PALSAR DEM. Model Earth Syst Environ 5:907–924. https://doi.org/10.1007/s40808-019-00578-y

  • Niyazi B, Zaidi S, Masoud M (2019) Comparative study of different types of digital elevation models on the basis of drainage morphometric parameters (case study of Wadi Fatimah Basin, KSA). Earth Syst Environ 3:539–550. https://doi.org/10.1007/s41748-019-00111-2

    Article  Google Scholar 

  • NRSA (National Remote Sensing Agency), (2007) Natural resources census: national land use and land cover mapping using multi-temporal AWiFS data, project report. Publication No. NRSA/LULC/1:250 K/2007-1National Remote Sensing Agency, Hyderabad, India

  • Obi Reddy GP, Maji AK, Gajbhiye KS (2004) Drainage morphometry and its influence on landform characteristics in a basaltic terrain, Central India - a remote sensing and GIS approach. Int J Appl Earth Obs Geoinf 6:1–16. https://doi.org/10.1016/j.jag.2004.06.003

    Article  Google Scholar 

  • Olszevski N, Filho EIF, da Costa LM, Schaefer CEGR, Souza ED, Costa ODAV (2011) Morphology and hydrological aspects of black river basin, division of state of Rio de Janeiro and Minas Gerais,Morfologia e aspectos hidrológicos da bacia hidrográfica do Rio Preto, divisa dos estados do Rio de Janeiro e de Minas Gerais. Rev Arvore 35:485–492. https://doi.org/10.1590/S0100-67622011000300011

    Article  Google Scholar 

  • Ozdemir H, Bird D (2009) Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods. Environ Geol 56:1405–1415. https://doi.org/10.1007/s00254-008-1235-y

    Article  Google Scholar 

  • Pankaj A, Kumar P (2009) GIS-based morphometric analysis of five major sub-watersheds of Song River, Dehradun district, Uttarakhand with special reference to landslide incidences. J Indian Soc Remote Sens 37:157–166. https://doi.org/10.1007/s12524-009-0007-9

    Article  Google Scholar 

  • Patel A, Katiyar SK, Prasad V (2016) Performances evaluation of different open source DEM using differential global positioning system (DGPS). Egypt J Remote Sens Sp Sci 19:7–16. https://doi.org/10.1016/j.ejrs.2015.12.004

    Article  Google Scholar 

  • Prabhakaran A, Jawahar Raj N (2018) Mapping and analysis of tectonic lineaments of Pachamalai hills, Tamil Nadu, India using geospatial technology. Geol Ecol Landscapes 2:81–103. https://doi.org/10.1080/24749508.2018.1452481

    Article  Google Scholar 

  • Prabhakar AK, Singh KK, Lohani AK, Chandniha SK (2019) Study of Champua watershed for management of resources by using morphometric analysis and satellite imagery. Appl Water Sci 9:1–16. https://doi.org/10.1007/s13201-019-1003-z

  • Prakash K, Rawat D, Singh S, Chaubey K, Kanhaiya S, Mohanty T (2019) Morphometric analysis using SRTM and GIS in synergy with depiction: a case study of the Karmanasa River basin, North central India. Appl Water Sci 9:1–10. https://doi.org/10.1007/s13201-018-0887-3

  • Rahmati O, Samadi M, Shahabi H, Azareh A, Rafiei-Sardooi AH, Melesse AM, Pradhan B, Chapi K, Shirzadi A (2019) SWPT: an automated GIS-based tool for prioritization of sub-watersheds based on morphometric and topo-hydrological factors. Geosci Front 10:2167–2175. https://doi.org/10.1016/j.gsf.2019.03.009

    Article  Google Scholar 

  • Rai P K, Mishra V M, Mohan K (2017) A study of morphometric evaluation of the Son basin, India using geospatial approach. Remote Sensing Applications: Society and Environment 7:9–20

  • Rai PK, Mohan K, Mishra S, Ahmad A, Mishra VN (2017) A GIS-based approach in drainage morphometric analysis of Kanhar River Basin, India. Appl Water Sci 7:217–232. https://doi.org/10.1007/s13201-014-0238-y

    Article  Google Scholar 

  • Rather MA, Satish Kumar J, Farooq M, Rashid H (2017) Assessing the influence of watershed characteristics on soil erosion susceptibility of Jhelum basin in Kashmir Himalayas. Arab J Geosci 10:1–25. https://doi.org/10.1007/s12517-017-2847-x

  • Rawat KS, Singh SK, Singh MI, Garg BL (2019) Comparative evaluation of vertical accuracy of elevated points with ground control points from ASTERDEM and SRTMDEM with respect to CARTOSAT-1DEM. Remote Sens Appl Soc Environ 13:289–297. https://doi.org/10.1016/j.rsase.2018.11.005

  • Ray RK, Syed TH, Saha D, Sarkar BC (2020) Modeling the impact of rainfall variations and management interventions on the groundwater regime of a hard-rock terrain in central India. Hydrogeol J 28:1209–1227. https://doi.org/10.1007/s10040-020-02132-y

    Article  Google Scholar 

  • Sachindra DA, Ahmed K, Rashid MM, Shahid S, Perera BJC (2018) Statistical downscaling of precipitation using machine learning techniques. Atmos Res 212:240–258. https://doi.org/10.1016/j.atmosres.2018.05.022

    Article  Google Scholar 

  • Sangireddy H, Stark CP, Kladzyk A, Passalacqua P (2016) GeoNet: an open source software for the automatic and objective extraction of channel heads, channel network, and channel morphology from high resolution topography data. Environ Model Softw 83:58–73. https://doi.org/10.1016/j.envsoft.2016.04.026

    Article  Google Scholar 

  • Sarkar S, Gundekar HG (2007) Geomorphological parameters: are they indicators for installation of a hydropower site?. In International Conference on Small Hydropower-Hydro Sri Lanka (Vol. 22, p. 24)

  • Sarkar T, Kannaujiya S, Taloor AK, Ray PKC, Chauhan P (2020) Integrated study of GRACE data derived interannual groundwater storage variability over water stressed Indian regions. Groundw Sustain Dev 10:100376. https://doi.org/10.1016/j.gsd.2020.100376

    Article  Google Scholar 

  • Satheeshkumar S, Venkateswaran S (2018) Predilection of sustainable recharge structures using morphometric parameters and decision making model in the Vaniyar sub basin, South India. Appl Water Sci 8:1–18. https://doi.org/10.1007/s13201-018-0844-1

  • ScHUMM S (1954) Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey: Dept. Geology, Columbia Univ (No. 8, pp. 271-30). New York, Tech Rept

  • Schumm SA (1956) Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey. Bull Geol Soc Am 67(5):597–646

  • Setti S, Maheswaran R, Radha D, Sridhar V, Barik KK, Narasimham ML (2020) Attribution of hydrologic changes in a tropical river basin to rainfall variability and land-use change: case study from India. J Hydrol Eng 25:1–15. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001937

    Article  Google Scholar 

  • Shortridge A, Messina J (2011) Spatial structure and landscape associations of SRTM error. Remote Sens Environ 115:1576–1587. https://doi.org/10.1016/j.rse.2011.02.017

    Article  Google Scholar 

  • Smith KG (1950) Standards for grading texture of erosional topography. Am J Sci 248:655–668

    Article  Google Scholar 

  • Strahler AN (1952) Dynamic basis of geomorphology. Geol Soc Am Bull 63(9):923–938

    Article  Google Scholar 

  • Strahler AN (1954) Statistical analysis in geomorphic research. J Geol 62(1):1–25

    Article  Google Scholar 

  • Strahler AN (1956) Quantitative slope analysis. Geol Soc Am Bull 67(5):571–596

    Article  Google Scholar 

  • Strahler AN (1957) Quantitative Analysis of watershed geomorphology, transactions of the American Geophysical Union. Trans Am Geophys Union 38:913–920

    Article  Google Scholar 

  • Strahler AN (1958) Dimensional analysis applied to fluvially eroded landforms. Geol Soc Am Bull 69(3):279–300

  • Strahler AN (1964) Part II. Quantitative geomorphology of drainage basins and channel networks. Handbook of Applied Hydrology. McGraw-Hill, New York, pp 4–39

    Google Scholar 

  • Suwandana E, Kawamura K, Sakuno Y, Kustivanto E, Raharjo B (2012) Evaluation of aster GDEM2 in comparison with GDEM1, SRTM DEM and topographic-map-derived DEM using inundation area analysis and RTK-DGPS data. Remote Sens 4:2419–2431. https://doi.org/10.3390/rs4082419

    Article  Google Scholar 

  • Tachikawa T, Hato M, Kaku M, Iwasaki A (2011) Characteristics of ASTER GDEM version 2. In: 2011 IEEE International Geoscience and Remote Sensing Symposium. IEEE, pp 3657–3660

  • Tadono T, Ishida H, Oda F, Naito S, Minakawa K, Iwamoto H (2014) Precise global DEM generation by ALOS PRISM. ISPRS Ann Photogramm Remote Sens Spat Inf Sci II–4:71–76. https://doi.org/10.5194/isprsannals-II-4-71-2014

    Article  Google Scholar 

  • Thomas J, Joseph S, Thrivikramji KP, Abe G, Kannam N (2012) Morphometrical analysis of two tropical mountain river basins of contrasting environmental settings, the southern Western Ghats, India. Environ Earth Sci 66:2353–2366. https://doi.org/10.1007/s12665-011-1457-2

    Article  Google Scholar 

  • Vaze J, Teng J, Spencer G (2010) Impact of DEM accuracy and resolution on topographic indices. Environ Model Softw 25:1086–1098. https://doi.org/10.1016/j.envsoft.2010.03.014

    Article  Google Scholar 

  • Weydahl DJ, Sagstuen J, Dick B, Rønning H (2007) SRTM DEM accuracy assessment over vegetated areas in Norway. Int J Remote Sens 28:3513–3527. https://doi.org/10.1080/01431160600993447

    Article  Google Scholar 

  • Yue L, Shen H, Zhang L, Zheng X, Zhang F, Yuan Q (2017) High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations. ISPRS J Photogramm Remote Sens 123:20–34. https://doi.org/10.1016/j.isprsjprs.2016.11.002

    Article  Google Scholar 

  • Zheng X, Xiong H, Gong J, Yue L (2015) A robust channel network extraction method combining discrete curve evolution and the skeleton construction technique. Adv Water Resour 83:17–27. https://doi.org/10.1016/j.advwatres.2015.05.003

    Article  Google Scholar 

Download references

Funding

Dr R. Maheswaran gratefully acknowledges the funding received from the Department of Science and Technology, Water Technology Initiative under the project DST/WTI/DD/2k17/0079. The authors also acknowledge Surveycon Ltd. Visakhapatnam for providing the DGPS survey data used in this study.

Author information

Authors and Affiliations

  1. Department of Civil Engineering, MVGR College of Engineering, Vizianagaram, Andhra Pradesh, 535005, India

    Venkatesh Kasi, Ramdas Pinninti, Landa Sankar Rao, Maheswaran Rathinasamy, Chandramouli Sangamreddi & Rajeshwar Rao Kuppili

  2. Department of Mechanical Engineering, MVGR College of Engineering, Vizianagaram, Andhra Pradesh, 535005, India

    Dandu Radha Prasada Raju

Authors
  1. Venkatesh Kasi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ramdas Pinninti
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Landa Sankar Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Maheswaran Rathinasamy
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chandramouli Sangamreddi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Rajeshwar Rao Kuppili
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Dandu Radha Prasada Raju
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maheswaran Rathinasamy.

Additional information

Responsible Editor: Biswajeet Pradhan

Electronic supplementary material

ESM 1

(DOCX 16 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kasi, V., Pinninti, R., Landa, S. et al. Comparison of different digital elevation models for drainage morphometric parameters: a case study from South India. Arab J Geosci 13, 1050 (2020). https://doi.org/10.1007/s12517-020-06049-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-020-06049-4

Keywords

  • Drainage morphometry
  • Comparison of DEM
  • Cartosat
  • Vertical accuracy