Skip to main content

Advertisement

SpringerLink
Log in

Inter-comparison and assessment of digital elevation models for hydrological applications in the Upper Mahi River Basin

  • Original Paper
  • Published:
Applied Geomatics Aims and scope Submit manuscript

Abstract

This study evaluates and compares the accuracy and reliability of multiple freely available digital elevation models (DEMs) including Copernicus Global Land Operations (GLO), Advanced Land Observing Satellite (ALOS), Cartosat, Shuttle Radar Topography Mission (SRTM), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for hydrological applications in the Mahi River upper basin in Western India. Through watershed delineation, statistical analysis, error quantification, and 2D hydraulic modeling using HEC-RAS, this research assesses the performance of these DEMs with GLO DEM as the reference. GLO DEM is used as the reference because key findings show it most accurately delineates watershed boundaries and stream networks and has the fewest sinks. ALOS also demonstrates strong performance, with 70.47% watershed boundary similarity to GLO. Cartosat shows reasonable accuracy in watershed delineation with a Jaccard Index (JI) of 68.41% while SRTM and ASTER appear less reliable. Statistical analysis reveals ALOS slightly overestimates while other DEMs underestimate elevations compared to GLO for most of the slope classes. Flood modeling shows GLO produces the smoothest inundation, with ALOS second-best. Overall, GLO and ALOS emerge as the most accurate and reliable options followed by Cartosat among freely available datasets for the study area. The research provides insights into DEM performance to inform selection and improve hydrological applications involving terrain data for the study area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding author, Vikas Kumar Rana, vikas.rana-wremi@msubaroda.ac.in, upon reasonable request.

References

  • Cain MK, Zhang Z, Yuan KH (2017) Univariate and multivariate skewness and kurtosis for measuring nonnormality: prevalence, influence and estimation. Behav Res Methods 49(5):1716–1735. https://doi.org/10.3758/s13428-016-0814-1

    Article  PubMed  Google Scholar 

  • Chaplot V (2014) Impact of spatial input data resolution on hydrological and erosion modeling: recommendations from a global assessment. Phys Chem Earth 67:23–35. https://doi.org/10.1016/j.pce.2013.09.020

    Article  ADS  Google Scholar 

  • Crespi M, De Vendictis L, Poli D, Wolff K, Colosimo G, Gruen A, Volpe F (2008) Radiometric quality and DSM generation analysis of CartoSat-1 stereo imagery. Int Arch Photogramm Remote Sens Spat Inf Sci 37(3):1349–1355

    Google Scholar 

  • Cuellar AC, Cenci L, Santella C, Albinet C (2022) Evaluating the Copernicus Dem dataset potential for the identification of (flash) flood-prone areas by using a geomorphological approach. In: IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE, pp 5997–6000

    Chapter  Google Scholar 

  • Elhag M, Yilmaz N (2021) Insights of remote sensing data to surmount rainfall/runoff data limitations of the downstream catchment of Pineios River, Greece. Environ Earth Sci 80:1–13

    Article  Google Scholar 

  • Erskine RH, Green TR, Ramirez JA, MacDonald LH (2006) Comparison of grid-based algorithms for computing upslope contributing area. Water Resour Res 42:W09416

    Article  ADS  Google Scholar 

  • Farran MM, Elfeki A, Elhag M, Chaabani A (2021) A comparative study of the estimation methods for NRCS curve number of natural arid basins and the impact on flash flood predications. Arab J Geosci 14:1–23

    Article  Google Scholar 

  • Franks S, Rengarajan R (2023) Evaluation of Copernicus DEM and comparison to the DEM used for Landsat Collection-2 processing. Remote Sens 15(10):2509

    Article  ADS  Google Scholar 

  • Ghannadi MA, Alebooye S, Izadi M, Ghanadi A (2023) Vertical accuracy assessment of Copernicus DEM (case study: Tehran and Jam cities). ISPRS Ann Photogramm Remote Sens Spat Inf Sci 10:209–214

    Article  Google Scholar 

  • González Moradas MDR, Viveen W, Vidal Villalobos RA, Villegas Lanza JC (2023) A performance comparison of SRTM v. 3.0, AW3D30, ASTER GDEM3, Copernicus and TanDEM-X for tectonogeomorphic analysis in the South American Andes. Catena 228:107160. https://doi.org/10.1016/j.catena.2023.107160

  • Jain SK, Agarwal PK, Singh VPT (2007) Sabarmati and Mahi basins. In: Hydrology and water resources of India. Springer, Berlin/Heidelberg, Germany, pp 561–595

    Chapter  Google Scholar 

  • Jing C, Shortridge A, Lin S, Wu J (2014) Comparison and validation of SRTM and ASTER GDEM for a subtropical landscape in Southeastern China. Int J Digit Earth 7:969–992

    Article  Google Scholar 

  • Kim J, Noh J, Son K, Kim I (2012) Impacts of GIS data quality on determination of runoff and suspended sediments in the Imha watershed in Korea. Geosci J 16:181–192

    Article  CAS  Google Scholar 

  • Li S, MacMillan RA, Lobb DA, McConkey BG, Moulin A, Fraser WR (2011) LiDAR DEM error analyses and topographic depression identification in a hummocky landscape in the prairie region of Canada. Geomorphology 129(3–4):263–275. https://doi.org/10.1016/j.geomorph.2011.02.020

    Article  ADS  Google Scholar 

  • Li X, Hu J, Liu X, Yu J, Feng CC (2022) Adaptive digital elevation models construction method based on nonparametric regression. Trans GIS 26(5):2263–2282

    Article  Google Scholar 

  • Liao C, Zhou T, Xu D, Tan Z, Bisht G, Cooper MG et al (2022) Topological relationship-based flow direction modeling: stream burning and depression filling. Authorea Preprints

    Google Scholar 

  • Lindsay JB, Creed IF (2006) Distinguishing actual and artefact depressions in digital elevation data. Comput Geosci 32(8):1192–1204. https://doi.org/10.1016/j.cageo.2005.11.002

    Article  ADS  Google Scholar 

  • Mutar AQ, Mustafa MT, Hameed MA (2021) The impact of (DEM) accuracy on the watersheds areas as a function of spatial data. Period Eng Nat Sci 9:1118–1130

    Google Scholar 

  • Niculita M (2023) Copernicus DEM vs. LiDAR: assessment of landform accuracy representation at regional scale, vol No. EGU23-10090. Copernicus Meetings

    Google Scholar 

  • O’Loughlin F, Paiva R, Durand M, Alsdorf D, Bates P (2016) A multi-sensor approach towards a global vegetation corrected SRTM DEM product. Remote Sens Environ 182:49–59

    Article  ADS  Google Scholar 

  • Persendt FC, Gomez C (2016) Assessment of drainage network extractions in a low-relief area of the Cuvelai Basin (Namibia) from multiple sources: LiDAR, topographic maps, and digital aerial orthophotographs. Geomorphology 260:32–50. https://doi.org/10.1016/j.geomorph.2015.06.047

    Article  ADS  Google Scholar 

  • Pryde JK, Osorio J, Wolfe ML, Heatwole CD, Benham BL, Cardenas A (2007) Comparison of watershed boundaries derived from SRTM and ASTER digital elevation datasets and from a digitized topographic map. In: Presented at the 2007 ASABE Annual International Meeting. Minneapolis Convention Center, Minneapolis, MN. https://vtechworks.lib.vt.edu/items/a2353e6d-2414-44ab-a092-476976fb0c02/full

  • Rana VK, Suryanarayana TMV (2019) Visual and statistical comparison of ASTER, SRTM, and Cartosat digital elevation models for watershed. J geovis spat anal 3:12. https://doi.org/10.1007/s41651-019-0036-z

    Article  Google Scholar 

  • Saksena S, Merwade V (2015) Incorporating the effect of DEM resolution and accuracy for improved flood inundation mapping. J Hydrol 530:180–194

    Article  Google Scholar 

  • Shastry A, Durand M (2019) Utilizing flood inundation observations to obtain floodplain topography in data-scarce regions. Front Earth Sci 6:243

    Article  ADS  Google Scholar 

  • Shimada M, Tadono T, Rosenqvist A (2010) Advanced land observing satellite (ALOS) and monitoring global environmental change. Proc IEEE 98(5):780–799

    Article  CAS  Google Scholar 

  • Tadono T, Shimada M, Murakami H, Takaku J (2009) Calibration of PRISM and AVNIR-2 onboard ALOS “Daichi”. IEEE Trans Geosci Remote Sens 47(12):4042–4050

    Article  ADS  Google Scholar 

  • Tadono T, Takaku J, Tsutsui K, Oda F, Nagai H (2015) Status of 'ALOS World 3D (AW3D)' global DSM generation. In: 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Article 7326657 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2015-November). Institute of Electrical and Electronics Engineers Inc., pp 3822–3825. https://doi.org/10.1109/IGARSS.2015.7326657

  • Takaku J, Tadono T, Tsutsui K (2014) Generation of high resolution global DSM from ALOS PRISM. ISPRS —. Int Arch Photogramm Remote Sens Spat Inf Sci XL-4:243–248 http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-4/243/2014/

    Article  Google Scholar 

  • Trambadia NK, Patel DP, Patel VM, Gundalia MJ (2022) Comparison of two open-source digital elevation models for 1D hydrodynamic flow analysis: a case of Ozat River basin, Gujarat, India. Model Earth Syst Environ 8(4):5433–5447

    Article  Google Scholar 

  • Trevisani S, Skrypitsyna TN, Florinsky IV (2023) Global digital elevation models for terrain morphology analysis in mountain environments: insights on Copernicus GLO-30 and ALOS AW3D30 for a large Alpine area. Environ Earth Sci 82(9):198

    Article  ADS  Google Scholar 

  • Wang W, Yang X, Yao T (2012) Evaluation of ASTER GDEM and SRTM and their suitability in hydraulic modelling of a glacial lake outburst flood in Southeast Tibet. Hydrol Process 26(2):213–225. https://doi.org/10.1002/hyp.8127

    Article  ADS  Google Scholar 

  • Willmott CJ, Matsuura K (2006) On the use of dimensioned measures of error to evaluate the performance of spatial interpolators. Int J Geogr Inf Sci 20(1):89–102

    Article  Google Scholar 

  • Zhu D, Ren Q, Xuan Y, Chen Y, Cluckie ID (2013) An effective depression filling algorithm for DEM-based 2-D surface flow modelling. Hydrol Earth Syst Sci 17(2):495–505. https://doi.org/10.5194/hess17-495-201

    Article  ADS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Water Resources Engineering and Management Institute, Faculty of Technology & Engineering, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, India

    Dweep Pandya, Vikas Kumar Rana & Tallavajhala Maruthi Venkata Suryanarayana

Authors
  1. Dweep Pandya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vikas Kumar Rana
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tallavajhala Maruthi Venkata Suryanarayana
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vikas Kumar Rana.

Ethics declarations

This study is in full compliance with all applicable ethical standards.

Ethical approval

The presented research has not involved human subjects, human material, or human data and therefore ethical approval has not been required.

Informed consent

This study does not involve any subject participation and therefore informed consent is not applicable.

Conflict of interest

The authors declare no competing interests.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pandya, D., Rana, V.K. & Suryanarayana, T.M.V. Inter-comparison and assessment of digital elevation models for hydrological applications in the Upper Mahi River Basin. Appl Geomat 16, 191–214 (2024). https://doi.org/10.1007/s12518-023-00547-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12518-023-00547-2

Keywords

Search

Navigation