Assessing the accuracy of global digital elevation models for hydrological analysis: the cases of Syria and Russia
https://doi.org/10.21285/2227-2917-2024-3-501-512
EDN: TNXRYF
Abstract
Digital elevation models provide valuable information about the surface topography. The resolution and accuracy of the data used to create the models are critical for the results of hydrological analysis. Available global digital elevation models obtain high potential in terms of data sources; however, their performance requires meticulous evaluation for different terrain characteristics and applications. Aim. To determine the accuracy and resolution of data provided by current and old global models, namely SRTM 1, SRTM GL1, V3 ASTER, GMTED2010, PALSAR ALOS, and GTOPO 30, using the example of two terrains. The study considers the areas in Syria (Syrian coast) and Russia (Chernoyarsky and Akhtubinsky districts in the Astrakhan region) represented by different elevation models. A matching degree between model and real elevations measured by GPS was determined to carry out the hydrological analysis of the land surface. For this purpose, three statistical measures, including range, standard deviation and correlation were defined by means of BaseCamp, ARCGIS PRO & SAGA_GIS software. Data resolution indicates the degree of detail represented in the DEM dataset, which is established by the spatial sampling interval or the size of the grid cell used to represent the land surface. Data accuracy refers to the matching degree between the elevation values derived from the DEM and the actual data obtained on the surface. Results. In terms of correlation coefficient and standard deviation, the GMTED 2010 and ASTER V3 model for the Syrian region and the ALOS PALSAR and SRTM GL 1 model for the Russian region prove to be the most effective for hydrological analysis in the absence of accurate local models.
About the Author
H. Alali
Russian State Agrarian University – Moscow Timiryazev Agricultural Academy
Russian Federation
Russian Federation
Hothefa Alali, Postgraduate Student
Author ID: 1212752
49 Timiryazevskay St., Moscow 127434
References
1. Ilinich V.V., Perminov A.V., Belolybcev A.I., Naumova A. A. Assessment of the Impact of Changes in Storm Rainfall and Landscape Characteristics on the Maximum Flow of Small Rivers. Springer Water. 2020:717-725. https://doi.org/10.1007/978-981-15-5436-0_55. EDN: KDLPNN.
2. Gusev V.L., Potapov S.L., Sinkova M.G. Open Sources Digital Terrain Models and Digital Elevation Models Accuracy Estimation. Izvestia vuzov. Geodesy and Aerophotosurveying. 2022;66(1):52-63. (In Russ.). https://doi.org/10.30533/0536-101X-2022-66-1-52-63. EDN: UYHXGM.
3. Koshel' S.M., Entin A.L. Contemporary Methods for Calculating Surface Water Distribution from Digital Elevation Models. Geomorfologi. 2016;6:24-34. (In Russ.). EDN: WZPQOH.
4. Pavlova A.N. Geomodeling of River Basin Based of the Space Data SRTM (as Example of Tereshka River). Izvestiya Saratovskogo universiteta. Novaya seriya. Seriya Nauki o Zemle. 2009;9(1):39-44. (In Russ.). EDN: JVCBHW.
5. Guliyev A.Sh.O. Evaluation of The Height Accuracy of Air Laser Scanning for Automation of Spatial Transformations of the Functional Model for The Regions. Interexpo GEO-Siberia. 2018;1(4):43-51. (In Russ.). EDN: VSFLHW.
6. Fernandez A., Adamowski J., Petroselli A. Analysis of the Behavior of Three Digital Elevation Model Correction Methods on Critical Natural Scenarios. Journal of Hydrology: Regional Studies. 2016;8:304-315. https://doi.org/10.1016/j.ejrh.2016.09.009.
7. Florinsky I.V., Skrypitsyna T.N., Trevisani S., Romaikin S.V. Statistical and Visual Quality Assessment of Nearly-Global and Continental Digital Elevation Models of Trentino, Italy. Remote Sensing Letters. 2019;10(8):726-735. https://doi.org/10.1080/2150704X.2019.1602790.
8. Ermolaev O.P., Semenov F.V. Use of Digital Terrain Models in Morphometric Analysis of Tectonic Structures and Prospecting of Placers of Alluvial Genesis. Geography and Natural Resources. 2014;1:142-147. (In Russ.). EDN: RXNVPP.
9. Bryzzhev A.V., Rukhovich D.I., Koroleva P.V., Kalinina N.V., Vil'chevskaya E.V., Dolinina E.A. [et al.] Organization of Retrospective Monitoring of Soil Cover and Lands in The Azov District of the Rostov Region. Eurasian Soil Science. 2013;11:1294-1315. (In Russ.). https://doi.org/10.7868/S0032180X13110026. EDN: REKBUH.
10. Mukherjee S., Joshi P.K., Mukherjee S., Ghosh A., Garg R.D., Mukhopadhyay A. Evaluation of Vertical Accuracy of Open Source Digital Elevation Model (DEM). International Journal of Applied Earth Observation and Geoinformation. 2013;21:205-217. https://doi.org/10.1016/j.jag.2012.09.004.
11. Muborakov Kh., Ruziev A.S., Abdullaev I.U. On The Use of Remote Sensing Materials for Calculating Design Parameters and Monitoring the Regime of Reservoirs. Izvestiya Geograficheskogo obshchestva Uzbekistana. Spetsial'nyi tom. 2018:179-181. (In Russ.).
12. Astapovich A.V., Zhbanov K.K., Medyannikov D.O., Yakovlev A.I. Relief Model of an Inaccessible Territory, Built Based On the Results of Integrating Heterogeneous Satellite Information. Proceedings of the Mozhaisky Military Space Academy. 2021;677:75-83. (In Russ.). EDN: WDKYET.
13. Biau G., Devroye L. Lectures On the Nearest Neighbor Method. New York: Springer, 2015. 300 p.
14. Fisher R., Hobgen S., Mandaya I., Kaho N.R., Zulkarnain Satellite Image Analysis and Terrain Modelling – A practical manual for natural resource management, disaster risk and development planning using free geospatial data and software. Charles Darwin University, Universitas Nusa Cendana dan Universitas Halu Oleo, 2017. 151 p.
15. Ilinich V.V., Perminov A.V., Naumova A.A. Assessment of The Impact of Climatic Characteristics and Landscape Changes On the Maximum Flow of Small Watersheds. Monthly Journal on Construction and Architecture. 2021;16(9):1228-1235. (In Russ.). https://doi.org/10.22227/1997-0935.2021.9.1228-1235. EDN: UDKCUS.
16. Althumania D., Achour H. External Validation of the ASTER GDEM2, GMTED2010 and CGIAR-CSI-SRTM v4.1 Free Access Digital Elevation Models (DEMs) in Tunisia and Algeria. Journal of Remote Sensing. 2014;6(5):4600-4620. https://doi.org/10.3390/rs6054600.
17. Patel A., Katiyar S.K., Prasad V. Performance Evaluation of Different Open Source DEM Using Differential Global Positioning System (DGPS). The Egyptian Journal of Remote Sensing and Space Sciences. 2016;19(1):7-16. https://doi.org/10.1016/j.ejrs.2015.12.004.
18. Ilinich V.V., Perminov A.V., Naumova A.A. Impact of Landscape and Climate Changes On the Maximum Runoff of Small Watersheds. Hydraulic Structures Construction. 2022;7:15-19. (In Russ.). EDN: AZIXGJ.
19. Alali H., Perminov A.V. Monitoring of The 16 Tishrin Reservoir Using GIS-Technologies and Remote Sensing. Reclamation and Water Management. 2024;1:11-16. (In Russ.). https://doi.org/10.32962/0235-2524-2024-1-11-16. EDN:AKHRPC.
20. Alali H., Perminov A.V. Water Evaporation from The 16 Tishrin Reservoir in Syria: Volume Measurement and Economic Impact Assessment. Land Reclamation and Hydraulic Engineering. 2023;13(3):314-331. (In Russ.). https://doi.org/10.31774/2712-9357-2023-13-3-314-331. EDN: XFAYAM.
21. Alali H., Perminov A.V. Use of Modern GIS Technologies in The Analysis of Hydrological Data of the Alkabeer Alshamali River in Syria. Hydraulic Structures Construction. 2024;4:49-54. (In Russ.). https://doi.org/10.34831/EP.2024.57.90.006. EDN: MVOLRE.
22. Alali H., Perminov A.V., Rednikov S.N., Alsadek E.S. Morphometric Analysis of Al Kabir Al Shamali River Basin in Syria Using Aster (Digital Elevation Model) Image Based On GIS-Technology. Journal of Science and Education of North-West Russia. 2024;10(1):46-58. (In Russ.). EDN: YTMFDM.
23. Bukharitsin P.I., Ovcharova A.Yu., Tokareva A.A., Kutlusurina G.V. Geoecology of Natural Complexes of the Lower Volga Under Conditions of Anthropogenic Impact: Collective Monograph. Deutschland: LAP LAMBERT Academic Publiching, 2020. 288 p. (In Russ.).
Review
For citations:
Alali H. Assessing the accuracy of global digital elevation models for hydrological analysis: the cases of Syria and Russia. Izvestiya vuzov. Investitsii. Stroitelstvo. Nedvizhimost. 2024;14(3):501-512. (In Russ.) https://doi.org/10.21285/2227-2917-2024-3-501-512. EDN: TNXRYF
Views:
75
Email this article 