Problems of determining the first orders of rivers using the example of the Putilka River
DOI:
https://doi.org/10.31861/Keywords:
river system,, ordinal structures,, Rzhanitsyn method,, Strahler method,, first-order rivers,, hydrographic modeling,, remote sensing,, satellite imagery,, PALSAR,, Sentinel-2,, terrain modeling,, river sources,, cartographic analysisAbstract
This article examines the challenges of identifying first-order rivers in mountainous conditions using the sources of the Putylka River (Chernivtsi region) as a case study. The Rzhanitsyn and Strahler ordinal methods were used to analyze the hierarchy of the river system. The research was conducted using expedition data, cartographic materials, Sentinel-2 satellite images, and terrain modeling data (PALSAR). Google Maps imagery was also used for result verification.
The analysis results showed that discrepancies between field data, modeled streams, and cartographic materials were minimal. However, rivers initially classified as first-order may, in some cases, belong to the second order.
The study highlights the importance of a combined approach that includes remote sensing, terrain modeling, and field research. This approach improves the accuracy of river flow identification and order determination. Special attention is given to refining the classification criteria for first-order rivers to minimize errors in hydrographic modeling
References
1. Gravelius, H. (1914) Morphometry of Drainage Bassins. Elsevier, Amsterdan.
2. Horton, R. E. (1945), Erosional development of streams and their drainage basins: hydro-physical approach to quantitative morphology, Geological Society of America Bulletin 56 (3): 275-370
3. Strahler, A. N. (1957), Quantitative analysis of watershed geomorphology, Transactions of the American Geophysical Union 8 (6): 913-920.
4. Shreve, R., (1966), Statistical Law of Stream Numbers, J. Geol., 74, 17-37.
5. Prof. Dr. Peter Kogut, https://eos.com/blog/types-of-remote-sensing/
6. ASF DAAC 2015, ALOS PALSAR_Radiometric_Terrain_Corrected_hi_res; Includes Material ©JAXA/METI 2007.
7. Li, J.; Ma, R.; Cao, Z.; Xue, K.; Xiong, J.; Hu, M.; Feng, X (2022). Satellite Detection of Surface Water Extent: A Review of Methodology. Water 2022, 14, 1148. https://doi.org/10.3390/w14071148
8. L. WANG and H. LIU (2005), An efficient method for identifying and filling surface depressions indigital elevation models for hydrologic analysis and modelling, International Journal of Geographical Information ScienceVol. 000, No. 000, 0 Month 2005, 1–21
9. O'Callaghan, J.F. / Mark, D.M. (1984): 'The extraction of drainage networks from digital elevation data',Computer Vision, Graphics and Image Processing, 28:323-344.
