Estimation of River Migration Rates Based on Monitoring Meander Changes Using Sentinel-2 Satellite Images

Document Type : Original Article

Authors

1 Ph.D Student of Water Structures, Dept. of Water Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Water Engineering Dept., Gorgan University of Agricultural Sciences and Natural Resources

3 Prof., Dept. of Water Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

4 Prof., Dept. of Water Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

Abstract

Monitoring morphological changes in meandering rivers, particularly in inaccessible areas or those lacking field data, has always faced operational challenges. Although remote sensing technology offers a promising solution to these challenges, most previous studies have focused on wide rivers, and its effectiveness for rivers with an average width of less than 50 meters has not been evaluated. This research aims to evaluate the accuracy of remote sensing methods in estimating migration rates and extracting river centerlines, using the Atrak River as a case study. In this study, using Sentinel-2 satellite images (from 2016 to 2021), six spectral indices (NDVI, NDWI, MNDWI, AWEI, EWI, WIR) were compared to extract the water surface of a section of the Atrak River near Korand and Hootan villages. After image preprocessing, the river centerline was extracted in QGIS, and its accuracy was evaluated using RMSE, length difference percentage, and spatial agreement with Google Earth reference data. Calibration results for 2016 showed that the MNDWI index, with the lowest error (RMSE = 6.09 m), the smallest length difference (0.47%), and the highest spatial agreement (94.13%), was the most accurate index for centerline extraction. Verification of this index for 2021 also confirmed its acceptable performance, with a length difference of 1.45% and an agreement of 85.95%. The findings clearly demonstrate the effectiveness of remote sensing and the superiority of the MNDWI index for quantitative and accurate monitoring of morphological changes in medium-width rivers.

Keywords

Main Subjects

References

Basnayaka, V., Samarasinghe, J. T., Gunathilake, M. B., Muttil, N., Hettiarachchi, D. C., Abeynayaka, A., Rathnayake, U. (2022). Analysis of meandering river morphodynamics using satellite remote sensing data—an application in the lower Deduru Oya (River), Sri Lanka. Land, 11(7), 1091.
Brice, J. C. (1974). Evolution of meander loops.Geol. Soc. Am. Bull, 85, 581-86.
Carlson, T. N., & Ripley, D. A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote sensing of Environment, 62(3), 241-252.
 
 
 
Du Y, Zhang Y, Ling F, Wang Q, Li W, Li X. Water Bodies’ Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band. Remote Sensing. 2016; 8(4):354.
Jiang W, Ni Y, Pang Z, Li X, Ju H, He G, Lv J, Yang K, Fu J, Qin X. (2021). An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery. Water, 13(12),1647.
Leinenkugel, P. (2010). The Combined Use of Optical and SAR Data for Large Area Impervious Surface Mapping. Doctoral dissertation, University Salzburg.
Maghsoudi, M. , Zamanzadeh, S. , Yamani, M. and Hajizadeh, A. (2017) Morphometric Assessment of Meandering River in Arid Region Using Improvement Model (Case Study: Maroon River). Journal of Water Resource and Protection, 9, 358-377.
‏Nagel, G. W., Darby, S. E., Leyland, J. (2023). The use of satellite remote sensing for exploring river meander migration. Earth-Science Reviews, 104607,1-15.
Pham-Duc, B. (2024). Comparison of multi-source satellite remote sensing observations for monitoring the variations of small lakes: a case study of Dai Lai Lake (Vietnam). Journal of Water and Climate Change, 15(1), 157-170.
Schumm, S. A. (1985). Patterns of alluvial rivers. Annual Review of Earth and Planetary Sciences, 13(1), 5–27.
Shen, L., Li, C. (2010). Water body extraction from Landsat ETM+ imagery using adaboost algorithm. In 2010 18th International Conference on Geoinformatics. IEEE.
Wang, S., Baig, M. H. A., Zhang, L., Jiang, H., Ji, Y., Zhao, H., & Tian, J. (2015). A simple enhanced water index (EWI) for percent surface water estimation using Landsat data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(1), 90-97.
Wang, Z., Li, J., Lin, Y., Meng, Y., & Liu, J. (2020). GrabRiver: graph-theory-based river width extraction from remote sensing imagery. IEEE Geoscience and Remote Sensing Letters, 19, 1-5.
Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), 3025–3033
Journal of Hydrogeomorphology
Volume 13, Issue 48 - Serial Number 48
September 2026
Pages 43-21

Files

History

  • Receive Date: 04 August 2025
  • Revise Date: 05 January 2026
  • Accept Date: 07 January 2026

Share

How to cite

Statistics