SPATIAL ASSESSMENT AND ANALYSIS OF MUDFLOW HAZARD ZONES IN THE SURKHANDARYA RIVER BASIN USING GIS AND REMOTE SENSING-BASED STATISTICAL MODELS
Keywords:
mudflow hazard, GIS, remote sensing, Frequency Ratio, ROC/AUC, Surkhandarya, Uzbekistan.Abstract
Mountainous and foothill regions of Surkhandarya Province (Uzbekistan) are increasingly affected by mudflow events driven by climate change, glacier retreat and intense seasonal rainfall. This study presents a spatial assessment of mudflow hazard zones in the Surkhandarya River basin (13 500 km²) using an integrated GIS and remote sensing approach. A geospatial database of 115 mudflow inventory points (2022-2024) was compiled and seven conditioning factors (TWI, SPI, rainfall, drainage density, lithology, NDVI and slope aspect) were standardized at 30 m resolution. Hazard zonation was carried out using the Frequency Ratio (FR) model, validated with ROC/AUC analysis (AUC=0.856). The study area was classified into five hazard categories. Results indicate that the very high hazard zone covers 265.17 km², of which 60% lies in Tajikistan (Tursunzoda district, 124.17 km²) and 40% in Uzbekistan (Sariosiyo district, 77.98 km²). Land cover analysis revealed that 163.05 km² of very high hazard areas overlap with cropland and 82.42 km² with settlements, highlighting the urgent need for risk reduction measures along the Karatag-Tupalang river confluence.
References
Centre for Research on the Epidemiology of Disasters (CRED). EM-DAT: The International Disaster Database, 2024. Available at: https://www.emdat.be
Häusler, H., Schlechter, M., Schrott, L. Climate change, glacier retreat and related natural hazards in high mountain regions of Central Asia. Geomorphology, 273, 2016, pp. 45-58.
Khasanov, S., Juliev, M., Uzbekov, U., et al. Landslides and related mudflow hazards in Central Asia: a review with emphasis on GIS and remote sensing approaches. GeoScape, 15(2), 2021, pp. 134-145. https://doi.org/10.2478/geosc-2021-0011
Chub, V. E., Trofimov, G. N., Merkushkin, A. S. Mudflow phenomena of Uzbekistan. Tashkent: NIGMI Uzhydromet, 2007, 109 p.
Lee, S., Pradhan, B. Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides, 4, 2007, pp. 33-41. https://doi.org/10.1007/s10346-006-0047-y
Abdo, H. G., Almohamad, H., Al Dughairi, A. A., et al. Spatial implementation of frequency ratio, statistical index and index of entropy models for landslide susceptibility mapping. Geoscience Letters, 9(45), 2022, pp. 1-24. https://doi.org/10.1186/s40562-022-00256-5
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., Guzzetti, F. A review of statistically-based landslide susceptibility models. Earth-Science Reviews, 180, 2018, pp. 60-91. https://doi.org/10.1016/j.earscirev.2018.03.001
Funk, C., Peterson, P., Landsfeld, M., et al. The climate hazards infrared precipitation with stations - a new environmental record for monitoring extremes. Scientific Data, 2, 150066, 2015. https://doi.org/10.1038/sdata.2015.66
Hamidullayev, Sh., Oymatov, R. Mudflow risk in Surkhandarya Province: causes, trends and contributing factors. Proceedings of the Scientific-Practical Conference "Development of Specialized Higher Education and Science in the Context of Globalization", TIIAME NRU, Tashkent, 2025, pp. 397-401.
Fazilova, D., Magdiyev, H., Makhmudov, M., Fazilov, A. A multi-criteria GIS model for geohazard assessment in the Charvak reservoir area, Uzbekistan. Egyptian Journal of Remote Sensing and Space Science, 28(3), 2025, pp. 587-596. https://doi.org/10.1016/j.ejrs.2025.09.003
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