Gully erosion mapping based on hydro-geomorphometric factors and geographic information system

Area of Science:

• Geosciences
• Environmental Science
• Geography

Background:

• Gully erosion poses significant environmental and economic challenges.
• Accurate susceptibility mapping is vital for effective land management and disaster mitigation.
• Traditional methods often lack the precision and cost-effectiveness required for regional assessments.

Purpose of the Study:

• To develop a precise and cost-effective Gully Erosion Susceptibility Map (GEM) for western Iran.
• To compare the performance of the Geographically Weighted Regression (GWR) model against Frequency Ratio (FreqR) and Logistic Regression (LogR) models.
• To identify key hydro-geomorphometric factors influencing gully erosion in the study area.

Main Methods:

• Utilized Geographic Information System (GIS) and remote sensing data (aerial photographs, Google Earth images).
• Prepared twenty hydro-geomorphometric parameter layers and gully inventory maps from field surveys.
• Applied and compared GWR, FreqR, and LogR statistical models for susceptibility zonation.

Main Results:

• The GWR model achieved the highest accuracy (84.5% AUC-ROC), outperforming LogR (79.1%) and FreqR (78%).
• Key factors influencing gully erosion included soil type, rock unit, slope aspect, altitude, and precipitation.
• The study successfully delineated areas susceptible to gully erosion with high precision.

Conclusions:

• The GWR model demonstrates superior performance for gully erosion susceptibility mapping compared to bivariate and other multivariate statistical models.
• Hydro-geomorphological parameters are critical for accurate gully erosion zonation.
• The proposed methodology provides a valuable tool for regional natural hazard assessment and management.