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A Conditional Probability-Based Model for Geological Hazard Susceptibility Assessment

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Due to the complexity of geological environments, hazards such as rockfalls, landslides, and debris flows often exhibit significant heterogeneity. Their spatial distributions typically display clustering across various scales. In this study, we propose a conditional probability-based model for assessing geological hazard susceptibility, which incorporates the cumulative effects of multiple geological environmental factors. This model is particularly suited for large regions with complex geological patterns.To quantitatively evaluate the geological hazard susceptibility index for the study area, we first applied the Certainty Factor (CF) method to normalize 11 geological environmental factors within the same range. Subsequently, we introduced positive contribution (W⁺) and negative contribution (W⁻) parameters to measure the contribution of each factor to hazard occurrence. Using these parameters, we calculated the comprehensive influence coefficient (C) of each factor. The influence coefficients were then normalized to determine the weights of the geological environmental factors. Finally, the hazard susceptibility index (G) for the region was obtained by aggregating the CF values and their respective weights for the 11 factors.Weights of Geological Environmental Factors for Hazard Susceptibility AssessmentGeological Factors Geological Environmental Factors Weights Topography and Geomorphology Elevation(m) 0.265 Topography and Geomorphology Slope(°) 0.038 Topography and Geomorphology Aspect(°) 0.026 Lithology Lithology Type 0.010 Geological Structure Seismic Acceleration(g) 0.090 Geological Structure Distance to Fault(m) 0.003 Meteorological and Hydrological Conditions Hydrogeological Type 0.036 Meteorological and Hydrological Conditions Water System Density(km/km2) 0.093 Meteorological and Hydrological Conditions Annual Precipitation (mm) 0.156 Human Engineering Activities Road Density(km/km2) 0.119 Human Engineering Activities Density of urban and large industrial buildings(one/km2) 0.163 We applied this model to the Ili Valley region in Xinjiang, Northwest China, using data from 1,810 documented hazards. In the Geographic Information System (GIS) environment, we selected, processed, and analyzed 11 geological environmental factors, including elevation, slope angle, slope aspect, lithology, seismic acceleration, distance to faults, hydrogeological type, drainage density, annual rainfall, road density, and the density of urban and large civil infrastructure distributions. The model’s validation demonstrated reliable predictive performance for the study area. This research provides a practical method for evaluating geological hazard susceptibility, offering valuable insights for geohazard assessment and risk management.Certainty Factor (CF) and Geological Hazard Susceptibility Index (G) Calculation Results for Geological Environmental Factors
Title: A Conditional Probability-Based Model for Geological Hazard Susceptibility Assessment
Description:
Due to the complexity of geological environments, hazards such as rockfalls, landslides, and debris flows often exhibit significant heterogeneity.
Their spatial distributions typically display clustering across various scales.
In this study, we propose a conditional probability-based model for assessing geological hazard susceptibility, which incorporates the cumulative effects of multiple geological environmental factors.
This model is particularly suited for large regions with complex geological patterns.
To quantitatively evaluate the geological hazard susceptibility index for the study area, we first applied the Certainty Factor (CF) method to normalize 11 geological environmental factors within the same range.
Subsequently, we introduced positive contribution (W⁺) and negative contribution (W⁻) parameters to measure the contribution of each factor to hazard occurrence.
Using these parameters, we calculated the comprehensive influence coefficient (C) of each factor.
The influence coefficients were then normalized to determine the weights of the geological environmental factors.
Finally, the hazard susceptibility index (G) for the region was obtained by aggregating the CF values and their respective weights for the 11 factors.
Weights of Geological Environmental Factors for Hazard Susceptibility AssessmentGeological Factors Geological Environmental Factors Weights Topography and Geomorphology Elevation(m) 0.
265 Topography and Geomorphology Slope(°) 0.
038 Topography and Geomorphology Aspect(°) 0.
026 Lithology Lithology Type 0.
010 Geological Structure Seismic Acceleration(g) 0.
090 Geological Structure Distance to Fault(m) 0.
003 Meteorological and Hydrological Conditions Hydrogeological Type 0.
036 Meteorological and Hydrological Conditions Water System Density(km/km2) 0.
093 Meteorological and Hydrological Conditions Annual Precipitation (mm) 0.
156 Human Engineering Activities Road Density(km/km2) 0.
119 Human Engineering Activities Density of urban and large industrial buildings(one/km2) 0.
163 We applied this model to the Ili Valley region in Xinjiang, Northwest China, using data from 1,810 documented hazards.
In the Geographic Information System (GIS) environment, we selected, processed, and analyzed 11 geological environmental factors, including elevation, slope angle, slope aspect, lithology, seismic acceleration, distance to faults, hydrogeological type, drainage density, annual rainfall, road density, and the density of urban and large civil infrastructure distributions.
The model’s validation demonstrated reliable predictive performance for the study area.
This research provides a practical method for evaluating geological hazard susceptibility, offering valuable insights for geohazard assessment and risk management.
Certainty Factor (CF) and Geological Hazard Susceptibility Index (G) Calculation Results for Geological Environmental Factors.

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