*5.5. Generation of Flash Flood Susceptibility Maps*

In this step, flash flood susceptibility maps of Tafresh watershed were prepared based on ABM-CDT, Bag-CDT, Dag-CDT, MBAB-CDT hybrid machine learning models and CDT model in ArcGIS software. To construct the flash flood susceptibility maps, flash flood susceptibility indexes generated from the construction of the models were used to assign all pixels of the study area. Thereafter, these indexes were classified into five classes of flash flood susceptibility, namely very low, low, moderate, high, and very high to construct final maps using geometric interval classification method available in GIS software.

#### **6. Results and Discussion**

#### *6.1. Impact Weight of each Class of Variables A*ff*ecting Flash Flood Susceptibility by FR Method*

The impact weight of each class of variables was determined based on the comparative analyses of relationships between the location of past floods with the topographical and geo-environmental variables affecting flash flood occurrences (Figure 5). Analysis indicated that the highest weight in the variable of altitude classes belongs to the elevation class of 1296–1823 m. In the slope percentage of the surface slope, the weight of 0–9.3 degrees was the highest weight. In the slope direction variable, the northwest slope direction has a higher weight than the other aspects. In variable distance from the fault class of 400–500 m, weight has more influence than other classes. Examination of the variable distance from river showed that most of the flood-related weight was located at 0–100 m class. In the

rainfall variable, the rainfall class 250–300 mm has higher weight than the other class. This means this class of rainfall belongs to threshold value for the occurrence of flash flood. Higher rainfall above this value can also cause flash flood depending on the duration in combination with other factors. Land use classes of the orchard and residential, which are in proximity to the main river and at gentle slopes, had the highest weighting factor compared to other land uses. Soil analysis indicates that the weight of the inceptisols soil is higher than that of the rocky outcrops. The lithology in this area indicates that Qom formation (OMq) has higher weight than other classes.

**Figure 5.** Frequency analysis of flash flood occurrence on the factor maps.
