**3.4.2 Results of risk mapping and hydrological modelling**

Altogether 210 catchments were delineated in the study area. Their average size is 42 km2, the smallest is 2 km2, while the largest is 300 km2 in area. Figure 10 shows the catchments delineated using the above described method. Considering the combined effect of hydrology and precipitation pattern in Southern Transdanubia, there is a risk of flash flood with a return period of maximum 10 years in almost all mountains and hills of the region.

The categories shown on the output risk map indicate a relatively good correspondence with observed locations of flooding and inundations during the May, 2010 events and the map seems reliable for risk assessment purposes (Fig. 10).

Fig. 10. A flood risk map of Southern Transdanubia prepared using the rapid screening technique. 1 = lowest risk; 2 = highest risk

Altogether 210 catchments were delineated in the study area. Their average size is 42 km2, the smallest is 2 km2, while the largest is 300 km2 in area. Figure 10 shows the catchments delineated using the above described method. Considering the combined effect of hydrology and precipitation pattern in Southern Transdanubia, there is a risk of flash flood with a return period of maximum 10 years in almost all mountains and hills of the region. The categories shown on the output risk map indicate a relatively good correspondence with observed locations of flooding and inundations during the May, 2010 events and the

Fig. 10. A flood risk map of Southern Transdanubia prepared using the rapid screening

technique. 1 = lowest risk; 2 = highest risk

**3.4.2 Results of risk mapping and hydrological modelling** 

map seems reliable for risk assessment purposes (Fig. 10).

The basically static approach of GIS-based modelling (focusing on passive factors of inundation risk) is supplemented by hydrodynamic modelling, which expresses basic physical and hydrological relationships with mathematical equations (Maddox et al. 1979). Runoff is represented in critical flow or stage value, which is further analyzed with a flood transformation model. If appropriate data of sufficient spatial resolution are available, the HEC software environment is also suitable for the estimation of the extention of potentially inundated areas. Thus, it can also fulfil a verification function.

Firstly, the HEC-HMS model determines the actual discharge responding to critical rainfall for the catchment under study. However, the output data verification will only be feasible if stream gauge data are available for the catchment. If the simulation is carried out on an unexplored catchment, total runoff (flow) has to be estimated by empirically based equations (Koris, 2002).

Threshold precipitation values, i.e. those that trigger floods with a given return period are determined for various flood levels. In our investigations, based on observed rainfall, a 400 year return period (during which probably a series of undocumented flash flood events occurred) had to be taken into consideration. In this case, in addition to the actual rainfall values, we have to acquire comprehensive knowledge on the entire hydrological cycle, including information on elements like the hydraulic conductivity and infiltration rate of soils, canopy and surface storage. The numerical models also involve topographical analyses, but they are focused on the study of cross-sections. Valley cross-sections are established at predetermined spacing and analyzed along the whole length of the watercourse (Fig. 11). The actual width of the cross-section is designed with regard to the critical flood level above the valley floor or the mean long-term water stage. River flow or stage values are then determined for each cross-section (Fig. 11).

Fig. 11. Cross-sections across the Bükkösd Stream valley (left) and water levels at a sample cross-section for floods of a given probability computed by the HEC-RAS model (right)

Flash Flood Hazards 47

statistics, settlements, residential areas and farmlands are potentially affected by flooding and serious damage from floods can be predicted. The choice of methodological approaches to the topic is rapidly broadening. The combination of rapid screening methods, GIS-based risk assessment with numerical hydrological modelling and the flowchart analysis of

This research was supported by the Baross Gábor Program (Grant No. REG\_DD\_KFI\_09/PTE\_TM09), the Hungarian Science Fundation (OTKA, Grant No. T 68903) and the Bolyai János Scholarship. The authors are grateful for the data and support provided by the Hungarian Meteorological Service, the South-Transdanubian Water Management Directorate (DDKÖVIZIG), the VITUKI Rt. and the Mecsekérc Zrt. The authors are especially indebted to Ákos Horváth, Gábor Horváth, András Varannai, Gergely

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**6. Acknowledgements** 

**7. References** 

Today numerical models are widely applied tools to simulate the areal extent of inundations and flooding along a watercourse (i.e during riverine floods) (Gaume et al., 2004). They are also suitable for flood simulation in urban environments, where the proportion of permeable surfaces are limited and impervious paved surfaces are widespread (e.g. Xia et al., 2011). Numerical modelling is particularly suitable for the analyses of risk scenarios, such as dam breaching, and also capable of the exact localization and parameterization of the elements of the channel and drainage systems (e.g. bridges, levees and culverts) and even appropriate for the 3D representation of these structures.
