Modeling Flood Hazard Due to Climate Change in Small Mountainous Catchments

Stoyan NEDKOV

Introduction

Climate change is often represented by increase of extreme phenomena, like storms, torrential rains, and floods. Their regional and local dimensions vary from one area to another. This is especially valid for the regime and distribution of precipitation. Even for a country with relatively small territory, like , precipitation in some areas has increased during the last decades, while in others it has decreased. The only precipitation characteristic with undoubted trend of increase for most of the territory is the heavy and torrential rains (VELEV 2005, BOCHEVA et al. 2007). This means that, even in cases with no increase in the annual precipitation, there are less storm events but their quantity and intensity are higher. Torrential rains are one of the most important factors for flood formation and there is a significant increase in the number of this hazardous phenomenon during the last few years. The causal relationship between the increasing number of torrential rains and flood events for the last decades in Bulgaria can be illustrated with an example from River basin (fig. 1).

(a) (b) Fig. 1: Number of floods (a) and torrential rains (b) for the period 1990-2005 in Yantra River basin (NEDKOV & NIKOLOVA 2006)

The problem is more serious in the mountainous areas, where the amount of precipitations is normally larger and the topography facilitates a rapid increase of surface runoff and formation of disastrous peak flows. Spatial distribution of precipitation in the mountains is usually discontinuous. This is even more typical for the torrential rains, the influence of which is often concentrated in some parts of the river basin. They seldom exert simultaneous effect on all the tributaries of the main river (NIKOLOVA 2007). Therefore, it is necessary to investigate in detail the influence of the small catchments on the formation of peak flow in the mountainous areas and, further, the impact of the increased number and Modeling Flood Hazard Due to Climate Change in Small Mountainous Catchments 173 quantity of the heavy and torrential rains. This study presents an approach that utilizes GIS tools for modeling the impact of increasing incidence of torrential rains on the formation of peak flows and flood hazards, as well as the response of small catchments with different landscape structure.

1 GIS Modeling

GIS is a powerful tool for modeling the processes taking place within catchment basins which affect the formation of peak flows. The Automated Geospatial Assessment Tool (AGWA), designed to facilitate all phases of the modeling for two widely used hydrologic models (SWAT and KINEROS) in GIS environment, has been used to delineate and parameterize the catchments. Kinematic Runoff and Erosion Model (KINEROS) has been used to simulate the influence of rainfalls with different intensity and quantity on the peak flow during particular storm events. It is a distributed, physically based, event model describing the processes of interception, dynamic infiltration, surface runoff, and erosion from catchments characterized by predominantly overland flow. The catchment is conceptualized as a cascade and channels, over which flow is routed in a top-down approach using a finite difference solution of the one-dimensional kinematic wave equations (SEMMENS et al. 2005). The investigation was carried out in the case study area of Malki River before it enters the town of (Bulgaria). Situated in the northern slopes of Stara Planina Mountain the area spreads over 54.5 km2 and has an average altitude of 1164 m. The observations carried out during the last decades show that there is a significant increase in the number and quantity of the torrential rains, which corresponds to a similar trend observed in the rest of the country. The model has been used in four small catchments within the area. The initial investigation and model calibration was carried out in the catchment of Ravna River (a tributary of Malki Iskar), because there is a hydrometric station for measurement of the river flow there. Simulated data was calibrated against runoff and precipitation data for five measured storm events. The relationship between the increasing rainfalls intensity and the peak flow was analyzed. The model has been adjusted for every event, in order to present the particular conditions of the state of the landscape during the observations, including initial soil moisture, saturated hydraulic conductivity, channel and plane roughness. Numerous rainfall files were prepared to present the increase of precipitation’s amount using 2 mm step. The model has been run with everyone of them and the simulated quantities of the peak flow have been put on a graph that shows the relationship between the increasing intensity of the rainfalls and the peak flow change.

2 Results

The resulting curve (fig. 2) shows that the increasing intensity in the beginning causes almost no response in the river discharge. It means that the whole amount of water from the rainfall goes for interception and infiltration. The peak flow of the river starts to increase gradually after a particular intensity of the rainfall is reached. Its value is strongly dependent on the available moisture before the start of the storm event. More moisture

174 S. Nedkov

Fig. 2: Change of the peak flow in the Ravna River as a result of the increase in the rainfall intensity: I – phase of no increase; II – phase of gradual increase; III – phase of rapid increase causes faster and earlier increase of the peak flow. As the rainfall intensity increases further, at a particular level the peak flow displays rapid growth and reaches disastrous quantities that cause floods. This level can be marked as a “critical point”, after which the flood risk rises enormously. Therefore, the peak flow response to the increasing rainfall intensity can be divided into three phases (fig. 2): 1) phase of no increase, when the landscape “absorbs” almost the whole amount of water; 2) phase of gradual increase, when part of the water is transformed into surface runoff; 3) phase of rapid growth, when the ability of the landscape to “absorb” water is close to zero and almost the whole amount of rainfall goes to the surface runoff. Next, the same procedure was implemented for the rivers Kobilya, Suha, and Jablanitsa using the same five events in order to investigate how the different catchment conditions affect the amount of peak flow. In this case, the three phases are also easily identified on the curve but their shape varies among the different catchments. The Ravna River shows the most rapid increase of the peak flow, which exceeds the other rivers at every point after the initial increase. The Suha River has slower increase in the second phase, but faster in the third. The situation is opposite for Kobilya and Jablanitsa, which have faster increase (than Suha) in the first phase, but slower in the third one. The rapid growth in these two rivers is not so expressive as Ravna and Suha. This results show that the “reaction” of the peak flow, as a result of the increasing precipitation intensity, can differ among small catchments even within relatively small area, due to the large heterogeneity of the mountainous landscapes. The most important characteristics causing these differences are topography (especially slope), land cover, and soil properties. Modeling Flood Hazard Due to Climate Change in Small Mountainous Catchments 175

3 Conclusion

The main conclusion is that, climate change causes an increase of torrential rains, which can lead to bigger and more disastrous floods. The model shows significant increase of the peak flow when rainfall quantity exceeds a particular “critical” level, after which the flood risk rises enormously. This level depends on the moisture conditions before the storm and seasonal state of the land cover. It also differs among catchments with different landscape features. The implementation of the presented approach provides an opportunity to assess the flood hazard in mountainous catchments and contribute to the development of early warning systems.

References

BOCHEVA, L. BOCHAVA, L. MARINOVA, T. & GOSPODINOV, I. (2007), Variability and trends of extreme precipitation events over Bulgaria. Proceedings of 4th European Conference on Severe Storms, Trieste, Italy, 10 – 14 September. NEDKOV, S. & NIKOLOVA, M. (2006), Modeling flood hazard in Yantra river basin. In: Proceedings from Balwois conference, Ohrid, May 23 – 26. NIKOLOVA, M. (2007), Climatic conditions for high waves and floods in the basin of Malki Iskar River above town of Etropole. Proceedings of the Second National Research Conference on Emergency Management and Protection of the Population, , November, 9 (in Bulgarian). SEMMENS, D., GOODRICH, D., UNCRICH, C., SMITH, R., WOOLISER D. & MILLER S. (2005), KINEROS2 and the AGWA Modeling Framework. International G-WADI Modeling Workshop. VELEV, S. (2005), Torrential rain in Bulgaria during XX century. Problems of Geography 1-2, pp. 169-172 (in Bulgarian).