Suchergebnisse

This paper analyzes the Girona River (Spain) flash flood, occurred on the 12th of October 2007, combining hydrological and hydraulic modeling with geomorphologic mapping and post-flood survey information. This research aims to reproduce the flood event in order to understand and decipher the flood processes and dynamics on a system of prograding alluvial fans. The hydrological model TETIS was used to characterize the shape and dimension of the October 2007 Girona River hydrograph. Subsequently, the flood event was reproduced using the free surface flow module of the model RiverFlow2D. The combination of hydrological and hydraulic models was evaluated using post-flood surveys defining maximum flooded area and flood depths. Then, simulations with different peak discharges were carried out to estimate the hydro-geomorphologic response of the Girona River floodplain, through the identification of the activation thresholds in different geomorphic elements. Results showed that the unit peak discharge of the October 2007 flood event (5 m3 s−1 km−2) was among the largest ever recorded in the area, according to the existing literature. Likewise, the hydraulic model showed a good performance in reproducing the flood event (FitA = 76%, RMSE = 0.65 m and NSE = 0.6), despite the complexity of the case, an ephemeral and ungauged river. The model simulation revealed the existence of an activation pattern of paleochannels and alluvial fans, which was altered by the presence of some anthropogenic disturbances. This multidisciplinary approach proved to be a useful strategy for understanding flash flood processes in ungauged catchments. It allowed understanding the mechanisms governing floods in alluvial fans systems and it represented a solid contribution for early warning plans and risk mitigation policies. ; This collaborative research was financed with the projects CGL2013-44917-R and SLWAMED CGL2014-58127-C3-2, of the Ministry of Economy and Competitiveness of the Spanish Government. Both projects were co-financed with FEDER ...

310 329 541 ; S ; This paper analyzes the Girona River (Spain) flash flood, occurred on the 12th of October 2007, combining hydrological and hydraulic modeling with geomorphologic mapping and post-flood survey information. This research aims to reproduce the flood event in order to understand and decipher the flood processes and dynamics on a system of prograding alluvial fans. The hydrological model TETIS was used to characterize the shape and dimension of the October 2007 Girona River hydrograph. Subsequently, the flood event was reproduced using the free surface flow module of the model RiverFlow2D. The combination of hydrological and hydraulic models was evaluated using post-flood surveys defining maximum flooded area and flood depths. Then, simulations with different peak discharges were carried out to estimate the hydro-geomorphologic response of the Girona River floodplain, through the identification of the activation thresholds in different geomorphic elements. Results showed that the unit peak discharge of the October 2007 flood event (5 m3 s−1 km−2) was among the largest ever recorded in the area, according to the existing literature. Likewise, the hydraulic model showed a good performance in reproducing the flood event (FitA = 76%, RMSE = 0.65 m and NSE = 0.6), despite the complexity of the case, an ephemeral and ungauged river. The model simulation revealed the existence of an activation pattern of paleochannels and alluvial fans, which was altered by the presence of some anthropogenic disturbances. This multidisciplinary approach proved to be a useful strategy for understanding flash flood processes in ungauged catchments. It allowed understanding the mechanisms governing floods in alluvial fans systems and it represented a solid contribution for early warning plans and risk mitigation policies. This collaborative research was financed with the projects CGL2013-44917-R and SLWAMED CGL2014-58127-C3-2, of the Ministry of Economy and Competitiveness of the Spanish Government. Both projects were ...

Abstract. The countries of Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan in Central Asia are highly prone to natural hazards, particularly floods, earthquakes, and landslides. The European Union, in collaboration with the World Bank and the Global Facility for Disaster Reduction and Recovery (GFDRR), created the programme Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) to advance disaster and climate resilience in the region. As part of the SFRARR project, the "Regionally consistent risk assessment for earthquakes and floods and selective landslide scenario analysis for strengthening financial resilience and accelerating risk reduction in Central Asia" was developed to achieve the project's objectives. This article presents the data, model, methodology, and results for the five Central Asian countries of the flood risk assessment, which represents the first high-resolution regional-scale transboundary risk assessment study in the area aiming to provide tools for decision-making. The output information will inform and enable the World Bank to initiate a policy dialogue. A fully probabilistic risk assessment for fluvial floods has been carried out for these countries to support regional and national risk financing and insurance applications, including potential indemnity and/or parametric risk financing solutions for a regional programme. A homogenised risk assessment methodology for the five countries and across multiple hazards (floods and earthquakes) and asset types has been adopted to obtain strategic financial solutions consistent across geographical areas and economic sectors. The largest relative (to the total exposed value) expected annual damages are found in Kazakhstan and Tajikistan, with values above 6 ‰. In the five considered countries, the largest relative expected annual damages by sector are found for the transport and agricultural sectors. Climate change is expected to have contrasting impacts, with increases in risk for some regions (the most severe increase is found in the Mangistauskaya region in Kazakhstan) and decreases for other regions (Lebap, Turkmenistan; Khatlon, Tajikistan; Samarkand, Uzbekistan; and Batken, Kyrgyz Republic).