Flood Modeling and Vulnerability Assessment in Ialomita River Basin, Romania
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Flood Modeling and Vulnerability Assessment in Ialomita River Basin, Romania Maria Cheveresan Technical University of Civil Engineering Bucharest, Romania [email protected] Abstract The floods from recent years are becoming more and more severe causing death of people and material losses. The floods with the probability of excedance of 1% are more frequent, phenomena due mainly to the climate change. In this context the lack of hazard and vulnerability maps at a river basin scale which should prevent the construction of new buildings in flood prone areas, lead to inevitable losses on long term. This paper treats the high water flow regime in Ialomita river basin and simple and efficient methods for assessing the vulnerability. Among the causes which generate floods are heavy rainfall and dam breaks which can produce real disasters downstream the section where they occur. Mathematical modeling, with the latest software generation, gives complete and detailed answers regarding flood extensions lag time for flood propagation, maximum velocities and depths in the studied area. Two accidental flood propagation models were created in case of four scenarios of Dridu dam failure, using Mike 11 and Mike 21. Comparing the results of these models differences were found due mainly to input data, noting that the 2D model gives the most accurate results. The resources invested in the creation of 2D models overpasses, as it was expected the creation of a 1D model from the data acquisition point of view but also because of the large computation time (aprox.30 hours for 190 de km river stretch). The vulnerability on Dridu-Tandarei reach in the worst case scenario of Dridu dam failure was evaluated based on economical and social indices as well as on the characteristics of the flood waves. Taking into account the lack of data and difficulties which may appear when assessing the vulnerability by tens of indices, a statistical approach was proposed leading to fast results. Keywords: Flooding, hazard maps, probabilities of exceedance, vulnerability assessment, statistics Introduction Ialomita river basin is situated in the south east part of Romania having 10.430 km2. In 2005 a severe flood caused great economical damage which practically reached the magnitude of 1% flood. Based on this event two hydraulic 1D and 2D models were created and calibrated and further used for assessing hazard maps for Ialomita river (main river in the basin) and for modeling dam break failure scenarios. The worst case scenario for dam failure was taken into account for vulnerability assesment in a statistical approach offering information for further evaluation of qualitative risk in Ialomita river basin. BALWOIS 2012 - Ohrid, Republic of Macedonia - 28 May, 2 June 2012 1 Figure 1. Location of Ialomita river basin Propagation of the flood wave caused by dam failure scenarios Dridu dam is situated at the junction of Ialomita River with Prahova River having an important role in the flood attenuation which can occur when the two flood waves are compounded. Four failure scenarios were proposed for Dridu dam taking into account the exploitation history and the incidents which occurred since the putting into operation (Table 1 [Stematiu&Sirbu, 2009). The worst scenario (2b), for which it is considered that one of the front tile of the dam structure would slide downstream, generates a flood wave with a maximum discharge of 2361 m3/s which is close to the 0,1% maximum discharge. Further in this analysis the worst case scenario 2b will be considered. Table 1 [Stematiu&Sirbu, 2009] Scenario Maximum inflow Maximum discharge of the flood wave Duration of the flood caused discharge (m3/s) caused by the dam failure (m3/s) by dam failure (h) 1 - 1349 47 2a 1280 2237 116 2b 1330 2361 76 3 420 1398 144 BALWOIS 2012 - Ohrid, Republic of Macedonia - 28 May, 2 June 2012 2 1D model setup For the 1D simulation of the worst case scenario a model was created and calibrated in Mike 11 for Ialomita river stretch between Dridu and Tandarei. The boundary conditions used in this 1D model were the accidental flood wave at the upstream end and the rating curve at the downstream end. The extension of the flood in case of 2b scenario can be seen in Fig. 1. Figure 1. Maximum extension of the flood in case of the 2b failure scenarios obtained through 1D modeling 2D model setup For the creation of the 2D model on the area of interest between Dridu and Tandarei, HD module from Mike 21 was used setting the following elements: -DTM in the modeled area as fix grid having 40m x 50m resolution (Fig.2) -Simulation time step (10s) and simulation time (10 days) – the real time for computation on an Intell 2 core duo 4GB DIM was in average 30 hours -Boundary conditions -Drying (0.02 m)/flooding (0.03 m) depths conditions -Initial conditions grid with initial water level on the modeled area -Eddy viscosity parameter – 0.04 m2/s -Roughness coefficients as Manning M ranging between 20-40 m1/3/s Figure 2. DTM on Dridu-Tandarei river stretch BALWOIS 2012 - Ohrid, Republic of Macedonia - 28 May, 2 June 2012 3 The simulation was done in several phases by generating Hot Start files at the end of each phase which was used as initial conditions for the next ones. Maximum depths and velocities were obtained for each grid cell in the modeled area (Fig. 3 and 4). Figure 3. Maximum water depths on Dridu-Tandarei River stretch in case of 2b scenario Figure 4. Maximum velocities on Dridu -Tandarei River stretch in case of 2b scenario Comparison between 1D and 2D model on Dridu Tandarei river stretch The results from the 1D model and those for the 2D model in case of the worst scenario for Dridu dam failure were compared in order to determine advantages and disadvantages of using these models. The first comparison aspect referred to data used in the two models. 1D models require less topographical data than 2D models, where continuous information is required with a precision of cm. This difference is reflected in the results meaning that 1D models provide sparsely results in the longitudinal profile (sometimes based on interpolated cross sections) and constant in transversal direction. The 2D models BALWOIS 2012 - Ohrid, Republic of Macedonia - 28 May, 2 June 2012 4 offer much more results in a continuous manner like maximum depths and velocities grids. From the precision point of view, 1D models provide a flood area by intersection with the DTM. The 2D models calculate through the 2D Saint Venant equations much more precise results for each grid cell in the river bed and flood area. From the maximum discharge point of view the two models were analyzed in 5 significant cross sections along the modeled stretch. The discharges obtained through 2D modeling are with approximately 28% lower than the results from the 1D model. The propagation times are in average with 40% higher for the 2D model than the 1D model results. Figure 5. 1D propagation in Dridu, Cosereni, Ciochina, Slobozia and Tandarei cross sections Figure 6. 2D propagation in Dridu, Cosereni, Ciochina, Slobozia and Tandarei cross sections Comparing the water depths in the two models it came out that the differences are in both directions, positive as well as negative (Fig.7) BALWOIS 2012 - Ohrid, Republic of Macedonia - 28 May, 2 June 2012 5 Figure 7. Differences in water depths for the 1D and 2D models Vulnerability assessment in Ialomita River Basin In order to asses the vulnerability in case of Dridu dam a list of vulnerability indicators were proposed (Table 2). Table 2 Vulnerability Indicators Indicators’ component abreviation Social Total number of inhabitants in the affected area NLZA Total number of inhabitants over 70 years of age NL70 Total number of children under 3 years of age NC3 Economical Total number of affected houses NCA Total numer of bridges NP Total length of affected roads LDA Total length of affected railways LCFA Total surface of affected agricultural terrain STAA Total surface of affected forests SPA Total number of cows in affected area NBZA Total number of pigs in affected area NPZA Total number of sheep in affected area NOZA Total number of goats in affected area NCZA Environmental Surface of protected areas SZP Total number of landfill deposits in the affected area NDDZA A statistical approach allows for a social and economical assessment of the vulnerability with good precision and limited resources. The indicators proposed for the assessment of the vulnerability offer qualitative information about the vulnerable objects in the analyzed area. From this total only 10% will produce real damages. According to the data published on the National Institute of Statistics and the Ialomita County Institute of Statistics websites the population density was 66,6 inhabitants/km2 in 2002. Knowing the flood extension area, it is possible to assess the total surface of the flooded settlements and consequently the total number of affected inhabitants. The same source provides information about the BALWOIS 2012 - Ohrid, Republic of Macedonia - 28 May, 2 June 2012 6 population division on age categories. In case of flooding or other major disasters the age plays an important role in evacuating the population, persons over 70 of age and children under 3 years of age being much more vulnerable than the rest of population. Statistical data regarding population distribution on age categories in percentages in Ialomita County and the distribution of the number of inhabitants in every settlement in Ialomita County can be found in Tables 3 and 4: Table 3.Population on age classes in percentages for Ialomita County GRUPA DE VARSTA SEXUL POPULATIA REGIUNEA DE DEZVOLTARE STABILA 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75 ani JUDETUL TOTAL ani ani ani ani ani ani ani ani ani ani ani ani ani ani ani si peste A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 IALOMITA 100.0 5.4 5.6 7.5 7.2 6.9 7.7 9.5 5.0 6.1 6.9 6.1 5.0 5.7 5.8 4.5 5.0 Table 4.