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Simulation of Dam-Break Flood Wave and Inundation Mapping: a Case Study of Attabad Lake

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Simulation of Dam-Break Flood Wave and Inundation Mapping: a Case Study of Attabad Lake ISSN 2347 - 3983 Wasim Karam et al ., International Journal of EmergingVolume Trends 9. No. in Enginee 6, Junering 2021 Research, 9(6), June 2021, 703 – 714 International Journal of Emerging Trends in Engineering Research Available Online at http://www.warse.org/IJETER/static/pdf/file/ijeter15962021.pdf https://doi.org/10.30534/ijeter/2021/15962021 Simulation of Dam-Break Flood Wave and Inundation Mapping: A Case study of Attabad Lake Wasim Karam 1 , Fayaz A. Khan 2 , Muhammad Alam 3 , Sajjad Ali 4 1 Lab. Engineer, Department of Civil Engineering, University of Engineering and Technology Mardan, Pakistan, [email protected] 2 Assistant Professor, National Institute of Urban Infrastructure Planning, University of Engineering and Technology Peshawar, Pakistan, [email protected] 3,4 Assistant Professor, Department of Civil Engineering, University of Engineering and Technology Mardan, Pakistan, [email protected], [email protected] ABSTRACT 1. INTRODUCTION The break study of Landslide or embankment dams is more To establish sustainable management of the water resources essential due to uncertainty in their composition and lack of dams are much necessary. Dams are constructed to obstruct knowledge of their response to other natural events because the flow path of a river stream and make good use of the water they are natural and not properly designed for any disaster. that is ponded upstream of the structure. Dams can be The paper aims to improve different methods of hydraulic classified in many ways, Based on the material of the dam, modeling of dam break. In this present study dam break of dams are classified into embankment dams, concrete dams, Attabad lake is simulated using the computational fluid and masonry dams [1]. More of the same a lake is a natural dynamics technique. The numerical model (FLOW-3D) is pool of water caused by blockage of the river or underground developed to solve the Reynolds averaged Navier-Stoke stream. equation fully in 3D to predict peak flow depth at different cross-sections, peak velocity, peak discharge, time to peak Dam serves a variety of purposes such as water supply for depth, and time to peak discharge. The standard RNG irrigation, for drinking purposes, flood protection and turbulence model is employed to simulate turbulence and then generation of electric power, recreation and navigation, etc. flood inundation maps and velocity vectors for flow at villages [2] . However, despite all the safety that is incurred in its are drawn. The results show that most of the flood wave design, there always lies a risk of breaching in dams. Dams modeled through the Hunza river channel, is contained by the may fail due to large earthquakes, insufficient spillway flood plain of Hunza River but for some of the villages i.e. capacity, piping, seepage, and extreme storms [3] . A dam Miaun and chalat, which are situated inside the flood plain of break is a complete or incomplete catastrophic failure of a dam Hunza River are at higher risk of inundation but the flood that causes an uncontrolled release of water. The flood wave arrival time estimated for these villages is 31 and 44 min travels at a very high speed in the downstream reach of the respectively which is enough time for the evacuation of the channel. Dam Breaks has some devastating consequences population to safer areas while for some villages like Hassan including damage to property and infrastructure, loss of life. Abad situated adjacent to Ali Abad is at higher risk of On the other hand, it also possess some serious ecological inundation while the estimated flood arrival time for the impacts. [4] village is 12 min which are not enough for the evacuation of the population hence will need some extra flood protection The most common concern about dam break failures is that structures for flood containment. The estimate of the peak they are abrupt which causes immediate flooding downstream velocities implies higher shear stress in the river plain, risk of of the dam which leaves very little time for evacuation of heavy erosion, damage to agricultural lands, residencies, and residents or protection of the property. In contrast flooding morphological changes are projected. The analysis of the dam from the rainfall or snowmelt can be predicted days or weeks break i.e. Peak depths, Peak Velocities, flood arrival time, and in advance. That’s why Dam breaks kill thousands of people flood inundation maps should only be used as a guide in future across the globe. Some notable dam breaks are Malpasset risk analysis and flood management. dam-break failure in France in 1959 (killed 500 people), Vaoint dam failure in Italy in 1963 (killed 2600 people), Teton Key words: Attabad Lake, Computational Fluid Dynamics, dam failure in Idaho United states in 1976 (killed 11 people Dam Break Simulation, FLOW-3D, Flood inundation and 13000 cattle). Emergency action plans have to be prepared Mapping, Navier stokes equation, Three dimensional Model. for every dam higher than 20 m with a reservoir volume over 15Mm 3 [5]. Therefore accurate estimates of the flood arrival time, flow depths, velocities are important for emergency planning and flood hazard assessment because of the very least 703 Wasim Karam et al ., International Journal of Emerging Trends in Engineering Research, 9(6), June 2021, 703 – 714 margin that we have in contrast to the flooding from rainfall or gradually varied [8]. This means that changes in channel snowmelt. Since the most important part of flood hazard properties, such as cross-section shape, invert level, flow assessment is the delineation of the flood plain and the depth, and pressure distribution, are negligible at shorter identification of high-risk areas [6]. Hence predicting the distances. Which makes it hard for these models to simulate high-risk areas is possible by drawing the flood inundation areas of rapid acceleration or deceleration. The numerical maps. However, to predict these quantities we need to solve solution used by two-dimensional hydraulic models is usually the governing equations they are unsteady and contain terms of based on a shallow water equation, from which the pressure gradient, viscosity which need a lot of boundary Saint-Venant equation is derived for unidirectional flow. conditions making it very difficult to solve them manually for Traditionally, the mesh has been a fixed-space rectilinear grid with the governing equations solved. But two-dimensional such complex situations. Either, we can use scale-down hydraulic models assume that flow is one- or two-dimensional, models but scale-down models can describe a very limited vertical variations in the flow properties are neglected [9]. amount of problems with very limited operating conditions. Then comes the 3D models which can easily simulate the Moreover, scale-down models in cases of dam-break are also downstream, lateral, and vertical components of flow. not very efficient because replicating the complex bed topography in the laboratory can be a very expansive and Robb and Vasquez investigated the capability of two fully laborious job. To do so even for simple dam-break scenarios three-dimensional computational (3D) fluid dynamics models and non-variant bed topography a lot of technical assistance and one two-dimensional (2D) depth-averaged model. They and financial resources are required. Alternatively, Flood found out that the results from CFD models (3D) show quite an inundation maps are obtained by simulating the flood through improvement over those from the depth-averaged model (2D). the terrain with the given initial and boundary conditions using [4] Numerical Models. Numerical models discretize the partial Ozmen-Cagatay and Kocaman presented an experimental differential equations and give an approximate solution to the and numerical investigation of the dam-break flow in the problem. With the help of numerical models we can analyze presence of obstacles over initially dry bed conditions. A any fluid dynamics problem for the actual flow domain and comparison was made between the shallow water equation, virtually any realistic operating conditions. Reynolds’s Averaged Navier Stoke Equation, and physical model. The experimental setup contained a rectangular The discretization techniques that are normally in use are channel 8.9m long, 0.3m wide, and 0.34m high. FLOW-3D the finite difference method, finite volume method, and finite was used for numerical investigation solving RANS Equation with k-e Turbulence Model and it was concluded that the shallow water equation is capable of generating free surface profiles and the process requires less CPU time for large computational domains. The measuring technique adopted in the experiment yields accurate results and the RANS model reproduces the flow under investigation with reasonable accuracy while the simple SWE model indicates some discrepancies particularly in predicting the negative wave propagation. [10] L. Toombes and H. Chanson performed an experiment on the weir and examined the validity of different numerical models. They verified the predictions of the models against physical data. 4 different hydraulic models i.e. FLOW 3D, HEC-RAS, MIKE11, and MIKE 21 were used to simulate flow over a weir and flow in a sloppy channel with a hydraulic Figure 1: Finding solution to fluid dynamics problems jump and found that Flow 3D with its ability to model vertical element method. For this purpose, many numerical modeling velocity component, flow accelerations and non-hydrostatic tools are used. As the Figure 1 shows we can analyze a pressure produce accurate results matching the results of the problem for all desired quantities and with high resolution in physical model. Moreover, they concluded that the inability of space and time. Numerical models are Quantitative 1-D models to simulate supercritical flow and the ‘water predictions of a flow phenomenon. These models make some column’ effect of two-dimensional models can cause approximations to solve the principles that govern the significant inaccuracy in model predictions.
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