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This research validates the CCHE2D hydrodynamic model flood simulation results using a series of satellite imagery and several digital image processing techniques. Previously CCHE2D model simulation results have been validated using measured experiment and field channel flow data. In this study, remotely sensed data has been experimented to provide...
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... C(x) is the mean of the cluster that pixel x is assigned to, N is the number of pixels, c indicates the number of clusters, and b is the number of spectral bands. Density Slicing Density slicing is a digital data interpretation method used in analysis of remotely sensed imagery to enhance the information gathered from an individual brightness band. Density slicing is done by dividing the range of brightness in a single band into intervals, then assigning each interval to a color (Campbell, 2002). In the near infra-red (NIR) spectral channel water usually absorbs most of the incident energy of sunlight (Hossain and Easson, 2007). This concept was applied in this study ( Fig. 3a) and we subset the band 4 (NIR) of Landsat 5/7 and AVNIR 2 imagery and band 2 (NIR) of MODIS imagery to generate the land-water classified imagery. The NIR band was sliced into 256 levels of brightness and a threshold value was obtained to separate water from all non-water features in the study site. The threshold value was determined by using the thematic clusters derived from unsupervised classification scheme using the ISODATA clustering algorithm. The obtained threshold values are 40 and 51 for Landsat 5 TM imagery acquired on April 29 and June 16, 2008; 45 and 32 for MODIS imagery acquired on June 17 and 19, 2008; and 45 for ALOS AVNIR2 imagery acquired on June 21, 2008 respectively. Using these threshold values a spatial model (Fig 3b) was developed in ERDAS Imagine 9.2 image processing software to generate the flood maps, and flood extent maps were produced for each image acquisition dates during flood event. Fig. 4 shows the generated flood extent imagery displayed on the Landsat 7 ETM+ imagery acquired in June, 2003. CCHE2D was applied to study the flood propagations of the Midwest flood 2008. The CCHE2D finite element model for free surface flows was modified to compute the flood propagation. Unlike most of the flood models that solve only the shallow water equations, terms for taking into account of turbulence effects are also included in the modified CCHE2D flood model, because the simulations have to deal with the subcritical channel flow in the main channel of the Mississippi River and the super critical levee breaching flows. The CCHE2D flood model is a special version of the general CCHE2D model using an explicit time marching scheme. The explicit computation is necessary to handle the levee breaching flow efficiently near breaching locations and around breaching time. However, after the breached levees are completely open, and the flows in its vicinity become less rapid, a more efficient implicit method should be applied to speed up the overall computation. In this study, the levee breaching and flood propagation were computed using a hybrid explicit/implicit solution method which greatly speeded up the computation and reduced the total computation time. There were seven levee breaching observed in the studied flood zone. Five of them were along the right levee and two of them occurred on the left levee just downstream of the lock and dam 20 of the Mississippi River. ALOS PRISM imagery acquired at 2.5 m resolution was used to identify the locations and dimensions of these breaching (Fig. 5a), which were used for the flood simulation as input parameters. Lacking knowledge about how these levees were breached: overtopping, collapsing or due to piping, it was assumed all the beaching involved were due to overtopping which induced a vertical incision with a constant erosion rate. To make the computations more efficient, widths of the breaching observed with satellite imagery (Fig. 5a) were used for flood simulation. The computations were conducted using a 198x550 quadrilateral mesh. The topography of the simulation domain is shown in Fig 5b. The Manning’s roughness coefficients in the main channel of the Mississippi River and over the flood plains were estimated using the land use and land cover information obtained from remote sensing data (Fig.5c). The levees along the river were represented with two lines of mesh. The observed unsteady flow discharge and water surface elevation were applied for boundary conditions. The CCHE2D Flood simulation results were validated using the remote sensing derived flood extent imagery in both qualitative and quantitative ways. In qualitative validation the simulation results for the available image acquisition dates and time were extracted and displayed on the non-flooded imagery in conjunction with the satellite observed flood extent imagery at a constant scale and visually compared (Fig. 6). In quantitative validation 33 frames of the simulated flood scenarios were converted to vector data and the areas were calculated for flood inundation in each frame using the tools in ArcGIS 9.3. The calculated areas were plotted against simulation time steps. Areas of the satellite observed flood extent ...
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Citations
... is is an integrated package for simulation and analysis of free surface flows, sediment transport, and morphological processes. Hossain et al. [15] examination approves the CCHE2D hydrodynamic model flood replication results utilizing a progression of satellite imagery and a few advanced digital image processing procedures. Kim [16] studied the changes in the bed of the Geum River in South Korea by using the CCHE2D model. ...
Distribution of flow and velocity in a meandering river is important in river hydraulics to be investigated from a practical point of view in relation to the bank protection, navigation, water intakes, and sediment transport-depositional patterns. When flow enters a bend, the centrifugal force arising from the channel curvature leads to a transversal slope in the water surface. The interaction between the centrifugal force and transversal pressure gradient causes secondary flows in cross-sections, and the secondary flows spread further by moving along the bend. Hence, at the bends, these processes lead to longitudinal velocity increase in the inner wall and decrease at the outer wall. In this paper, experimentation is carried out for two different bed roughness on a 4.11 sinuosity meandering channel with 110° crossover. Longitudinal velocity distribution is analysed with the graphical illustrations for the detailed experimental study. Study of flow profile across the crossover is also particularly important as the inner bank of the bend changes to the outer bank and vice versa which has a significant effect on the water surface profile and hence on the velocity distribution along the full meander path. The objective of the analysis is to determine the effect of curvature and roughness on the velocity profiles, throughout the meander path. It is determined that the resistance of flow, on the smoother bed channel, is higher than that of the channel with higher Manning’s n above a certain depth at the apex and transition sections. A reciprocal study of the experimental investigation is attempted with a numerical hydrodynamic tool, namely, CCHE (Centre for Computational Hydroscience and Engineering) developed by NCCHE, University of Mississippi, US. The model is applied to simulate the inbank flow velocity distribution and validate the experimental observation for the meandering channel with rough bed.
... ) and density slicing technique (Campbell 2002; Hossain et al. 2009) and by classifying areas as water and nonwater to separate the areas occupied by different water bodies in the study site. The ISODATA clustering algorithm was applied on the optical imagery (Landsat-5 TM data) and density slicing technique was applied on the microwave imagery (Radarsat-1 SAR and ERS SAR data). ...
Recent research in mesoscale hydrology suggests that the size of the reservoirs and the land-use/land-cover (LULC) patterns near them impact the extreme weather [e.g., probable maximum flood (PMF)]. A key question was addressed by W. Yigzaw et al.: How do reservoir size and/or LULC modify extreme flood patterns, specifically PMF via modification of probable maximum precipitation (PMP)? Using the American River watershed (ARW) as a representative example of an impounded watershed with Folsom Dam as the flood control structure, they applied the distributed Variable Infiltration Capacity (VIC) model to simulate the PMF from the atmospheric feedbacks simulated for various LULC scenarios. The current study presents a methodology to extend the impacts of these modified extreme flood patterns on the downstream Sacramento County, California. The research question addressed is, what are the relative effects of downstream flood hazards to population on the American River system under various PMF scenarios for the Folsom Dam? To address this goal, a two-dimensional flood model, the Flood in Two Dimensions–Graphics Processing Unit (Flood2D-GPU), is calibrated using synthetic aperture radar (SAR) and Landsat satellite observations and observed flood stage data. The calibration process emphasized challenges associated with using National Elevation Dataset (NED) digital elevation model (DEM) and topographic light detection and ranging (lidar)–derived DEMs to achieve realistic flood inundation. Following this calibration exercise, the flood model was used to simulate four land-use scenarios (control, predam, reservoir double, and nonirrigation). The flood hazards are quantified as downstream flood hazard zones by estimating flood depths and velocities and its impacts on risk to population using depth–velocity hazard relationships provided by U.S. Bureau of Reclamation (USBR). From the preliminary application of methodology in this study, it is evident from comparing downstream flood hazard that similar trends in PMF comparisons reported by W. Yigzaw et al. were observed. Between the control and nonirrigation, the downstream flood hazard is pronounced by −3.90% for the judgment zone and −2.40% for high hazard zones. Comparing the control and predam scenarios, these differences are amplified, ranging between 0.17% and −1.34%. While there was no change detected in the peak PMF discharges between the control and reservoir-double scenarios, it still yielded an increase in high hazard areas for the latter. Based on this preliminary bottom-up vulnerability assessment study, it is evident that what was observed in PMF comparisons by W. Yigzaw et al. is confirmed in comparisons between control versus predam and control versus nonirrigation. While there was no change detected in the peak PMF discharges between the control and reservoir-double scenarios, it still yielded a noticeable change in the total areal extents: specifically, an increase in high hazard areas for the latter. Continued studies in bottom-up vulnerability assessment of flood hazards will aid in developing suitable mitigation and adaptation options for a much needed resilient urban infrastructure.
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A large number of embankment structures, including dams, levees,
dikes, and barriers, have been built by humans or formed naturally
along rivers, lakes, and coastal lines around the world. Most of
these structures play very important roles in flood defense,
although many are also used for water supply, power generation,
transportation, and sediment retention. Because these structures can
sustain only limited safety levels and are subject to decay, they may
fail owing to various triggering mechanisms (Costa 1985; Foster
et al. 2000; Allsop et al. 2007), particularly with a high probability
of failure under extreme conditions. These failures pose significant
flood risks to people and property in the inundation area and cause
an interruption of services provided by these structures. Examples
of such events include the failure of the Teton Dam in 1976 (Ponce
1982) and the New Orleans levee failures during Hurricane Katrina
in 2005 (Sills et al. 2008), as shown in Figs. 1 and 2. Clearly, understanding
and prediction of embankment failure processes are crucial
for water infrastructure management.
The humid tropics are generally resource-rich lands. They possess adequate water supply, naturally fertile soils, and a favorable terrain. The morphology of these areas ranges from flat lowland delta to river valleys associated with gently rolling uplands. Most of the major deltas in the world (e.g., Ganges, Mississippi, Niger, Okavango, and Mekong deltas) host large population centers, megacities, complex irrigation systems, and a water-sensitive ecosystem because of their easy access to abundant fresh water and fertile soils. Humid deltas of developing nations support extensive agricultural production. Flooding (extreme and normal) is recurrent in these humid deltas. Floods promote as well as hamper agricultural productivity (depending on the magnitude and spatial extent). Therefore, the socioeconomic fabric of the rural areas of humid deltas in developing nations is intricately related to recurrent flooding, agricultural productivity, and crop loss patterns.
