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" Development of Morphologically Consistent Digital Elevation Model for Improving Riverine Flood Impact Assessment in Data-Poor Areas "
Bhuyian, Md. Nowfel Mahmud
Kalyanapu, Alfred J.
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Latin Dissertation
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English
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| Record Number
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1105415
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| Doc. No
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TLpq2309522496
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| Main Entry
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Bhuyian, Md. Nowfel Mahmud
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Kalyanapu, Alfred J.
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| Title & Author
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Development of Morphologically Consistent Digital Elevation Model for Improving Riverine Flood Impact Assessment in Data-Poor Areas\ Bhuyian, Md. Nowfel MahmudKalyanapu, Alfred J.
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| College
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Tennessee Technological University
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| Date
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2019
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| student score
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2019
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| Degree
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Ph.D.
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| Page No
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196
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| Abstract
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Flood Impact Assessment (FIA) is an integral part of flood risk management (FRM) that requires extensive data collection and rigorous modeling. Elevation data is one of the main inputs for this venture that is often fulfilled by digital elevation models (DEM). DEM provides a continuous representation of terrain and may cover a large area. However, the accuracy and details of terrain in a DEM depend on its source and spatial resolution. Regardless of the source and spatial resolution, DEMs most often do not provide accurate river bathymetric elevations thus misrepresent conveyance. Additionally, DEM is a static dataset providing a snapshot of the terrain during the time of data acquisition. Therefore, DEM cannot show any change in terrain that may have happened afterward. But, waterbodies such as rivers are among the most dynamic terrain features that change both in short (annual) and long term (decadal) scale. Therefore, representing the conveyance and capturing the planform dynamics of rivers in terrain dataset is especially critical for FIA. These shortcomings of a DEM is often addressed via merging ground surveyed data with DEM. However, collecting ground surveyed data is challenging in remote, inaccessible and data-poor areas. Thus, the objective of this dissertation is to assess the uncertainties in DEMs for representing river morphology (planform and conveyance) and propose DEM correction algorithms for producing morphologically consistent DEM to improve riverine FIA in data-poor areas. This dissertation has proposed three algorithms (or methods) that can predict planform and effective river conveyance for developing morphologically consistent DEM. The methods are Slope Adjusted Mean Bed Level Elevation (SAMBLE), River Bathymetry via Satellite Image Compilation (RiBaSIC) and Altimeter-based River Bathymetry via Satellite Image Compilation (Alt-RiBaSIC). They are designed to suit hydrologically well gauged, partially-gauged, and ungauged areas. The algorithms are tested on multiple rivers representing different river characteristics and varying levels of data-gap. The application of these algorithms for FIA over the Kushiyara River in Bangladesh showed DEMs corrected by each of these algorithms outperform the FIA via uncorrected DEM. Therefore, the algorithms are expected to be useful in FIA in other data-poor areas.
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Civil engineering
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Geomorphology
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Hydrologic sciences
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Natural resource management
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Remote sensing
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Water resources management
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