Development of Morphologically Consistent Digital Elevation Model for Improving Riverine Flood Impact Assessment in Data-Poor Areas
نام عام مواد
[Thesis]
نام نخستين پديدآور
Bhuyian, Md. Nowfel Mahmud
نام ساير پديدآوران
Kalyanapu, Alfred J.
وضعیت نشر و پخش و غیره
نام ناشر، پخش کننده و غيره
Tennessee Technological University
تاریخ نشرو بخش و غیره
2019
مشخصات ظاهری
نام خاص و کميت اثر
196
یادداشتهای مربوط به پایان نامه ها
جزئيات پايان نامه و نوع درجه آن
Ph.D.
کسي که مدرک را اعطا کرده
Tennessee Technological University
امتياز متن
2019
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
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.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Civil engineering
موضوع مستند نشده
Geomorphology
موضوع مستند نشده
Hydrologic sciences
موضوع مستند نشده
Natural resource management
موضوع مستند نشده
Remote sensing
موضوع مستند نشده
Water resources management
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )