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Analysis of Sinkhole Susceptibility and Karst Distribution in the Northern Shenandoah Valley, Virginia: Implications for Low Impact Development (LID) Site Suitability ModelsHyland, Sara Elizabeth 15 June 2005 (has links)
Increased stormwater runoff due to urban development in the northern Shenandoah Valley (NSV) region of Virginia has prompted local officials and representatives to consider Low Impact Development (LID) as a stormwater management technique. LID is based on infiltrating stormwater runoff at the source through practices such as bioretention, rain gardens, and grass swales. The karst terrain that underlies the Shenandoah Valley presents a major barrier to the use of LID. Infiltration of surface runoff in karst landscapes may threaten groundwater quality and the stability of the bedrock. In 2004 the Center for Geospatial Information Technology (CGIT) at Virginia Tech developed an LID site suitability model for the NSV region incorporating karst as a key component in distinguishing unsuitable from suitable conditions for LID. But, due to the difficulty of mapping karst, the karst layer used in the site suitability model is very coarse in resolution, based primarily on carbonate versus non-carbonate rock.
This study uses a 1:24,000 scale sinkhole map derived from sinkhole boundaries identified by geologist David Hubbard (1984) of the Virginia Department of Mines and Minerals (DMME) to develop a more detailed karst map for a sub-watershed of the NSV region. The analysis uses geospatial techniques to determine the relationship between sinkhole distribution and four major landscape factors: bedrock type, soil depth to bedrock, proximity to geologic faults, and proximity to surface streams. The analysis identified three major trends in sinkhole occurrence: (1) sinkholes are more abundant in relatively pure carbonate rocks of Ordivician age; (2) sinkhole occurrence increases with proximity to fault lines; and (3) sinkholes are sparse near streams, most abundant 600 to 1400 feet away from surface streams. Based on these findings a sinkhole susceptibility index was produced using weighted overlay analysis in ArcGIS. The sinkhole susceptibility index provides a more detailed karst layer for the LID site suitability maps and can be used by the NSV region as a predictive tool for future sinkhole occurrence. / Master of Science
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Flood Impact Analysis using GIS : A case study for Lake Roxen and Lake Glan - SwedenVaghani, Vimalkumar January 2005 (has links)
<p>Floods are common natural disaster occurring in most parts of the world. This results in damage to human life and deterioration of environment. There have been immense uses of technology to mitigate measures of flood disaster i.e. structurally and non-structurally. Undoubtedly, structural measures are very expensive and time consuming which involves physical work like construction of dams, reservoirs, bridges, channel improvement, river diversion and other embankments to keep floods away from people. Whereas non-structural measures is concerned with planning like flood forecasting and warning, flood plain zoning, relief and rehabilitation for reducing the risk of flood damage to keep people away from floods. Thus, non-structural measures involve analysis, planning providing spatial information on maps with high accuracy in less time. Non-structural measures can help decision maker to plan an effective emergency response towards flood disaster. A one of the good way to plan non-structural measures is to analyze impact of flood in the flood prone areas. The thesis tries to analyze impact of flood on environment along the demarcated flood prone areas of Lake Roxen and Lake Glan in Östergötland County, Sweden. The thesis also proposes how to use current flood information during flood emergency utilizing geographical information system. This provides spatial information for area in the flood zone for assessment regarding flood vulnerability.</p><p>Using map overlay analysis in GIS software (ArcGIS); flood prone areas and topographic data along Lake Roxen and Lake Glan were digitized from PDF maps. Thus, the thesis work is an effort to analyze impact of flood when areas along Lake Roxen and Lake Glan are flooded. ESRI® GIS software Arc Map 9 and Arc View 3.3 is used for data preparation, integrating, analyzing, and spatial data with attribute table information. Finally, to show GIS can be an effective tool for development of flood emergency system as a part of disaster preparedness by the decision makers.</p>
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Flood Impact Analysis using GIS : A case study for Lake Roxen and Lake Glan - SwedenVaghani, Vimalkumar January 2005 (has links)
Floods are common natural disaster occurring in most parts of the world. This results in damage to human life and deterioration of environment. There have been immense uses of technology to mitigate measures of flood disaster i.e. structurally and non-structurally. Undoubtedly, structural measures are very expensive and time consuming which involves physical work like construction of dams, reservoirs, bridges, channel improvement, river diversion and other embankments to keep floods away from people. Whereas non-structural measures is concerned with planning like flood forecasting and warning, flood plain zoning, relief and rehabilitation for reducing the risk of flood damage to keep people away from floods. Thus, non-structural measures involve analysis, planning providing spatial information on maps with high accuracy in less time. Non-structural measures can help decision maker to plan an effective emergency response towards flood disaster. A one of the good way to plan non-structural measures is to analyze impact of flood in the flood prone areas. The thesis tries to analyze impact of flood on environment along the demarcated flood prone areas of Lake Roxen and Lake Glan in Östergötland County, Sweden. The thesis also proposes how to use current flood information during flood emergency utilizing geographical information system. This provides spatial information for area in the flood zone for assessment regarding flood vulnerability. Using map overlay analysis in GIS software (ArcGIS); flood prone areas and topographic data along Lake Roxen and Lake Glan were digitized from PDF maps. Thus, the thesis work is an effort to analyze impact of flood when areas along Lake Roxen and Lake Glan are flooded. ESRI® GIS software Arc Map 9 and Arc View 3.3 is used for data preparation, integrating, analyzing, and spatial data with attribute table information. Finally, to show GIS can be an effective tool for development of flood emergency system as a part of disaster preparedness by the decision makers.
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