Long-term bed degradation in Maryland streams (phase 3, part I) : urban streams in the Piedmont Plateau province.
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2014-05-01
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Abstract:Estimation of potential long-term down-cutting of the stream bed is necessary for evaluation and design of bridges for scour and culverts for fish passage. The purpose of this study has been to improve predictions of this potential long-term bed degradation (LTBD) in Maryland streams through the measurement and analysis of stream bed and waterway structure survey data and bridge plans. Long-term bed degradation was defined as the vertical change in the channel profile other than that caused by local or contraction scour. Part 1 of a two-part study of urban streams in the Piedmont Plateau province was completed. Many sites were selected for sampling; the remainder of the sample will be selected in Part 2. The range of watershed drainage areas of the selected LTBD sampling sites is 0.2 mi2 to approxi- mately 40 mi2; only one site, however, has a drainage area greater than 6 mi2. The current range of impervious area of the LTBD sampling sites is approximately 19% to 58%, but only one site has an impervious area of less than 25%. The current range of valley slopes of the LTBD sampling sites is approximately 0.5% to 4%. Given the high correlation of LTBD with valley slope found in previous investigation of LTBD and the lack of data for Part 1 sites with slopes lower than 0.5%, additional data on streams with less than 0.5 % slope is needed and will be collected in Part 2. A database of preliminary estimates of LTBD was initiated. Additional data collection in regions of the urban Piedmont Plateau is required to cover the range of watershed areas, percentage of impervious area, and valley slope for a comprehensive assessment of LTBD in the urban Piedmont. Travel time and access were factors that increased the time required to screen and select sampling locations. Site selection, data collection, and analysis will be completed in Part 2 of this project. The results of this study are preliminary and should only be applied to assess data gaps.
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