UVM Theses and Dissertations
Format:
Print
Author:
Pelletier, Keith C.
Dept./Program:
Natural Resources
Year:
2011
Degree:
MS
Abstract:
Sediment, either directly or in association with nutrients, is a major cause for impairment of rivers and streams, impacting drinking water, aquatic habitat, and recreational use. Improved understanding of the importance of fluvial erosion processes affecting sediment and nutrient loading on watershed scales is needed to effectively manage the ecological health of Lake Champlain and its tributaries. In this study, we examine the use of high-spatial resolution digital orthophotography, QuickBird satellite imagery and airborne LiDAR data within a GIS framework to quantify sediment loading due to stream channel lateral migration at watershed scales. Our study areas include Allen Brook and Indian Brook in northwestern Vermont. Stream lateral migration was mapped based on location changes of mapped stream centerlines digitized from imagery acquired in 1999,2004 and 2005.
Soil volume loss was then calculated as a function of overlapping stream centerlines over the time intervals ofthe imagery in combination with streambank height derived from the LiDAR data. Estimates of soil volume loss were then multiplied by measured soil bulk density data to estimate sediment loading and summarized by reach and watershed. Mean lateral, migration rates ranged from 0 -16m over the six year period represented by the imagery. Sediment loading was estimated at 961 MT yr⁻¹ and 1051 MT yr⁻¹ for Allen Brook and Indian Brook respectively over the 1999 -2005 study period. These results represent a significant improvement over previous limited point sampling approaches and confirm that lateral channel migration represents a significant source of sediment loading in these streams.
To estimate the impact of impervious surface areas on sediment loading to streams, total impervious area (TIA) and effective impervious area (EIA), that is the impervious area that is hydrologically-connected to nearby streams, were also quantified using enhanced digital elevation models (DEMs) derived from LiDAR data, QuickBird satellite imagery, object-based image analysis techniques, and hydrologic flow modeling. TIA across all subwatersheds within the two study areas ranged from 2% -27% although less than 1% ofthe total watershed was hydrologically-connected to either Allen or Indian Brook. These results demonstrate the potential of geospatial technologies to rapidly, reliably and cost-effectively support and improve upon traditional stream monitoring methodologies, and aid efforts, to partition, estimate and manage sediment loading on stream reach and watershed scales.
Soil volume loss was then calculated as a function of overlapping stream centerlines over the time intervals ofthe imagery in combination with streambank height derived from the LiDAR data. Estimates of soil volume loss were then multiplied by measured soil bulk density data to estimate sediment loading and summarized by reach and watershed. Mean lateral, migration rates ranged from 0 -16m over the six year period represented by the imagery. Sediment loading was estimated at 961 MT yr⁻¹ and 1051 MT yr⁻¹ for Allen Brook and Indian Brook respectively over the 1999 -2005 study period. These results represent a significant improvement over previous limited point sampling approaches and confirm that lateral channel migration represents a significant source of sediment loading in these streams.
To estimate the impact of impervious surface areas on sediment loading to streams, total impervious area (TIA) and effective impervious area (EIA), that is the impervious area that is hydrologically-connected to nearby streams, were also quantified using enhanced digital elevation models (DEMs) derived from LiDAR data, QuickBird satellite imagery, object-based image analysis techniques, and hydrologic flow modeling. TIA across all subwatersheds within the two study areas ranged from 2% -27% although less than 1% ofthe total watershed was hydrologically-connected to either Allen or Indian Brook. These results demonstrate the potential of geospatial technologies to rapidly, reliably and cost-effectively support and improve upon traditional stream monitoring methodologies, and aid efforts, to partition, estimate and manage sediment loading on stream reach and watershed scales.