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dc.contributor.advisor Mahesh, Rao en
dc.contributor.author Melosh, Celeste E. en
dc.date.accessioned 2016-03-07T17:05:37Z en
dc.date.available 2016-03-07T17:05:37Z en
dc.date.issued 2015-12 en
dc.identifier.uri http://hdl.handle.net/10211.3/163225 en
dc.description Thesis (M.S.)--Humboldt State University, Natural Resources: Forestry Watershed and Wildland Sciences, 2015 en
dc.description.abstract Directly connected impervious areas collect and deliver unfiltered runoff to modified and impacted urban waterways. Modeling flow over the landscape is an effective method of observing drainage patterns and predicting peak runoff levels. Model improvements can increase our ability to identify key areas with high runoff and pollutant output. This is a crucial issue in the Lake Tahoe Basin where lakeshore urban development has increased and lake clarity has been declining for years. This study aims to evaluate an integrated LiDAR and GIS-based modeling approach that uses a fine-scaled ground surface and impervious surface connectivity to predict the runoff volumes in the Lake Tahoe Basin. This study produced two rainfall-runoff models for each of three small urban basins in South Lake Tahoe with various levels of impervious surface. A land use classification was generated using NAIP color infrared and LiDAR data. In addition to land use, hydrological characteristics, basins and drainages derived from LiDAR and 10-meter digital elevation models were used in the models. The US Army Corps of Engineers Hydrologic Engineering Center’s Hydrologic Modeling System version 3.5 was used to model runoff peaks and volumes for 10-meter and LiDAR derived inputs for each site. The flow modeled for LiDAR inputs was compared to flow modeled with lower-resolution 10-meter layers as well as observed monitoring data. Flow was successfully modeled for most storms; producing runoff that mimicked observed flow patterns. The most common errors found were lower modeled peak flows in thunderstorms, modeled volumes inconsistent with observed volumes during winter storms and periods of flow found in either the modeled or observed data but not both. In general, the LiDAR and 10-meter models produced similar flow outputs to each other. The 10-meter models produced slightly better peak flow values while the LiDAR produced better volume outputs. However, these differences were small and fell within the margin of error. Although the models did not benefit from the added data resolution, LiDAR will still prove to be a valuable management tool. The LiDAR flow network analysis for this study demonstrates an impressive increase in the visualization of micro scale flow patterns across the urban landscape. This improved ability to pinpoint where and over what surface water flows as it makes its way from the sky to the stream will aid urban basin managers in identifying key pollutant inputs and placing retention sites and diversions. en
dc.language.iso en_US en
dc.publisher Humboldt State University en
dc.subject Hydrology en
dc.subject Hydrologic model en
dc.subject Lake Tahoe en
dc.subject LiDAR en
dc.subject HEC-HMS en
dc.subject Runoff en
dc.subject Data resolution en
dc.subject Classification en
dc.title Modeling runoff levels over impervious surfaces in the Lake Tahoe basin using varying data resolution en
dc.type Masters Thesis en
dc.description.program Natural Resources en


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