Improving Stream Typing with Lidar
NRSIG Budget: $100,000
Project Budget: $100,000
Sponsors: WA DNR
Timeline: November 2015 through June 2016
Partners: WA DNR, CMER

Background

The Washington State Forest Practices Habitat Conservation Plan (HCP) specifies that the Washington State Department of Natural Resources (DNR) will prepare water type maps showing the location of fish and non-fish waters within the forested areas of the state. The current west side water typing model failed to achieve the required statistical accuracy of 95% in separating fish habitat streams and non-fish habitat streams. Large sources of error included the inability to detect barriers, the inaccurate location of digital elevation model (DEM) generated streams, and the use of error-prone DEM generated watersheds to quantify upstream basin areas. To improve the predictive precision of model higher resolution and more current lidar based topographic information could be used. This project will compare a lidar based implementation of the existing west side model and the improved Fransen et al model in the Mashel watershed and the existing 2005 east side model in the Darland Mountain watershed against the original ten meter United States Geologic Survey (USGS) DEM and identify potential opportunities to improve the model with high resolution topographic information.

Our Work

Component 1: Replicate the existing water typing models and improved Fransen et al model

The objective of this task is to replicate work done by Fransen et al to establish fish/non-fish accuracy statistics in the Mashel watershed on the west side and the Darland Mtn watershed on the eastside. In the Mashel both the existing 2003 west side model and the Fransen et al improved model will be tested. In the Darland Mtn watershed the existing 2005 east side model will be tested. Current data on the upper limit of fish occurrence (ULO) will be used to generate model accuracies. Statistical accuracy will be assessed by total error (ft.) as a percent of total watershed stream length (ft.). Depending on the quality and availability of ULO and Perennial Initiation Point (PIP) data, a subset of basins in the watersheds may be selected for analysis, rather than the entire watershed.

Component 2: Implement the existing water typing models using Lidar

The objective of this task is to replicate work done by Fransen et al. to establish fish/non-fish accuracy statistics using high-resolution, current topographic information derived from lidar for comparison to the baseline USGS 10 meter DEM model in both the Mashel and Darland Mtn watersheds.

Component 3: Explore additional Lidar resolutions and variables for model improvement

The objective of this task is to test increased resolution lidar-derived topographic models and explore additional model variables that have potential to increase model accuracy.

Results

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Deliverables

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