LiDAR-derived Drainage Network for Calvert Island - British Columbia - Canada

This dataset provides LiDAR derived stream locations for Calvert and Hecate Islands, British Columbia. Stream locations were delineated from a 3 m digital elevation model (DEM). For each stream segment, the dataset includes a unique identifier and Strahler stream order assignment. This dataset is the result of “traditional” hydrological modeling conducted using the 2012 and 2014 LiDAR-based topographically complete bare earth DEM with a 10 m buffer around the coastline to ensure all modeled streams reach the ocean. After extraction, stream networks were clipped to the shoreline of the Island. Although this LiDAR derived stream network represents a large improvement over the best alternative stream map for the area – in terms of spatial accuracy and resolution – appropriate caution should be used when interpreting the modeled stream locations, given the methodology used. Hydrologic modelling of drainage networks from digital elevation models can produce drainage systems of varying detail (density and length of small tributary streams) depending on the thresholds used to define initiation of streams. We defined a stream initiation threshold by selecting a “net flow accumulation value” that best agreed with stream occurrence and initiation observed on aerial imagery and in the field. Net flow accumulation is obtained by taking the Log (base 10) of the flow accumulation raster produced during the hydrologic modelling exercise. We examined net flow accumulation values of 2.0 through 4.0 (in increments of 0.5), ultimately selecting a single value of 3.0 because it appeared to best determine stream initiation for the overall study area. Based on our field observations – which were opportunistic and of limited extent – higher values tend to omit observed surface channels and lower values tend to predict streams where surface channels are not observed. With a threshold value of 3.0, headwater stream reaches alternate between surface and subsurface flow, depending on local soil conditions. Choosing a single value for the entire landscape likely means that streams are over predicted in some areas and under predicted in others, depending on local conditions (e.g., terrain, soil type and depth). Modeling stream initiation as a function of local conditions could improve the stream network map but would require a large and representative sample of field observations. “Traditional hydrologic modeling” in this context refers to the following workflow: - Filling in sinks in a bare-earth DEM to produce a “hydrologically correct DEM” - Producing a flow direction raster from the hydrologically correct DEM - Producing a flow accumulation raster from the hydrologically correct DEM - Extracting the “stream” network from the flow accumulation raster (in this case from the net flow accumulation raster for values greater than or equal to 3.0). Streams networks which "run through" (drain into, and out of) water bodies have been maintained as one drainage network, rather than terminating one drainage system at the point of inflow to the water body and initiating another at the point of outflow. This approach maintains the continuity and ordering of the stream network within a watershed. Users who require a stream network that omits stream channels from waterbodies can readily ‘clip’ those stream segments (e.g., for an assessment of the erosive power of a stream network). All work in the production of this dataset has been conducted in ESRI’s ArcGIS for Desktop 10.3 using the Spatial Analyst extension’s Hydrologic Modeling Toolset. For further details on the methodology employed in the production of this dataset please contact santiago@hakai.org This version of the drainage network has not been dissolved and contains the following attributes: - STRMRDR: Stream order based on the Strahler method. - SG_LNGTH: Stream segment length in meters. - MC_FLAG: Main channel flag; used to identify stream segments in a network which constitute a main channel. Main channels have been identified for each watershed by programmatically assigning this flag to the highest stream order segments in any given watershed. Dataset Contributors: Hakai Institute, Santiago Gonzalez Arriola, Gordon W. Frazer, Ian Giesbrecht, Bill Floyd, Keith Holmes.

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