National Elevation Data Strategy update, July 2020

Bélanger, Diane; Papasodoro, C; Turgeon-Pelchat, Mathieu; Proulx-Bourque, Jean-Samuel; Vachon, Carl

doi:10.4095/326942

Cited by 1 publication

(1 citation statement)

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“…2a, d, j, g, m) were acquired from the HRDEM dataset, provided by Natural Resources Canada (NRCan). This dataset provides digital terrain models (DTMs) of scenes from across Canada, covering about 400,000 km 2 of area (Bélanger et al 2020). These models were generated using airborne Light Detection and Ranging (LiDAR) measurements.…”

Section: Digital Terrain Modelsmentioning

confidence: 99%

GIS derived synthetic rating curves and HAND model to support on-the-fly flood mapping

2021

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A timely and cost-effective method of creating inundation maps could assist first responders in allocating resources and personnel in the event of a flood or in preparation of a future disaster. The Height Above Nearest Drainage (HAND) model could be implemented into an on-the-fly flood mapping application for a Canada-wide service. The HAND model requires water level (m) data inputs while many sources of hydrological data in Canada only provide discharge (m3/sec) data. Synthetic rating curves (SRCs), created using river geometry/characteristics and the Manning’s formula, could be utilized to provide an approximate water level given a discharge input. A challenge with creating SRCs includes representing how multiple different land covers will slow impact flow due to texture and bulky features (i.e., smooth asphalt versus rocky river channel); this relates to the roughness coefficient (n). In our study, two methods of representing multiple n values were experimented with (a weighted method and a minimum-median method) and were compared to using a fixed n method. A custom ArcGIS tool, Canadian Estimator of Ratings Curves using HAND and Discharge (CERC-HAND-D), was developed to create SRCs using all three methods. Control data were sourced from gauge stations across Canada in the form of rating curves. Results indicate that in areas with medium to medium–high river gradients (S > 0.002 m/m) or with river reaches under 5 km, the CERC-HAND-D tool creates more accurate SRCs (NRMSE = 3.7–8.8%, Percent Bias = −7.8%—9.4%), with the minimum-median method being the preferred n method.

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Section: Digital Terrain Modelsmentioning

confidence: 99%