Investigating the spatial distribution of water levels in the Mackenzie Delta using airborne LiDAR

Abstract

Airborne light detection and ranging (LiDAR) data were used to map water level (WL) and hydraulic gradients (δH/δx) in the Mackenzie Delta. The LiDAR WL data were validated against eight independent hydrometric gauge measurements and demonstrated mean offsets from − 0·22 to + 0·04 m (σ< 0·11). LiDAR‐based WL gradients could be estimated with confidence over channel lengths exceeding 5–10 km where the WL change exceeded local noise levels in the LiDAR data. For the entire Delta, the LiDAR sample coverage indicated a rate of change in longitudinal gradient (δ 2 H/δx) of 5·5 × 10 −10 m m −2 ; therefore offering a potential means to estimate average flood stage hydraulic gradient for areas of the Delta not sampled or monitored. In the Outer Delta, within‐channel and terrain gradient measurements all returned a consistent estimate of − 1 × 10 −5 m m −1 , suggesting that this is a typical hydraulic gradient for the downstream end of the Delta. For short reaches (<10 km) of the Peel and Middle Channels in the middle of the Delta, significant and consistent hydraulic gradient estimates of − 5 × 10 −5 m m −1 were observed. Evidence that hydraulic gradients can vary over short distances, however, was observed in the Peel Channel immediately upstream of Aklavik. A positive elevation anomaly (bulge) of > 0·1 m was observed at a channel constriction entering a meander bend, suggesting a localized modification of the channel hydraulics. Furthermore, water levels in the anabranch channels of the Peel River were almost 1 m higher than in Middle Channel of the Mackenzie River. This suggests: (i) the channels are elevated and have shallower bank heights in this part of the delta, leading to increased cross‐delta and along‐channel hydraulic gradients; and/or (ii) a proportion of the Peel River flow is lost to Middle Channel due to drainage across the delta through anastamosing channels. This study has demonstrated that airborne LiDAR data contain valuable information describing Arctic river delta water surface and hydraulic attributes that would be challenging to acquire by other means.