The influence of roads on depressional storage capacity estimates from high-resolution LiDAR DEMs in a Canadian Prairie agricultural basin

The Canadian Prairies are a post-glacial agricultural landscape, where millions of small depressions store surface water, form wetlands and control runoff contributing area. Their management is key to flood and drought hydrology, groundwater recharge, ecological integrity, migratory bird habitat and agricultural productivity. Depression drainage and infilling is common in the region, where it is often used to increase cropped area. The regularly spaced, rural 'grid-road' network also impedes drainage, but associated culvert drainage can mitigate those effects. Management of depressions can be informed by hydrological modelling, but accurate surface water storage capacity estimates are needed to ensure accurate model results. Simple representation of road embankments in digital elevation models (DEMs) neglects the effects of culvert drainage. Here, a raster-based depression-filling algorithm was used to delineate depressions from three LiDAR-derived DEMs: a 10-m DEM with roads intact, a 2-m DEM with roads intact, and a 2-m DEM with roads breached at culvert locations. Road breaching was conducted manually in the 2-m DEM to remove artifact depressions that form alongside roads where culverts exist. Results indicated that increasing DEM resolution from 10-m to 2-m in a 393.5 km(2) basin did not significantly change depression area or storage capacity estimates; however, breaching roads in the 2-m DEM decreased depression area by 29% (from 98.5 km(2) to 69.8 km(2)) and estimated storage capacity by 48% (from 47.4 x 10(6) m(3) to 23.8 x 10(6) m(3)), compared to leaving roads intact in the 2-m DEM. Depressions delineated from the 2-m roads-breached DEM also covered 48% more area and offered 53% more storage capacity than Canadian Wetland Inventory (CWI) aerial-photograph delineated wetlands, which occupied 47.1 km(2) with an estimated storage capacity of 15.5 x 10(6) m(3). The implications of these results for the ability of hydrological models to calculate runoff contributing areas and streamflow are discussed.