Hopkinson, Christopher
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- ItemA bi-temporal airborne lidar shrub-to-tree aboveground biomass model for the taiga of western Canada(Taylor & Francis, 2024) Flade, Linda; Hopkinson, Christopher; Chasmer, LauraMonitoring aboveground biomass (AGB) is critical for carbon reporting and quantifying ecosystem change. AGB from field data can be scaled to the region using airborne lidar. However, lidar-based AGB products emphasize upland forests, which may not represent the conditions in rapidly changing peatland complexes in the southern Taiga of western Canada. In addition, to ensure that modeled AGB changes do not incorporate systematic error due to differences between older and newer lidar technologies, model transfer tests are required. The aim of this study was to develop one bi-temporal lidar-based AGB model applicable to (1) vegetation structures at varying vertical and horizontal continuity in this region and to (2) data collected with an earlier generation lidar system for which Canada-wide aerial coverage is available. Goodness-of-fit metrics show that AGB can be modeled with moderate (R2 = 48%–58% Taiga Shield, peatlands) to high accuracies (R2 = 83%–89% Taiga Plains, upland/permafrost plateau forests including ecotones) by using the point clouds average height and 90th height percentile within a weighted approach as function of modeled AGB and calibrating the earlier lidar data. These results are important for quantifying climate change effects on forest to peatland ecotones.
- ItemWarmer air temperatures predicted to result in wetland drying in the Upper Columbia River Valley, British Columbia, Canada(Elsevier, 2025) Rodrigues, Italo S.; Hopkinson, Christopher; Chasmer, Laura; MacDonald, Ryan J.; Bayley, Suzanne E.Climatic warming is likely to affect the Canadian Rockies, leading to changes in the land cover (LC) and hydrological cycles. This study estimates climate-induced changes in LC (open water, marsh, wet meadow, and woody/shrub) in the Upper Columbia River Wetlands (UCRW), British Columbia, Canada, from 1984 to 2040. An artificial Neural Network (ANN) approach was used with Landsat series archive data from 1984 to 2022 to project seasonal LC change from 2020s to 2040s. Concurrently, hydroclimatic-based models (using air temperature and precipitation to predict river discharge at the UCRW, 1984–2022) were developed (average Nash Sutcliffe: training 0.75 and validation of 0.70) to predict (1984–2040) river discharge forced by Representative Concentration Pathway (RCP) 4.5 and 8.5. The 1984–2022 regression between river discharge and UCRW open water area was forced by RCP scenario river discharge results, calculating open water area for both scenarios. ANN-predicted LC with a Kappa of 0.85 (average of all seasons) for 2020s reference and projected LC, and 0.82 for reference and projected LC change maps (2000s–2020s). From 2020s to 2040s, the ANN projected a reduction (−5 %) of open water areas during late summer (August to mid-September) in the UCRW, consistent with RCP 4.5 forecasts. The peak of the open water area in the UCRW is projected to shift from summer (late-May to July) to spring (April to mid-May) in both RCP scenarios. The projected changing hydrological conditions reduced the marsh area (−1 % to −12 %) and increased the wet meadow (+1 % to +4 %) mostly in the summer and late summer. Meanwhile, woody and shrubby vegetation on the floodplain increased (3 % to 5 %), indicating that the floodplain is projected to dry out.
- ItemUsing bi-temporal lidar to evaluate canopy structure and ecotone influence on Landsat vegetation index trends within a boreal wetland complex(MDPI, 2025) Aslami, Farnoosh; Hopkinson, Christopher; Chasmer, Laura; Mahoney, Craig; Peters, Daniel L.Wetland ecosystems are sensitive to climate variation, yet tracking vegetation type and structure changes through time remains a challenge. This study examines how Landsat-derived vegetation indices (NDVI and EVI) correspond with lidar-derived canopy height model (CHM) changes from 2000 to 2018 across the wetland landscape of the Peace–Athabasca Delta (PAD), Canada. By comparing CHM change and NDVI and EVI trends across woody and herbaceous land covers, this study fills a gap in understanding long-term vegetation responses in northern wetlands. Findings show that ~35% of the study area experienced canopy growth, while 2% saw a reduction in height. CHM change revealed 11% ecotonal expansion, where shrub and treed swamps encroached on meadow and marsh areas. NDVI and EVI correlated significantly (p < 0.001) with CHM, particularly in shrub swamps (r2 = 0.40, 0.35) and upland forests (NDVI r2 = 0.37). However, EVI trends aligned more strongly with canopy expansion, while NDVI captured mature tree height growth and wetland drying, indicated by rising land surface temperatures (LST). These results highlight the contrasting responses of NDVI and EVI—NDVI being more sensitive to moisture-related changes such as wetland drying, and EVI aligning more closely with canopy structural changes—emphasizing the value of combining lidar and satellite indices to monitor wetland ecosystems in a warming climate.
- ItemQuality control impacts on total precipitation gauge records for montane valley and ridge sites in SW Alberta, Canada(MDPI, 2022) Barnes, Celeste; Hopkinson, ChristopherThis paper presents adjustment routines for Geonor totalizing precipitation gauge data collected from the headwaters of the Oldman River, within the southwestern Alberta Canadian Rockies. The gauges are situated at mountain valley and alpine ridge locations with varying degrees of canopy cover. These data are prone to sensor noise and environment-induced measurement errors requiring an ordered set of quality control (QC) corrections using nearby weather station data. Sensor noise at valley sites with single-vibrating wire gauges accounted for the removal of 5% to 8% (49–76 mm) of annual precipitation. This was compensated for by an increase of 6% to 8% (50–76 mm) from under-catch. A three-wire ridge gauge did not experience significant sensor noise; however, the under-catch of snow resulted in 42% to 52% (784–1342 mm) increased precipitation. When all QC corrections were applied, the annual cumulative precipitation at the ridge demonstrated increases of 39% to 49% (731–1269 mm), while the valley gauge adjustments were −4% to 1% (−39 mm to 13 mm). Public sector totalizing precipitation gauge records often undergo minimal QC. Care must be exercised to check the corrections applied to such records when used to estimate watershed water balance or precipitation orographic enhancement. Systematic errors at open high-elevation sites may exceed nearby valley or forest sites.
- ItemMontane seasonal and elevational precipitation gradients in the southern Rockies of Alberta, Canada(Wiley, 2025) Barnes, Celeste; MacDonald, Ryan J.; Hopkinson, ChrisModelling precipitation inputs in mountainous terrain is challenging for water resource managers given sparse monitoring sites and complex physical hydroclimatic processes. Government of Alberta weather station uncorrected and bias-corrected precipitation datasets were used to examine elevational precipitation gradients (EPGs) and seasonality of EPGs for six South-Saskatchewan River headwater sites (alpine, sub-alpine, valley). January EPG from valley to alpine sites (730 m elevation difference) using uncorrected precipitation was 19 mm/100 m. Corrected EPG was approximately three times greater (61 mm/100 m). The valley received more precipitation than the alpine (inverse EPG) in late spring and summer. A seasonal signal was present whereby all sites demonstrated 50%–70% lower summertime precipitation relative to winter months, with the greatest seasonal variance at the alpine site. Winter watershed-level spatialized precipitation volume was compared to modelled snow water equivalent (SWE) associated with two late-winter airborne lidar surveys. Uncorrected volumes (2020: 64.0 × 106m3, 2021: 63.2 × 106m3) were slightly higher than modelled mean SWE (2020: 51.6 × 106m3, 2021: 44.2 × 106m3) whereas bias-corrected (2020: 120.5 × 106m3, 2021: 119.7 × 106m3) almost doubled the estimate. Corrected precipitation is assumed closer to the true value. Cumulative sublimation, evaporation and snowmelt losses result in ground-level snowpack yield that deviates from total atmospheric precipitation in an increasingly negative manner. The 2020/2021 simulations suggest wintertime atmospheric precipitation exceeds late-winter snowpack accumulation by up to 57% and 63%, respectively. A loss of 16 × 106m3 (7%) watershed SWE from the alpine zone was partially attributed to redistribution downslope to the treeline-ecotone. Physical snowpack losses from sublimation and melt, or modelling uncertainty due to precipitation correction and alpine snow-density uncertainties can also contribute to observed discrepancies between in situ SWE and cumulative precipitation. Ignoring bias-correction in headwater precipitation estimates can greatly impact headwater precipitation volume estimates and ignoring EPG seasonality is likely to result in under-estimated winter and over-estimated summer yields.