Fang et al. (2025) Modelling river ice processes in a small-steep-regulated river

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-12-11
• Authors: Hongwei Fang, Mark Loewen, Yuntong She
• DOI: 10.1016/j.jhydrol.2025.134781

Research Groups

• Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada

Short Summary

This study revised the University of Alberta’s River1D model to improve its simulation of complex river ice processes, including aufeis evolution, in small-steep-regulated rivers. The enhanced model was successfully calibrated and validated on the Aishihik River, providing a valuable tool for assessing flow regulation impacts, mitigating ice hazards, and evaluating climate change scenarios.

Objective

• To improve how ice processes on small-steep rivers are simulated in river ice models by revising the University of Alberta’s public-domain River1D Ice Process model to enhance predictions of border and anchor ice and to include an algorithm for simulating aufeis growth and decay.

Study Configuration

• Spatial Scale: Aishihik River, Yukon, Canada. The modelled reach extends approximately 28.1 km (from Kp -0.6 to Kp 27.5). The river has a steep slope (~0.003), a channel width ranging from 25 to 35 m, and wide floodplains (~50 to 300 m in width).
• Temporal Scale: Two winter seasons:
  • Calibration: November 1, 2020, to April 27, 2021.
  • Validation: November 1, 2021, to April 30, 2022.

Methodology and Data

• Models used: University of Alberta’s River1D Ice Process model, with several key enhancements:
  • Removal of the floating border ice assumption.
  • Implementation of a border ice retreat algorithm (based on the Russell-Head formula).
  • Addition of an aufeis formation algorithm for both main channel and floodplain aufeis.
  • Development of a quasi-2D border ice profile algorithm.
  • Refinement of the anchor ice thermal release algorithm to account for thermal interaction between substrate flow and anchor ice.
• Data sources:
  • Field Observations (Aishihik River, Yukon, Canada):
    • Water levels and temperatures (Solinst Levelogger 3001, RBRsoloT, HOBO TidbiT at 5-6 locations, 15-minute intervals).
    • Border ice fraction (estimated from geo-rectified time-lapse images from 5-6 field cameras and UAV ortho-mosaics).
    • Main channel ice thickness (measured near Kp 25.8).
    • Main channel ice surface elevation (measured near Kp 25.2).
    • Floodplain aufeis surface elevations, thickness, and extent (surveyed along 4 transects).
  • Input Data:
    • River cross-sections (42 surveyed, interpolated to 889 modelled sections).
    • Tailrace discharge (15-minute interval, from Yukon Energy Corporation).
    • West Aishihik River discharge (Water Survey Canada).
    • East Aishihik River discharge (estimated).
    • Air temperature (15-minute interval, Solinst Barologger Edge).
    • Incoming solar radiation (estimated using ASHRAE and Kasten-Czeplak models, validated with HOBO U30 weather station data).
    • Cloud cover data (NAV Canada Whitehorse Airport Weather Station).

Main Results

• Water Temperature: Achieved an average Root Mean Square Error (RMSE) of 0.11 °C and Mean Absolute Error (MAE) of 0.07 °C across all sensor locations and simulation periods.
• Water Levels: Predictions were in reasonable agreement with observations, with RMSE values ranging from 0.20 to 0.25 m.
• Border Ice: Modelled growth and retreat patterns aligned well with field observations, with the new retreat algorithm significantly enhancing simulation accuracy.
• Floodplain Aufeis:
  • Average aufeis surface elevation: Modelled values had an average difference of 0.08 m from observed.
  • Aufeis thickness: Mean difference between modelled and observed average thickness was 0.09 m (ranging from 0.01 to 0.23 m).
  • Lateral extent: Modelled extent deviated from surveys by an average of 45 m.
• Main Channel Ice: Averaged ice thickness was simulated to within 0.15 m of observations. Modelled ice surface elevations were in close agreement with field measurements.
• Open Water Calibration: Calibrated Manning’s n for the main channel was 0.035, and for floodplains was 0.05. Average RMSE for water levels during open water calibration and validation was 0.047 m and 0.036 m, respectively.

Contributions

• Model Enhancement: First comprehensive revision of the River1D model specifically tailored for small-steep-regulated rivers, incorporating critical processes previously unaddressed or simplified in existing models (e.g., bank-fast border ice, aufeis evolution, quasi-2D border ice profiles, thermal border ice retreat, and refined anchor ice thermal release).
• Improved Accuracy: Demonstrated significantly improved performance in simulating water temperature, water levels, border ice dynamics, and aufeis formation in a complex river environment.
• Practical Tool: Provides a valuable, enhanced tool for:
  • Assessing the impacts of hydropower-induced flow regulation on river ice processes.
  • Mitigating ice-related hazards (e.g., intake blockages, flooding).
  • Evaluating climate change scenarios on ice regimes.
  • Potential applicability to small-steep-unregulated rivers.
• Comprehensive Validation: Rigorous calibration and validation using extensive, multi-season field data from a challenging river system (Aishihik River).

Funding

• Crown-Indigenous Relations and Northern Affairs Canada’s (CIRNAC) Climate Change Preparedness in the North (CCPN) Program.
• China Scholarship Council (CSC).
• University of Alberta.

Citation

@article{Fang2025Modelling,
  author = {Fang, Hongwei and Loewen, Mark and She, Yuntong},
  title = {Modelling river ice processes in a small-steep-regulated river},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.134781},
  url = {https://doi.org/10.1016/j.jhydrol.2025.134781}
}