Hervé Awoye


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Learning from hydrological models’ challenges: A case study from the Nelson basin model intercomparison project
Mansoor Ahmed, Tricia A. Stadnyk, Alain Pietroniro, Hervé Awoye, A. R. Bajracharya, Juliane Mai, Bryan A. Tolson, Helen C. Shen, James R. Craig, Melissa Gervais, Kevin Sagan, Shane G. Wruth, Kristina Koenig, Rajtantra Lilhare, Stephen J. Déry, Scott Pokorny, Henry David Venema, Ameer Muhammad, Mahkameh Taheri
Journal of Hydrology, Volume 623

Intercomparison studies play an important, but limited role in understanding the usefulness and limitations of currently available hydrological models. Comparison studies are often limited to well-behaved hydrological regimes, where rainfall-runoff processes dominate the hydrological response. These efforts have not covered western Canada due to the difficulty in simulating that region’s complex cold region hydrology with varying spatiotemporal contributing areas. This intercomparison study is the first of a series of studies under the intercomparison project of the international and interprovincial transboundary Nelson-Churchill River Basin (NCRB) in North America (Nelson-MIP), which encompasses different ecozones with major areas of the non-contributing Prairie potholes, forests, glaciers, mountains, and permafrost. The performance of eight hydrological and land surface models is compared at different unregulated watersheds within the NCRB. This is done to assess the models’ streamflow performance and overall fidelity without and with calibration, to capture the underlying physics of the region and to better understand why models struggle to accurately simulate its hydrology. Results show that some of the participating models have difficulties in simulating streamflow and/or internal hydrological variables (e.g., evapotranspiration) over Prairie watersheds but most models performed well elsewhere. This stems from model structural deficiencies, despite the various models being well calibrated to observed streamflow. Some model structural changes are identified for the participating models for future improvement. The outcomes of this study offer guidance for practitioners for the accurate prediction of NCRB streamflow, and for increasing confidence in future projections of water resources supply and management.


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Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E)
Juliane Mai, Bryan A. Tolson, Helen C. Shen, Étienne Gaborit, Vincent Fortin, Nicolas Gasset, Hervé Awoye, Tricia A. Stadnyk, Lauren M. Fry, Emily A. Bradley, Frank Seglenieks, André Guy Tranquille Temgoua, Daniel Princz, Shervan Gharari, Amin Haghnegahdar, Mohamed Elshamy, Saman Razavi, Martin Gauch, Jimmy Lin, Xiaojing Ni, Yongping Yuan, Meghan McLeod, N. B. Basu, Rohini Kumar, Oldřich Rakovec, Luis Samaniego, Sabine Attinger, Narayan Kumar Shrestha, Prasad Daggupati, Tirthankar Roy, Sungwook Wi, Timothy Hunter, James R. Craig, Alain Pietroniro
Journal of Hydrologic Engineering, Volume 26, Issue 9

AbstractHydrologic model intercomparison studies help to evaluate the agility of models to simulate variables such as streamflow, evaporation, and soil moisture. This study is the third in a sequen...


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Time Variant Sensitivity Analysis of Hydrological Model Parameters in a Cold Region Using Flow Signatures
A. R. Bajracharya, Hervé Awoye, Tricia A. Stadnyk, Masoud Asadzadeh
Water, Volume 12, Issue 4

The complex terrain, seasonality, and cold region hydrology of the Nelson Churchill River Basin (NCRB) presents a formidable challenge for hydrological modeling, which complicates the calibration of model parameters. Seasonality leads to different hydrological processes dominating at different times of the year, which translates to time variant sensitivity in model parameters. In this study, Hydrological Predictions for the Environment model (HYPE) is set up in the NCRB to analyze the time variant sensitivity analysis (TVSA) of model parameters using a Global Sensitivity Analysis technique known as Variogram Analysis of Response Surfaces (VARS). TVSA can identify parameters that are highly influential in a short period but relatively uninfluential over the whole simulation period. TVSA is generally effective in identifying model’s sensitivity to event-based parameters related to cold region processes such as snowmelt and frozen soil. This can guide event-based calibration, useful for operational flood forecasting. In contrast to residual based metrics, flow signatures, specifically the slope of the mid-segment of the flow duration curve, allows VARS to detect the influential parameters throughout the timescale of analysis. The results are beneficial for the calibration process in complex and multi-dimensional models by targeting the informative parameters, which are associated with the cold region hydrological processes.