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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2019-154
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-154
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 12 Jun 2019

Submitted as: research article | 12 Jun 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Characterizing Uncertainty in the Hydraulic Parameters of Oil Sands Mine Reclamation Covers and its Influence on Water Balance Predictions

Md. Shahabul Alam1, S. Lee Barbour1,2, and Mingbin Huang1,3 Md. Shahabul Alam et al.
  • 1Department of Civil, Geological and Environmental Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada
  • 2Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, S7N 3H5, Canada
  • 3Center for Excellence in Quaternary Science and Global Change, Chinese Academy of Sciences, Xian 710061, China

Abstract. One technique to evaluate the performance of oil sands reclamation covers is through the simulation of long-term water balance using calibrated soil–vegetation–atmosphere–transfer models. Conventional practice has been to derive a single set of optimized hydraulic parameters through inverse modelling (IM) based on short-term (< 5–10 y) monitoring datasets. This approach is unable to characterize the impact of variability in the cover properties. This study utilizes IM to optimize the hydraulic properties for 12 soil cover designs, replicated in triplicate, at Syncrude's Aurora North mine site. The hydraulic parameters for three soil types (peat coversoil, coarse-textured subsoil, and lean oil sand substrate) were optimized at each monitoring site from 2013–2016. The resulting 155 optimized parameter values were used to define distributions for each parameter/soil type, while the Progressive Latin Hypercube Sampling (PLHS) method was used to sample parameter values randomly from the optimized parameter distributions. Water balance models with the sampled parameter sets were used to evaluate variations in the maximum sustainable leaf area index (LAI) for five illustrative covers and quantify uncertainty associated with long-term water balance components and LAI values. Overall, the PLHS method was able to capture broader variability in the water balance components than a discrete interval sampling method. The results also highlight that climate variability dominates the simulated variability in actual evapotranspiration, and that climate and parameter uncertainty have a similar influence on the variability in net percolation.

Md. Shahabul Alam et al.
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Short summary
This study quantifies uncertainties in the prediction of long-term water balance for mine reclamation soil covers based using random sampling of model parameter distributions. Parameter distributions were obtained from model optimization for field monitoring data. Variability in climate is a greater source of uncertainty than the model parameters in evaporation predictions, while climate variability and model parameters exert similar uncertainty on predictions of net percolation.
This study quantifies uncertainties in the prediction of long-term water balance for mine...
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