Articles | Volume 24, issue 2
Hydrol. Earth Syst. Sci., 24, 735–759, 2020
Hydrol. Earth Syst. Sci., 24, 735–759, 2020

Research article 18 Feb 2020

Research article | 18 Feb 2020

Characterizing uncertainty in the hydraulic parameters of oil sands mine reclamation covers and its influence on water balance predictions

M. Shahabul Alam et al.

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Subject: Vadose Zone Hydrology | Techniques and Approaches: Modelling approaches
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Understanding the mass, momentum, and energy transfer in the frozen soil with three levels of model complexities
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Hydrol. Earth Syst. Sci. Discuss.,,, 2020
Revised manuscript accepted for HESS
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Simulating preferential soil water flow and tracer transport using the Lagrangian Soil Water and Solute Transport Model
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Cited articles

Alam, M. S., Barbour, L., Huang, M., and Doucette, L.: An evaluation of parameter uncertainty in the calibration of a soil-vegetation-atmosphere-transfer (SVAT) model for a reclamation cover on LOS, in: 70th Canadian Geotechnical Society Conference, GeoOttawa 2017, Ottawa, Ontario, 2–4 October 2017, 8 pp., 2017. 
Alam, M. S., Barbour, S. L., Elshorbagy, A., and Huang, M.: The impact of climate change on the water balance of oil sands reclamation covers and natural soil profiles, J. Hydrometeorol., 19, 1731–1752,, 2018a. 
Alam, M. S., Barbour, S. L., and Huang, M.: An evaluation of soil hydraulic parameter uncertainty on the hydrologic performances of oil sands reclamation covers, in: 71st Canadian Geotechnical Society Conference, GeoEdmonton 2018, Edmonton, Alberta, 23–26 September 2018, 8 pp., 2018b. 
ASTM: Standard test method for particle-size analysis of soils, method D422-63, American Society for Testing and Materials, Philadelphia, PA, 1998. 
Arya, L. M., Leij, F. J., van Genuchten, M. Th., and Shouse, P. J.: Scaling parameter to predict the soil water characteristic from particle-size distribution data, Soil Sci. Soc. Am. J., 63, 510–519, 1999. 
Short summary
This study quantifies uncertainties in the prediction of long-term water balance for mine reclamation soil covers 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.