Prediction of acid rock drainage in waste rock piles Part 1: Water film model for geochemical reactions and application to a full-scale case study

Ma, Liang; Huang, Cheng Hung; Liu, Zhong‐Sheng; Morin, Kevin A.; Aziz, Mike; Meints, Cody

doi:10.1016/j.jconhyd.2018.11.012

Cited by 12 publications

(1 citation statement)

References 18 publications

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“…The rapid development of numerical models was promoted on the one hand by the increasingly high power and low costs of computational machines, and on the other hand by the increasing awareness of the importance of embedding heterogeneities for model predictions (heterogeneity is hardly embedded into analytical solutions). Nowadays, multiphase multicomponent reactive transport models are able to simulate a wide range of processes, including both advective and diffusive gas transport, the effects of oxidizing agents in contact with sulfidic materials and the interaction between minerals and pore-fluids (da Silva et al 2009;Ma et al 2019;Mayer et al 2015;Molson et al 2005;Muniruzzaman et al 2020;Sracek et al 2004;Wang et al 2019).…”

Section: First Modelsmentioning

confidence: 99%

Mechanistic models supporting uncertainty quantification of water quality predictions in heterogeneous mining waste rocks: a review

Muniruzzaman

Pedretti

2020

Stoch Environ Res Risk Assess

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Polluted drainage from weathering of sulfide-rich waste rock deposits can cause long-term impairment to waterways and biodiversity near mining sites. Mechanistic models represent established tools to support the predictions of the quantity and quality of waste rock drainage, and their associated risks. Yet, model-based predictions in typical waste rock systems are ubiquitously uncertain because of the strongly heterogeneous nature of these waste deposits. Embedding heterogeneity within predictive modeling is complicated by the magnitude and level of knowledge of the waste rock heterogeneity, and the large number of scale-dependent parameters feeding the model equations. This review encompasses deterministic and stochastic modeling approaches that emphasize consolidated tools and emerging modeling solutions to deal with heterogeneity for the modeling of waste rocks. Physical (e.g., variability of texture, hydraulic and pneumatic properties), geochemical (e.g., variability of mineralogy and kinetic parameters), and thermal heterogeneities are evaluated. The review points out the importance of stochastic modeling as a fundamental approach to embed uncertainty in long-term model-based decisions. Regulators and decision makers must be convinced of the benefit of using stochastic modeling, which is still considered to belong mainly to the academic sphere.

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