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Accurate prediction of post-reclamation water quality allows reclamation
specialists to determine if future wastes will be acid generating
or metal leaching and what impacts may be expected as a result.
By having this predictive capability, long-term site management
costs can be significantly reduced by preventing acid generation
and metal leaching before they become a problem. In addition, results
from prediction are used by regulatory agencies to aid in permitting
decisions. Generally, where analysis indicates that poor post-reclamation
water quality is anticipated, permits to mine are granted with restrictions
or are denied altogether.
Prediction procedures have improved significantly in the last fifteen
years. Previously, because prediction can be complex, procedures
used to predict post-reclamation water quality were no more effective
than flipping a coin. Since then, a great deal of effort has gone
into improving the procedures. For example, in Pennsylvania, statistics
indicate that overall, its permitting decisions are now accurate
98% of the time. Most of the work in prediction has focused on methods
to characterize which strata are acid producing, potentially acid
producing, neutral or alkaline (MEND,
2000).
Most often, laboratory methods are used to predict the acid generating
potential of a given contaminant sample (i.e. tailings, waste rock,
overburden). Static testing
is the most common laboratory method. Kinetic
testing, a more elaborate method, may also be used when static
testing cannot provide adequate information. Another option for
determining acid generating potential is modeling.
Models attempt to simulate the weathering processes that cause the
formation of acid drainage. Discussions on laboratory testing methods
and modeling are given in the following sections.
For more information on prediction methods, see the following sources
that discuss prediction methods in depth:
Problem | Compliance
| Health & Safety | Sampling
| Analytical | Data
Quality
Site Assessment | Prediction
| Construction | GIS
| Monitoring & Assessment
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