Dynamic models extend the critical loads concept, providing predictions of the timing of change.  They are used both to simulate future trajectories of change under different deposition scenarios, and to estimate the changes that would be required to achieve acceptable ecosystem status by a given year (“target loads”).  Dynamic models are being continuously refined in response to new scientific understanding and data. 

The MAGIC model is one of the most widely used models of soil and water acidification, which also incorporates an intermediate-complexity representation of the nitrogen cycle. At present, MAGIC is used to model acidity and nitrogen leaching to surface waters. The VSD model is similar to MAGIC, but with slightly simpler process representation and lower data requirements.  The VSD is designed to run for large numbers of locations via an Access database, which makes it suitable for running at a high spatial resolution for terrestrial ecosystems. The GBMOVE model is a static, empirical model which relates soil physical and chemical conditions (which may be generated by MAGIC or VSD), along with information on management and climate, to the probability of occurrence for individual plant species.

Further Reading

CLRTAP (2004). Manual on methodologies and criteria for Modelling and Mapping Critical Loads & Levels and Air Pollution Effects, Risks and Trends.

Coordination Centre for Effects

Cosby, B.J., Hornberger, G.M., Galloway, J.N. & Wright, R.F. 1985. Modelling the effects of acid deposition: Assessment of a lumped parameter model of soil water and streamwater chemistry. Water Resources Research, 21(1): 51-63.

Cosby, B.J., Ferrier, R.C., Jenkins, A. & Wright, R.F. 2001. Modelling the effects of acid deposition: refinements, adjustments and inclusion of nitrogen dynamics in the MAGIC model. Hydrology and Earth System Sciences, 5(3): 499-517.

Posch, M. & Reinds, G.J. 2008. A very simple dynamic soil acidification model for scenario analyses and target load calculations. Environmental Modelling & Software, 24: 329-340.