Predictive modelling
Principles and tools simplifying the 'real thing' to predict 
something, e.g. the behaviour of a contaminant, the effectivity
of a remediation, etc.

 

Land contamination may occur as a result of
spills, leaks and discharges of polluting and toxic chemicals,
disposal of liquid and solid waste and unregulated historical
land uses. It may exist within the ground or groundwater
and may migrate long distances before affecting human health,
sensitive plants or animals, polluting groundwater and
rivers or affecting the safety of buildings.

The
objective of the predictive modelling is to understand
and predict quantitatively the pathways of contaminant
transport and the resulting exposure, often through the
use of computer programs which simulate or model the chemicals'
behaviour. The models can be conceptual, physical or mathematical.
Simulation models are increasingly used to investigate
processes and solve practical problems in a wide variety
of disciplines eg. climatology, ecology, hydrology, geomorphology,
engineering. When we can establish a quantitative link
between sources, exposure, and risk of effects we are in
a strong position to control sources to acceptably low levels,
avoiding the problems of unacceptable contamination from
excessive sources on the one hand, and uneconomic, unnecessary
regulations on the other. Such balanced regulation is best
effected through full and quantitative information about
the substances' fate.

GIS and modelling provide new capabilities for
analysing the space/time distribution of ecological phenomena.
The primary environmental regimes provide a consistent
framework for examining ecological process and pattern
from global- to nano- scales. The multi-scaled nature of
these driving processes requires an integration of climate
modelling, terrain analysis, substrate and land cover
data at specified scales of analysis. The key point is that
ecological systems are hierarchically structured by the
constraining influences of the primary environmental
regimes. Analytical procedures based on these concepts
provide the basis for the quantification and prediction.
Also, Environmental Domain Analysis based on the same scale-dependent
models of the primary environmental regimes, provides
complimentary and essential context where biological
data are limited.

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