SLICKMOD : A spatial model of oil spill dispersal rates and
extents in aquatic environments.
This page provides information and data from the project :
AMBIODUCTO
: Decision support tools for minimising pipeline leaks and their
environmental impacts through spatial simulation of risk and the
prioritisation of monitoring and maintenance activities
The data represent the results of a research project carried
out by Dr.
Mark Mulligan at Kings College London and
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of Petroproduccion and are derived from a
variety of original data sources.
A spatial model for the simulation of oil transport velocities,
and contaminated areas from pipeline leakage incidents in terrestrial
and aquatic environments was developed and applied to examining
contamination from historic pipeline leakages in the Ecuadorian
Amazon. The model can also be used to simulate scenario leaks
and identify particularlyt sensitive areas in which contamination
will spread quickly, far or will impact significantly on downstream
populations, protected areas or fluvial resources.
See the model documentation here
- The model is available on request from Dr.
Mark Mulligan at Kings College London
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To run the model computers will need at least 1 GB of free
disk space and at least 512 MB memory and the following software
installed : PCRASTER GIS (free from PCRASTER
Environmental Software). Adobe Acrobat (free from www.adobe.com).
Computers will also need to be connected to the internet.
 Downloading
and installing PCRASTER on your own computer
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- ACKNOWLEDGMENT AND CITATION
- We kindly ask any users to cite this data
in any published material produced using this data. Citations
should be made as follows:
Mulligan, M. and Larrea, J.M.
(2007) SLICKMOD
: A spatial model of oil spill dispersal rates and extents in
aquatic environments. http://www.ambiotek.com/slickmod
- DISTRIBUTION
- Users are prohibited from any commercial,
non-free resale, or redistribution without explicit written permission
from Kings College London (
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) Users should
acknowledge Kings College London as the source used in the creation
of any reports, publications, new data sets, derived products,
or services resulting from the use of this data set. Kings College
London also request reprints of any publications and notification
of any redistributing efforts.
- NO WARRANTY OR LIABILITY
- Kings College London provides these data
without any warranty of any kind whatsoever, either express or
implied, including warranties of merchantability and fitness
for a particular purpose. Kings College London shall not be liable
for incidental, consequential, or special damages arising out
of the use of any data downloaded.
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