Environmental Engineering Reference
In-Depth Information
standards of scientific communication. In our opinion, modelling does not pose
conditions other than those relevant in science in general. The development of
easily accessible repositories improves the conditions to allow scientific peers to
exchange models and to independently verify the correctness of given results.
Frequently, some extended parts which are not directly necessary for the direct
understanding of model organization and functioning can be placed in an annex or
as accompanying material on the internet. Specialized scientific journals have
standards on how to document the model code itself and how to allow in a crucial
case an investigation that could prove that the results are actually obtained through
the model application (and not fictitious). If the code is treated as proprietary, it
must be held available in the case of the requirement for formal inspection. In case
that there should be reason to investigate the integrity of the scientific work, the
authors must be able to prove to have followed the scientific code of conduct.
1
Results Section
Model output can be represented within figures, tables or statistics, frequently in
comparison with empirical data. The specific algorithms used for their generation
should be explained in the text. If the text has a more methodological focus, the
results of sensitivity analysis and the model validation are also expected here.
Discussion Section
The discussion should encompass the model development (if applicable) and the
results to the research question as posed in the introduction and compared with
findings of other authors in the same or related fields. Validity considerations and
application ranges are of special interest here, as well as the relevance of the results
for further application and development.
23.6 Concluding Remarks
It is important to be aware that the model development does not end with code
writing. Following the availability of a fully functional model, an extended phase
of model evaluation is necessary which comprises the model calibration and
determination of parameters, the identification of model sensitivity to changes
of single parameters or a combination of parameters and the comparison of
model performance and structure with empirically determined values and causal
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e.g. US National Science Foundation (
http://www.nsf.gov/bfa/dias/policy/rcr.jsp
), German Science
Foundation (
http://www.dfg.de/foerderung/rechtliche_rahmenbedingungen/gwp/index.html
).
