Environmental Modelling and Software publishes contributions, in the form of research articles, reviews, short communications as well
as software and data news, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent,
understand, predict or manage the behaviour ... click here for full Aims & Scope
Environmental Modelling and Software publishes contributions, in the form of research articles, reviews, short communications as well
as software and data news, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent,
understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to
a wide scientific and professional audience.
It seeks presentation of
• Generic frameworks, techniques and issues which
either integrate a range of disciplines and sectors or apply across a range
• Model development, model evaluation, process
identification and applications in diverse sectors of the environment (as outlined below) provided they reveal insights and contribute
to the store of knowledge. Insights can relate to the generality and limitations of the modelling, methods, the model application and/or
the systems modelled. Insights should be ones that are generalizable in some way and are likely to be of interest to those studying other
systems and, preferably, other system types.
• Development and application of environmental software, information and decision
support systems
• Issues and methods related to the integrated modeling, assessment and management of environmental systems
- including relevant policy and institutional analysis, public participation principles and methods, decision making methods, model integration,
quality assurance and evaluation of models, data and procedures.
Authors must specify clearly the objectives of their models and/or
software, and report on the essential steps that were used in their development, normally including the rationale for the type of approach
selected and substantial testing and evaluation of it - comparisons with alternative approaches and methods are encouraged. The purpose
of this specification, evaluation and reporting is to convey the rigour and credibility of the work and therefore its potential to contribute
to knowledge acquisition. To this latter end, authors are expected to briefly review and cite the historical progress made for their
problem and clearly show how their work adds value to the literature.
The journal encourages submission of Short Communications
of less than 3,000 words, and items of Software and Data News of less than 750 words.
For these and the regular papers, supplementary
material such as software demonstrations, model simulations and additional performance tests, can be posted in electronic form and commented
upon by users.
Authors are invited to submit relevant contributions in the following areas:
• Generic and pervasive frameworks,
techniques and issues - including system identification theory and practice, model conception, model integration, model and/or software
evaluation, sensitivity and uncertainty assessment, visualization, scale and regionalization issues
• Integrated assessment
and management of systems (river basins, regions etc.) for enhancing sustainability outcomes - including linked socioeconomic and biophysical
models that may be developed with stakeholders for understanding systems, communication and learning, and improving system outcomes
• Artificial Intelligence (AI) techniques and systems, such as knowledge-based systems / expert systems, case-based reasoning
systems, data mining, multi-agent systems, Bayesian networks, artificial neural networks, fuzzy logic, or knowledge elicitation and knowledge
acquisition methods
• Decision support systems and environmental information systems- implementation and use of environmental
data and models to support all phases and aspects of decision making, in particular supporting group and participatory decision making
processes. Intelligent Environmental Decision Support Systems can include qualitative, quantitative, mathematical, statistical, AI models
and meta-models
• Process-identification of environmental dynamics for instance of surface and subsurface hydrology, limnology,
meteorology, geophysics with special respect to the interaction of anthroposphere and biosphere.
• GIS, remote sensing and
image processing
These methodological developments should be illustrated with applications in the environmental fields, e.g.
•
Resource management including water, land, biological, transport systems
• Pollution of different media such as air, water,
soil, noise, radiation, as well as multimedia problems
• Global pollution and global climate change
• Regional studies
of resource consumption and/or nature conservation in open landscapes as well as in urban regions
• Environmental accidents,
prevention and emergency response - resilience, vulnerability, self-repair, damage limitation, and security in infrastructures
•
Environmental engineering and technology
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