Aim & Scope
Environmental Modelling & Software publishes contributions, in the form of research articles, reviews, introductory overviews, and position papers on advances in the area of environmental modelling and software. Our aim is to improve our capacity to represent, understand, predict or manage the behaviour of natural environmental systems, including air, water, and land components, 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;
;Real-world applications of software technologies - particularly state-of-the-art environmental software able to deal with complex requirements, conflicting user perspectives, and/or evolving data structures. Aspects related to software usability, reliability, verification and validation should be backed up with quantitative results as much as possible. Development and maintenance costs, and adoption and penetration of the software in the target user groups should be addressed. Licensing issues and open source access should be clearly specified;
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.
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