Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, 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
• 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.

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.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

Environmental Modelling and Software welcomes review articles on the topics above, especially ones that relate to generic modelling and/or software issues, or are cross-disciplinary in their problem treatment.
Potential authors of review articles should contact either Dr Jakeman or Dr Rizzoli to discuss the topic and coverage of their review. The journal has also published several Position Papers on key topics within its aims and scope at http://www.iemss.org/society/index.php/position-papers

Introductory Overviews are designed to provide a concise topic overview that caters to the eclectic readership of EMS. These articles aim to break down barriers to shared understanding and dialogue within multidisciplinary teams, and to make environmental modelling dimensions more accessible to a wider audience. Introductory Overviews include an introduction to the fundamentals of the topic and reference to key literature. Relevant concepts are presented in relatively simple terms, but with the audience assumed to have some basic knowledge of environmental modelling and mathematics. These articles are not intended to be comprehensive reviews but non-technical primers on essential modelling concepts. Introductory Overviews are peer reviewed and are by invitation only; ideas for Introductory Overviews can however be canvassed with any of the Editors.

Editorial board


  • D.P. Ames
    Brigham Young University, Provo, Utah, USA

Honorary Editor-in-Chief

  • A.J. Jakeman
    Australian National University, Canberra, Australian Capital Territory, Australia


  • K. Gibert
    Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
  • L. Marshall
    UNSW Australia, Sydney, New South Wales, Australia
  • S. Reis
    Centre for Ecology & Hydrology (CEH), Edinburgh, UK

Associate Editors

  • T. Berger
    Universität Hohenheim, Stuttgart, Germany
  • M. Borsuk
    Dartmouth College, Hanover, New Hampshire, USA
  • A. Castelletti
    Politecnico di Milano, Milano, Italy
  • M. Donatelli
    Council for Agricultural Research and Economics (CREA), Bologna, Italy
  • G. Guariso
    Politecnico di Milano, Milano, Italy
  • A. Jolma
    Finnish Environment Institute (SYKE), Helsinki, Finland
  • H.R. Maier
    University of Adelaide, Adelaide, South Australia, Australia
  • S. Marsili-Libelli
    Università degli Studi di Firenze, Firenze, Italy
  • B. Robson
    CSIRO (The Commonwealth Scientific and Industrial Research Organization), Canberra, Australian Capital Territory, Australia
  • M. Sànchez-Marrè
    Universitat Politècnica de Catalunya (UPC), Barcelona, Catalonia, Spain
  • R. Seppelt
    Helmholtz Centre for Environmental Research - UFZ, Leipzig, and Martin-Luther-Universität, Halle-Wittenberg, Germany

Emeritus Editor

  • A.A. Jennings
    Case Western Reserve University, Cleveland, Ohio, USA

Editorial Board

  • M. Acutis
    Facoltà di Agraria, Milano, Italy
  • K. Alexandridis
    University of the Virgin Islands, St. Thomas, Virgin Islands, U.S.
  • R.M. Argent
    Bureau of Meteorology, Melbourne, Victoria, Australia
  • L. Bernard
    Technische Universität Dresden, Dresden, Germany
  • J. Coen
    National Center for Atmospheric Research, Boulder, Colorado, USA
  • O. David
    Colorado State University, Fort Collins, Colorado, USA
  • I. Demir
    University of Iowa, Iowa City, Iowa, USA
  • R. Denzer
    Hochschule für Technik und Wirtschaft des Saarlandes, Saarbrücken, Germany
  • Q. Duan
    Beijing Normal University, Beijing, China
  • A. Ernest
    The University of Texas Rio Grande Valley, Edinburg, Texas, USA
  • T. Filatova
    University of Twente, Enschede, Netherlands
  • S. Galelli
    Singapore University of Technology and Design, Singapore
  • C. Giupponi
    Università Ca' Foscari Venezia, Venezia, Italy
  • J.L. Goodall
    University of Virginia, Charlottesville, Virginia, USA
  • T.R. Green
    U.S. Department of Agriculture (USDA), Fort Collins, Colorado, USA
  • C. Gualtieri
    University of Naples Federico II, Napoli, Italy
  • J. Guillaume
    Aalto University, Espoo, Finland
  • M.C. Hill
    University of Kansas, Lawrence, Kansas, USA
  • M.R. Hipsey
    University of Western Australia, Perth, Western Australia, Australia
  • B. Hodges
    University of Texas at Austin, Austin, Texas, USA
  • A. Holzkaemper
    AGROSCOPE, Zürich, Switzerland
  • R.J. Hunt
    U.S. Geological Survey (USGS), Middleton, Wisconsin, USA
  • A.V.M. Ines
    Columbia University, Palisades, New York, USA
  • G. Iovine
    National Research Council of Italy (CNR), Cosenza, Italy
  • D. Karssenberg
    Utrecht University, Utrecht, Netherlands
  • K.J. Keesman
    Wageningen University, Wageningen, Netherlands
  • T. Kokkonen
    Aalto University, Espoo, Finland
  • R. Oglesby
    University of Nebraska, Lincoln, NE, USA
  • G. Petropoulos
    Aberystwyth University, Aberystwyth, UK
  • S.A. Pierce
    University of Texas at Austin, Austin, Texas, USA
  • N.W.T. Quinn
    Lawrence Berkeley National Laboratory, Berkeley, California, USA
  • M. Ratto
    European Commission Joint Research Centre (JRC), Ispra, Italy
  • S. Razavi
    University of Saskatchewan, Saskatoon, Saskatchewan, Canada
  • P. Reed
    Cornell University, Ithaca, New York, USA
  • J.-D. Rinaudo
    BRGM, Montpellier, France
  • C. Smith
    University of Queensland, Brisbane, Queensland, Australia
  • V. Snow
    AgResearch, Lincoln, New Zealand
  • C.J. Taylor
    Lancaster University, Lancaster, England, UK
  • A. van Griensven
    IHE Delft Institute for Water Education, Delft, Netherlands
  • P.A. Vanrolleghem
    Université Laval, Laval, Quebec, Canada
  • I. Vardavas
    University of Crete, Crete, Greece
  • P.H. Verburg
    VU University Amsterdam, The Netherlands
  • W Vervoort
    The University of Sydney, Eveleigh, New South Wales, Australia
  • K. Voigt
    Deutsches Forschungszentrum für Gesundheit und Umwelt, München, Germany
  • M. Volk
    Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
  • J. Vrugt
    University of California at Irvine, Irvine, California, USA
  • Z.-L. Yang
    University of Texas at Austin, Austin, Texas, USA