Official Journal of the International Environmental Modelling & Software Society

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.

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.

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 Modelling & 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 the Editor-in-Chief 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

Special Issue on Open Source GIS And Remote Sensing tools for Landslide and Geohazards assessment
Submission Date: 2024-07-31

Scientific progress is achieved as a combination ofindividual and community efforts. This is particularly valid for technological advancements, where new ideas and results are shared with the scientific community for further polishing. In the context of geohazards, the process is equally important and in this historical moment, when many research groups develop their own independent solutions, it is crucial to share tools and software to maximize their visibility but also their use and impact. For this reason, this special issue seeks to publish contributions that have codes, plugins, tools and software developed with the purpose of monitoring, modeling and assessing geohazards, and also to openly share them with colleagues across the world as open-source format.

We welcome submissions that have worked towards developing codes to automatize geohazard simulations or numerical analyses. Similarly, we invite contributions where plugins have been built to be called from well-established geospatial environments (e.g., QGIS). The same is valid for standalone software that may have been developed independently of pre-existing computing environments, web apps and web services (e.g. API).

We stress here that no constraint will be applied to the type of numerical solutions, whether they come from empirical experiments, statistical and machine learning models or physics-based simulations, they will all be positively received. Analogously, we also welcome contributions spanning over all natural hazards, positively considering hydrological, geomorphological, pedological processes, but also other geophysical hazards (e.g., framed as part of seismological or
meteorological research).

Guest editors:

Dr. Giacomo Titti, Eng. PhD
Organization: Department of Civil, Chemical, Environmental, and Material Engineering, Alma Mater Studiorum-University of Bologna, Bologna, Italy
Email: giacomo.titti@unibo.it 
Area(s) of Expertise: software development, numerical modeling, landslide susceptibility, GIS, spatial analysis

Dr. Luigi Lombardo, PhD
Organization: Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands
Email: l.lombardo@utwente.nl 
Area(s) of Expertise: Data-driven modeling, compound hazards, geospatial analysis 

Mr. Ashok Daha, MSc
Organization: Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede,The Netherlands
Email: a.dahal@utwente.nl 
Area(s) of Expertise: Machine learning, deep learning, geophysics, physics-based simulations 

Dr. Gabriele Amato, PhD
Organization: ItalFerr SpA, Italy
Email: amato.gabriele.88@gmail.com 
Area(s) of Expertise: Landslide hazard, remote sensing, inventory mapping, spatio-temporal modeling

Dr. Alessandro Sarretta, PhD.
Organization: Research Institute for Geohydrological Protection, National Council of Research, Padova, Italy
Email: alessandro.sarretta@irpi.cnr.it 
Area(s) of Expertise: Spatial data infrastructures, Interoperable services, Decision support systems, Participatory mapping, Spatial analysis

Dr. Calogero Schillaci, PhD.
Organization:  Joint Research Centre, Belgium
Email: calogero.schillaci@ec.europa.eu 
Area(s) of Expertise: Land degradation, digital soil mapping, Agronomy, GIS e RS

Dr. Aldo Lipani, PhD
Organization: University College London, London, United Kingdom
Email: aldo.lipani@ucl.ac.uk 
Area(s) of Expertise: Machine learning, deep learning, natural language processing

Prof. Marco Acutis, PhD
Organization: University of Milan
Email: marco.acutis@unimi.it 
Area(s) of Expertise: Cropping system simulation models, nitrogen and water management, soil organic matter dynamics, statistical methods

Manuscript submission information:

When submitting your manuscript please select the article type “VSI: Tools for geohazards”. Please submit your manuscript before the submission deadline (Jul 31, 2024).

All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.

Please ensure you read the Guide for Authors before writing your manuscript. The Guide for Authors and the link to submit your manuscript is available on the Journal’s homepage (at Environmental Modelling & Software - Journal - Elsevier).

Keywords:

natural hazard, open-source, tools and software, monitoring, modeling

Special Issue on System modelling in the "Big Science" era for environmental foresight
Submission Date: 2024-10-31

System modelling is essential for forecasting and understanding in environmental science. Recently, system modelling is undergoing changes in the "Big Science" era, characterized by complex problems, rapid-emerging resources (e.g., data, models, and computing resources), and broad collaborations. To facilitate environmental modelling, wide studies from various fields have been conducted, and different supporting platforms are expected to be established. Adherently, the sharing, exchange, and integration of knowledge and resources from multiple fields is becoming a significant method for modelling various environmental issues in terms of water pollution, renewable energy, climate change, ecosystem protection, and human well-being. In this special collection, we solicit manuscripts on new advances that break through domain barriers in the direction of environmental modelling, including observation, assimilation, open modelling, and integrated modelling. We particularly encourage studies that focus on the new generation of environmental models oriented to Future Earth, Global Change, and Sustainable Development.

Guest editors:

Dr. Fengyuan Zhang, PhD
School of Environment, Nanjing Normal University, China
Email: zhangfengyuan@nnu.edu.cn
Area(s) of Expertise: Geographic modelling, model sharing and reuse, model interoperability, GIS

Prof. Michael Barton, PhD
School of Human Evolution and Social Change, Arizona State University, USA
Email: Michael.Barton@asu.edu
Area(s) of Expertise: Socioecological systems, geospatial technologies, computational modelling, complex systems science, evolutionary theory, lithic technology

Prof. Yong Ge, PhD
Jiangxi Normal University and Institute of Geographic Sciences and Natural Resources Research, CAS, China.
Email: gey@lreis.ac.cn
Area(s) of Expertise: Statistical aspects of spatial and spatiotemporal data, spatial-temporal sampling, scaling, remote sensing image analysis and spatial data quality

Dr. Barry Croke, PhD
Institute for Water Futures, Australian National University, Australia
Email: barry.croke@anu.edu.au
Area(s) of Expertise: Surfacewater hydrology, hydrogeology, natural resource management, environmental science and management

Prof. Ioannis Athanasiadis, PhD
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, The Netherlands
Email: ioannis.athanasiadis@wur.nl
Area(s) of Expertise: Artificial intelligence for understanding nature, and big data science applications that relate to environment, agriculture, food and the quality of life

Prof. Daniel P. Ames, PhD
Editor-in-Chief of Environmental Modelling & Software
Department of Civil and Construction Engineering, Brigham Young University, USA
Email: dan.ames@byu.edu
Area(s) of Expertise: Geospatial data analysis, hydroinformatics, engineering software applications for hydrology, alternative energy, uncertainty analysis, GIS programming

Manuscript submission information:

When submitting your manuscript please select the article type “VSI: Sys-mod in Big Sci”. Please submit your manuscript before the submission deadline (Oct 31, 2024).

All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.

Please ensure you read the Guide for Authors before writing your manuscript. The Guide for Authors and the link to submit your manuscript is available on the Journal’s homepage (at Environmental Modelling & Software - Journal - Elsevier).

Keywords:

System modelling, environmental modelling, Big Science, open modelling, model integration

Special Issue on Good Modelling Practice
Submission Date: 2024-12-31

Collaborating Journals: Socio-Environmental Systems Modelling (SESMO), Environmental Modelling and Software (EMS), and Ecological Modelling (ECOMOD)

Modelling, computational, conceptual or otherwise, has become an indispensable tool for dealing with complex socio-environmental systems (SES), whether the purpose be system understanding, prediction or social learning. It is crucial therefore that any modelling undertaken be adequate in its practices for the purposes. But despite early advances this century, guidance and protocols for good modelling practice (GMP) in different settings have been lacking.

This joint special issue intends to provide a platform for visible and ongoing attention to what ought to be the current standard(s) for an appropriate modelling protocol that considers uncertainty in all its facets and promotes transparency in the quest for robust and reliable results. It aims to bring together and highlight work that develops, applies, or evaluates procedures for a trustworthy modelling workflow or that investigates good modelling practices for particular aspects of the workflow. We invite research that aims to improve the scientific basis of the entire modelling chain and places good modelling practice in focus. Particular aspects of GMP might include (but are not limited to) contributions on:

    Developing modelling conceptual maps, protocols and workflows
    Benchmarking model results
    Developing robust parameterization, calibration and evaluation frameworks
    Going beyond common metrics in assessing model performance and realism, including qualitative methods
    Conducting controlled model comparison studies
    Investigating subjectivity and reflexivity along the modelling chain, and addressing model fitness for purpose
    Identifying and prioritising sources of uncertainty and/or investigating uncertainty propagation along the modelling chain, and data acquisition planning for reducing uncertainty
    Communicating model results and their uncertainty to end users of model results
    Evaluating implications of model limitations and identifying priorities for future model development

    Examples of developing FAIR principles for digital assets in the modelling chain (Findable, Accessible, Interoperable and Reusable – see https://www.comses.net/education/responsible-practices/)

Note that interpretation of what is an SES is considered widely. Systems for example may include ecological, hydrological, energy, policy, health and social sectors, often a combination of these or others. An aim is to share experiences of GMP across sectors and disciplines.

Which journal to publish in?

Authors can submit to one of the three journals but only one must be chosen. It is envisaged that manuscripts will be reviewed and assessed by the relevant journal selected by the author(s) and Guest Editors will be across all manuscript processes.

Guest editors:

Dr. Hsiao-Hsuan (Rose) Wang, ECOMOD 
Organization: Ecological Systems Laboratory, Department of Ecology and Conservation Biology, Texas A&M University. College Station, Texas, USA.
Email: Hsiaohsuan.Wang@ag.tamu.edu
Area(s) of Expertise: System ecology; Ecological modelling; Environmental management

Dr. Sondoss Elsawah, EMS 
Organization: University of New South Wales Canberra, Australia
Email: s.elsawah@unsw.edu.au 
Area(s) of Expertise: Complex systems modelling, participatory modelling, interdisciplinary science

Dr. Tony Jakeman, SESMO 
Organization: Australian National University, Canberra, Australia
Email:  tony.jakeman@anu.edu.au 
Area(s) of Expertise: Modelling practice, uncertainty analysis, system identification, hydrology

Manuscript submission information:

Deadlines for submission

Enquiries and Abstracts of 500 words as soon as possible to any of the three Guest Editors above. Full papers by December 31st, 2024.

For any queries in submitting your manuscript to Environmental Modelling and Software, please kindly contact Dr. Sondoss Elsawah (s.elsawah@adfa.edu.au). Please reach out to Dr. Hsiao-Hsuan (Rose) Wang for ECOMOD and Dr. Tony Jakeman for SESMO respectively.

When submitting your manuscript please select the article type “VSI: Good Modelling Practice”. Please submit your manuscript before the submission deadline.

All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.

Please ensure you read the Guide for Authors before writing your manuscript. The Guide for Authors and the link to submit your manuscript is available on the Journal’s homepage (at Environmental Modelling & Software - Journal - Elsevier).

Keywords:

Modelling practices; Integrated assessment and modelling; Socio-ecological systems; Decision support; uncertainty; scaling