Environmental Modelling and Software - Impact Factor

Environmental Modelling and Software - Elsevier | 2024 Impact Factor:4.6 | Cite Score:9.8 | Q1

Environmental Modelling and Software Journal

Impact Factor and Journal Rank of Environmental Modelling and Software

About: Environmental Modelling and Software is a peer-reviewed journal published by Elsevier. It focuses on research in the field of environmental modeling and software development, providing a platform for researchers, academics, and practitioners to publish original research articles, reviews, and case studies that advance the understanding and application of modeling techniques and software tools in environmental science and engineering.
Objective: The primary objective of Environmental Modelling and Software is to promote research and innovation in environmental modeling and software development. The journal aims to explore methodologies, tools, and applications that enhance the modeling and simulation of environmental processes, systems, and phenomena. By publishing high-quality research, the journal contributes to the advancement of environmental modeling techniques and their impact on environmental management, policy-making, and sustainability.
Interdisciplinary Focus: Environmental Modelling and Software adopts an interdisciplinary approach, welcoming contributions from various fields related to environmental modeling and software development, including but not limited to, Environmental Science, Engineering, Computer Science, Geographic Information Systems (GIS), Remote Sensing, Hydrology, Ecology, Climate Science, Urban Planning, Public Health. This interdisciplinary perspective fosters collaboration and innovation, leading to the development of advanced modeling techniques and software tools that address the complex challenges in environmental research and management.
Global Reach and Impact: With a broad international readership and authorship, Environmental Modelling and Software has a global reach and impact. Its publications contribute to the dissemination of knowledge and advancements in environmental modeling worldwide. The journal content influences both academic research and practical applications, driving progress in areas such as climate modeling, ecosystem management, pollution control, natural resource management, and environmental risk assessment.
High Standards and Rigorous Review: Maintaining high academic standards, Environmental Modelling and Software conducts a rigorous peer-review process. Each submitted manuscript undergoes thorough evaluation by experts in the field to ensure the quality, originality, and scientific rigor of the research. This stringent review process upholds the integrity and reputation of the journal, ensuring that only high-quality and impactful research is published.
Significance: Environmental Modelling and Software plays a significant role in advancing research and practice in environmental modeling and software development. By providing a platform for the publication of cutting-edge research findings, the journal contributes to the growth of knowledge and innovation in environmental science and engineering. It serves as an essential resource for researchers, policymakers, and practitioners seeking to leverage modeling techniques and software tools to address environmental challenges, inform decision-making, and promote sustainable development.

Journal Home: Journal Homepage

Editor-in-Chief: Daniel Ames

Scope: The Environmental Modelling and Software journal, published by Elsevier, is a prestigious peer-reviewed publication that focuses on the development, application, and evaluation of environmental models and software tools. It serves as a platform for researchers, practitioners, and policymakers to exchange knowledge and advancements in environmental modelling and software development. Here is an overview of its key focus areas and scope:
1. Environmental Model Development:
Research on the development of environmental models to simulate and predict various natural processes, including hydrological processes, atmospheric processes, ecological dynamics, and contaminant transport.
Studies on model conceptualization, parameterization, calibration, and validation techniques.
2. Software Tools and Platforms:
Advancements in the design and implementation of software tools and platforms for environmental modelling, including integrated modelling environments, graphical user interfaces (GUIs), and web-based applications.
Research on open-source software development, interoperability standards, and model coupling frameworks.
3. Model Integration and Coupling:
Exploration of techniques for integrating and coupling different environmental models to address complex interdisciplinary research questions and management challenges.
Studies on model interoperability, data exchange standards, and workflow automation in integrated modelling systems.
4. Uncertainty and Sensitivity Analysis:
Research on uncertainty quantification and sensitivity analysis techniques in environmental modelling, including Monte Carlo simulations, Bayesian methods, and variance-based sensitivity analysis.
Studies on the propagation of uncertainty through models and the impact of input data uncertainties on model predictions.
5. Model Calibration and Validation:
Advancements in model calibration and validation techniques, including statistical methods, optimization algorithms, and remote sensing data assimilation.
Research on model evaluation metrics, validation protocols, and the importance of uncertainty quantification in model validation.
6. Decision Support Systems:
Exploration of decision support systems (DSS) based on environmental models, including tools for environmental risk assessment, land use planning, water resources management, and ecosystem restoration.
Studies on stakeholder engagement, participatory modelling approaches, and the integration of environmental models into decision-making processes.
7. Spatial and Temporal Modelling:
Research on spatial and temporal aspects of environmental modelling, including spatially explicit models, dynamic models, and models that account for temporal variability and trends.
Studies on the integration of remote sensing data, geographical information systems (GIS), and spatiotemporal modelling techniques.
8. Environmental Data Science:
Advancements in data-driven approaches to environmental modelling, including machine learning techniques, data mining, and big data analytics.
Research on the use of sensor networks, citizen science data, and high-resolution environmental data in model development and validation.
9. Environmental Impact Assessment:
Exploration of environmental impact assessment (EIA) models and tools for predicting and assessing the potential environmental consequences of human activities and development projects.
Studies on cumulative effects assessment, risk-based approaches, and the integration of environmental models into regulatory frameworks.
10. Climate Change Modelling:
Research on models and software tools for simulating and projecting climate change impacts, including global climate models (GCMs), regional climate models (RCMs), and impact assessment models.
Studies on uncertainty in climate projections, adaptation strategies, and the role of environmental modelling in climate policy and decision-making.