Computational Geosciences
Link: https://www.springer.com/journal/10596
Description: Computational Geosciences is a peer-reviewed journal publishing high-quality research on mathematical modeling, simulation, and numerical analysis applied to geoscientific problems, emphasizing advanced computational methods.
Key Words: mathematical modeling, numerical methods, simulation, geosciences, subsurface flow, data assimilation, high-performance computing, computational mathematics, uncertainty assessment, algorithms
Introduction:
Computational Geosciences, published by Springer Netherlands, is a leading peer-reviewed journal dedicated to advancing the application of computational techniques in the geosciences. Established in 1997, it focuses on high-quality papers that explore mathematical modeling, simulation, numerical analysis, and other computational methodologies to address complex geoscientific challenges. The journal is a vital platform for interdisciplinary collaboration among mathematicians, engineers, physicists, chemists, and geoscientists, fostering innovative solutions for problems in subsurface, surface, and atmospheric processes. Its ISSN is 1420-0597, and it is published quarterly, with an impact factor of 2.60 in 2023, reflecting a strong influence in its field, though it experienced a slight decline of 13.04% from the previous year. The journal ranks in the Q2 quartile for categories like Computational Mathematics, Computational Theory, and Computers in Earth Sciences, with an SJR score of 0.663 and an h-index of 79, indicating significant academic impact.
The journal’s scope is centered on advanced numerical methods for modeling subsurface flow and transport, with specific emphasis on aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high-performance parallel and grid computing. It also welcomes papers applying these methods to broader geoscientific fields, including geomechanics, geophysics, oceanography, and meteorology. Research published in Computational Geosciences often involves cutting-edge computational paradigms, such as finite element methods, finite volume methods, and machine learning techniques, to tackle topics like hydrogeology, reservoir simulation, and porous media flow. The journal encourages submissions that demonstrate novelty, practical importance, and rigorous scientific validation, with a strict peer-review process ensuring high standards.
Computational Geosciences supports a variety of article types, including research papers (up to 5,000 words), review papers (up to 10,000 words), case studies (up to 5,000 words), book or software reviews (1,500 words), and letters to the editor. Review papers require an approved outline from an editor prior to submission, ensuring relevance and depth. The journal promotes open science by requiring code and data to be shared via repositories like GitHub, with open-source licenses clearly indicated, and manuscripts with non-open-source code are desk-rejected. This commitment to reproducibility and accessibility is further supported by its data-sharing policies, encouraging authors to archive datasets in repositories and provide descriptive captions for accessibility.
The journal’s editorial board, including editors-in-chief Clint Dawson, Ivan Yotov, and Mary F. Wheeler, comprises leading scholars who ensure rigorous evaluation of submissions. It is indexed in major databases like Web of Science, Scopus, and Guide2Research, and its publications often involve contributions from top institutions such as Stanford University, University of Bergen, and the University of Texas at Austin. Computational Geosciences also fosters innovation by publishing work on emerging areas like computational electrochemistry, machine learning in geosciences, and differentiable simulators. Its open-access companion journal, Applied Computing & Geosciences, offers an alternative publication route with an article transfer service to streamline submissions. With a focus on both academic excellence and industrial relevance, Computational Geosciences continues to be a pivotal resource for advancing computational approaches in Earth sciences.
