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Stochastic Environmental Research and Risk Assessment

Stochastic Environmental Research and Risk Assessment

Editor-in-Chief: George Christakos

ISSN: 1436-3240 (print version)
ISSN: 1436-3259 (electronic version)

Journal no. 477

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An interview with the Editor-in-Chief

Dr. George Christakos
Professor of Geography
Birch Distinguished Professor
Department of Geography
San Diego State University
Storm Hall 314
San Diego, CA 92182-4493, USA

Why is the journal important to the field? 

It is unique in terms of its focus on the blending of stochastic reasoning, spatiotemporal natural variation, in-situ uncertainty assessment, and interdisciplinarity. As such, SERRA hosts both methodological and applied papers on environmental phenomena and public health systems, in the broad sense.
It makes a very clear contribution in integrating different scientific fields within the stochastic context, and communicating them effectively, something that is apparently lacking in other journals interested in the study of environmental uncertainties and risks.

What is the key distinguishing aspect of the journal?  

The quartet: stochastic thinking - interdisciplinarity - vision - openness.
The journal is open to new ideas, to thought-provoking papers, and to young authors. Novel methodologies that were firstly proposed in SERRA are subsequently used and further developed elsewhere.
The journal reflects the stochastic features of environmental systems, and focuses on stochastic data science related research —this is very relevant due to large volume of data available in the modern world.
Unlike more theoretical journals, SERRA’s papers already deal with concrete and well-developed problems concerning engineering/hydrology/climate/environment/health.

How has the journal shaped/contributed to the field since its launch? 

The journal started with quite a narrow scope (reflected in the original title “Stochastic Hydrology & Hydraulics”) but then became a journal embracing very broad subjects with contributions from many areas of science.
It promotes the integrated study of uncertainty, space-time heterogeneity, and risk for environmental systems.
SERRA acts as a showroom for new stochastic methodologies with focus on practical problems; these methods are therefore used in applied journals. In this respect, InCites Citation Reports by Clarivate Analytics clearly show the strong relationship and transfer between SERRA and hydrological/climatic journals.
Many robust statistical methods were originally highlighted in this journal.

Which emerging research trend is reflected in the journal? Which current trends shape the field? 

Science-based spatiotemporal statistics and probability logic, interdisciplinary stochastic modeling, risk analysis and management (incl. dramatic events such as earthquakes and tsunamis).
Using newly available environmental (big) data from remote sensors, unmanned vehicles (drones), phones, etc.
Methods to account for space-time (nonstationary) effects of anthropogenic activities (not only “climate change”, but also land use, urbanization, exploitation of natural resources, etc.).

Key advice to first-time authors? 

This is a unique journal for studies related to spatiotemporal phenomena, environmental uncertainties and risks using novel concepts and tools.
First-time authors should bear in mind that SERRA is open to new (and perhaps controversial) ideas, and to interdisciplinary works. However, these ideas should be supported by convincing arguments and good literature reviews. Before submission, the authors should be sure that the overall quality of their work (in terms of presentation and technical rigor) match that of high quality works in the field. SERRA is considered an incubator for original stochastic methods to study environmental, earth and atmospheric phenomena, public health systems, and risk assessment.
First-time authors should bear in mind SERRA’s mission, history, and reputation, and its impact on applied research.

Some of the most influential articles of 2017 published in Stochastic Environmental Research and Risk Assessment: 

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For authors and editors

  • Journal Citation Reports®
    2018 Impact Factor
  • 2.807
  • Aims and Scope

    Aims and Scope


    Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas:

    - Spatiotemporal analysis and mapping of natural processes.

    - Enviroinformatics.

    - Environmental risk assessment, reliability analysis and decision making.

    - Surface and subsurface hydrology and hydraulics.

    - Multiphase porous media domains and contaminant transport modelling.

    - Hazardous waste site characterization.

    - Stochastic turbulence and random hydrodynamic fields.

    - Chaotic and fractal systems.

    - Random waves and seafloor morphology.

    - Stochastic atmospheric and climate processes.

    - Air pollution and quality assessment research.

    - Modern geostatistics.

    - Mechanisms of pollutant formation, emission, exposure and absorption.

    - Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection.

    - Bioinformatics.

    - Probabilistic methods in ecology and population biology.

    - Epidemiological investigations.

    - Models using stochastic differential equations stochastic or partial differential equations.

    - Hazardous waste site characterization.                                   

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