Modeling Tools for Environmental Engineers and Scientists

Nirmala Khandan (New Mexico State University, Las Cruces, USA)

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English

CRC Press
30 June 2020

Agriculture & related industries; Mathematical modelling; Environmental science, engineering & technology; Agricultural science

Modeling Tools for Environmental Engineers and Scientists enables environmental professionals, faculty, and students with minimal computer programming skills to develop computer-based mathematical models for natural and engineered environmental systems. The author illustrates how commercially available syntax-free authoring software can be adapted to create customized, high-level models of environmental phenomena in groundwater, soil, aquatic, and atmospheric systems, and in engineered reactors.

This book includes a review of mathematical modeling and fundamental concepts such as material balance, reactor configurations, and fate and transport of environmental contaminants. It illustrates, using numerous examples, how mathematical and dynamic modeling software can be applied in analyzing and simulating natural and engineered environmental systems. The tools and examples included are applicable to a wide range of problems, both in the classroom and in the field.

By: Nirmala Khandan (New Mexico State University Las Cruces USA)
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 229mm, Width: 152mm,
Weight: 453g
ISBN: 9780367578701
ISBN 10: 0367578700
Pages: 328
Publication Date: 30 June 2020
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Nirmala Khandan

Reviews for Modeling Tools for Environmental Engineers and Scientists

This book provides a catalog, descriptions and reviews 'Ecological models' ranging from statistical extrapolation models to population, Ecosystem and landscape models. The editors are leaders in the field. They and the authors have performed a valuable service to the ecorisk community. It is now the task of practitioners to explore this array of models and determine how to implement them in specific cases using realistically available data sets. -Glenn W. Suter, II, United States EPA, Cincinnati, Ohio, USA