Uncertainty in the predictions of science when applied to the environment is an issue of great current relevance in relation to the impacts of climate change, protecting against natural and man-made disasters, pollutant transport and sustainable resource management. However, it is often ignored both by scientists and decision makers, or interpreted as a conflict or disagreement between scientists. This is not necessarily the case, the scientists might well agree, but their predictions would still be uncertain and knowledge of that uncertainty might be important in decision making. Environmental Modelling: An Uncertain Future? introduces students, scientists and decision makers to: the different concepts and techniques of uncertainty estimation in environmental prediction the philosophical background to different concepts of uncertainty the constraint of uncertainties by the collection of observations and data assimilation in real-time forecasting techniques for decision making under uncertainty. This book will be relevant to environmental modellers, practitioners and decision makers in hydrology, hydraulics, ecology, meteorology and oceanography, geomorphology, geochemistry, soil science, pollutant transport and climate change. A companion website for the book can be found at www.uncertain-future.org.uk

Modeling Uncertainty in the Earth Sciences highlights the various issues, techniques and practical modeling tools available for modeling the uncertainty of complex Earth systems and the impact that it has on practical situations. The aim of the book is to provide an introductory overview which covers a broad range of tried-and-tested tools. Descriptions of concepts, philosophies, challenges, methodologies and workflows give the reader an understanding of the best way to make decisions under uncertainty for Earth Science problems. The book covers key issues such as: Spatial and time aspect; large complexity and dimensionality; computation power; costs of 'engineering' the Earth; uncertainty in the modeling and decision process. Focusing on reliable and practical methods this book provides an invaluable primer for the complex area of decision making with uncertainty in the Earth Sciences.

Integrated regional models are conceptual and mathematical models that describe the physical environment, biological interactions, human decision-making, and human impact on the environment. Efforts are now being made to integrate regional models from the physical, biological and social sciences in order to respond to diverse environmental problems. This volume explores the latest research developments on processes operating at a variety of scales, including regions, and how scientists can combine their efforts to develop models linking biological, physical, and human systems. Data requirements for successful integrated regional models are identified and discussed. Chapters also consider methodological questions, such as whether to integrate disciplinary approaches at the beginning or the end of the modelling process, and whether integrated regional models should focus on specific regions or specific problems. The information in this volume will enable the reader to view problems such as coastal zone management, atmospheric pollution, non-point source pollution, commodity production in forested areas, and urban expansion in a broad, conceptual context. Researchers and graduate students in ecology, biology, geography and geology will benefit from this innovative approach to contemporary environmental problems.

This book examines the impacts of global change on terrestrial ecosystems. Emphasis is placed on impacts of atmospheric, climate and land use change, and the book discusses the future challenges and the scientific frameworks to address them. Finally, the book explores fundamental new research developments and the need for stronger integration of natural and human dimensions in addressing the challenge of global change.

This book presents an overview of modeling and simulation of environmental systems via diverse research problems and pertinent case studies. It is divided into four parts covering sustainable water resources modeling, air pollution modeling, Internet of Things (IoT) based applications in environmental systems, and future algorithms and conceptual frameworks in environmental systems. Each of the chapters demonstrate how the models, indicators, and ecological processes could be applied directly in the environmental sub-disciplines. It includes range of concepts and case studies focusing on a holistic management approach at the global level for environmental practitioners. Features: Covers computational approaches as applied to problems of air and water pollution domain. Delivers generic methods of modeling with spatio-temporal analyses using soft computation and programming paradigms. Includes theoretical aspects of environmental processes with their complexity and programmable mathematical approaches. Adopts a realistic approach involving formulas, algorithms, and techniques to establish mathematical models/computations. Provides a pathway for real-time implementation of complex modeling problem formulations including case studies. This book is aimed at researchers, professionals and graduate students in Environmental Engineering, Computational Engineering/Computer Science, Modeling/Simulation, Environmental Management, Environmental Modeling and Operations Research.