Natural Hazard Uncertainty Assessment

Modeling and Decision Support

Karin Riley, Peter Webley, Matthew Thompson

• Publisher: American Geophysical Union
• Year: 2016
• ISBN:
  9781119028093
• Edition: 1
• Topic: Scienze fisiche
• Subtopic: Geologia e scienze della terra

Uncertainties are pervasive in natural hazards, and it is crucial to develop robust and meaningful approaches to characterize and communicate uncertainties to inform modeling efforts. In this monograph we provide a broad, cross-disciplinary overview of issues relating to uncertainties faced in natural hazard and risk assessment. We introduce some basic tenets of uncertainty analysis, discuss issues related to communication and decision support, and offer numerous examples of analyses and modeling approaches that vary by context and scope. Contributors include scientists from across the full breath of the natural hazard scientific community, from those in real-time analysis of natural hazards to those in the research community from academia and government. Key themes and highlights include:

• Substantial breadth and depth of analysis in terms of the types of natural hazards addressed, the disciplinary perspectives represented, and the number of studies included
• Targeted, application-centered analyses with a focus on development and use of modeling techniques to address various sources of uncertainty
• Emphasis on the impacts of climate change on natural hazard processes and outcomes
• Recommendations for cross-disciplinary and science transfer across natural hazard sciences

This volume will be an excellent resource for those interested in the current work on uncertainty classification/quantification and will document common and emergent research themes to allow all to learn from each other and build a more connected but still diverse and ever growing community of scientists. Read an interview with the editors to find out more:
https://eos.org/editors-vox/reducing-uncertainty-in-hazard-prediction

1
Uncertainty in Natural Hazards, Modeling and Decision Support: An Introduction to This Volume

Karin Riley,¹ Matthew Thompson,¹ Peter Webley,² and Kevin D. Hyde³

¹ Rocky Mountain Research Station, US Forest Service, Missoula, Montana, USA

² Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska, USA

³ University of Wyoming, Laramie, Wyoming, USA

1.1. INTRODUCTION

Modeling has been used to characterize and map natural hazards and hazard susceptibility for decades. Uncertainties are pervasive in natural hazards analysis, including a limited ability to predict where and when extreme events will occur, with what consequences, and driven by what contributing factors. Modeling efforts are challenged by the intrinsic variability of natural and human systems, missing or erroneous data, parametric uncertainty, model‐based or structural uncertainty, and knowledge gaps, among other factors. Further, scientists and engineers must translate these uncertainties to inform policy decision making, which entails its own set of uncertainties regarding valuation, understanding limitations, societal preferences, and cost‐benefit analysis. Thus, it is crucial to develop robust and meaningful approaches to characterize and communicate uncertainties.

Only recently have researchers begun to systematically characterize and quantify uncertainty in the modeling of natural hazards. Many factors drive the emergence of these capabilities, such as technological advances through increased computational power and conceptual development of the nature and complexity of uncertainty. These advances, along with increased sophistication in uncertainty analysis and modeling, are currently enabling the use of probabilistic simulation modeling, new methods that use observational data to constrain the modeling approaches used, and other quantitative techniques in the subdisciplines of natural hazards. In turn, these advances are allowing assessments of uncertainty that may not have been possible in the past.

Given the expanding vulnerability of human populations and natural systems, management professionals are ever more frequently called upon to apply natural hazard modeling in decision support. When scientists enter into predictive services, they share professional, moral, legal, and ethical responsibilities to account for the uncertainties inherent in predictions. Where hazard predictions are flawed, limited resources may be unjustifiably be spent in the wrong locations, property may be lost, already stressed ecosystems may be critically damaged, and potentially avoidable loss of human life may occur. These essential concerns for reliable decision support compel thorough characterization of the uncertainties inherent in predictive models.

1.2. ORIGINS AND OBJECTIVES OF THIS VOLUME

This volume is an outcome of the 2013 American Geophysical Union (AGU) Fall Meeting session entitled “Uncertainty in Natural Hazard Assessment: Volcanoes, Earthquakes, Wildfires, and Weather Phenomena,” which was a combination of two AGU Focus Group Sections: Natural Hazards and Volcanology/Geochemistry/Petrology. The session was inspired in part by the AGU SWIRL program, which encourages interdisciplinary research. In 2013, the SWIRL program offered a theme “Characterizing Uncertainty.” In the session, researchers from volcanology, wildfire, landslide analysis, and other fields were brought together to compare results in characterizing uncertainties and developing methods for spatial and temporal understanding of event probability. This monograph focuses largely on the work presented at this AGU session, as well as other presentations from across the 2013 AGU fall meeting that had a focus associated with the AGU SWIRL theme, “Characterizing Uncertainty.”

The principal objectives of this monograph are to provide breadth in terms of the types of natural hazards analyzed, to provide depth of analysis for each type of natural hazard in terms of varying disciplinary perspectives, and to examine emerging techniques in detail. As a result, the volume is largely application focused and targeted, with an emphasis on assorted tools and techniques to address various sources of uncertainty. An additional emphasis area includes analyzing the impacts of climate change on natural hazard processes and outcomes. We chose studies from various continents to highlight the global relevance of this work in mitigating hazards to human life and other natural and socioeconomic values at risk. In assembling studies across types of natural hazards, we illuminate methodologies that currently cross subdisciplines, and identify possibilities for novel applications of current methodologies in new disciplines.

To our knowledge, this volume is unique in that it brings together scientists from across the full breadth of the AGU scientific community, including those in real‐time analysis of natural hazards and those in the natural science research community. Taken together, the chapters provide documentation of the common themes that cross these disciplines, allowing members of the AGU and broader natural hazards communities to learn from each other and build a more connected network.

We hope this will be a useful resource for those interested in current work on uncertainty classification and quantification and that it will encourage information exchange regarding characterization of uncertainty across disciplines in the natural and social sciences and will generally benefit the wider scientific community. While the work does not exhaustively address every possible type of hazard or analysis method, it provides a survey of emerging techniques in assessment of uncertainty in natural hazard modeling, and is a starting point for application of novel techniques across disciplines.

1.3. STRUCTURE

The remainder of this chapter introduces the contents of each part and chapter, and then distills emergent themes for techniques and perspectives that span the range of natural hazards studied. The monograph is composed of three main parts: (1) Uncertainty, Communication, and Decision Support (4 chapters); (2) Geological Hazards (7 chapters); and (3) Biophysical and Climatic Hazards (10 chapters). Specific types of natural hazards analyzed include volcanoes, earthquakes, landslides, wildfires, storms, and nested disturbance events such as postfire debris flows.

1.3.1. Part I: Uncertainty, Communication, and Decision Support

Here we provide a broad, cross‐disciplinary overview of issues relating to uncertainty characterization, uncertainty communication, and decision support. Whereas most chapters in the subsequent two sections address specific quantitative analysis and modeling techniques, we begin with more qualitative concerns. We address questions related to various facets of uncertainty, introduce some basic tenets of uncertainty analysis, discuss challenges of clear communication across disciplines, and contemplate the role of uncertainty assessment in decision processes as well as at the science‐policy interface.

In Chapter 2, Thompson and Warmink provide an overarching framework for identifying and classifying uncertainties. While they focus on uncertainty analysis in the context of modeling, the basic framework can be expanded to consider sources of uncertainty across the stages of decision making and risk management. While other typologies and frameworks exist and may be more suitable to a specific domain, the main point is the importance of beginning with the transparent and systematic identification of uncertainties to guide subsequent modeling and decision processes.

In Chapter 3, Rauser and Geppert focus on the problem of communicating uncertainty between disciplines. The authors bring to bear perspectives from the Earth system science community, leveraging insights from a series of workshops and conferences focused on understanding and interpreting uncertainty. Like natural hazards analysis, the field of Earth system science integrates a wide range of scientific disciplines, and so lessons on developing a common language of uncertainty across disciplines are highly relevant. As with Thompson and Warmink [Chapter 2, this volume], the authors stress the importance of being clear and explicit regarding the types and characteristics of uncertainties faced.

Last, Thompson et al. [Chapter 4, this volume] and Webley [Chapter 5, this volume] provide examples of operational decision support systems that incorporate uncertainty and probability. Thompson and coauthors focus on the context of wildfire incident management, and discuss the use of stochastic fire simulation to generate probabilistic information on possible fire spread, how this information can facilitate strat...

Table of contents

• COVER
• TITLE PAGE
• TABLE OF CONTENTS
• CONTRIBUTORS
• 1 Uncertainty in Natural Hazards, Modeling and Decision Support
• Part I: Uncertainty, Communication, and Decision Support
• Part II: Geological Hazards
• Part III: Biophysical and Climatic Hazards
• INDEX
• END USER LICENSE AGREEMENT