Natural Hazard Uncertainty Assessment: Modeling and Decision Support

ISBN-13: 9781119027867 / Angielski / Twarda / 2016 / 360 str.

Peter Webley; Karin Riley; Matthew Thompson

Opis

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.

Recenzje

"This volume, edited by Karin Riley, Peter Webley, and Matthew Thompson, tackles the often–neglected topic of uncertainty in judging the effectiveness of the natural disaster models used when informing action...While not for casual reading, this volume nonetheless provides an approachable way to learn about the realities of natural disaster modelling. In addition, it highlights the importance of uncertainty, an inseparable part of science that is very often ignored." (Phenotype June 2017)

Spis treści

Contributors vii

1 Uncertainty in Natural Hazards, Modeling and Decision Support: An Introduction to This Volume 1
Karin Riley, Matthew Thompson, Peter Webley, and Kevin D Hyde

Part I: Uncertainty, Communication, and Decision Support 9

2 Natural Hazard Modeling and Uncertainty Analysis 11
Matthew Thompson and Jord J Warmink

3 Understanding Uncertainty as a Key Interdisciplinary Problem in Earth System Science 21
Florian Rauser and Gernot Geppert

4 Uncertainty and Probability in Wildfire Management Decision Support: An Example from the United States 31
Matthew Thompson, David Calkin, Joe H Scott, and Michael Hand

5 Role of Uncertainty in Decision Support for Volcanic Ash Cloud Modeling 43
Peter Webley

Part II: Geological Hazards 57

6 Building an Uncertainty Modeling Framework for Real–Time VATD 59
Peter Webley, Abani Patra, Marcus Bursik, E Bruce Pitman, Jonathan Dehn, Tarung Singh, Puneet Singla, Matthew D Jones, Reza Madankan, E Ramona Stefanescu, and Solene Pouget

7 Uncertainties in Estimating Magma Source Parameters from InSAR Observation 89
Wenyu Gong, Zhong Lu, and Franz Meyer

8 Improving Model Simulations of Volcanic Emission Clouds and Assessing Model Uncertainties 105
Nina Iren Kristiansen, Delia Arnold, Christian Maurer, Julius Vira, Razvan Rădulescu, Damien Martin, ndreas Stohl, Kerstin Stebel, Mikhail Sofiev, Colin O’Dowd, and Gerhard Wotawa

9 Uncertainty Assessment of Pyroclastic Density Currents at Mount Vesuvius (Italy) Simulated Through the Energy Cone Model 125
Pablo Tierz, Laura Sandri, Antonio Costa, Roberto Sulpizio, Lucia Zaccarelli, Mauro Antonio Di Vito, and Warner Marzocchi

10 Earthquake Loss Estimation in the Gyeongju Area, Southeastern Korea, Using a Site Classification Map 147
Su Young Kang and Kwang–Hee Kim

11 Implications of Different Digital Elevation Models and Preprocessing Techniques to Delineate Debris Flow Inundation Hazard Zones in El Salvador 167
Eric Ross Anderson, Robert E Griffin, and Daniel E Irwin

12 Evaluating the Performance of FLO2D for Simulating Past Lahar Events at the Most Active Mexican Volcanoes: Popocatépetl and Volcán de Colima 179
Lizeth Caballero, Lucia Capra, and Rosario Vázquez

Part III: Biophysical and Climatic Hazards 191

13 An Uncertainty Analysis of Wildfire Modeling 193
Karin Riley and Matthew Thompson

14 Fire and Smoke Remote Sensing and Modeling Uncertainties: Case Studies in Northern Sub]Saharan Africa 215
Charles Ichoku, Luke T Ellison, Yun Yue, Jun Wang, and Johannes W Kaiser

15 Uncertainty and Complexity Tradeoffs When Integrating Fire Spread with Hydroecological Projections 231
Maureen C Kennedy and Donald McKenzie

16 Uncertainty Quantification and Propagation for Projections of Extremes in Monthly Area Burned Under Climate Change: A Case Study in the Coastal Plain of Georgia, USA 245
Adam J Terando, Brian Reich, Krishna Pacifici, Jennifer Costanza, Alexa McKerrow, and Jaime A Collazo

17 Simulating Vegetation Change, Carbon Cycling, and Fire Over the Western United States Using CMIP5 Climate Projections 257
D Bachelet, T Sheehan, K Ferschweiler, and J Abatzoglou

18 Sensitivity of Vegetation Fires to Climate, Vegetation, and Anthropogenic Drivers in the HESFIRE Model: Consequences for Fire Modeling and Projection Uncertainties 277
Yannick Le Page

19 Uncertainties in Predicting Debris Flow Hazards Following Wildfire 287
Kevin D Hyde, Karin Riley, and Cathelijne Stoof

20 Capturing Spatiotemporal Variation in Wildfires for Improving Postwildfire Debris–Flow Hazard Assessments 301 
Jessica R Haas, Matthew Thompson, Anne Tillery, and Joe H Scott

21 Uncertainty in Estimation of Debris–Flow Triggering Rainfall: Evaluation and Impact on Identification of Threshold Relationships 319
E I Nikolopoulos, F Marra, and M Borga

22 Prospects in Landslide Prediction: Confronting the Challenges of Precipitation Uncertainty 329
Natasha Markuzon, Catherine Slesnick, Erin Leidy, John Regan, Xiang Gao, and Adam Schlosser

Index 337