UNIVERSITY of CALIFORNIA Santa Barbara an Analysis
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UNIVERSITY OF CALIFORNIA Santa Barbara An Analysis of Landslide Risk and Vulnerability in Distinct Realities: Low-Income Communities in Brazil and a Wealthy Community in the United States A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Geography by Erica Akemi Goto Committee in charge: Professor Keith Clarke, Committee Co-Chair Professor Edward Keller, Committee Co-Chair Professor Hugo Loáiciga Professor Summer Gray March 2021 The dissertation of Erica Akemi Goto is approved. _____________________________________________ Hugo Loáiciga _____________________________________________ Summer Gray _____________________________________________ Keith Clarke, Committee Co-Chair _____________________________________________ Edward Keller, Committee Co-Chair February 2021 An Analysis of Landslide Risk and Vulnerability in Distinct Realities: Low-Income Communities in Brazil and a Wealthy Community in the United States Copyright © 2020 by Erica Akemi Goto iii ACKNOWLEDGMENTS I would like to thank everyone that made this research possible. Many thanks to Dr. Eduardo Soares Macedo who helped me with the AHP variables and helped me reach out to other experts, to all the other IPT technicians who took the time to answer the AHP questionnaire, to all the technicians at the São Bernardo do Campo Municipality, especially Luiz Antonio Neves Costa and Fabiana Mendez de Souza, who guided me on choosing the best neighborhood for conducting my research in their city and local residents, who kept me safe during the fieldwork, to the Laboratório de Mecânica de Rochas of the University of São Paulo, especially Eduardo Carlos Heitzmann who guided me in the lab and Maria Eugenia Boscov who allow me to use their laboratory to perform part of my research, and to colleagues and friends who helped me conduct fieldwork at São Bernardo do Campo (Paul Alessio, Lucas Ciola, Carlos Eduardo Silva, Mauricio Hirata, Danilo Lomonaco Vitorelli). I would like to thank my lab colleagues who supported my work by exchanging ideas and forming a writing group. Special thanks to Rafael, Marcela, Haiyun, and Mike. I would like to thank my committee members, Hugo Loáiciga and Summer Gray, for taking the time to meet with me, criticize my work, and give suggestions. I also would like to thank Summer Gray for the opportunity to work closely with her, mentor me, and offer support during difficult times during the last two years. A special thank you to Robby Nadler, who helped me in my writing trajectory and always knew when and how to criticize in a nice way. Special thanks to my advisors, Keith Clarke and Edward Keller, for guiding and supporting me during my research. I would like to thank my parents and my sister for supporting me in all moments. I also would like to thank the Brazilian Government and the Science Without Borders Fellowship that supported me financially for 4 years. iv VITA OF ERICA AKEMI GOTO December 2020 EDUCATION Bachelor of Social Communication, University of Sao Paulo, Sao Paulo, 2006 Bachelor of Teaching Geoscience and Environmental Education, University of Sao Paulo, Sao Paulo, 2013 Master of Geoscience, University of Campinas, Campinas, 2014 Doctor in Geography, University of California, Santa Barbara, June 2020 (expected) PROFESSIONAL EMPLOYMENT Summer 2020: Research Assistant, Department of East Asian Language & Cultural Studies, University of California, Santa Barbara Summer 2000, 2019, 2018: Graduate Student Research, Earth Research Institute – University of California, Santa Barbara 2019-2020: Teaching Assistant, Department of Environmental Studies, University of California, Santa Barbara 2020: Instructor, Department of Environmental Studies, University of California, Santa Barbara 2015-2018: Teaching Assistant, Department of Geographyt, University of California, Santa Barbara PUBLICATIONS “Ordinal Logistic Regression to automatic classify shallow landslide risk level in Sao Paulo city, Brazil,” Landslide inventory mapping and vulnerability assessment (2020) “A mixed-methods approach to understanding debris flow vulnerability in Montecito, CA. Landslide inventory mapping and vulnerability assessment,” Landslide inventory mapping and vulnerability assessment (2020) “Using Expert’s Knowledge based on the Analytical Hierarchical Process (AHP) and the Brazilian Government Methodology (BGM) to map and compute the level of risk for shallow landslides in Brazil.,” submitted (2019) “A tool to compute the landslide degree of risk using R-Studio and R-Shiny,” Proceedings of the 4th ACM SIGSPATIAL International Workshop on Safety and Resilience (2018), ACM, New York. v AWARDS WLF5 Travel and Registration Support, 2019 Conference Grant - Dangermond Travel Funds Award, University of California, Santa Barbara, 2018, 2019 Student best paper - 4th ACM SIGSPATIAL International Workshop on Safety and Resilience, 2018 Conference Grant - UCSB GSA,2018 Summer fellowship – Earth Research Institute (ERI), 2016, 2017 Field Work Grant - Leal Anne Kerry Mertes Scholarship Award, 2016-2017 Ph.D. fellowship - Science Without Borders, CAPES, Brazilian Government, 2014-2018 FIELDS OF STUDY Major Field: Geography vi ABSTRACT by Erica Akemi Goto Landslides are natural events that occur in many parts of the world in both developed and developing countries. They can be triggered by rainfall, earthquakes, volcanos, and a combination of post-fire and rainfall. However, the impact they cause in a community can be very different, based on how the community can anticipate and respond. They can cause material losses and some minor property damage, but also, they can become natural disasters, resulting in significant material and human losses. One way to avoid and mitigate landslide disasters is by implementing Disaster Risk Reduction measures, such as risk mapping or developing an evacuation plan. These measures help municipalities plan before an event occurs, thereby protecting their communities and being proactive. In this doctoral dissertation, the focus is on two of these Disaster Risk Reduction measures: risk and vulnerability assessments. In the first part, the study is conducted in the Metropolitan Area of Sao Paulo, Brazil. In these urban areas, shallow landslides are frequent in low-income neighborhoods on hillslopes, especially during summer months, when intense rainfall frequently occurs. Chapters 2 and 3 propose two distinct methodologies to quantify an inventory-based shallow landslide risk mapping. The quantification is intended to reduce bias and standardize risk mapping methodology. In chapter 2, experts’ knowledge and the Analytical Hierarchical Process (AHP) method is applied to compute weights for variables, and application is developed and used to calculate the risk level automatically. In this study, variables that vii illustrate instability in the terrain were the ones with the highest contribution for a higher risk. In chapter 3, a large dataset from a previous mapping of Sao Paulo city and Ordinal Logistic Regression (OLR) was used to select essential variables and to compute their weights. The equation calculated can be used in the developed application to compute the risk level automatically. In chapter 4, a spatial analysis of the slope stability using SHALSTAB and Factor of Safety and saturated hydraulic conductivity was computed in two hillslopes of São Bernardo do Campo, in the Metropolitan area of Sao Paulo. In one of these sites, the hillslope is disturbed by human activities (previous homes, cut and filling, landfill), and in the second site, the hillslope is undisturbed. The saturated hydraulic conductivity and the slope stability analysis illustrate that the disturbed site has less homogeneous soil than does the undisturbed site. Additionally, based on the soil characteristics and results from SHALSTAB and Factor of Safety analysis, the undisturbed hillslope is more stable than the disturbed hillslope. The second part of the study was conducted in Montecito, California. The study was proposed after the 2018 Montecito debris flows that killed 23 people and damaged more than 400 homes. In this study, I used a parallel mixed-methods approach and a temporal-spatial analysis to understand the main factors that made the community vulnerable to debris-flows and to determine who were the most vulnerable people. The study concludes that the most vulnerable people were informal workers (gardens, housekeepers, caretakers, nannies), renters, and residents of areas that were in the voluntary evacuation zone. Lack of education about debris-flows and previous debris-flows in the region by the community increased the vulnerability of the entire community. Moreover, the institutional vulnerability was high for the entire community, but county measures in the aftermath contributed to the community viii resilience. Keywords: landslide, debris-flows, risk, landslide assessment, weights of evidence, SHALSTAB, vulnerability, AHP, OLR, mixed-methods. ix TABLE OF CONTENTS ACKNOWLEDGMENTS ..................................................................................................... iv ABSTRACT ........................................................................................................................... vii ABBREVIATIONS ............................................................................................................... xii EQUATION SYMBOLS ..................................................................................................... xiii LIST OF EQUATIONS ......................................................................................................