Eric Tate

Bio: Eric Tate is an academic researcher from University of Iowa. The author has contributed to research in topics: Social vulnerability & Flood myth. The author has an hindex of 19, co-authored 33 publications receiving 4579 citations. Previous affiliations of Eric Tate include University of South Carolina.

A place-based model for understanding community resilience to natural disasters

Abstract: There is considerable research interest on the meaning and measurement of resilience from a variety of research perspectives including those from the hazards/disasters and global change communities. The identification of standards and metrics for measuring disaster resilience is one of the challenges faced by local, state, and federal agencies, especially in the United States. This paper provides a new framework, the disaster resilience of place (DROP) model, designed to improve comparative assessments of disaster resilience at the local or community level. A candidate set of variables for implementing the model are also presented as a first step towards its implementation.

Social vulnerability to floods: Review of case studies and implications for measurement

Abstract: A leading challenge in measuring social vulnerability to hazards is for output metrics to better reflect the context in which vulnerability occurs. Through a meta-analysis of 67 flood disaster case studies (1997–2013), this paper profiles the leading drivers of social vulnerability to floods. The results identify demographic characteristics, socioeconomic status, and health as the leading empirical drivers of social vulnerability to damaging flood events. However, risk perception and coping capacity also featured prominently in the case studies, yet these factors tend to be poorly reflected in many social vulnerability indicators. The influence of social vulnerability drivers varied considerably by disaster stage and national setting, highlighting the importance of context in understanding social vulnerability precursors, processes, and outcomes. To help tailor quantitative indicators of social vulnerability to flood contexts, the article concludes with recommendations concerning temporal context, measurability, and indicator interrelationships.

Social vulnerability indices: a comparative assessment using uncertainty and sensitivity analysis

Abstract: Social vulnerability indices have emerged over the past decade as quantitative measures of the social dimensions of natural hazards vulnerability. But how reliable are the index rankings? Validation of indices with external reference data has posed a persistent challenge in large part because social vulnerability is multidimensional and not directly observable. This article applies global sensitivity analyses to internally validate the methods used in the most common social vulnerability index designs: deductive, hierarchical, and inductive. Uncertainty analysis is performed to assess the robustness of index ranks when reasonable alternative index configurations are modeled. The hierarchical design was found to be the most accurate, while the inductive model was the most precise. Sensitivity analysis is employed to understand which decisions in the vulnerability index construction process have the greatest influence on the stability of output rankings. The deductive index ranks are found to be the most sensitive to the choice of transformation method, hierarchical models to the selection of weighting scheme, and inductive indices to the indicator set and scale of analysis. Specific recommendations for each stage of index construction are provided so that the next generation of social vulnerability indices can be developed with a greater degree of transparency, robustness, and reliability.

HAZUS-MH Flood Loss Estimation Methodology. II. Damage and Loss Assessment

Abstract: Part I of this two-part paper provided an overview of the HAZUS-MH Flood Model and a discussion of its capabilities for characterizing riverine and coastal flooding. Included was a discussion of the Flood Information Tool, which permits rapid analysis of a wide variety of stream discharge data and topographic mapping to determine flood-frequencies over entire floodplains. This paper reports on the damage and loss estimation capability of the Flood Model, which includes a library of more than 900 damage curves for use in estimating damage to various types of buildings and infrastructure. Based on estimated property damage, the model estimates shelter needs and direct and indirect economic losses arising from floods. Analyses for the effects of flood warning, the benefits of levees, structural elevation, and flood mapping restudies are also facilitated with the Flood Model.

HAZUS-MH Flood Loss Estimation Methodology. I: Overview and Flood Hazard Characterization

Abstract: Part I of this two-part paper provides an overview of the HAZUS-MH Flood Model and a discussion of its capabilities for characterizing riverine and coastal flooding hazard. Included is a discussion of the Flood Information Tool, which permits rapid analysis of a wide variety of stream discharge data and topographic mapping to determine flood-frequencies over entire floodplains. Part II reports on the damage and loss estimation capability of the Flood Model, which includes a library of more than 900 damage curves for use in estimating damage to various types of buildings and infrastructure. Based on estimated property damage, the model estimates shelter needs and direct and indirect economic losses arising from floods. Analyses for the benefits of flood warning, levees, structural elevation, and flood mapping restudies are examples of analyses that can be performed with the Flood Model.

Applied Linear Regression Models

Abstract: (1991). Applied Linear Regression Models. Journal of Quality Technology: Vol. 23, No. 1, pp. 76-77.

Disaster Resilience Indicators for Benchmarking Baseline Conditions

Abstract: There is considerable federal interest in disaster resilience as a mechanism for mitigating the impacts to local communities, yet the identification of metrics and standards for measuring resilience remain a challenge This paper provides a methodology and a set of indicators for measuring baseline characteristics of communities that foster resilience By establishing baseline conditions, it becomes possible to monitor changes in resilience over time in particular places and to compare one place to another We apply our methodology to counties within the Southeastern United States as a proof of concept The results show that spatial variations in disaster resilience exist and are especially evident in the rural/urban divide, where metropolitan areas have higher levels of resilience than rural counties However, the individual drivers of the disaster resilience (or lack thereof)-social, economic, institutional, infrastructure, and community capacities-vary widely

Linkages between vulnerability, resilience, and adaptive capacity

Abstract: Cet article analyse les relations conceptuelles (imprecises) de la vulnerabilite, de la resilience et de la capacite d’adaptation aux changements climatiques selon le systeme socio-ecologique (socio-ecologigal systems – SES) afin de comprendre et anticiper le comportement des composantes sociales et ecologiques du systeme. Une serie de questions est proposee par l’auteur sur la specification de ces termes afin de developper une structure conceptuelle qui inclut les dimensions naturelles et so...