Dissertations, Theses, and Capstone Projects

Date of Degree

2-2024

Document Type

Dissertation

Degree Name

Ph.D.

Program

Earth & Environmental Sciences

Advisor

Juliana Maantay

Committee Members

Elia Machado

Deborah Balk

Glen Johnson

Subject Categories

Demography, Population, and Ecology | Environmental Indicators and Impact Assessment | Environmental Monitoring | Geographic Information Sciences | Physical and Environmental Geography | Place and Environment | Spatial Science

Keywords

Low elevation coastal zone (LECZ), Social vulnerability, risk to hydro-climate related hazards, National Family Health Survey of India (NFHS-4) dataset, spatial analysis, India

Abstract

Background & Problem Statement:

This study assessed social vulnerability and risk to hydroclimate hazards of Indian urban and rural populations in the Low Elevation Coastal Zone (LECZ), a contiguous coastal area with elevations less than 10 meters. The LECZ is considered an at-risk area as hydroclimate hazards tend to be heightened. Moreover, being the most populous country in the world, any hydroclimate hazards that hit the LECZ would disproportionately impact a large number of Indian populations. Understanding the social vulnerability and risk of the LECZ populations can help mitigate and prevent potential adverse outcomes for the populations.

Importantly, this study used the 2015-16 National Family Health Survey (NFHS-4) datasets as the data source for social vulnerability evaluation. The NFHS-4 datasets included GPS survey locations representing surveyed household clusters. However, all GPS locations have been intentionally displaced to protect the interviewees’ privacy. Therefore, this study also aimed to evaluate how the NFHS-4 GPS survey location displacements impact social vulnerability and risk measurements.

Research questions:

The study aimed to answer the following research questions: (1) What was the potential social vulnerability and risk to hydroclimate hazards of LECZ urban and rural populations? (2) How did social vulnerability and risk vary by state? (3) What was the uncertainty of the social vulnerability and risk in the LECZ when considering the displacement of the NFHS-4 GPS survey points?

Analysis/Methods:

To answer the research questions, the LECZ social vulnerability index (LSVI) scores and LECZ risk index (LRI) scores were calculated for all thirteen LECZ states and for urban and rural populations. The Intergovernmental Panel on Climate Change’s Fifth Assessment Report (IPCC AR5) framework for climate change risk was employed as the conceptual model in indices’ constructions.

Geographic Information Systems (GIS) and spatial techniques were used to analyze and integrate the NFHS-4 datasets with other spatial datasets, including global human settlement layer (GHSL) datasets and LECZ data. Furthermore, a sensitivity analysis was performed to evaluate the impacts of the NFHS-4 GPS survey location displacements on the index scores by calculating LSVI and LRI scores under four different scenarios, namely, the benchmark, the use-as-given scenario, the alternative scenario, and the maximized scenario. Each scenario used different spatial criteria in selecting NFHS-4 household samples relative to the LECZ. R programming language packages were used to calculate index scores and perform statistical tests on the index scores.

Findings & Results:

The results show that LECZ populations in all LECZ states were socially vulnerable and at risk. The index score rankings from all scenarios yielded similar results and were in agreement. Social vulnerability and risk have identical patterns: the statewide rural population has the highest social vulnerability and the highest risk. The LECZ rural population has the second highest social vulnerability and risk. Statewide urban population has the third highest social vulnerability and risk. LECZ rural population has the lowest social vulnerability and the lowest risk.

The ranking agreement across scenarios also implied that the NFHS-4 dataset could be used to assess social vulnerability and risk within the LECZ at a state level. However, a researcher should classify LECZ states into groups rather than using absolute ranking numbers to represent all states' social vulnerability and risk rankings.

Moreover, the maximized scenario was chosen to represent the social vulnerability and risk of LECZ populations. A choropleth map visualizing the maximized scenario’s index scores reveals that most east coastal states are extremely socially vulnerable or extremely at risk, or both. The west coastal states are relatively less socially vulnerable and less at risk than the east coastal states. However, most west coastal states tend to have higher risk ranking positions than social vulnerability ranking positions.

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