The Spatial Dependence of Flood Hazard and Risk in the United States

Understanding the spatial or geographical dependence of income inequality and regional inequality is crucial in the study of inequality. This paper employs a multi-scale, multi-mechanism framework to map and analyze historical patterns of regional and income inequality in the United States (US) by using state and regional panel data spanning over a century. To explore the patterns systematically and see the role of spatial partitioning, we organize the data around several established geographical partitions before conducting various geographical information system (GIS) analyses and statistical techniques. We also investigate the spatial dependence of income inequality and regional inequality. We find that spatial autocorrelation exists for both types of inequality in the US. However, the magnitude of spatial dependence for regional inequality is declining whereas it is volatile for income inequality over time. While income inequality has been at its peak in the most recent decades, we also notice that regional inequality is at its lowest point. As for the choice of partitioning, we observe that within inequality dominates for Census Divisions and Bureau of Economic Analysis (BEA) regions. Conversely, we see that between inequality overall contributes the most to the inequality among Census Regions.

Download Full-text

Climatology of Flooding in the United States

Oxford Research Encyclopedia of Natural Hazard Science ◽

10.1093/acrefore/9780199389407.013.123 ◽

2017 ◽

Cited By ~ 7

Author(s):

Gabriele Villarini ◽

Louise Slater

Keyword(s):

United States ◽

Flood Hazard ◽

Large Body ◽

The United States ◽

Temporal Changes ◽

Flood Frequency ◽

Flood Frequency Analysis ◽

Anthropogenic Factors ◽

Past Century ◽

Flood Peak

Flood losses in the United States have increased dramatically over the course of the past century, averaging US$7.96 billion in damages per year for the 30-year period ranging from 1985 to 2014. In terms of human fatalities, floods are the second largest weather-related hazard in the United States, causing approximately 80 deaths per year over the same period. Given the wide-reaching impacts of flooding across the United States, the evaluation of flood-generating mechanisms and of the drivers of changing flood hazard are two areas of active research. Flood frequency analysis has traditionally been based on statistical analyses of the observed flood distributions that rarely distinguish among physical flood-generating processes. However, recent scientific advances have shown that flood frequency distributions are often characterized by “mixed populations” arising from multiple flood-generating mechanisms, which can be challenging to disentangle. Flood events can be driven by a variety of physical mechanisms, including rain and snowmelt, frontal systems, monsoons, intense tropical cyclones, and more generic cyclonic storms. Temporal changes in the frequency and magnitude of flooding have also been the subject of a large body of work in recent decades. The science has moved from a focus on the detection of trends and shifts in flood peak distributions towards the attribution of these changes, with particular emphasis on climatic and anthropogenic factors, including urbanization and changes in agricultural practices. A better understanding of these temporal changes in flood peak distributions, as well as of the physical flood-generating mechanisms, will enable us to move forward with the estimation of future flood design values in the context of both climatic and anthropogenic change.

Download Full-text

Spatial Dependence in the Relationship between Climate Change and Internal Migration: Evidence from the United States

SSRN Electronic Journal ◽

10.2139/ssrn.3906643 ◽

2021 ◽

Author(s):

Marius Braun

Keyword(s):

Climate Change ◽

United States ◽

Internal Migration ◽

Spatial Dependence ◽

The United States ◽

The Relationship

Download Full-text

How likely are widespread floods in US river basins? Seeking answers using a stochastic, wavelet-based approach

10.5194/egusphere-egu2020-1781 ◽

2020 ◽

Author(s):

Manuela Irene Brunner ◽

Simon Papalexiou ◽

Eric Gilleland

Keyword(s):

United States ◽

River Basin ◽

Flood Hazard ◽

Public Awareness ◽

River Basins ◽

The United States ◽

Large River ◽

Simultaneous Occurrence ◽

Large Set ◽

Flood Events

Flooding can affect large regions leading to high economic and societal costs. Estimating regional flood risk is crucial for developing adaptation strategies, public awareness policies, and protection structures. Yet, estimating regional flood hazard is not trivial because of the few large flood events observed. Here, we derive regional flood hazard estimates for large river basins in the United States by using a stochastic streamflow generator. This allows us to increase the number of flood events available for the analysis and to investigate the simultaneous occurrence of flooding in different parts of a river basin. We propose the continuous, stochastic simulation approach (PRSim.wave), which combines a non-parametric spatio-temporal model based on the wavelet transform with the parametric kappa distribution. The model reproduces the temporal and distributional characteristics of streamflow at individual sites and retains the spatial dependencies between sites even for spatial extremes. We use PRSim.wave to generate long and spatially consistent time series of daily discharge for a large set of catchments in the conterminous United States. For each catchment, we extract flood events from the simulated series using a peak-over-threshold approach to derive a spatial dataset of flood occurrences. Using this dataset, we estimate how probable it is that a certain percentage of stations within a specific river basin is jointly flooded. We show that: (1) there are strong regional differences in the likelihood of joint and potentially widespread flooding and (2) there are spatial differences in regional flood hazard estimates which could not be derived from observed data only. We deem our approach a valuable tool for water managers and policy makers to make informed decisions on the risk of widespread flooding.

Download Full-text

Flood hazard management in the United States and the National Flood Insurance Program

Geoforum ◽

10.1016/0016-7185(84)90023-x ◽

1984 ◽

Vol 15 (4) ◽

pp. 525-542 ◽

Cited By ~ 9

Author(s):

Nigel W. Arnell

Keyword(s):

United States ◽

Flood Hazard ◽

The United States ◽

Flood Insurance ◽

National Flood Insurance Program ◽

Hazard Management ◽

Insurance Program ◽

Flood Hazard Management

Download Full-text

Analysis of Flood Fatalities in the United States, 1959–2019

Water ◽

10.3390/w13131871 ◽

2021 ◽

Vol 13 (13) ◽

pp. 1871

Author(s):

Zhongyu Han ◽

Hatim O. Sharif

Keyword(s):

United States ◽

Risk Factors ◽

Flood Hazard ◽

Age Groups ◽

The United States ◽

Flood Events ◽

Flash Flooding ◽

Factors Associated ◽

Different Types ◽

Spatial And Temporal Characteristics

Flooding is one of the main weather-related disasters that cause numerous fatalities every year across the globe. This study examines flood fatalities reported in the contiguous United States (US) from 1959 to 2019. The last two decades witnessed major flood events, changing the ranking of the top states compared to previous studies, with the exception of Texas, which had significantly higher flood-related fatalities than any other state. The rankings of counties within some states changed as well. The study aims to improve understanding of the situational conditions, demographics, and spatial and temporal characteristics associated with flood fatalities. The analysis reveals that flash flooding is associated with more fatalities than other flood types. In general, males are much more likely to be killed in floods than females. The analysis also suggests that people in the age groups of 10–19, 20–29, and 0–9 are the most vulnerable to flood hazard. Purposely driving or walking into floodwaters accounts for more than 86% of total flood fatalities. Thus, the vast majority of flood fatalities are preventable. The results will help identify the risk factors associated with different types of flooding and the vulnerability of the exposed communities.

Download Full-text

Community Flood Impacts and Infrastructure: Examining National Flood Impacts Using a High Precision Assessment Tool in the United States

Water ◽

10.3390/w13213125 ◽

2021 ◽

Vol 13 (21) ◽

pp. 3125

Author(s):

Jeremy R. Porter ◽

Evelyn Shu ◽

Michael Amodeo ◽

Ho Hsieh ◽

Ziyan Chu ◽

...

Keyword(s):

United States ◽

High Resolution ◽

Flood Risk ◽

Local Community ◽

Assessment Tool ◽

Flood Hazard ◽

Past Research ◽

The United States ◽

Social Infrastructure ◽

Flood Impacts

Changing environmental conditions are driving worsening flood events, with consequences for counties, cities, towns, and local communities. To understand individual flood risk within this changing climate, local community resiliency and infrastructure impacts must also be considered. Past research has attempted to capture this but has faced several limitations. This study provides a nation-wide model of community flooding impacts within the United States currently and in 30 years through the use of high-resolution input data (parcel-level), multi-source flood hazard information (four major flood types), multi-return period hazard information (six return periods), operational threshold integration, and future-facing projections. Impacts are quantified here as the level of flooding relative to operational thresholds. This study finds that over the next 30 years, millions of additional properties will be impacted, as aspects of risk are expected to increase for residential properties by 10%, roads by 3%, commercial properties by 7%, critical infrastructure facilities by 6%, and social infrastructure facilities by 9%. Additionally, certain counties and cities persistently display impact patterns. A high-resolution model capturing aspects of flood risk as related to community infrastructure is important for an understanding of overall community risk.

Download Full-text