Why did so many people die in the Lower Ninth Ward?

Posted on August 29, 2015 By

My last blog addressed a question that I’ve gotten the most over the last decade: how many people died because of Hurricane Katrina impacts in Louisiana? This blog post deals with the next most common question that I get: Why did so many people die in the Lower Ninth Ward?

Typically, the person asking, whether a reporter, researcher, policy analyst, or anyone else, follows the question with the suggestion that it has to do with evacuation rates being lower there because of the social-economic characteristics of the neighborhood’s population. My response is that there is no evidence to support this explanation and that the true explanation lies with hydrodynamics, specifically depth and flow velocity, and not social-economics. In what follows, I lay out the rationale for this explanation. Details are available in my dissertation, which has been published as a scientific monograph.  This specific avenue of my research has also been presented at the 2011 Basic of the Basin Workshop.

The figure below is the result of a point pattern analysis of the victim recovery locations. It shows the density of the points interpolated to a grid. The figure shows that the density of victims is indeed strongest in the Lower Ninth Ward, adjacent to the two catastrophic failures of the levees along the Inner Harbor Navigational Canal, also known as the Industrial Canal. However, this map is just based on the raw count of victims and does not take into account the distribution of the underlying population at risk.

Kernel Density of Katrina VictimsMap of the Kernal Density Point Pattern Analysis of Hurricane Katrina Victim Recovery Locations.


Following basic epidemiological practice, disaster health impacts are measured and modeled as a rate (proportion) relative to an underlying “at risk” population. The rationale is fairly simple: you need a measure of risk that is independent of the size of the population. However, measuring that population denominator gets tricky when when the population is highly dynamic, such as the case when an estimated 80% evacuated to outside of the region before a hurricane while many of remaining people relocated to official and unofficial shelters and refuges within the region.

To obtain the underlying population denominator to calculate the flood fatality rate, I started with the spatial distribution of the population based on the 2000 Census, then adjusted the number for the change in population by 2005 along with the percent of the population that evacuated and the percent of the population that registered in the official shelters. Using GIS software, the calculations where completed at the Census blockgroup level, and the resulting layer I termed the “at risk” population. Next, I identified just the blockgroups that experienced flooding, and called this layer the “flood exposed population.” Finally, I counted the total number of flood fatalities for each blockgroup, and then divided this by the flood exposed population to get what I called the “flood fatality rate” layer.

The flood fatality rate is shown in the figure below. It can be seen that after accounting for the underlying population at risk, that the Lower Ninth Ward still shows up as having the highest fatality rate. Indeed, the fatality rate here was four times the average for New Orleans. While the average flood fatality rate for New Orleans was 0.9% (588 flood deaths/61,563 flood exposed person), the flood fatality rate for the Lower Ninth Ward was 4% (80 flood deaths/1,983 flood exposed persons.)


The Flood Fatality Rate for New Orleans and St. Bernard Parish.


The above calculation assumes an uniform evacuation and sheltering rate for all of New Orleans. This assumption is necessary given that there is very little reliable data on inner-parish variability in the evacuation rate. What data is available however is consistent with my estimate of the flood exposed population. On a regional level, my estimate of the flood exposed population came in at 66,000, which agrees well with the estimated 65,000 people rescued. The second figure is based on a thorough review the after-action reports and similar documentation. For the Lower Ninth Ward, my calculations indicated 1,983 persons remained in the Lower Ninth Ward, which is very close to the 2,000 rescues there reported by the Louisiana Wildlife and Fisheries Department. So, the data simply does not support the notion that the evacuation was less effective for the Lower Ninth Ward.


GIS based estimated of the flood exposed population for Orleans and St. Bernard Parishes.


Number of people rescues in the aftermath of Hurricane Katrina, based on review of after-action and similar reports.

After calculating the flood fatality rate layer, I then sought to explain the observed patterns through statistical modelling that included the flood hazard characteristics and the population vulnerability attributes. In terms of flood hazard characteristics, I was able to use a highly precise and accurate flood depth grid (based off of LIDAR, satellite imagery, and high water marks) along with the results of the SOBEK hydrodynamic model that provided depth, velocity, depth times velocity, rate-of-rise, and arrival time. For the population vulnerability attributes, I used 2000 Census datasets.

In my statistical analysis, I found that the hydrodynamic variable mattered much more than the social-economic variables. Water depth, flow velocity matter most, and specifically the product of depth and velocity was the most significant variable explaining the patterns of the flood fatality rate. When I examined the population attributes, I found that the percent of the population that was African-American was statistically significant, but the value of coefficient indicated that it did not have a substantive impact. Increasing the percent African-American from 45% to 95% while holding all the variable constant increases the flood fatality rate by a mere 0.2%. Other social-economic variable, including car ownership, were either not statistically significant or had no meaningful impact. These results indicate that none of the factors that we might think are associated with lower evacuation and sheltering rates in the Lower Ninth Ward have any bearing in explaining the high number of flood deaths there.



Map of depth times velocity, based on the SOBEK model.

So why did the flood waters have such lethally high flow velocities there? The answer has nothing to with the characteristics of the people who lived in the Lower Ninth Ward. The answer has to do with what I call the Lower Ninth Ward’s unfortunate location at the “last exit of the MRGO storm surge highway.” The MRGO (short for the Mississippi River Gulf Outline) is a man-made navigational canal that was dug through the marsh in Orleans and St. Bernard parishes east of the Industrial Canal, another man-made navigation canal the connects the Mississippi River with Lake Pontchartrain and separates the Lower Ninth Ward from central New Orleans. During Hurricane Katrina, this configuration of man-made canals served as a storm surge conveyance channel that both conveyed the surge to the heart of New Orleans and amplified its flow velocity. This is the storm surge that bulldozed the concrete and steel floodwalls protecting the Lower Ninth Ward and then bulldozed all but one house over a 20 block area.

Most floodwaters that flow through a levee breach are pulled through the breach by gravity, and they show modest flow velocities as a result. In contrast, the flood waters that flowed into the Lower Ninth Ward were not just pulled by gravity, these waters were also pushed through the breach because of the MRGO funnel effect. The figures below show results obtained from the ADCIRC storm surge simulation. The top figure shows that the surge flow velocity was 8 ft/s in the canal system, nearly three times the value in the open water of Lake Borgne. The second figure shows velocity vectors. As you can see, the arrows point straight toward the Lower Ninth Ward. While these results are based on the assumption that the levee did not breach, they show that once the levees did breach fast moving surge waters were pushed into the neighborhood because of the storm surge funnel effect of the MRGO.


Storm Surge Velocity Values from the ADCIRC Model (assumes no levee breaches.)



Storm Surge Velocity Vectors from the ADCIRC Model (assumes no levee breaches.)

To collaborate this line of reasoning, I will move away from fatalities and talk about building damage, specifically the residential building damage assessment dataset for New Orleans. This assessment was based on a visual inspection of buildings to determine the percent of the building that was damaged. I was able to geocode 65,000 of the residences (about 60% of the total) to create a point dataset for use in GIS mapping and analysis. The first map shows each building as a color coded point based on percent damage. The concentration of red dots in the Lower Ninth Ward is obvious. The second map shows an interpolation of this dataset. An interpolation is similar to the point density analysis described above, except that the interpolated values represent both the density of points and the magnitude of the damage for each point. It shows that the apparent concentration of damage in the Lower Ninth Ward is indeed a statistically significant effect.

Now, houses do not evacuate, so the variations in the residential building damage cannot be explained in terms of variability in the evacuation effectiveness. Indeed, in looking at this data in relation to the flood hazard characteristics, my colleagues Aimilia Pistrika and Bas Jonkman found that it was the lethal and destructive combination of depth and velocity that explains the cluster of structural damage in the Lower Ninth Ward, just like my research found that these variable explain the fatality rate there that is four times the average for New Orleans.

Residential Damage Points

Map of Residential Structure Damage for New Orleans.

Residential Damage Raster

Map of Interpolated Residential Structure Damage for New Orleans.

To conclude, the patterns of the recovery locations for the deceased victims of Hurricane Katrina show that the Lower Ninth Ward experienced the highest concentration of deaths due to the disaster. There is no evidence that this pattern relates to the notion that the evacuation was less effective there. Indeed, there is no evidence to even support the notion that the evacuation of the Lower Ninth Ward was less effective than in the other parts of New Orleans. When accounting for evacuation and sheltering, the flood fatality rate for the Lower Ninth Ward is four times the average rate for New Orleans. When comparing the flood fatality rate to the flood hazard characteristics and the population vulnerability attributes, the depth and depth times velocity were the most significant variables. These two variables also explain much of the observed patterns in building damage.

Corps of EngineersDisaster GeographyDisaster MappingDisaster ResponseFloodGISHotshotshurricaneHurricane KatrinaMan-made DisasterMapsNew Orleansstorm surge     , , , , , , , ,

Making Sense of Hurricane Katrina’s Death Toll

Posted on August 28, 2015 By


How many people died because of the Hurricane Katrina?

I’ve gotten that question a lot over the last few days, with reporters being specifically interested in Louisiana and New Orleans. It is a question that I spent 7 years focused on, which culminated in my dissertation in 2011 which was published as a scientific monograph in 2015. I can tell you that it is a difficult question the answer, and that the final number is both dependent on how you ask the question and subject to some uncertainty.

First, the easy part:
–  Mississippi: 238
–  Florida: 14
–  Alabama: 2
–  Georgia: 2
–  Ohio: 2
–  Kentucky: 1

These are the number of deaths attributed directly to Hurricane Katrina’s impacts in those states. These numbers are largely undisputed and they total to 259 U.S. Hurricane Katrina related deaths outside Louisiana. While the storm caused minor impacts in the Bahamas and Cuba, I am not aware of any storm related deaths outside the U.S.

When examining Hurricane Katrina’s impacts in Louisiana, arriving at a consistent death toll becomes complicated and nuanced. First, consider that are a few different ways to count and classify disaster related deaths. The most common way is to classify deaths as either directly or indirectly related to the disaster. Usually, the direct deaths are presented as the disaster’s official toll, with the indirect deaths mentioned as an aside. This scheme has a number of shortcomings, most notably “indirectly” is ambiguous and open ended.

Another method is to look at the cause of death and then refer to the International Classification of Diseases coding system to see which ones fall under the category for “victims of a cataclysmic storm”. A third way would be to gather reports from the families of those who are believed to have died from the storm. A fourth way would be to use obituary listings. Finally, the approach which I adopted for my dissertation is to look at the types of circumstances of the recorded deceased victims.

Various deaths tolls have been reported for Hurricane Katrina’s impacts in Louisiana. The official figure for Louisiana comes from the State Medical Examiner’s Office, which was formed by an executive decision by the governor in the immediate aftermath of the storm. They were tasked with overseeing the recovery, examination, identification, and eventual release to the families for the victims that were recovered from areas where local capabilities were decimated by the flood, meaning Orleans and St. Bernard Parishes. When they closed on August 2, 2006, their final report stated that “there have been 1,464 victims of Hurricane Katrina from Louisiana.”


Screenshot of an archived version of the August 2, 2006 final report on Hurricane Katrina Deceased Victims from the Louisiana State Medical Examiners Office.  The original site has been scrubbed from the web.


However, this estimate reflects some uncertainties and bias that resulted from the operational environment of the Medical Examiner’s Office. For example, this count reflects two arbitrary dates: October 1, 2005 and August 2, 2006. The first date is the date that was chosen as the cutoff date for considering victims that die while displaced due to the storm. A person who died on September 30 because of disruptions in routine care of chronic conditions while in a shelter in Colorado would count, but not a person who died on October 2 of identical circumstances. The second date reflects the date the office closed down. Victims whose bodies were not found until after that date are not counted, even if they met all the other criteria. Finally, this count likely reflects a bias resulting from the Medical Examiner’s goal to ensuring that families of the disaster victims obtained burial related disaster assistance, and thus should be classified as related to Hurricane Katrina.

In an effort to better understand the toll of the disaster, a group of epidemiologists with Centers for Disease Control and Louisiana Department of Health and Hospital completed an independent review of the State Medical Examiner’s Office records. Brunkart, Namuland, and Ratard (2008) compared victim’s cause-of-death to criteria in the International Classification of Diseases. They concluded that 986 victims fit the criteria of “victims of a cataclysmic storm”, of which 971 occurred in Louisiana and 15 occurred outside the state. They also noted that due to limitations in the records, the true number is likely higher. Still given their utilization of internationally accepted standards, this would be the best number (along the above listed figures from other states) to use when comparing the toll of Hurricane Katrina to other disasters.

For my dissertation research, I created what I call the “Hurricane Katrina Victim Database.” This was my effort to compile as complete and accurate a record as possible. In doing so, I worked closely with the State Medical Examiner, and many of my primary sources came from them. I did not stop there though, and included other victims with reliable documentation. These include 20 victims from Jefferson Parish listed in The Times-Picayune, 6 victims described to me by the Plaquemines Parish emergency manager, and 40 victims found in Orleans Parish after the Medical Examiner ceased operations. In the end, my database listed 1572 victims of Hurricane Katrina’s impacts in Louisiana.

One thing about this disaster that I think we have taken for granted is the level of detailed data that it produced. In doing this research, I worked with high resolution satellite imagery, detailed elevation and flood depth datasets, the results state-of-the-art computer models including ADCIRC and SOBEK, and many other datasets.


Deceased victim recovery locations along with depth of flood waters for Greater New Orleans area.


These datasets gave me important hazard characteristics, such as wind speed and flood depth, at the locations where bodies were found. The SOBEK model even provided velocity of the flood waters and its rate-of-rise. My research team and I also completed the grim task of visiting over 400 locations where victims had been found after the disaster. During these field surveys, we measured water marks and first floor elevations. We also looked for signs of structural damage, indications of attempted escape and rescue, and evidence of disability, such as handicap license plates and decals indicating things like oxygen tanks.


With evacuees scattered across the country, Hurricane Katrina related deaths among Louisiana residents were also scattered across the country.

Using all this data and trying to make sense of these trends, I borrowed a concept from a paper written by two of my colleagues. Jonkman and Kelman in 2005 published a paper called “An Analysis of the Causes and Circumstances of Flood Disaster Deaths.” I did not have access to the medical cause of death for each victim, but I did have enough information to draw inferences regarding the causes of death.

Specifically, of the 1572 victims in my database, I found that nearly all of them could be put into one of three categories: i) direct flood deaths, ii) emergency circumstances deaths, and iii) evacuation/displacement deaths. A fourth category included up to 16 possible wind related deaths, and then a separate study described below covers long-term deaths.  One main strength of using this framework is that a major disaster response is organized around the circumstances of the victims more than the specific medical conditions of the victims.



Inference tree used to classified victims in terms of the circumstances of death


Within the direct flood deaths category, there are 557 known victims. When the victims recovered from unknown recovery locations and a portion of the missing are added, the most likely number of flood deaths is between 600 and 700. Among the known flood deaths, the mean age was 69, 52% were black, and 54% were male.

In the emergency circumstances death category, there are 284 known victims. Of these, 152 were recovered from hospitals, 19 from nursing homes, and 42 from a shelter, school, or temporary medical clinic. The mean age was 70, and they were 57% black and 53% female. This category also includes 10 victims whose listed age was zero and are assumed to be still-born babies from flooded and powerless hospitals.

The final category was evacuation/displacement deaths, and it includes 631 known victims. This total includes 364 victims that died outside Louisiana, 243 victims reported from Louisiana parish that received evacuees, and 24 reported by the Medical Examiner. With a mean age of 71, these victims were 61% female and 57% Caucasian.

By the way, if you add the 1572 victims in the database to the 259 victims in other states, you get something close to the most cited total of 1,833.


Screenshot (taken August 28, 2015) of Google search results for “Katrina Death Tool”  The 1,833 figures is based on a 2005 NOAA report.


What didn’t I include?

Like the other estimates, my database has limitations. Specifically, I did not second guess the judgement of Medical Examiner on whether or not individual victims should be included. I merely sought to complement their numbers with additional victims that would apply under their criteria. So their October 1 cutoff date applies to my total, even though I know that the disaster continued to kill after that date. Two sources shed some light on those numbers.

Professor John Mutter is a professor with the Earth Institute at Columbia University. Following the disaster, he compiled his own list of victims based on reports from the families. He even created a web based reporting system. While his list had been published on the internet for a while, it was not available as of the time of this writing. I was however able to find a July 2008 archived version of the site that lists 1294 total deceased along with 595 missing. Among his deceased, he lists 914 as residents of New Orleans. In my database, 853 victims were residents of New Orleans, and any additional ones listed by Mutter are likely attributable long term impacts.


Screedshot of July 2008 archive summarizing the list of victims compiled by Professor John Mutter.


Finally, Dr. Kevin Stephens and his co-authors took a different approach to obtain an estimate of long term deaths attributed to the disaster. Comparing obituaries listed in the Times-Picayune during the first six months of 2006 with the same period in 2004, they estimated 1,600 excess deaths attributable to the long term impacts of the storm. If you apply this value at a uniform rate over the 2 year initial recovery period, you get an estimate of 6,400 long terms deaths due to Hurricane Katrina’s impacts in Louisiana.

Yes, it is complicated, but let me try to summarize things by answering two key, but distinct questions.

First, what is number to use when comparing the death toll from Hurricane Katrina to other disasters? This would be 1,245, based on the 259 deaths outside of Louisiana and the 986 Louisiana victims that were classified as “Victims of a Cataclysmic Storm.”

Second, what is the best estimate of the true number of lives lost in Louisiana due to Hurricane Katrina and the catastrophic levee failures around Louisiana? This number would be around 8,000, based on the 1,572 victims documented in my database plus the estimated 6,400 long term deaths plus up to 130 people reported missing.

Disaster GeographyDisaster MappingFloodGISHurricane Katrina     , , , ,

DisasterMap.net’s Analysis of the National Levee Database and 2010 Census

Posted on August 14, 2015 By

US Levees and Bad Levees


Our nation depends on levees and floodwalls to protect our communities, our homes, and our vital economic assets. America has nearly 15,000 floodwalls and almost 22,000 levees, according to our interpretation of a database maintained by the Army Corps of Engineers. These structures protect over 85,000 sq. miles that include 1,800 named Census places with a total population of 65 million people. However, not all of these levees are in good shape, and an estimated 6.8 million people live in a named place that has one of the 392 levee and floodwalls that have been rated “unacceptable.”

This project combined data from a nationwide database on levees and floodwalls with population and housing data to explore the depths of this dependence. We’ve found that millions of Americans depend on these levees to protect their homes. However, not all of these levees are “good levees,” and millions of people and homes are left at risk due to our nation’s “bad levees.”

The National Levee Database documents the nation’s levees, the areas they protect, and their condition. This project combines this database with 2010 Census population and housing data to examine the people that the good levees protect and the people at risk due to the bad levees. The project consists of a web visualization for all levees and one for the bad levees. Each webpage consists of an interactive web map, interactive graphics, and basic summary statistics. This blog post summarizes our findings, while a technical note provides details on the data analysis. Finally, we also created this static map showing the levees throughout the United States.  Together, we hope these tools help citizens, journalists, and others to better understand America’s relationship with it’s levees from national, regional, and local perspectives.

Data and Analysis

The US Army Corps of Engineers maintains the National Levee Database (NLD) and an associated public access website. The website includes an interactive web map viewer and tools for custom reports. For this project, the levee centerlines, the floodwalls, and the protected areas layers were obtained from NLD Web Feature Service in January 2015 and then processed with the desktop QGIS program.

We also obtained the unacceptable levee list using the NLD’s report tool. From the report tool, we downloaded a spreadsheet that included the results of the last inspection. We then filtered the spreadsheet for those that were rated “unacceptable” after their last periodic inspection. We then mapped the approximate location of these bad levees. Our technical note describes limitations to the accuracy of the location recorded for the bad levees.

To examine the demographic context of these levees, population and housing data were obtained from the 2010 US Census. A downloadable geodatabase provides data on total population, total homes, and occupied homes at the county, place, and tract levels. A series of desktop GIS processing steps (described in the technical note) extracted the counties, places, and tracts that have a levee protected area or a bad levee within its bounds. From there, these datasets were used to derive basic statistics, described in the next two sections, summarizing the people and houses adjacent to levee protected areas and near the bad levees.

Of note, the different aggregation levels (county, place, and tract ) for the census data correspond to different geographic units of analysis. Unfortunately, none of the geographies provide the spatial detail needed to precisely estimate the number of people living in the levee protected areas. Still, each of the three spatial units have different strengths in assessing the relationship between levees and settlement patterns.

Tracts likely provide the closest measure of the population and homes within the levee protected areas, though these still likely overestimate the true number. The tracts are a well defined Census unit that provides complete coverage of the U.S. with units drawing based on “an optimum size of 4,000 people.” To minimize variation in the population size, Census tracts vary greatly in their geographic size. Dense, urban tracts are small and tightly spaced, while rural tracts are large and spread out. Because most of the population residing in leveed areas are also in urban areas, the tracts provide the most accurate measure of the population and homes directly within the protected areas.

Places represent communities that are defined through social bounds and economic interactions. Unlike counties and tracts, this unit does not provide continuous nationwide coverage, though the “unnamed” areas contain a small percentage of the total population. Large places, such as Sacramento and Memphis, can include many tracts, while small places such as Willow Brook, KS can cover only a small portion of a large rural tract. Finally, counties are well defined economic units with specific direct and indirect benefits/impacts tied to the levee protected areas, such as employment rates and property tax revenue.

While none of the Census geographies correspond directly with the outlines of the levee areas, it is important to keep in mind the impacts of levee extend beyond just the people and houses located within the protected areas. Levees and floodwalls also provide indirect benefits to a community, particularly for areas where waterborne commerce is a major part of the economy.

Figure 1 below illustrate the different Census geographies with respect to the NLD layers.

Figure 1: Maps depicting NLD layers over the the different Census geometries. Sacramento is a large named place that is mostly inside a levee protected area, and most of its Census tracts are completely within levee protected area. Memphis is another large Census place but only a small portion is protected. Only a few of it’s tracts are within protected areas. Hutchinson City, KA is a small Census place that is partially levee protected. Unlike the dense urban areas, most of it’s tracts are only partially protected.

Results: All Levees

This section describes the basic summary statistics for the levees, floodwalls, and leveed areas and then discusses our results from overlaying these NLD layers with the three Census layers.

According to the NLD, there are over 21,000 levee reaches and 14,000 floodwall reaches in America. The levees total over 13,000 miles, while the floodwalls span only 80 miles. Combined, they protect an estimated 85,000 sq. miles. The largest levee is 233 miles, while the largest floodwall is 7 miles. The largest protected area is 10,500 sq. miles. See Table 1.

Table 1: Summary of levees, floodwalls, and leveed areas.

Levees (miles)

Floodwalls (miles)

Leveed Area (sq mi)





Maximum value








Mean value




Out of 74,000 total Census tracts, there are 5,359 Census tracts that have a levee or floodwall, and they have a total population of 22 million along with 9 million total housing units of which 8 million are occupied.Census named places comprise any named place (incorporated or not) registered with the US Census bureau. These can be a large city or a simple intersection with a few dozen nearby houses. Out of a total of 30,000 named places, there are 1,820 named Census places that have a levee. The total population of these places is 65 million. There are 27 million total housing units, of which 24 million are occupied.Finally, out of 3,200 counties in the US, 761 counties have a levee or floodwall within their bounds. They have a total population of 149 million, 62 million total housing units, and 55 million occupied housing units.

Table 2: Summary Statistics for Counties, Places, and Tracts



Total Population

Total Houses

Occupied Houses

















Table 3: Top 20 highest population places with a levee protected area.


Levee System


Total Houses

Occupied Houses

New York city

Oakwood Creek West Bank




Los Angeles city

Ballona Creek 1




Houston city

Lynchburg Pump Station




Phoenix city

Glen Harbor LB Downstream




San Diego city

Tijuana River 3




Dallas city

Kaufman LID 6 East Fork Trinity RB




San Jose city

Guadalupe River – LB




Indianapolis city

Indianapolis Levee System




Columbus city

West Columbus, OH, LPP




Fort Worth city

Waterworks Levee Clear Fork RB




El Paso city

Central El Paso Fort Bliss Diversion, Levee




Memphis city

Memphis – Wolf River Backwater Levee System




Washington city






Nashville, TN – Metro Center





Louisville Metro Levee System




Portland city

Multnomah – East




Oklahoma City city

North Canadian Waste Water Treatment Levee




Albuquerque city

Alb. Middle Rio Grande, West Levee




Tucson city

Tucson Diversion Channel 4




Sacramento city

American River FCD – Dry Cr, NEMDC, Arcade Cr





Results: Unacceptable Levees

There are 392 levee reaches that were rated “unacceptable” during their last inspection. The total length of the levees is over 3,000 miles, and they protect over 13 million acres. Another 1,033 levee reaches that protect 15 million acres were rated “minimally acceptable.” Only 116 (7.5%) of the levees that had been inspected were rated “acceptable.” Of note, nearly 40% of the levee reaches did not have an inspection result listed, so the number of people and houses at risk due to bad levees is almost certainly much higher.

Table 4: Summary of the Last Inspection Rating based on the NLD system report downloaded on January 9, 2015.Last Routine Inspection Rating

Last Routine Inspection Rating


Total Length (Miles)

Total Leveed Area (Acres)













not listed








In total, there are over 5,000 Census tracts with bad levees with nearly 22 million people living inside them. They contain 9 million total houses and 8 million occupied houses.There are 774 counties that haves bad levees with a total population of nearly 40 million, 16 million total houses, and nearly 15 million occupied houses.Among named Census places, there are 127 that have bad levees. They have a population of 6.8 million, nearly 3 million total houses, and 2.7 million occupied houses.

Table 5: Bad levee summary statistics for state, county, place, tract



Total Population

Total Houses

Occupied Houses

















Table 6: Top ten highest population Places with Bad Levee


Levee System


Total Houses

Occupied Houses

Fort Worth city

White Settlement Levee West Fork RB




Memphis city

Ensley Levee System




Washington city





Cleveland city

Euclid Creek, Cleveland, Ohio – Local Flood Protection




Bakersfield city

Kern River left bank – Bakersfield




Stockton city

Littlejohn Creek left bank – Unit 1




Toledo city

Point Place, Maumee Bay/Ottawa River




Irving city

Irving Flood Control District Section-1 East Levee




Arlington CDP





Shreveport city

Red River – West Agurs




Augusta/Richmond County

Augusta Levee




Providence city

Fox Point HSPP – Providence, RI




Sioux Falls city

Sioux Falls – Diversion Channel LB – South




Rockford city





Alexandria city





Ponce zona urbana

Portugues West




New Haven city

West Riv RB – New Haven, CT




Hartford city

N&S Br Park Riv, Park Riv Conduit Sys-Hartford, CT




Waterbury city

Naugatuck Riv LB – Waterbury & Watertown, CT




Palm Bay city

Upper St. Johns River Basin, North






The relationship between levees and settlement patterns is complex, but undeniable. This exploratory research took at a first stab at exploring this relationship using recent data from the the USACE and the US Census. While preliminary, these results do show that levees and floodwalls are important to American communities.Some preliminary conclusions drawn from this exploratory analysis include:

  • Over 1,800 named Census places with tens of millions people and houses have a leveed area within its bounds.
  • Nearly 800 counties throughout America receive tax revenue and job opportunities from their leveed areas.
  • Nearly 7 million people scattered across 129 Census places are at risk because of a bad levee.
  • Some 176 counties with 39 million people must worry about how these bad levees could impacts their revenue and employment situation.

Until verified, these results should be taken with a grain of salt. Further study and analysis using the rich data provided by the Corps with the National Levee Database should examine this relationship in greater detail.We want these tools to be resources for anyone, whether they are researchers, work for government, and citizens concerned about the levees around them. The statistics here just touch the surface of what’s available.Where your interests are national, regional, and local our two websites give you the ability to interact with the data and to explore your own interests. If nothing else, type in your zip code in the address search box (upper right corner) to see what levees and floodwalls or what bad levees and floodwalls are near you.

Corps of EngineersDisaster GeographyDisaster MappingDisaster PlanningDisaster PreparednessDisasterMap.netFloodFlood FightingFlood Hazard DeterminationsGISHurricanesInfrastructureInteractiveLevees.orgMitigationstorm surgeUncategorized     , , , , , ,