Blue Zones: Identifying Adaptation Opportunities Using Past, Present, and Future Flooding in New York City

ABSTRACT

Climate change poses escalating risks to urban populations and infrastructure, making adaptation strategies urgent. We overlaid the pre‐urban, natural hydrology of New York City's five boroughs with places that flood today and predictions of future flooding to identify coincident localities (“Blue Zones”) where adaptation is needed. We identified 538 Blue Zones, which collectively cover 21% of the city's land area, affecting approximately 1.2 million people and 11% of city buildings. Over two‐thirds of the flood‐prone area is estimated to be threatened by coastal flooding; 36% from combined coastal and pluvial flooding; and 5% from pluvial flooding only. Analysis of land tenure revealed that two‐thirds of Blue Zone area is managed by government entities. Urban historical ecology provides important insights not only about the past but the future of cities.

Understanding the historical ecology prior to the construction of the city can help reframe the way we see the current urban landscape, promote ideas about how we adapt to current realities, and prepare for future ones. We overlaid the pre‐urban, natural hydrology of New York City's five boroughs with places that flood today and predictions of future flooding, to identify coincident localities (“Blue Zones”) where adaptation is needed.

1. Introduction

Cities face threats from climate change and need to adapt to mitigate and minimize losses of life and property [1, 2]. Sea level rise and extreme weather events driven by climate change heighten the risks of flooding, coastal erosion, groundwater salinization, and other hazards in low‐lying coastal areas [3, 4]. Extreme rainfall provides additional challenges, especially since many cities have high proportions of impervious cover and many former waterways in topographic local minima have been filled by development [4, 5].

Changing urban landscapes, even when the need is clear and the priority high, is difficult and time‐consuming. There are strong historical legacies influencing the distributions of the building stock, transportation networks, and stormwater and sewage infrastructure, related to historic and current patterns of investment, jurisdictional authority, and land tenure. None of these are easy to change, but all influence how precipitation interacts with the city and where flooding will occur. Decisions taken by previous generations may open or close opportunities to adapt today and into the future [6]. Moreover, cities are complicated social entities with complex power dynamics. Change can be frustratingly slow whereas weather induced disasters, once it begins to rain, can be terrifyingly fast [7, 8].

Water, in contrast, is straightforward: it flows downhill. To adapt the urban form to make cities more resilient to climate change, we need to be similarly clear and compelling. One way to construct such arguments is to appeal to the past [9, 10]. Understanding the historical ecology—particularly the geographic distribution of streams and wetlands prior to the construction of the city—can help reframe the way we see the current urban landscape, promote ideas about how we adapt to current realities, and prepare for future contingencies.

In New York, climate change is predicted to bring more intense storms, greater amounts of precipitation, and higher sea levels [11, 12]. Models of future flooding in New York City with climate change [13] reproduced in striking fidelity the historic distributions of streams and wetlands suggested by studies of environmental history [14, 15]. Anecdotal accounts about where flooding is occurring today compared to the patterns of formerly aquatic ecosystems showed a surprising level of correlation between past and present [16]. In 2012, Hurricane Sandy inundated mainly parts of the city that were formerly beaches and tidal marshes. In 2021, Hurricane Ida revealed flood zones in the same places as ancient ponds, wetlands, and streams [17, 18, 19]. We hypothesized that these intense precipitation events may be causing streams and wetlands to reappear in similar places to where they historically occurred because, despite the vast changes over the last 400 years, as the writer Toni Morrison said, “water seems to have a memory” [20]. In plain terms, this translates into low places often remain low despite urbanization, and water flows downhill.

To test this hypothesis systematically, we conducted a comparative analysis of where New York City once flooded, where it floods now, and where it is predicted to flood in the future, using the available data. A “Blue Zone” in this context is defined as a place that was wet, is wet, and will be wet, and therefore a place where flood‐adaptation efforts are necessary.

2. Methods

2.1. Data Sources

2.1.1. Flood Risk

2.1.1.1. Past Flooding

Drawing on materials developed through our Welikia Project, we assembled information on historically flood‐prone ecosystems from historical maps, first‐hand accounts, and local histories of New York City's hydrology [21, 22]. We focused on three categories of ecosystems: Marine ecosystems including marine water below the estimated c. 1609 mean tide, which are now landfilled; intertidal ecosystems, including former high and low salt marshes, tidal creeks, beaches, and dunes; and freshwater ecosystems including former upland streams, freshwater wetlands, rivers, and ponds (Table 1). Selected historical maps showing streams, wetlands, and other aspects of the natural hydrology from 1767 to 1924 (Supporting Information Table 1) were georeferenced with a root‐mean‐square error of 50 m or better and relevant features (streams, wetlands, ponds, etc.) digitized. Features from the various sources were synthesized into consensus data layers, incorporating qualitative information derived from the literature. Linear features (streams and some small tidal creeks) were buffered by 10 m to generate polygonal features before analysis.

TABLE 1.

Flood indicators analyzed for New York City Blue Zones.

Time frame	Flooding indicators	Flooding type indicated	References
Past	Historical streams	Pluvial	[14, 21]
	Historical natural ponds
	Historical freshwater rivers
	Historical freshwater wetlands
	Historical tidal marshes	Coastal
	Historical tidal channels
	Historical beaches and dunes
	Historical marine
Present	311 calls	Pluvial and coastal	[23]
	DEP stormwater resiliency—Moderate storm/current sea level	Pluvial	[24]
	FEMA preliminary flood hazard—100‐year storm event (1% probability)	Coastal	[25, 26]
	Hurricane sandy inundation zone	Coastal	[27]
Future	DEP stormwater resiliency—Moderate storm/2050 sea level	Pluvial and coastal	[24]
	DEP stormwater resiliency—Extreme storm/2080 sea level	Pluvial and coastal	[24]
	FEMA preliminary flood hazard maps—500‐year storm event (0.2% probability)	Coastal	[25, 26]

2.1.1.2. Current Flooding

To assess areas that currently flood, we utilized four datasets: Public reports compiled by the City of New York's 311 service calls; the New York City Department of Environmental Protection's (DEP) New York City Stormwater Flood Map; and the US Federal Emergency Management Agency's (FEMA) 2015 Preliminary Flood Hazard data, and the 2012 Hurricane Sandy inundation zone (Table 1) [23, 24, 25, 26, 27].

The city's 311 service call system records observations from the public on a variety of nonemergency issues. Operators code calls by type and route them to the appropriate agencies for response. Each call is given a location by address and a time stamp. We pulled the entire log from January 2010 to January 2025 and extracted reports regarding “Highway Flooding,” “Street Flooding,” and “Catch Basin Clogged/Flooding.”

The DEP stormwater modeling approach deployed a rain‐on‐mesh model that routes surface flooding according to the topography in hydraulically independent areas defined by the sewer networks leading to wastewater treatment facilities. The modeling approach used Innovyze's InfoWorks ICM software for rainfall–runoff and sewer routing [28, 29]. Parks, cemeteries, and other areas that are not part of the DEP's stormwater drainage network were excluded from the analysis. All streets and buildings were considered impermeable. Coastal flooding from storm surge and monthly high tide flooding was not modeled. Rainfall amounts and mean sea levels for each scenario were based on data from the New York City Panel on Climate Change 2015 Report [13, 30, 31]. To represent flooding today, we used the “Moderate Flooding Scenario with Current Sea Levels,” which simulated floods caused by 2 in. of rain in an hour, overwhelming local drainage systems [13]. The current stormwater management system is designed to handle rainfall between 1.5 and 1.75 inches of rain per hour, depending on when the sewer was built [32].

In the New York City region, FEMA preliminary flood hazard data relates primarily to coastal flooding associated with high tides and storm surge [33]. New York City has disputed some of the detailed findings, which is why the data are considered “preliminary” [34]. To represent flooding today, we utilized the 100‐year storm event (1% annual probability), which identifies floodplains with model‐backed water surface elevations. Landowners are required to have flood insurance in such areas [26].

The sandy inundation zone shows areas in New York City that were affected by flooding during Hurricane Sandy which made landfall on October 29, 2012. These data show the extent of storm surge flooding during a spring tide. Hurricane Sandy caused $19 billion in damage and took 43 lives, at the time the second most costly natural disaster event in US history [35].

2.1.1.3. Future Flooding

For future flooding we used two DEP Stormwater Flood Map scenarios: “Moderate Flooding with 2050 Sea Level Rise” and “Extreme Flooding Scenario with 2080 Sea Level Rise.” The Extreme Flooding Scenario simulated floods caused by 3.5 in. of rain in a single hour [13, 24]. We also used the FEMA 2015 Preliminary Flood Hazard data for a 500‐year storm event (0.2% annual probability) [26].

2.1.2. Atomic Polygons

To analyze across the time periods of flooding, we used the “Atomic Polygon” layer generated by the New York City Department of City Planning as a common spatial framework [36]. Atomic polygons are bounded by contemporary city street centerlines to represent city blocks. We identified large areas without city‐managed streets, such as parks, cemeteries, and airports. We then divided these large nonstreet areas into smaller units by creating a grid. This grid's cell size was based on the mean city block size (11,559 m²) plus one standard deviation (47,551 m²). The process ensured that all large areas were represented by spatial units consistent with the rest of the urban street grid. Finally, any nonland areas within these polygons were removed.

2.1.3. Land Tenure

We collated information on land tenure from the city's tax lot geographic database, MapPLUTO, which describes private and public ownership patterns, supplemented by detailed data from the city's building footprint layer [37, 38], City Owned and Leased Properties (COLP) dataset [39], New York State Tax Parcels State Owned Parcels dataset [40], New York State Parks Property dataset [41], Federal Real Property Public dataset [42], and National Park Service Boundaries [43].

We constructed the land tenure dataset based on the MapPLUTO tax lots. City owned and leased properties were flagged with “ownership” = “C” (City) or “O” (Other—owned by either a public authority or the state or federal government) or “M” (Mixed city and private ownership). State properties were identified by overlaying the state parcels and parks with the tax lots. Federal properties were similarly identified based on the overlap of national park properties, or the points identified as FASTA in tax lots. Where a given tax lot was attributed to multiple government levels, we tracked the various combinations (e.g., City + State, City + Federal, State + Federal, and City + State + Federal). If no government jurisdiction applied to a tax lot, it was considered privately held. Areas outside of tax lots and within blocks were considered the “right of way.”

2.1.4. Population

We obtained summaries of persons per census block from the 2020 US Census Bureau counts for New York City recompiled and adjusted by the New York City Department of Planning [44, 45].

2.1.5. Building Stock

We obtained data on building footprints from New York City Department of Technology and Innovation [38].

2.2. Analytical Methods

2.2.1. Geographic Coordinate System

We projected all layers into the coordinate system used by New York City: State Plane New York Long Island. Areas were calculated to the nearest square meter. All geographic analyses were conducted using ArcGIS v.8 and the python module GeoPandas [46, 47].

2.2.2. Blue Zone Delineation

We performed a spatial union between the past, present, and future flooding layers and the atomic polygon layer to determine the area of overlap on a per block basis.

2.2.2.1. Sensitivity Analysis

We conducted a sensitivity analysis regarding the amount and proportion of overlap between flood layers and atomic polygons that should be used to represent a flood‐prone block (Supporting Information Table 2). Requiring more overlap resulted in fewer blocks considered at high flood risk, whereas decreasing the required overlap increased the number of blocks considered at risk. Although the decision is somewhat arbitrary, we concluded that any block where the overlap of the flooding layer and the block equaled at least 10% of the block's area should qualify as flood prone. For the 311‐call data, we counted the number of calls per polygon and examined different thresholds. We concluded five calls or more per block over the 10‐year span of call records to be indicative of repeated flooding.

2.2.2.2. Blue Zone Delineation

We analyzed different combinations of criteria to present patterns of past, present, and future flooding. A “Blue Zone” was defined as a block or set of contiguous blocks that flooded in the past based on the historical ecology, floods today, and is predicted to flood in the future.

For historic flooding, we considered any block that cumulatively had 10% or more of its area in the flood‐prone ecosystem types detailed above. For present and future flooding, we considered each layer separately. For example, a presently flooded block had more than 10% of its area covered by DEP's “Moderate flood with current sea level rise scenario” or 10% of its area covered by FEMA's PFIRM 1% probability or five or more 311 calls. We set flags in the database representing whether each block had past, present, or future flooding. Any block that satisfied all three criteria was considered part of a Blue Zone. By selecting combinations of flags, we could also examine other intersections: past and future, present and future, past and present, and so forth.

2.2.2.3. Watershed Delineation

Using 1‐m resolution topography collected in 2010 [48], we derived modern subwatersheds of New York City. We employed the ESRI ArcGIS Hydrology tools in the Spatial Analyst extension [46].

These tools model how water runs across the surface of a topographical layer including locating sinks, identifying flow accumulation and flow direction, and classify land in watersheds. We selected pour points along the modern coastline and between third‐ and fourth‐order streams derived using a 1000 cell threshold. Blue Zone atomic polygon blocks were grouped by watershed polygon. Blocks that crossed watershed boundaries were assigned where the greatest overlap occurred. Contiguous blocks were grouped together by watershed to create the final set of Blue Zones (Supporting Information Table 3).

2.2.3. Blue Zone Characterization

2.2.3.1. Geography and Land Tenure

We characterized each Blue Zone in terms of the number of blocks it contained and its total geographic area. The land tenure layer was overlaid on the Blue Zones to calculate the percentage of land ownership by type (Table 2 and Supporting Information Table 4).

TABLE 2.

Land tenure analysis of Blue Zones in New York City.

Tenure	Land area of the city (km2)	Percent land area of the city	Land area of the Blue Zone (km2)	Percent land area in Blue Zone
Private	375.67	48%	57.25	34%
Right of waya	195.47	25%	33.82	20%
New York City	129.34	17%	38.42	23%
City and other governmentb	36.81	5%	20.77	12%
Federal	27.00	3%	15.54	9%
New York State	13.97	2%	3.57	2%
State and Federal	3.76	0.5%	0.52	0.3%

^aRight of way includes streets, sidewalks, plazas, and other areas outside city taxable lots but falling within atomic polygons defined by the street center lines.

^bIncludes lots owned by various combinations of City and Federal, City and State, and City, State, and Federal agencies.

2.2.3.2. Flooding Type

We characterized each Blue Zone by type of flooding: pluvial, coastal, and combination. We recorded each of the flooding input layers in terms of its type (Table 1). We used as indicators of pluvial flooding layers of historic streams, ponds, and freshwater wetlands, and the various DEP Stormwater models; indicators of coastal flooding were the remaining historic ecosystems (beaches, dunes, tidal marshes, etc.) and the FEMA PFIRM layers (Table 1, Table 3, and Supporting Information Table 5).

TABLE 3.

Types of flood risk in Blue Zones by borough.

Borough	Type of flooding (% Blue Zone area susceptible by flooding type)
	Only coastal	Only pluvial	Pluvial and coastal
Bronx	66%	7%	27%
Brooklyn	48%	4%	48%
Manhattan	44%	2%	54%
Queens	60%	7%	27%
Staten Island	70%	3%	27%
New York City (all five boroughs)	59%	5%	36%

2.2.3.3. Population and Building Stock

We estimated population counts in Blue Zones and other geographies by intersecting the census block geographies [49] with to other layers, calculating the area of overlap, and allocating the people from the block proportionally by area, ignoring areas of “right of way.” We calculated the number of and total land area of building footprints.

3. Results

New York City is low, coastal, and wet, built on an archipelago in an estuary. Approximately 35% of the modern land area of New York were once aquatic or marine ecosystems when Henry Hudson sailed into New York Harbor in September 1609, inclusive of known streams, wetlands, tidal marshes, beaches, dunes, or marine waters. Contemporary measures of flooding collectively indicate 52% of the city now floods or is at risk of flooding at the block scale. Models of future flooding suggest a similar magnitude area (47% of the city land area) will be subject to flooding, though the spatial pattern changes as climate change intensifies precipitation, creating spatial patterns reminiscent of the historical ecology (Figures 1 and 2). Flooding from intense rainfall events is a historic, immediate, and future concern of the city.

FIGURE 1.

Block‐level flood risk in New York City in the (A) past; (B) present; (C) future; and (D) Blue Zones, which find the intersection of past, present, and future flood risk. See Section 2.

FIGURE 2.

A Venn diagram of the analytical approach, with the areas of overlap between layers representing past, present, and future flood risk in New York City. Percentages indicate the proportion of the land area represented by each set of layers and the overlaps between them. Blue Zones are the most conservative treatment.

How widespread is the concern? We identified 538 Blue Zones covering 21% of the city land area (Figure 2 and Table 4). Blue Zones are the spatial union of blocks that flooded in the past, flood today, and are predicted to flood in the future (Figure 3). Blue Zones range in size from 8569 m² to 4,539,876 m². We found that 59% of the area of Blue Zones was predominantly at risk from coastal flooding, caused by high tides and coastal storms; 5% from predominantly inland, pluvial flooding, such as intense rain events; and 36% from a combination of coastal and pluvial flooding types (Table 3 and Supporting Information Table 5).

TABLE 4.

Summary of Blue Zones by borough.

Borough	Blue Zones
	Total number of Blue Zones	Total area (km2; % of total land area)	Total number of people (% of total city population)	Total number of structures (% of total building footprints)
Bronx	101	4207 (2%)	94,549 (1%)	9053 (1%)
Brooklyna	122	9915 (5%)	321,495 (4%)	37,305 (3%)
Manhattan	69	3292 (2%)	283,503 (3%)	5629 (1%)
Queensa	141	16,266 (8%)	293,503 (3%)	51,218 (5%)
Staten Island	105	8311 (4%)	50,510 (1%)	15,043 (1%)
New York City	538	41,993 (21%)	1,048,881 (12%)	118,248 (11%)

^aThree Blue Zones cross from Brooklyn into Queens. These have been lumped into Queens for the purpose of this tabulation.

FIGURE 3.

Blue Zone case study on the border of the boroughs of Brooklyn and Queens, New York. (A) past flood risk, based on the distribution of freshwater, intertidal, and marine ecosystems, c. 1609; (B) current flood risk from multiple sources, c. 2021; (C) future flood risk from multiple sources, c. 2080; (D) Blue Zones; (E) modern watersheds derived from topography (different colors indicate watersheds); (F) assembly of Blue Zones by watershed.

Analysis of census data suggested that approximately 12% of the city's population of 8.8 million live in the Blue Zones, with the largest percentage of at‐risk people living in the boroughs of Brooklyn, Queens, and Manhattan (Table 4), where in each case more than 250,000 people may be impacted by flooding. We also analyzed the number of building footprints to find that 11% of the city's structures have been built in Blue Zones, with the greatest numbers in Queens and Brooklyn. Overlay of Blue Zones against listed New York City Housing Authority housing projects revealed that 31% (88 buildings) of housing projects are situated in areas vulnerable to flood (Supporting Information Table 6).

We found that Blue Zones are disproportionally managed by government agencies compared to private landholders (Table 2 and Supporting Information Table 4). We estimate that 34% of the land area of Blue Zones is managed by private individuals and entities (as opposed to 48% of the city as a whole); 20% of Blue Zones lie in the right of way (including streets, sidewalks, highways, and pedestrian plazas) compared to 25% of the city as a whole; and that city government manages entirely or in part 56% of the Blue Zone area as compared to 22% of the city as a whole. The Federal government manages 9% of Blue Zones and New York State approximately 2% within New York City.

Within city government, the Parks department manages the greatest proportion of city‐managed land in Blue Zones (52% of city‐managed lots), followed by the Department of Environmental Protection (6% of city‐managed lots; Table 5). A wide array of other agencies including the Department of Education, Police Department, and Fire Department also manage structures in flood‐prone Blue Zones. As a result, public housing, playgrounds, schools, police precincts, fire houses, and other vital city structures, are at risk of flooding.

TABLE 5.

Percent land area of single‐agency controlled, city‐owned lots in Blue Zones.

New York City Agency	Blue Zone land area managed by New York City (% managed)
New York City Department of Parks & Recreation (NYCDPR or Parks)	52%
New York City Department of Environmental Protection (NYCDEP)	6%
New York City Housing Authority (NYCHA)	6%
New York Police Department (NYPD)	3%
New York City Department of Education (NYCDOE)	3%
New York City Transit Authority (NYCTA)	2%
New York City Department of Sanitation (DSNY)	2%
New York City Department of Housing Preservation & Development (NYCHPD)	1%
New York City Department of Transportation (NYCDOT)	1%
New York City Department of Citywide Administrative Services (NYCDCAS)	1%
Metropolitan Transit Authority (MTA)	1%

4. Discussion

4.1. Research‐Based Conclusions

Most urban flood management strategies focus on where it is flooding now or where it has flooded in the recent past [50, 51]. Understanding future climate changes, while uncertain, are important to consider when predicting contemporary adaptation strategies [52]. Here, we develop an analysis that combines the present and the future patterns of flooding with the past, using our studies of the predevelopment natural hydrology as a guide to flood risk. Historical ecology provides important context for understanding modern ecological phenomena such as runoff.

Our results at the block‐by‐block scale in New York City indicate that the urban form has induced a greater area of flooding than was historically observed in the natural landscape. Extensive stormwater infrastructure has partially, but not completely, replaced the natural hydrology of the landscape. “Wet” (i.e., aquatic or marine) ecosystems once covered just over a third of the modern city's land area, but current and future flood risk covers nearly 50% of the land area. Flooding, as Hurricane Sandy in 2012 and Hurricane Ida in 2021 showed, can have significant personal and collective impacts on the city's population, economy, and nature. Flooding can come from multiple directions: from intense rainfall, from storm surge, or from a combination of the two.

4.2. Policy Implications

The following observations reflect our interpretation of the scientific results presented above and in the results section. We acknowledge that other researchers and policymakers may draw different conclusions based on the same evidence.

In some cases, it may be necessary to retreat from historically wet ecosystems and current topographic lows, especially in large watersheds where nature‐based solutions and traditional stormwater infrastructure are insufficient or too expensive to prevent loss of life and property. Some parts of the city where people live now may not be inhabitable in the future. In other areas, complementing storm drains and retention basins with nature‐based solutions such as bioswales, rain gardens, daylit streams, and green roofs may provide enough protection in the short to medium run. Approaches to flooding will likely require making changes at the landscape scale, including in nonflood zones. Areas outside of Blue Zones (comprising nearly four‐fifths, or 79% of the city) also have a role in flood resilience. Additional housing and infrastructure may be needed if the city's goal is for the population to stay the same or grow without increasing flood vulnerability. Transportation corridors such as roads or trains may also need to shift to drier areas or be adapted to become more flood resilient. Flooding is a city‐wide, landscape‐level phenomena and needs to be managed at that scale.

Flood risk in New York City, in our view, is inseparable from questions of social equity. Climate change threatens many people and places, but in responding we have an opportunity to not only redress flooding but also repair other urban issues such as the lack of affordable housing, the inefficiency of transportation, and past social harms regarding the placement of infrastructure. For example, we found nearly one‐third (32%) of New York City Housing Authority buildings were built in Blue Zone area. Because these buildings shelter low‐income New Yorkers, the issue of flooding is also one of environmental justice [53, 54].

Equity considerations also underscore the importance of planning at the right scale. Cities often manage problems by neighborhood or political entities such as community districts. However, this approach may be problematic when it comes to water (and other ecological flows) that do not respect neighborhood or political boundaries. Simply because one block is predicted to flood, it does not preclude water from flowing into neighboring blocks due to infrastructural elements such as curb cuts or natural topographical features like changes in slope. Protecting one tax lot or city block from pluvial rainfall events may change the risk profile for neighboring lots. For this reason, flood‐adaptation strategies cannot be implemented piecemeal; they must be designed and coordinated at the watershed scale, the natural unit of water movement and accumulation.

Who owns land within Blue Zones is critical to the adaptation measures chosen. We show here that government has an essential role to play on land it already manages, since these areas have a greater proportion of Blue Zones than private lands. It seems not coincidental to us that Blue Zones even today disproportionally remain under public management, presumably because such areas were historically less valuable for private land development. We hypothesize that the private lands on uplands (i.e., former forests and grasslands) were developed preferentially into neighborhoods, while low‐lying wet precincts were only converted when public needs became acute for schools, police precincts and fire houses, and public housing. Similarly, the major airports of New York City were built in flood zones, such as La Guardia International Airport in Bowery Bay and John F. Kennedy International Airport in the tidal marshlands lining Jamaica Bay, a function of the availability of large parcels of flat terrain when commercial aviation developed in the 1930s. As a result, these globally significant airhubs lie in Blue Zones.

Within the lands the city manages, parklands are particularly important, both because of the overlap with Blue Zones and because landscaped and natural areas (e.g., forests and wetlands) within parks have a particularly significant role in absorbing and slowing water. A recent report suggested that natural areas within parks absorb 17% runoff that would otherwise need to be conveyed and treated by built stormwater infrastructure. Healthy forested areas absorb nearly 10% more stormwater than degraded forested areas, according to the authors [55]. Managing natural areas, especially remaining, extant forests and wetlands, should be considered part of the city's flood‐adaptation strategy.

4.3. Dataset Caveats and Consequences

A few caveats on the datasets used here. Each input has limitations that require acknowledgment and consideration. The Welikia Project historical ecology layers represent a synthesis across many different sources (Supporting Information Table 1), primarily historical maps from the 18th to 20th century, supplemented by accounts, and ecological interpretation. Errors can creep in: misregistration of historical maps, omissions made intentionally or unintentionally by the cartographers, and misinterpretations. Generally, location accuracies in terms of root‐mean‐square efforts of less than 50 m were obtained, which corresponds generally to one block length.

The current‐day 311 calls represent approximately 15 years of observations (2010–2025), when residents report flooding events. Service calls may result from excessive amounts of rain or problems in the stormwater system, and different reporters have different thresholds for contacting the 311 system. Unresolved repeat problems may be ignored over time. Disparities in reporting behavior to 311 services likely reinforce underestimation of flooding hazards in under‐represented communities [56]. There are also some areas where 311 system calls are not recorded, for example, on Federal properties and the airports.

The DEP's stormwater resiliency maps are based on hydrological models that include sea level rise and moderate and extreme storm events. The models assume that rainfall is evenly distributed across the city, that all flood infrastructure functions properly at full capacity, and that buildings are completely impervious, all assumptions that can be questioned. These analyses did not include some important large parcels, including parklands, cemeteries, and other green spaces. Sensitivity analyses reported by the modeling team also suggest that adding more detail to the mapping of the stormwater system is needed to improve the results. Finally, the preliminary flood insurance risks maps from FEMA have been disputed by New York City because of concerns regarding some of the validation issues and the tidal effects.

Given these caveats, we adopted the most conservative approach possible: identifying the spatial union of where a given atomic polygon (i.e., block) flooded historically, evidence it floods now, predictions of where it may flood in the future. We used multiple indicators of historical flooding, current flooding, and future flood risk, with a 10% area threshold, derived from our reading of the sensitivity analysis (Supporting Information Table 2). Because the different inputs have different kinds of error, this consensus approach finds the places where flood resilience measures are most warranted.

Our analysis does not suggest which kinds of flood resilience measures are most appropriate in which settings. We numbered the 538 Blue Zones to encourage the efforts of architects, landscape architects, and other organizations and actors to propose detailed, Blue Zone‐specific interventions (Supporting Information Table 3). The Blue Zone locations, and their underlying data sources, can be viewed on our web mapping tool at https://urbanconservation.nybg.org/blue‐zones. Undoubtedly, multiple approaches are needed. These include mobility, defensive structures, flood hardening, ecosystem restoration, stream “daylighting,” or some combination of approaches [57]. Giving water a place to go in the 21% of the area represented by Blue Zones will help protect the 47% of the city where flooding is expected in the future because of watershed‐level effects.

5. Conclusions

The city's historical ecology provides a remarkably prescient guide to present‐day flooding patterns, despite the numerous changes that have occurred to the New York City landscape over the last 400 years. Historical ecology offers not just a record of what once was, but a framework for anticipating what might come to be. It helps contextualize the scale of the issue, the historical process inducing flooding today, and how we might design for more resilience to intense rainfall in the future.

Our results document the extent and location of consistently flood‐prone areas across time in the landscape that is now New York City. These findings suggest that building resilience will benefit from large‐scale, landscape‐level planning that transcends jurisdictional and ownership boundaries. Although much of the land within Blue Zones is publicly managed, no single agency can address the city's flooding challenge alone. Coordinated action across agencies, levels of government, and private landholders will be essential. These efforts should center on vulnerable populations who face the greatest risks of flooding as shown by this analysis of NYCHA properties in Blue Zones. This climate resilience effort also provides an opportunity to right many housing and environmental injustices that have been perpetuated since the city's inception.

Ultimately, water does not recognize political or parcel boundaries and neither should our hydrological planning. Viewing the city as a system of interconnected watersheds provides a basis for cross‐agency collaboration and interventions that restore ecological function while protecting communities. By grounding adaptation in both the city's hydrological past, its realities, and modeled futures, New York can serve as a model for how other urban landscapes might adapt to a wetter, more uncertain future.

Author Contributions

Eric W. Sanderson and Lucinda Royte conceived of analysis and methods, Lucinda Royte conducted the analyses, both contributed equally to the text.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting Information Table S1: nyas70248‐sup‐0001‐TableS1.xlsx

Supporting Information Table S2: nyas70248‐sup‐0002‐TableS2.xlsx

Supporting Information Table S3: nyas70248‐sup‐0003‐TableS3.xlsx

Supporting Information Table S4: nyas70248‐sup‐0004‐TableS4.xlsx

Supporting Information Table S5: nyas70248‐sup‐0005‐TableS5.xlsx

Supporting Information Table S6: nyas70248‐sup‐0006‐TableS6.xlsx

Data Availability Statement

A geographic dataset of atomic polygons with attribute information relating to Blue Zone identification and code used to generate Blue Zones are available at https://github.com/NYBG‐Conservation/Blue‐Zone‐Analysis. Blue Zone data and maps are also available to explore at https://urbanconservation.nybg.org/blue‐zones. Historical ecology datasets are available upon request to the authors upon completion of a data sharing agreement with the New York Botanical Garden. All analyses are possible using publicly available geographic information systems.