Economic Evaluation of Sea-Level Rise Adaptation Strongly Influenced By

Downloaded by guest on October 2, 2021 a Hummel A. feedbacks Michelle hydrodynamic by influenced adaptation strongly rise sea-level of evaluation Economic PNAS agri- from the runoff nutrient in upstream to zone” link its “dead and Mexico the of Gulf include examples High-profile project systems. to oversight approaches local fragmented (7). on implementation or and rely permitting management that hindered col- coastal structures often so, of governance are Even adaptation existing (11). shoreline by welfare to social approaches overall lective generally reduced (10), in those decision-making collective from resulting other communities from different impact arise outcomes to to would yield tends that damage action and individual (externalities) resulting settings, parties these and In patterns 9). erosion, (8, influence flooding, modification of shoreline human– and coupled of between are extent interactions hydrodynamics temporal hydrodynamic areas and spatial the coastal where systems, match Populated natural not (5–7). does threat that communities the scale coordination individual a cross-jurisdictional at by limited and with made entities often private adaptation are for or respond- strategies flooding in about coastal decisions challenge that critical to is be A threat could (2–4). this people to 2100 of ing are by millions livelihoods SLR of and to hundreds Lives globally, exposed (1). well; threat as this not risk does to at society adapt if to 2100 action by globally take damages in dollars of trillions S in resources rise sea-level adaptation spending wisely and reduc- bays. for coastal risk essential costs is shared demon- perspective uncounted planning ing and previously regional the actions a the that to adaptation reveal strate assessment uncoordinated we economic with threat, the associated the help of scale of can the scale storage, matching coast- water the By of for stretches line. other along space damages grad- and and flooding with alleviate those baylands as sloping strategic such segments, that can ually shoreline demonstrate cases certain also some of We in flooding m and protection. damages million local event from the 36 exceed flood prevented that as damages single flood regional flood- much a cause for even increase as million can by of $723 km) protection areas by 75 that other to find in scenar- (5 We ing rise segments California. sea-level Bay, shoreline and Francisco individual protection San shoreline in of ios expected the range damages assess and a flooding to regional from Here and models local understood. both economic of poorly and extent are hydrodynamic sea- however, combine from dynamic, we risk economic this the at of of distribution are spatial impact globally and magnitude people The rise. million other estuaries, level and 500 along bays nearly coastal damages in where structures associated shoreline—particularly these the and of benefits, parts flooding reduction $300 risk exacerbate alone, flood However,can 2100. local States by the forecast United are despite the costs pro- armoring critical in shoreline as in rise; billion seawalls for sea-level (received and 2021 against 30, levees May tection on approved and rely CA, Oakland, communities Security, Coastal and Environment, Development, in Studies 2020) for 17, Institute December Pacific review Gleick, H. Peter by Edited 98195 WA Seattle, Washington, of University Sciences, Forest and 94305; CA eateto ii niern,Uiest fTxsa rigo,Alntn X76019; TX Arlington, Arlington, at Texas of University Engineering, Civil of Department pta xenlte r omni ope human–natural coupled in common are externalities Spatial eeefloigi osa ein n sepce ocause to expected is and regions and coastal frequent in more flooding produce to severe threatens (SLR) rise ea-level 01Vl 1 o 9e2025961118 29 No. 118 Vol. 2021 c colfrMrn cec n ehooy nvriyo ascuet atot,Drmuh A077 and 02747; MA Dartmouth, Dartmouth, Massachusetts of University Technology, and Science Marine for School | adaptation a,1 | cnmcdamages economic oetGriffin Robert , | externalities b,c ai Arkema Katie , 3 n damages and | flooding b,d n neD Guerry D. Anne and , doi:10.1073/pnas.2025961118/-/DCSupplemental hsatcecnan uprigifrainoln at online information supporting contains article This 1 under distributed BY).y is (CC article access open This Submission.y Direct PNAS a is article This interest.y competing no declare authors The ulse uy1,2021. 12, July Published A.D.G. and K.A., R.G., M.A.H., and data; paper. R.G. analyzed the and wrote R.G. M.A.H. research; and designed M.A.H. A.D.G. research; and performed K.A., R.G., M.A.H., contributions: Author the of 60% nearly represent to forecast is It forward. moving protection (20). Oregon own coastal their in average build on to shore- 8% ineligible by adjacent structures are for that that values properties found property line study recent reduced A interactions (19). these areas to adjacent structures in protection with erosion interact induce also else- can projects Waves nourishment (18). from where under- input of sediment to hopes from lost the in benefiting subsequently or either communities is neighboring that frequently, in may beaches sediment less nourished communities for beaches paying individual their avoid result, nourish to a to As incentivized 17). neighbor- be to (16, sediment beaches of loss ing and nourishment mobilization beach coasts, of through open efficacy projects loca- the On affect at (12–15). can potential currents downstream alongshore flood and and upstream long both levels tions water has one influence it at building can systems, levee location and river modifications channel In that known management. shore- been of Spatial and context its litigation. the protection in of to varied line decade and led common a that also than are MA, externalities more Cape Nantucket, after the near and demise from farm 1990, eventual owners in wind property Act offshore adjacent Air Wind on Clean the impacts of visual revisions the the to in led plants that power the Midwest from in originating rain States acid United widespread northeastern Mississippi, the down carried culture owo orsodnemyb drse.Eal [email protected] Email: addressed. be may correspondence whom To ol rvd potnte ordc hrdrs ncoastal in actions risk shoreline shared local reduce globally. of regions to opportunities impacts provide regional could the for that efforts account areas. planning coordinated low-lying highlight into dam- in findings also the storage flood Integrating floodwater We regional strategic CA. alleviate through shore- Bay, to age individual opportunities Francisco flood of quantify San per protection and in million the segments from $723 line result to that unmeasured (up hydrodynamic event) previously damages Using quantify economic bay. shore- we regional or models, other estuary economic along same and inundation the within increase flood-reductionlines can local they provide flood- mitigate strategies benefits, protec- to these shoreline seawalls Although on and rely levees ing. as will such cities strategies coastal tion rise, levels sea As Significance hrln roigwl lyakyrl nrsodn oSLR to responding in role key a play will armoring Shoreline b h aua aia rjc,Safr nvriy Stanford, University, Stanford Project, Capital Natural The y b,d https://doi.org/10.1073/pnas.2025961118 raieCmosAtiuinLcne4.0 License Attribution Commons Creative . y d colo Environmental of School https://www.pnas.org/lookup/suppl/ | f10 of 1

ENVIRONMENTAL SCIENCES roughly $500 billion in US adaptation costs by 2100 (21). Despite can have the opposite effect, providing dissipation that attenu- evidence for a wide range of spillover effects resulting from ates water levels and produces regional flood reduction benefits shoreline modification and the billions in planned expenditures (26–30). Bays and estuaries represent 21% of overall shoreline on these modifications, there is limited understanding about length and 54% of global population at risk from SLR and how they influence shared economic risk across the coastal zone flooding—nearly half a billion people (see Materials and Meth- (5). Erosion and beach nourishment are better understood than ods). These densely populated areas with complex jurisdictional coastal flooding, where the only economic assessment of exter- boundaries are increasingly facing difficult and expensive deci- nalities is on the performance of critical infrastructure systems sions that demand a better understanding of shared risk along (22, 23). the coastline. To address these gaps and account for the physical and economic impacts of flooding on communities, here we couple Approach dynamic simulations of coastal inundation with models of build- San Francisco Bay is the largest coastal embayment in Califor- ing damage to examine flood damage externalities expected nia and is composed of four distinct subembayments: Suisun under a range of shoreline modification and SLR scenarios. Bay, San Pablo Bay, Central Bay, and South Bay (Fig. 1). Build- We focus on the densely populated San Francisco Bay Area, ings adjacent to the bay that are exposed to the effects of SLR as bay and estuarine systems in particular are characteristic over the next 150 y represent more than $180 billion in replace- of coastal locations that feature regional coastal hydrodynamic ment value and are home to a population of over 1.4 million interactions. In these settings, engineered protection can lead people (see Materials and Methods). Together, the nine counties to amplification of water levels, cause additional flooding in that surround San Francisco Bay represent the majority of pop- other locations, and in some cases adversely affect coastal veg- ulation and building exposure to coastal flooding in California etation and the shoreline protection benefits it provides (24, 25). (31). Shoreline modification is widespread throughout the bay, Conversely, shoreline modification to strategically store water with 6% of the shoreline behind levees designed specifically for

6 7 9

Sacramento- San Joaquin Delta Carquinez Strait 5 8 San Suisun Pablo Bay Bay 4 11 13 1 Richardson 38.0N 14 3 12 2 Corte Madera 3 San Rafael 15 4 Gallinas 5 Novato 2 6 Petalume 16 7 Napa-Sonoma 8 Carquinez North 9 Suisun Slough Central 17 10 Montezuma Slough 1 Bay 11 Port Chicago 12 Walnut 13 Carquinez South 18 14 Pinole 30 15 Wildcat Pacific 16 Point Richmond Ocean 29 17 East Bay Crescent 18 San Leandro 19 San Lorenzo 19 20 Alameda 28 21 Mowry 22 Santa Clara Valley 23 Stevens South 20 24 San Francisquito Bay 25 Belmont-Redwood 26 San Mateo 27 27 Colma-San Bruno 28 Yosemite-Visitacion 21 29 Mission-Islais 30 Golden Gate 26 05km 37.5N 25 24

California Headlands and Small Valleys 23 22 Study Alluvial Fans and Alluvial Plains Area Wide Alluvial Valleys

122.5W 122.0W

Fig. 1. Map of the San Francisco Bay Area, showing the 30 OLUs developed by ref. 35, their geomorphic classiﬁcations, and their names.

2 of 10 | PNAS Hummel et al. https://doi.org/10.1073/pnas.2025961118 Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks Downloaded by guest on October 2, 2021 Downloaded by guest on October 2, 2021 cnmceauto fsalvlrs dpainsrnl nune yhdoyai feedbacks hydrodynamic by influenced strongly adaptation rise sea-level of evaluation Economic al. et Hummel nnihoigOU ntesm uebyett einlor effects regional local to subembayment from effects. same interactions, baywide the in of OLUs an extent neighboring in for spatial on allow distribution the results habitat damage of and shoreline forecast analysis flood or combined to data The use attempt region. stock land not the building in do existing changes and the damages future use economic We estimate for event. to scenarios flood shoreline dam- protected one-off model in and a flood changes existing compute HAZUS the depth to between the curves flood ages from depth-damage the use data and overlay stock (39) we building flooding, for with this flooding maps eco- from associated tidal estimate impacts OLUs) To nomic other scenario. protection (in pro- SLR shoreline the external each same (within and the internal OLU) of at tected estimates sce- scenario explicit each shoreline spatially in volume existing provides OLU derived the similarly each for to to in volume estimates area water flood flood land this of Comparing the nario. volume across total values the these permanent find capture or integrate to flooding cycle We tidal tide experience inundation. spring that a areas during in tide inundation high depths at in water model maximum described varying the spatially are from extract scenarios we Here, modeled 29. these ref. (see water from bay scenario and resulting each dynamics levels tidal for in Changes shorelines Methods). bay circulation and tidal Materials the simulate with to 38) interactions (37, and Bay Francisco San of model slopes S1). steep Fig. and of Appendix, baylands (SI narrow head- consist (35) exhibit and valleys plains slopes, small alluvial moderate and and lands and width baylands fans intermediate wide of alluvial baylands by slopes, characterized the gradual are fea- for landscape and valleys on account alluvial influence Wide its that classified and tures. categories functions region are the geomorphic of ecosystem These history three geologic of (36). of set one possibilities into cohesive processes adaptation ecological a similar and physical and provide similar length together with coastline km, in that 75 repre- ranging to OLUs regions, 5 to These coastal from shoreline 1). and Bay (Fig. terrestrial Francisco planning sent San adaptation the SLR along (OLUs) inform 35 shore- units ref. 30 landscape we by operational The scenarios on delineated shoreline. based modification the are of segments shoreline line migration pro- and landward currently no SLR such not is, assume all where as flooding For maintained a to is by tected. vulnerable shoreline protected remains the completely it of is that rest shoreline the the which while in of seawall scenarios segment modification infras- an single shoreline Antarc- 30 present-day simulate a as all we rapid well includes scenario as under although that SLR tructure, (33), possible scenario each 2100 For shoreline also cm by (34). existing is 104 melt mean to cm ice-sheet 2009 30 tic 200 to of 1991 exceeding Francisco probability) the SLR San (67% above range for SLR likely projections of a above SLR cm suggest baseline). 200 Bay Bay and 2010 150, Francisco 100, January (50, San a scenarios from the SLR damages four in under economic Area strategies and inundation protection in implementing change quantify we spatial SLR, from the protection shoreline local-scale with ated water peak bay. of the can around distribution inundation amplitude spatial and tidal levels and in magnitude changes These the at wave 29). influence tidal 28, incoming (26, the shoreline of by reflection the enhancing tides perimeter and the bay the along the of areas of shallow amplification in damping cause frictional engineered can reducing Bay using seawalls Francisco protection like San shoreline structures in that SLR demonstrated and have adaptation modeling shoreline Recent (32). of routing berms, flood studies and as flooding engineer- modified affects that other shoreline ing or the infrastructure, of transportation 75% embankments, and protection flood eueatodmninl et-vrgdhydrodynamic depth-averaged two-dimensional, a use We associ- impacts economic regional of distribution the assess To inliudto nOU7 iial,we L sprotected, of addi- is 7 causes protection OLU 27) when to Similarly, example, 25 7. and OLU For 22 in inundation to bidirectional. OLUs tional 20 Bay also (OLUs shorelines South is Bay between South 7 relationship The OLU 10. and and addi- 9 particularly to Bay, OLUs leads Suisun in in similarly (landward) shoreline up-estuary 7 flooding in OLU tional flooding the additional Protecting cause down-estuary 7. and OLU the response affect level shoreline that water (seaward) the feedbacks with create interact to toward infrastructure Delta landward inlet Joaquin ocean to Sacramento–San the relationship the from its pro- propagating in are geographic tides Bay role Suisun tected, (Fig. and in important OLUs Bay characteristics an When patterns. South play inundation physical regional 7 and the OLU Bay of cases, in Suisun location both in 7 OLUs In OLU and 2). between Bay cross- notable Pablo These most San subembayments. are other interactions to embayment regionally extends that as time over change progresses. the may SLR protection demonstrates, shoreline example of this million impact As external 1.1 3E). additional (Fig. an scenario shoreline to leads 26 m OLU protecting by lost; flooding are m reducing 3D), million (Fig. provides 5.5 25 still OLU City 26 for OLU Foster protecting benefits the However, substantial of 3C). (Fig. shoreline parts the 25 SLR, along OLU of flooding of direct cm causing 100 overtopped, are At to levee 26. leading Seal OLU 3B), in of m (Fig. tection million mouth dry 6.5 the of remains reduction City at a 26 Foster pathway OLU that flood of such shoreline the Slough, the of of in elimination protection (San levee With comes 26 the 3A). OLU behind (Fig. flooding of 25 widespread OLU shoreline to neighbor- the leads a along which of Slough, Mateo), mouth elevated Seal the the into from channel, However, water SLR. protection ing additional of full pushes cm provides level 50 that sea at levee flooding a coastal (Fig. direct by (Belmont–Redwood) example, 25 surrounded For OLU is boundaries of eliminated. 3), part OLU are is lateral which coast City, across the Foster pathways from flood inland as stretching scenar- SLR 2), certain (Fig. under OLUs ios neighboring in 22 flooding OLU in tion of SLR. protection of m to cm million 200 due at 4.2 (Alameda) Valley) of Clara 20 (Santa increase interac- OLU maximum of in a magnitude flooding with the smaller, although is OLUs, tions Bay South flooding exacerbates other similarly OLUs in 18 certain (OLUs of Bay protection South 27), In elsewhere. to redirected is 10 increases OLU flooded Slough) m (Suisun million 9 pro- 30 almost OLU Slough) by other in (Montezuma in flooding 10 flooding shoreline, OLU its in tects increase when an example, to For leads OLUs. in typically capacity OLU between storage one floodwater greatest any 12), of to loss 9 generally subsequent (OLUs Bay and is Suisun protection In which subembayment. same the OLUs, in OLUs other in flooding SLR. of cm 200 to SLR of cm sce- 50 shoreline from existing range the flooding and to internal compared nario as in OLU reduction protected Values the the 1. in represent Fig. diagonal in shown the that is from along the resulting numbering shows OLUs OLU other column scenario. all Each in protection volume axis. flood horizontal in change scenar- the protection net along OLU The listed SLR. are of cm ios 200 cm, (D) 100 and (B) cm, cm, 150 50 (C) (A) at scenarios protection shoreline modeled Interactions. Inundation OLU on Scenarios Protection Shoreline of Effect 3 oeOUpoeto cnro locueetra flooding external cause also scenarios protection OLU Some oal,poeto fSuhByOU a edt reduc- a to lead can OLUs Bay South of protection Notably, external protection-induced represent values Off-diagonal ffloigi L 5(i.3F (Fig. 25 OLU in flooding of 3 t10c fSRadhge hs benefits these higher and SLR of cm 150 At . 5 ilo m million −551 i.2smaie h odipcsdet the to due impacts flood the summarizes 2 Fig. ,0 m −1,900 3 t10c fSR swtrta formerly that water as SLR, of cm 100 at 3 ffloigfrOU2 u opro- to due 25 OLU for flooding of 3 https://doi.org/10.1073/pnas.2025961118 3 o L 0(odnGt)at Gate) (Golden 30 OLU for o L Np–ooa at (Napa–Sonoma) 7 OLU for oprdwt h existing the with compared ) PNAS | f10 of 3 3 of

ENVIRONMENTAL SCIENCES Downloaded by guest on October 2, 2021 f10 of of cm 4 100 At dry. remains 25, OLU in here. levee included the not behind is located thus City, and Foster that such Slough, Seal (E of mouth the at (C pathway SLR flood the eliminates shoreline 26 3. Fig. 2. Fig. Ls2 o2 n 5 L ’ o lvto n ag area large shore- and when elevation floodwaters low for 7’s space OLU storage 25. and substantial 23 provide experiences notably to which most OLUs, (Napa–Sonoma), 20 Bay 7 OLU OLUs South OLU scenario. several boxes. protection in that by exacerbated from indicated is resulting are flooding highlighted. OLUs Bay also other South is all and scenarios, in protection Bay volume shoreline Suisun flood under in in OLUs interactions other change Subembayment with net 1. interactions the Fig. strong shows in column shown Each is axis. numbering horizontal the along are scenarios and and F ,poetn h L 6soeiecue diinlfloigi L 5 h 0-mSRseai hw h aeitrcina h 5-mscenario 150-cm the as interaction same the shows scenario SLR 200-cm The 25. OLU in flooding additional causes shoreline 26 OLU the protecting ), neato ewe Ls2 BlotRdod n 6(a ae)i ot a rnic a.A 0c fSR(A SLR of cm 50 At Bay. Francisco San South in Mateo) (San 26 and (Belmont–Redwood) 25 OLUs between Interaction | 0 m (C cm, 100 (B) cm, 50 (A) at scenarios protection OLU for volume flood in change Net https://doi.org/10.1073/pnas.2025961118 PNAS ,teFse iylvei vropd opoeto fteOU2 hrln rvdsol ata odrdcini L 5 t10c fSLR of cm 150 At 25. OLU in reduction flood partial only provides shoreline 26 OLU the of protection so overtopped, is levee City Foster the D),

OLU 26 protected OLU 26 unprotected Impacted OLU CD Impacted OLU AB B A San Mateo 10 15 20 25 30 10 15 20 25 30 OLU 26 5 5 Seal Slough Mouth of 5 0 0c fSR100cmofSLR 50 cmofSLR c m 515202530 515202530 San FranciscoBay o Belmont-Redwood f S 10 10 L R OLU 25 OLU 7 Protected OLU Foster City Suisun Bay D C South Bay cnmceauto fsalvlrs dpainsrnl nune yhdoyai feedbacks hydrodynamic by influenced strongly adaptation rise sea-level of evaluation Economic 10 15 20 25 30 10 15 20 25 30 5 5 rvd iia trg pc u r eaae rmters of rest the from separated which is are 10, but protection and space when 9 storage lost OLUs similar is Unlike provide shoreline. space its this along but implemented modified, not are lines 1 0 0 c 515202530 515202530 F E m o f S 10 10 L 150 cmofSLR R Protected OLU 0 mo L.Idvda L protection OLU Individual SLR. of cm 200 (D) and cm, 150 ) Water Depth(m) 0.0 Bay Area San Francisco Levee Foster City Protected OLU >4 3 2 1 <1 − − − 4 3 2 1.5 Net change in flood volume (m3) km 3.0 − − − − − 10 10 10 10 10 10 10 10 10 and 5 6 7 8 9 8 7 6 5 ,poeto fteOLU the of protection B), umle al. et Hummel Downloaded by guest on October 2, 2021 xenlfloigars l te Ls n (C ( and OLU, OLUs, protected other the all across flooding external (B) 4. Fig. flood- external induced protection in shoreline increases the to than through due greater move flooding generally to internal Over- are cycle. able in tidal is the reductions during water surrounding all, Bay less 12 Suisun into as to channel 2), 9 constricted a (Fig. OLUs to Bay in leads flooding Suisun Strait up-estuary Carquinez the in along reduction through South) North) (Carquinez (Carquinez transmission 8 13 energy OLUs and protecting tidal example, For reduce areas. slightly these narrow- areas additional may to these that leads narrower protection ing protecting at shoreline bay, located to the typically of are benefit parts OLUs these regional indicating Because other a flooding, 4C). small (Fig. external for in and in potential flooding headlands decreases the small certain exacerbating to of and leads protection amplifica- valleys (29) contrast, tidal bay In to OLUs. the leading reflective, within to boundary tion OLU more dissipative the and from floodwaters lost is shore- shifts store space the storage this when and protected, However, is fric- (29) types. line geomorphic provide tides other can the than readily valleys of alluvial damping gradual wide and tional elevations characterize low that least The and valleys. slopes valleys small also alluvial and are wide headlands flooding of for protection external experi- for in valleys largest Increases small generally and decreases. headlands smaller as and ence Alluvial plains valleys, 4A). alluvial (Fig. alluvial bay and wide the fans from as disconnected of are classified impacts areas OLUs low-lying result external of flooding and protection internal in internal from decreases the Large protection. determining shoreline in role tant propagate Influence. that Geomorphic Bay Central and Bay down-estuary Bay. Pablo in South into San changes to in the leads levels at bay position water 7’s the OLU of Strait, boundary Carquinez northern narrow the via bay the cnmceauto fsalvlrs dpainsrnl nune yhdoyai feedbacks hydrodynamic by influenced strongly adaptation rise 5% sea-level at of evaluation test Economic difference significant al. honest et Tukey Hummel a on in based provided are scenario, comparisons SLR pairwise a all within for types results geomorphic test across significance comparisons The level. pairwise significance all for values mean similar itiuino L odaddmg eut,smaie ygoopi ye (Left type. geomorphic by summarized results, damage and flood OLU of Distribution E xenldmgsars l te Ls n (F and OLUs, other all across damages external ) emrhccaatrsispa nimpor- an play characteristics Geomorphic − − − − − − C B A − 600 400 200 200 600 400 200 200 10 10 20 0 0 0 a a a 0m10m10m200cm 150cm 100cm 50cm 200cm 150cm 100cm 50cm 200cm 150cm 100cm 50cm a a a Flood Volume (millionsm b a b luilFn n luilPan HeadlandsandSmallValleys Alluvial Fansand Alluvial Plains a a a a a a b b b e odn itra lsetra)wt rtcin ( protection. with external) plus (internal flooding net ) c a a a a a b b b b a a 3 ) a a a b b b e aae itra lsetra)wt rtcin etr ersn statistically represent Letters protection. with external) plus (internal damages net ) External Internal Net nalohrSuhByOU,ttln 73mlina 0 mof cm 200 at million $723 totaling OLUs, Bay damages additional South to other the leads all which in for flood scenario, notable lateral protection especially 22 to OLU are due externalities reductions Damage damage protection. experience and may 5 cm, (Fig. which 150 SLR cm, 50 of at cm OLUs 200 other in damages primarily increased externalities in These result levels. South sea in higher 5 at OLUs widespread Fig. other and of in right damages Bay (top external South Bay large protecting to area hand, of leads other unit magnitude OLUs the potential per On the costs externalities. limiting and damage replacement ) S2 building Table Appendix, South low (SI lead- and relatively wetlands, Central of to consist of shoreline ing the parts of to portions large compared and Bay, sparse this more in Development is notable. as region inter- not damage are Bay the Suisun Bay, within Suisun actions in OLUs between interactions nal ranging 16), to 11 million. (OLUs 55 Bay to $0.4 Pablo from the San Bay, and Suisun of Strait, extent Internal Carquinez southern protected. the along is 25 across smallest shoreline are billion the OLU benefits 6.1 when to scenarios In SLR $1.4 where shoreline. four by 27), the reduced the to are along damages 18 internal (OLUs right Inter- alone, Bay SLR. lies South of development the cm diagonal, dense in 200 the largest (D) along and generally shown damages, cm, are economic 150 in (C) reductions cm, nal 100 (A) (B) at cm, scenarios protection 50 shoreline modeled the from resulting Interactions. OLU Inundation Coastal to Due Damages Economic three all for across volume 4E). scenarios flood (Fig. protection types in shoreline geomorphic regionally, OLU decrease, all net almost a in resulting ing, ncnrs otefloigrsls hc xii togexter- strong exhibit which results, flooding the to contrast In − − − − F E D 4,000 2,000 4,000 2,000 − 250 250 500 750 0 0 0 al S1. Table Appendix, SI a a a 0m10m10m200cm 150cm 100cm 50cm 200cm 150cm 100cm 50cm 200cm 150cm 100cm 50cm nenlfloigwti h rtce OLU, protected the within flooding internal (A) in change The ) a a a a a a D a m a a a i.5smaie h aaeinteractions damage the summarizes 5 Fig. a g a a a e Wide Alluvial ValleysWide Alluvial s Right a a a ( A, U ,wihbcm oepronounced more become which A–D), S ab D a a and C, nenldmgswithin damages internal (D) in change The ) m a a a i l l a b a i o n https://doi.org/10.1073/pnas.2025961118 s ab ,ecp o daetOLUs, adjacent for except D), a a ) a a a b a a PNAS | f10 of 5

ENVIRONMENTAL SCIENCES Downloaded by guest on October 2, 2021 f10 of 6 (Fig. levels sea higher at especially 5 scenarios, protection some a development of properties. are distribution high-value spatial that they and the interactions as as well hydrodynamic–shoreline as variation, flooding the govern greater both exhibit of results function damage (Fig. pattern scenarios the SLR consistent all 2), more across volume a flood shoreline. show external increasing opposite results of flooding the 23 OLUs the on for while Francisquito) also Thus, (San but 24 (Mowry), neighbors, and 21 its and (Stevens) for protect- Lorenzo) benefits example, (San reduction 19 For flood OLUs 5B). are provides (Fig. 20 that OLUs OLU reductions ing adjacent lead damage to SLR widespread limited of but cm not 100 protection small at that generally plot. interactions from each Bay resulting to in South OLUs boxes the contrast, other by In all indicated SLR. in are Bay damages Suisun economic and in Bay South change in net interactions the Subembayment shows 1. Fig. column in Each shown axis. is numbering horizontal OLU the scenario. along listed are scenarios 2i rtce.W rvd neapeo o population data damage how economic of supplement example to exter- an OLU used by when in provide be case affected the We could be is impacts protected. as to S3), is people Table 22 cause Appendix , additional (SI can 5,900 flooding here nal as considered many individ- scenarios as The protection strategies. shoreline adaptation consideration ual shoreline important developing another are when impacts population damage tures, at to scenario susceptible protection is external SLR. S2), of every with cm Table 200 valley nearly 22, Appendix , alluvial with OLU (SI wide an interactions a 5D). bay experiences for the (Fig. Bay cost in replacement Pablo damages building San in highest in an the million Rafael) experience $53 (San Bay respectively, additional damages, 3 South in in OLU million $70 Leandro) while and (San million $82 18 additional and 22 OLUs 5. Fig. C einletra aaeitrcin r lopeetin present also are interactions damage external Regional hl h ou foraayi so aaet struc- to damage on is analysis our of focus the While Discussion. and | 0 m (C cm, 100 (B) cm, 50 (A) at scenarios protection OLU for damages economic in change Net https://doi.org/10.1073/pnas.2025961118 PNAS .We L spoetda 0 mo SLR, of cm 200 at protected is 7 OLU When D).

Impacted OLU CD Impacted OLU A 10 15 20 25 30 10 15 20 25 30 5 5 5 0 c m 515202530 515202530 o f S 10 10 L R Protected OLU Suisun Bay South Bay cnmceauto fsalvlrs dpainsrnl nune yhdoyai feedbacks hydrodynamic by influenced strongly adaptation rise sea-level of evaluation Economic B 10 15 20 25 30 10 15 20 25 30 5 5 rtcin nldn pc o ae trg n proximity and storage from water volume flood for in fac- space changes identify including external we to protection, type, contribute geomorphic that OLU by m tors single million patterns a 36 flood of as Assessing protection large the as exter- to be from and cost can results volume inundation a that of baywide damages at parts in nal other come increase in The can and bay. nearby benefits the both these communities, shoreline that Area, damage other Bay shows flood Francisco analysis avoided San the this from in Although benefits infrastructure protection protective embayments. potential behind evaluating large coastal are developed when there highly consideration in important strategies feedbacks hydrodynamic an from are resulting externalities Regional 4E). (Fig. SLR of Discussion and cm 200 headlands and than cm 150 damages under external valleys small greater observed excep- of of the with most tion significant, type, statistically not geomorphic are by relationships patterns these flood con- external qualitatively are with valleys sistent damage alluvial external wide protecting While for flooding. patterns to development of 2016 exposure on mix its (based Database; a land Cover generally pasture Land is and National OLU grassland, of coastal wetlands, coastal type The of this reductions. in damage configuration large landscape similarly do to valleys translate signifi- alluvial and wide not statistically protecting internal for fans not large estimated the reductions is alluvial Surprisingly, flood comparison. this as pairwise though any classified for 4D), cant OLUs (Fig. plains in dam- alluvial greatest economic for internal appear than in ages damages reductions economic Estimated for volume. flood muted more are classifications Influence. Geomorphic 1 0 0 c 515202530 515202530 m o f S 10 10 L R Protected OLU 0 mo L.TeOUprotection OLU The SLR. of cm 200 (D) and cm, 150 ) ifrne ewe L geomorphic OLU between Differences 3 htlim- that S2) Fig. Appendix, SI n 73mlin respectively. million, $723 and Net change in damages (USD) −10 10 −10 −10 −10 10 10 7 8 9 7 10 9 8 umle al. et Hummel Downloaded by guest on October 2, 2021 cnmceauto fsalvlrs dpainsrnl nune yhdoyai feedbacks hydrodynamic by influenced strongly adaptation rise sea-level of evaluation Economic al. et Hummel when neglected strategies. be adaptation not infrastructure selecting proposed should and of evaluating and analysis cost–benefit alternatives substan- overall a infrastructure the be to may contributor externalities results tial damage our be caveats, these also these that will with Even demonstrate that 41). agriculture) (31, (e.g., flooding types water, by affected use transportation, land (e.g., or systems dam- energy) include and infrastructure not does other it to addition, damages In age higher scenario. to SLR given lead any likely estimate for the would probabilistic which at a SLR damage, not buildings repetitive is of and of to level cm damage else- flood 200 tidal flooding captures annual induced at only highest and estimate space bay storage This the increase flood where. of net across loss a damages the to to in lead due million could shoreline $293 a 7 building of OLU that the suggests along here Alternative presented barrier as analysis build to economic much the as times 1, four nearly cost would Alterna- 2 tive Although or scenario). causeway scenario) surrounding 2: the levee (Alternative and landscape bay 1: the between (Alternative pathways includ- flood shoreline maintaining study, the this in protecting the examined ing for strategies proxies shoreline as seen possible be bil- two can 2.5 options to adaptation $2.2 These cost (40). to lion exchange estimated tidal marshlands, maintains and bay that mil- the $650 causeway between cost a to constructing estimated 2) embankment, or on or lion, road levee the raised building a alter- 1) of The include top considered flooding. being future are of that effects natives adaptation the High- the mitigate considering road to is and of this alternatives Caltrans, events, length of agency, high-water Segments the transportation shoreline. during state of 7 flooding OLU half experience the than already along More (Fig. runs Bay Interstate 37 101. 37 Pablo region: way Highway San Highway the in of and of thoroughfares shoreline 80 case major northern two the the connects is along and runs Bay which Francisco 6), San exam- specific from A analyses. ple cost–benefit enhance help can nalities estimate to buildings here elsewhere. introduced exposed have impacts we these and like model flooding coastal a spa- require of will the other and overlap on to and rely extend damage distribution flood tial factors in these changes external While embayments, straits. narrow to for shown is shorelines existing with scenario SLR 100-cm Flooding reference. damages. the economic by associated influence and caused will strategy inundation adaptation or regional of embankment and or choice local levee The to causeway. raised a a susceptible of as top disrup- it is on future rebuilding road prevent the 37 to building adapted by Highway be either to tions, shoreline. need will (Napa–Sonoma) and flooding 7 SLR-induced OLU the ning 6. Fig. Petaluma OLU 6 rmapoetlvlprpcie nesadn odexter- flood understanding perspective, project-level a From iha 7 rnpraincrio frgoa motne span- importance, regional of corridor transportation a 37, Highway Napa-Sonoma OLU 7 San PabloBay 8km 0 2 Water Depth(m) 4 >4 3 2 1 <1 Bay Area San Francisco Highway 37 − − − 4 3 2 6 o 7 epe(0 IO)eswee t10c and number the cm be- outweighs who 7 100 7 OLU OLU At in outside people flooding elsewhere. of strategic number from BIPOC) the nefit flooding SLR, (30% avoiding of while cm people 7 150 OLU 570 in indigenous, Black, [BIPOC]) for (61% color people of 500 people for or flooding causes SLR of strategy. such any implementing and a evaluating be in certainly step would critical decision-makers among and discussions community stakeholders Inclusive broader multiple compensated. the if even of bay, benefit the the within to for object assets likely local would 21 sacrificing OLU commu- within decision-makers individuals, strategi- and However, both races nities, by to data. justified population all 21 be and OLU could of damage impacts allow the people external to mitigate more decision to flood for the cally Thus, benefits bay. flood- provides the allowing 21 across composition, OLU racial number in their total ing the and to flooded respect 150 people population with SLR, flooded of and both of the However, cm, cm in 21. increase 100 200 OLU an within At cm, to residents. 50 leads local protec- flooding at flooding strategic to without bay leads SLR the of who 21 throughout cm OLUs OLU people other of of in flooding while tion living Strategic decision, this people flooding. of represents avoid result are column 7 a OLU right as 21 in flooding the OLU living experience people who (B) the 21 SLR represents and or each column For 7 left above. the suggested OLU scenario, as (A) flood, strategically population when to the allowed flooding of by breakdown demographic affected infras- shows and critical 7 magnitude Fig. and areas, example, the For significance, importance. agricultural regional cultural of assets populations, or tructure historical vulnerable of of places protection includ- segments, ing shoreline specific protecting about decision the costs and benefits 43). net (24, the armoring influence of other may and that fisheries, recreation, services of ecosystem loss and degradation mainte- (25) potential and habitats the coastal construction include of they of do cost nor armoring, the of include nance not we do estimates here damage the report Importantly, flood bay. reduce the developed to throughout avoid flooding levels densely to strategic allow valleys already and alluvial development wide allows further in communities that incentivize to mechanism areas elsewhere a development from be proceeds the could development of their portion over a sign for to rights pro- owners rights property development allows of that associated gram transfer externalities A ben- economic protection. regional shoreline negative with substantial the provide avoiding could by efits areas these difficult strategic thus instead, in perspective; is flooding economic 21, valleys, regional and alluvial a 7 200 from wide justify OLUs at as to Protecting million classified S2). $194 both Table are to Appendix, which up (SI damages SLR in of increase are leads cm San net also values 21 regional both replacement OLU a in impacting total to protection in SLR, where Shoreline million highest. Bay, of the $293 South generally cm to and 200 Bay up at Pablo causes region. damages entire 7 net the OLU across regional damages protecting in of example, increase benefit net protec- For net a shoreline to high however, leads cases, the tion some considering In (42), protection. solution shoreline possible com- a externalities this, negative is highlighting as experience such S2 ), that cases communities Table In for area. pensation , Appendix this (SI of importance scenarios regional economic bil- the SLR net $1 all the exceeds in OLUs, still protection lion Bay shoreline South from other reduction damage in leads damages shoreline higher 25 OLU to the protecting region while example, the For across losses. damages aggregate 4F in reduction (Fig. OLU net an a protecting to cases, leads most strategic In for planning. opportunities adaptation potential regional into insight provide tection ncnrs,alwn L osrtgclyflo t5 cm 50 at flood strategically to 7 OLU allowing contrast, In influence may that factors related other course, of are, There pro- shoreline to due damages in change baywide of Estimates ,atog niiulOU a xeineincreased experience may OLUs individual although ), https://doi.org/10.1073/pnas.2025961118 PNAS | f10 of 7

ENVIRONMENTAL SCIENCES A to address the gap include expanding the authority of exist- 3000 ing regional planning and permitting agencies, such as the San Francisco Bay Conservation and Development Commission, or 2500 developing a collaborative management structure composed of multiple agencies working together to implement a regional vision, as proposed by the recent Bay Adapt initiative (45). Given 2000 the sizable potential flood damage externalities observed in this study, coordinated action is more likely to succeed if incen- 1500 tives are aligned to address disparate impacts across parties. Direct transfer payments as mentioned above may be an option Population 1000 to compensate areas that are strategically allowed to flood to reduce damages elsewhere; this is analogous to other payment for environmental service programs like water funds that pre- 500 serve upstream land to ensure downstream water quantity and quality (46). A more targeted approach could be modeled after 0 the Measure AA parcel tax, which funds restoration of the San I EIEIEIEFrancisco Bay shoreline by taxing all parcels in the nine counties that border the bay $12 annually for 20 y. By raising funding B 3000 for SLR adaptation at the regional level and tying it to development density, projects and policies could be prioritized based on White regionally defined criteria and funded principally by developed 2500 Black areas that stand to benefit most. Native Our results provide an initial estimate of the magnitude and 2000 Asian distribution of flood damage externalities across communities Pacific Islander when implementing coastal protection and strategic flood stor- Other 1500 age measures and can serve as a basis for transparent regional Two or more engagement that acknowledges these external costs. Although

Population the OLU-scale shoreline protection scenarios presented here are 1000 not necessarily representative of likely SLR adaptation plans for the region, the results highlight how geomorphic factors, 500 development density, and geographic location in the bay are likely to influence the regional impacts of shoreline protection projects. This information can support the evaluation and selec- 0 I EIEIEIEtion of actual adaptation plans and individual projects for the San Francisco Bay Area, which may include multiple simulta- 50cm 100cm 150cm 200cm neous shoreline modifications that are implemented at smaller Fig. 7. Total number and racial composition of people affected by the deci- scales than examined here (e.g., sub-OLU). Similar analyses that sion to strategically flood (A) OLU 7 and (B) OLU 21. For each SLR scenario, consider other drivers of extreme water levels and associated pat- the left column (I = internal) represents the people living in OLU 7 or 21 terns of flooding in addition to the tidal flooding mechanisms who experience flooding as a result of this decision, while the right column considered here would also help to inform adaptation decisions. (E = external) represents people living in other OLUs who avoid flooding. Our approach can be extended to other coastal estuaries with low-lying, dense development, such as the Chesapeake Bay on of people in OLU 7 who are affected, with comparable racial the US East Coast or the Bohai Sea in China, which exhibit composition between both groups. However, at 200 cm of SLR, similar hydrodynamic feedbacks (27, 47, 48) and would presum- the flooded population in OLU 7 (2,670 people, 64% BIPOC) ably benefit from an analysis of interrelated economic outcomes is once again similar in magnitude to the population that avoids from protection strategies. Accounting for the connectivity of flooding elsewhere (2,810 people, 56% BIPOC) and includes a local actions in coastal estuaries is a critical step toward identify- higher percentage of BIPOC residents, who often have fewer ing shoreline adaptation strategies that provide regional benefits resources to prepare for, respond to, and recover from natural while also mitigating unintended negative impacts. hazards such as flooding (44). In this case, accounting for the number of residents internal to OLU 7 that experience flooding Materials and Methods and the potential disparate impacts on the BIPOC population Hydrodynamic Modeling. We applied a two-dimensional depth-averaged may lead to alternative decisions about shoreline adaptation hydrodynamic model of San Francisco Bay developed as part of the US in OLU 7. As this example illustrates, augmenting information Geological Survey’s (USGS) Coastal Storm Modeling System (CoSMoS) (37, about physical and economic externalities with estimates of asso- 38). The model uses the Delft3D Flexible Mesh software (49), which applies ciated human impacts can provide an additional means through a finite volume approach on an unstructured grid to solve the governing shallow water equations which to evaluate proposed shoreline adaptation projects and to inform more equitable risk reduction. δh δuh δvh + + = 0 The work summarized here is an important first step toward δt δx δy understanding previously uncounted regional damage interac- ! tions and thus fills a critical information gap in the understand- δu δu δu δh δ2u δ2u 1 g + u + v = −g + ν + − kuku ing of shoreline protection and its consequences within San δt δx δy δx δx2 δy2 C2 h Francisco Bay. However, internalizing this information into deci- ! δv δv δv δh δ2v δ2v 1 g sion making will require overcoming the “governance gap” that + u + v = −g + ν + − kvkv, separates the scale of decision-making from the scale of the δt δx δy δy δx2 δy2 C2 h threat of SLR (7). Currently, the San Francisco Bay Area lacks where h is the water depth, u and v are the depth-averaged velocities, g a mechanism to reorient smaller-scale planning toward a coor- is the gravitational acceleration, ν is the viscosity, C is the drag coefficient, dinated, regional focus across jurisdictions. Possible avenues and x, y, and t are the space and time coordinates. Wetting and drying

8 of 10 | PNAS Hummel et al. https://doi.org/10.1073/pnas.2025961118 Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks Downloaded by guest on October 2, 2021 Downloaded by guest on October 2, 2021 3) edrvdttlrpi otvle trs oSRoe h et10yby y 150 next the profile risk over the SLR with consistent to OLUs, across risk blocks at census all values notes over cost aggregating release repair 3.2 total HAZUS derived FEMA’s We in (39). of guidance outside following block software census HAZUS each content the for and class structure occupancy spread by aggregate costs evenly reconstructed repair/replacement be We to block. assumed census are the classes is across structure here all function where damage expected model this the lumped of such a resolution as and spatial block, The census the type. is occupancy dataset inven- by explicit classified spatially structures nationwide of a tory HAZUS database, (FEMA’s) Stock Agency’s Building Management We General Emergency 2015 averse. Federal rep- risk region the Bay were Francisco in owners San resented the affected across underesti- structures if for would welfare analysis this and social conducted owners in property change of the neutrality mate risk assumes scenario protection This baseline that with (53). a associated gain/loss, between vari- welfare social compensating cost the of or estimate repair ation, an in provides scenario change protection and the scenario approach, sce- SLR this and Using protection all narios. and contents condition building no-intervention damaged baseline of the cost to under replacement cost the repair and expected properties the both flooded estimating (52), methodology function age Damages. Economic SLR. of amount that for scenario shoreline existing and where integral the using OLU each in surface land the and pathways. as OLU flow well protected overland along the as using neighbors between modeled OLU, its flooding extent prevents flooding each SLR This of 200-cm shorelines. walls. the boundary existing to impermeable coastal up boundaries high the lateral infinitely follow the using generally model walls hydrodynamic The the in 500-m a ally plus scenario SLR 500-cm mobiliz- the of of extent capable zone. inland transitional are the waves to wind-driven sediment of where extend ing points OLUs point direction, apex offshore cross-shore the the the In from or fans. alluvial boundaries and watershed headlands between major major boundaries lateral using the OLUs and includ- delineated headlands individual further type, and then plains, geomorphic They alluvial and valleys. by fans small broadly alluvial Area. valleys, bayshore Bay alluvial Francisco the wide San ing divided the 35 for ref. 35 ref. Briefly, by conducted delineation boundary Scenarios. Shoreline higher at disruptions flood month) per to days elevations. (minutes (multiple shorter-duration frequent per- and in but areas results hours) low-lying This some month. tide in each spring wk flooding a 2 manent during approximately tide on for high persists is at which study occur cycle, would simulations the that the of inundation from the Outputs focus represent shorelines. the the with because interactions simulations driven mete- include tidally the and not did in Sacramento We model. the forcing the for into orological inflows data point discharge as 150, Rivers historical with 100, Joaquin applied San 50, component (i.e., We tidal increment cm). SLR additional 200 the an and to equal added amplitude we and frequency scenario zero SLR each For (51). eesadcret xrce rmOeo tt nvriysTX8tidal TPXO8 University’s (M constituents State harmonic Oregon eight from for extracted model currents San these and the capture levels from to (32). extracted database enough Inventory was Shore Bay fine structures Francisco San not these Institute’s Estuary for was Francisco data resolution in Elevation embankments, grid features. and the berms, floodwalls, where levees, areas We engineered fea- across areas. protection as (50) shoreline such overland existing Database tures, delineated in Elevation further We m National domain. Coastal model 50 the horizontal USGS than 2-m the at less from available to data resolution approx- bathymetry areas and from topography offshore size seamless in in used ranged km cells Grid 3 S3). imately Fig. Appendix, the to (SI offshore contour extended depth and Delta Joaquin Sacramento–San applied the is roughness variable domain flow Spatially formulation. roughness the depth. Manning from flood the points using threshold grid a removing on or based adding by accomplished is cnmceauto fsalvlrs dpainsrnl nune yhdoyai feedbacks hydrodynamic by influenced strongly adaptation rise sea-level of evaluation Economic al. et Hummel o ahseai,w acltdtecag niudto oueacross volume inundation in change the calculated we scenario, each For individu- shoreline OLU each for scenarios protection implemented We efre h oe tteoencbudr ihJnay21 water 2010 January with boundary oceanic the at model the forced We in channels upstream and Bay Francisco San included domain model The ∆h V OLU stecag nwtrdphi ahgi ela oprdt the to compared as cell grid each in depth water in change the is steiudto volume, inundation the is esmltdflo aae sn h xetddam- expected the using damages flood simulated We edvlpdtesoeieseaisfo h OLU the from scenarios shoreline the developed We V OLU = Z A OLU A OLU dA, ∆h 2 S , stesraeae fteOLU, the of area surface the is 2 N , 2 K , 2 K , 1 O , 1 P , 1 −1,500-m n Q and , 1 ) betruhteDyddt eoioyat repository data Dryad 2z34tmpmb the through able obtain Availability. who Data or action. flooding protective experience the of who result region num- a the as the benefits determine across protective to SLR people scenario same then protection of the at We each ber scenario for block. shoreline OLU a existing where each the of areas in with in part counts or only population blocks the in census compared concentrated larger is in census approach biases development each to This residential throughout lead distributed flooding. could evenly by which is count affected block, population population people the block-level of that the number assumes to the value shoreline calculated determine each that We under to applied flooded (64). then was census that and block decennial scenario census San 2010 each the of the proportion across from the counts region population Bay block-level Francisco prior extracted two we of here, value modeled mean the 60). (2, of metric 4% risk exposure within this clas- global calculated is shorelines overall that here to studies The million closest estuaries. 867 live and of these bays estimate of influenced million tidally people 468 million as and 864 sified at that risk, population estimates at process total are This globally estimate as system. nearshore defined to this systems 2) in coastal risk (class to these influenced nearest sys- met tidally populations coastal that predominantly nearshore extracted population of we global typology (63), mapped the tems globally extract a coastline. to using reference Finally, used the criteria. as then layer was vector layer shoreline domain m This public global the 10 II using below Bank coastline, Data areas the World with identify contiguous to are that reprocessed elevation was in model (62). elevation model elevation digital digital The hole- global Research’s Mission Topography Agricultural sourced Radar International were Shuttle on filled data Group elevation Consultative global the and 2020 in from (61), population WorldPop Global using been 60). has mapped (2, what Zone” was in Coastal risk Elevation SLR “Low estimating the than work termed connected prior less hydrologically with at be consistent shoreline not coast, the would the to that to areas adjacent excluding living elevation, those m 10 as here flooding and Estuaries. and SLR Bays in Risk at Population one the as such 59). (58, analyses here value–based presented property under- of be trajectory. traditional may protection but through future communities values, for valued their priority replacement a on do be property may on depending populations we vulnerable focused results so analysis bias our S2), could While over account Fig. which distribution not population Appendix, (57), did or time (SI development We socioeconomic underestimates. land valleys in damage of changes alluvial for systematic portion wide small large a expect in contribute is not even agriculture and Crop flooding area, 41). by by (31, affected damages be economic also types to will land-use infras- or which energy) other agriculture), and incorporate equal, (e.g., water, not being transportation, examined did (e.g., else We and systems All buildings tructure estimates. to events. value damages flood economic long-term repeat only underpredicts for significantly account not this did and and nario block census each for means. classes for sample statistics on occupancy summary reported across derived from costs we cells all this repair across 100 From aggregate costs draw. sampled repair each estimated randomly for and types we block occupancy census block each within census map each flood estimate the for single a cost produce flood repair in to were variation of area functions with study depth-damage deal the To nonlinear raster. in pop- and flood cases densely depth the all less of in in resolution and the but larger than ha, much larger 3 be than can they less events areas flood generally and ulated past are from blocks FEMA extracted data Census by empirical we 56). using developed (55, Engineers HAZUS, as of a Corps classes, From as Army structure US costs, cost. the all repair replacement for to functions building depth appropriate total flood of relate that fraction functions depth-damage via Protection (54). States EnviroAtlas Environmental United from the coterminous available the on for map based population population OLUs total dasymetric 30-m the across Agency’s calculated aggregating We by (35). risk OLUs at the create to used definition iecmet.Ti rjc a upre yNFAad1411 the 1541181, Award the NSF and Foundation, by Wallenberg the supported Foundation, was Moore Betty project and Gordon This comments. tive ACKNOWLEDGMENTS. oetmt ouainipcsfrtesoeiepoeto scenarios protection shoreline the for impacts population estimate To sce- SLR each under event flood tidal one-off a as treated was Modeling blocks census across class occupancy each for damages flood assessed We 6)and (65) h aaadcd sdi hsaayi r avail- are analysis this in used code and data The https://doi.org/10.5061/dryad.g79cnp5pt etakMr tcyfrisgtu n construc- and insightful for Stacey Mark thank We https://doi.org/10.1073/pnas.2025961118 edfie ouaina ikfrom risk at population defined We https://doi.org/10.5061/dryad. PNAS (66). | f10 of 9

ENVIRONMENTAL SCIENCES National Oceanic and Atmospheric Administration’s Cooperative Institute at the University of California, Berkeley (supported by the University of for the North Atlantic Region. This research used the Savio computational California, Berkeley Chancellor, Vice Chancellor for Research, and Chief cluster resource provided by the Berkeley Research Computing program Information Ofﬁcer).

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