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Updated May 2026

Flood Risk in Michigan

Michigan carries a relatively low statewide average risk score of 9, with 100% of its 83 counties at A or B. 0 counties are in the F (extreme) tier, typically along major rivers or flood-prone basins. Statewide NFIP take-up is modest at 574 total claims.

83
Counties
574
NFIP Claims
$12,482,091
Total Payouts
9
Avg Risk Score

Grade Distribution Across Michigan

The grade mix is dominated by A — 100% of counties — meaning the typical place in this state has very low historical flood loss. The handful of B/C/D/F counties below define where risk is concentrated.

A
83
counties
B
0
counties
C
0
counties
D
0
counties
F
0
counties

How Michigan Compares Nationally

The U.S. county-level average composite score is 12. Michigan sits at 9, which is 3 points below the national average — meaningfully less flood-exposed than the typical U.S. state. 239 federal flood-related disaster declarations on file across 83 counties — roughly 2.9 per county on average. This is broadly typical for U.S. states with mixed terrain.

For full national context — every state ranked by average score and total claims — see the all-states overview. The riskiest-counties ranking and highest-payouts ranking drill into where loss is concentrated. Real-time stream-gauge readings are at USGS Water Data.

Riskiest in Michigan

CountyGradeScore
SaginawA18
MonroeA17
KalamazooA16
ArenacA15
OaklandA14

Safest in Michigan

CountyGradeScore
St. ClairA5
CalhounA6
WayneA7
AlgerA8
AlpenaA8

How Michigan's Risk Is Calculated

Every county in Michigan is scored on the same four factors that drive every county nationwide: NFIP claims density (40%), federally declared flood-disaster frequency (25%), average claim severity (20%), and year-over-year trend (15%). Source data comes from the public FEMA flood-mapping program and OpenFEMA endpoints. Detailed weighting math, plus the data's known limitations (county-level granularity, NFIP-participation bias, historical bias), is on the methodology page.

All 83 Counties in Michigan

Sorted by flood risk score, highest to lowest.

#CountyGradeScoreClaimsPayoutsDisasters
1SaginawA1841$1,370,9686
2MonroeA1735$576,6475
3KalamazooA1615$1,234,3002
4ArenacA1514$313,6944
5OaklandA1427$563,5044
6IoscoA146$9,9174
7InghamA1311$176,9404
8AlleganA114$6,6626
9MidlandA1169$3,475,6825
10BerrienA1114$354,7096
11GogebicA100$04
12HoughtonA100$04
13IoniaA101$05
14KentA1019$481,0094
15MuskegonA107$70,3525
16NewaygoA105$45,6555
17OsceolaA103$12,5865
18OttawaA1011$247,5625
19BayA1011$142,6795
20GeneseeA105$32,0515
21GratiotA105$18,3964
22HuronA100$04
23IsabellaA103$140,4814
24LapeerA100$04
25MecostaA100$04
26MontcalmA100$04
27OceanaA102$04
28SanilacA100$04
29ShiawasseeA101$9,0415
30TuscolaA101$12,9455
31Van BurenA100$05
32MenomineeA93$20,0003
33BaragaA90$03
34BarryA912$163,9273
35KeweenawA90$02
36MarquetteA92$20,5973
37OntonagonA90$03
38MacombA933$523,7457
39AlconaA91$5,4472
40CassA91$29,6982
41ClareA91$03
42ClintonA90$02
43CrawfordA90$02
44EatonA94$19,3233
45GladwinA91$27,0002
46IronA90$02
47JacksonA91$12,1372
48LakeA92$85,0793
49LivingstonA95$45,9393
50ManisteeA92$2702
51MasonA91$03
52St. JosephA96$73,8782
53WashtenawA92$403,9872
54AlgerA81$01
55AlpenaA81$01
56AntrimA80$01
57BenzieA81$01
58BranchA81$55,0001
59CharlevoixA82$5591
60CheboyganA86$20,0001
61ChippewaA80$01
62DeltaA80$01
63DickinsonA80$01
64EmmetA81$01
65Grand TraverseA85$5,7281
66HillsdaleA81$40,0001
67KalkaskaA80$01
68LeelanauA80$01
69LenaweeA80$01
70LuceA80$01
71MackinacA80$01
72MissaukeeA80$01
73MontmorencyA80$01
74OgemawA80$01
75OscodaA80$01
76OtsegoA80$01
77Presque IsleA80$01
78RoscommonA81$01
79SchoolcraftA80$01
80WexfordA82$65,0001
81WayneA7109$1,050,6476
82CalhounA66$24,7703
83St. ClairA550$493,5804

Frequently Asked Questions

What is the average flood risk score in Michigan?

Michigan's average composite flood risk score is 9 on a 0–100 scale, computed as the mean of all 83 county scores. That is 3 points below the U.S. county-level average of 12. Score components: 40% claims density, 25% disaster frequency, 20% claim severity, 15% trend.

Which counties in Michigan have the highest flood risk?

The riskiest county in Michigan is Saginaw with a composite score of 18 (grade A). The next four — Monroe, Kalamazoo, Arenac, Oakland — round out the top-five most exposed places in the state.

How many NFIP flood-insurance claims has Michigan filed?

FEMA's National Flood Insurance Program shows 574 claims on file from Michigan, with combined payouts of $12,482,091 across the dataset. 53 of the state's 83 counties have at least one NFIP claim recorded.

Are FEMA flood maps the same as your risk score?

No. The flood risk score on this page is a county-wide composite drawn from claims, disasters, severity, and trend. FEMA Flood Insurance Rate Maps (FIRMs, available at fema.gov/flood-maps) are parcel-level zone designations based on hydrologic modeling. The two answer different questions; serious decisions about insurance or building should use both, plus real-time hydrology from USGS Water Data.

When was the Michigan data last updated?

These figures were refreshed from the OpenFEMA API on 2026-05-16. FEMA itself publishes new NFIP claims on a quarterly cycle, so the data may lag actual events by up to three months.

Flood risk profile for Michigan: 83 counties, 574 NFIP claims, average composite score 9.

this entity is one of the data points covered by this site’s U.S. flood risk, NFIP claims, and disaster declarations dataset. The detail above comes directly from FEMA OpenFEMA datasets including the National Flood Hazard Layer and NFIP claims; the context that follows situates the headline numbers against the broader distribution across U.S. ZIPs, counties, and states.

Every number on this page links back to FEMA OpenFEMA datasets including the National Flood Hazard Layer and NFIP claims; the methodology page describes the inputs, refresh cadence, and known limitations of the underlying data product.

Practical use of this page is in combination with the comparison and ranking pages elsewhere on the site, which surface the same data for this entity’s peers within U.S. ZIPs, counties, and states. A single-entity reading without peer context can be misleading when an entity is an outlier on one axis but typical on another.