Data report · 2026

Ohio Water Damage Risk Index

Where in Ohio is a house most likely to take on water? We combined Census housing age with ten years of daily weather for 88 of Ohio's 88 counties to rank them.

Highest index

Clark

Score 76 of 100

Most pipe-freeze nights

Morrow

38 nights ≤ 20°F a year

Oldest housing

Cuyahoga

56% built before 1960

Most heavy-rain days

Clermont

9.6 days ≥ 1 inch a year

< 3838–4747–5353–61≥ 61 index (0–100)

Key findings

The five highest-scoring counties are Clark, Darke, Auglaize, Champaign, Allen. Each combines old housing with harsher-than-average winters or frequent downpours.
Cuyahoga County has the oldest housing in the state, with 56% of homes built before 1960, against a county median of 37%.
Morrow County averaged 38 nights a year at 20°F or colder, the most of any county in the data. The county median is 31.
Delaware County has the newest housing, with 51% of homes built since 2000, which pulls its index down even where winters are cold.

Weather: NOAA nClimGrid-Daily county averages, 2015–2024. Housing: ACS 2020-2024.

All counties

Select a column header to sort.

Rank	County	Index	Freeze nights	Pre-1960 homes	Heavy-rain days	Muggy nights
1	Clark	76	32	45%	7.5	41
2	Darke	75	33	47%	6.9	36
3	Auglaize	73	35	44%	6.3	35
4	Champaign	71	35	43%	6.8	33
5	Allen	70	33	43%	6	41
6	Van Wert	67	34	50%	5	36
7	Trumbull	66	37	44%	5.8	18
8	Crawford	65	36	52%	4.2	30
9	Hamilton	65	24	46%	8	55
10	Preble	65	32	39%	7.3	35
11	Williams	64	37	43%	5.5	26
12	Logan	62	36	38%	5.6	33
13	Miami	62	30	36%	7.2	45
14	Richland	62	38	43%	5.2	24
15	Shelby	62	35	34%	6.6	35
16	Ashland	61	37	43%	5.4	24
17	Cuyahoga	61	30	56%	4.7	42
18	Henry	61	33	46%	4.7	37
19	Knox	61	36	38%	6.1	21
20	Ashtabula	60	36	48%	4.3	23
21	Mahoning	60	36	46%	4.7	19
22	Columbiana	59	34	46%	5.7	18
23	Mercer	59	35	36%	5.9	33
24	Belmont	58	30	46%	6.5	28
25	Defiance	58	35	41%	5.3	32
26	Seneca	57	33	51%	3.6	34
27	Harrison	56	31	48%	5.6	27
28	Marion	56	33	46%	3.4	37
29	Scioto	56	25	42%	7.1	42
30	Wyandot	56	31	49%	3.7	40
31	Fayette	55	30	37%	6.1	38
32	Montgomery	55	28	40%	6	49
33	Coshocton	54	32	42%	5.7	30
34	Hardin	54	33	41%	4.2	40
35	Jefferson	54	30	53%	5.5	26
36	Fulton	53	35	39%	4.9	29
37	Paulding	53	34	34%	5.6	34
38	Sandusky	53	30	50%	3.4	41
39	Clinton	52	28	34%	7.2	40
40	Lucas	52	29	47%	3.8	44
41	Putnam	52	33	37%	4.4	41
42	Highland	51	29	32%	9.2	35
43	Ross	51	26	34%	7.4	42
44	Madison	50	31	32%	6	39
45	Huron	49	34	41%	3.9	31
46	Morrow	49	38	28%	5.6	26
47	Summit	49	31	43%	4	38
48	Perry	48	29	35%	6.8	31
49	Stark	48	32	43%	4.1	31
50	Tuscarawas	48	32	41%	4.7	31
51	Butler	47	28	26%	7.3	47
52	Monroe	47	29	33%	7.9	29
53	Muskingum	47	28	37%	6.3	35
54	Adams	45	27	29%	9.1	37
55	Geauga	45	37	29%	5.3	23
56	Hancock	45	31	37%	3.5	43
57	Greene	44	28	28%	6.4	46
58	Guernsey	44	31	38%	5.1	31
59	Pike	44	25	29%	8.5	41
60	Washington	44	23	35%	6.9	38
61	Brown	43	28	26%	9.2	35
62	Carroll	42	33	35%	4.8	26
63	Erie	41	28	41%	3.4	48
64	Union	41	34	21%	5.1	37
65	Clermont	40	24	19%	9.6	46
66	Franklin	40	29	25%	5.9	45
67	Lawrence	40	23	31%	6.7	46
68	Warren	40	25	14%	7.6	50
69	Wayne	40	35	31%	4.2	27
70	Jackson	39	26	31%	6.9	35
71	Delaware	38	32	10%	5.6	37
72	Holmes	38	35	25%	5.3	25
73	Lake	38	30	32%	4.6	38
74	Licking	38	32	26%	5.8	28
75	Lorain	38	31	33%	4	37
76	Athens	37	25	33%	6.8	32
77	Morgan	37	27	34%	6	32
78	Noble	36	29	31%	5.9	30
79	Portage	36	35	26%	4.6	24
80	Meigs	35	26	32%	6.6	30
81	Hocking	34	28	26%	6.3	33
82	Ottawa	34	28	34%	2.9	48
83	Pickaway	34	26	29%	5.5	44
84	Fairfield	33	28	25%	5.9	37
85	Gallia	33	25	21%	7	37
86	Medina	31	34	20%	3.7	33
87	Vinton	30	26	24%	6.8	31
88	Wood	29	29	26%	3.4	44

Methodology

For each county with weather data, we convert four factors to a percentile rank among those counties (0 = lowest, 100 = highest), then take a weighted average:

Pipe-freeze nights (nights ≤ 20°F / yr), weight 30%
Homes built before 1960 (% of homes), weight 30%
Heavy-rain days (days ≥ 1 in / yr), weight 25%
Muggy nights (nights ≥ 65°F / yr), weight 15%

Freezing weather and old plumbing get the most weight because burst and failing supply lines are among the most common causes of household water damage. Heavy rain drives basement flooding and sewer backups, and warm, muggy nights mark the humid air that lets mold follow. The index is relative: a low score means lower risk than other Ohio counties, not no risk.

Limits: weather values are county-wide averages, so hollows, ridges and lakeshores can differ; ACS housing figures are survey estimates; the index doesn't account for floodplains, soil, or local sewer systems. Full details on our data sources page.

Cite this data

You're welcome to use these figures with attribution. Suggested citation:

Local Water & Mold, "Ohio Water Damage Risk Index 2026," https://localwatermold.com/ohio/ohio-water-damage-risk/. Data: U.S. Census Bureau ACS 2020-2024; NOAA nClimGrid-Daily 2015–2024.