Data report · 2026

Kansas Water Damage Risk Index

Where in Kansas is a house most likely to take on water? We combined Census housing age with ten years of daily weather for 105 of Kansas's 105 counties to rank them.

Highest index

Washington

Score 67 of 100

Most pipe-freeze nights

Thomas

62 nights ≤ 20°F a year

Oldest housing

Lincoln

69% built before 1960

Most heavy-rain days

Neosho

12.2 days ≥ 1 inch a year

< 4141–4949–5454–58≥ 58 index (0–100)

Key findings

The five highest-scoring counties are Washington, Edwards, Republic, Jewell, Rush. Each combines old housing with harsher-than-average winters or frequent downpours.
Lincoln County has the oldest housing in the state, with 69% of homes built before 1960, against a county median of 48%.
Thomas County averaged 62 nights a year at 20°F or colder, the most of any county in the data. The county median is 39.
Geary County has the newest housing, with 40% 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	Washington	67	46	60%	7.1	54
2	Edwards	65	40	69%	6.9	52
3	Republic	65	44	65%	6.3	51
4	Jewell	64	46	59%	6.8	44
5	Rush	64	46	66%	6.2	46
6	Marshall	63	48	51%	8.7	52
7	Osborne	63	47	62%	5.7	47
8	Lincoln	62	40	69%	5.8	56
9	Rice	62	37	60%	6.9	62
10	Rooks	62	49	64%	4.7	41
11	Chase	61	35	53%	9.5	64
12	Dickinson	61	34	56%	8.3	72
13	Cloud	60	40	58%	6.3	58
14	Decatur	60	60	59%	3.3	24
15	Greenwood	60	28	54%	9.8	72
16	Smith	60	51	56%	5.3	42
17	Stafford	60	39	61%	6.2	57
18	Bourbon	59	23	52%	10.8	79
19	Labette	59	20	53%	11.9	82
20	Elk	58	26	55%	8.8	76
21	Montgomery	58	19	53%	10.2	84
22	Harper	57	26	58%	7.7	78
23	Pawnee	57	41	58%	5.8	50
24	Russell	57	42	56%	5.3	54
25	Barber	56	30	57%	7.1	70
26	Brown	56	43	46%	8.6	55
27	Clark	56	35	68%	4.9	64
28	Comanche	56	34	64%	6	64
29	Graham	56	52	56%	3.5	36
30	Kingman	56	31	55%	7.8	70
31	Lane	56	53	55%	3.5	35
32	Marion	56	34	55%	7.3	69
33	Morris	56	36	50%	8.7	64
34	Neosho	56	23	48%	12.2	79
35	Atchison	55	39	42%	9.7	59
36	Cheyenne	55	57	60%	2.4	14
37	Cowley	55	26	49%	9.9	77
38	Hodgeman	55	44	54%	5.4	51
39	Rawlins	55	59	55%	3.4	17
40	Anderson	54	27	47%	10.2	75
41	Wabaunsee	54	35	47%	9.4	64
42	Woodson	54	25	48%	9.9	78
43	Chautauqua	53	24	50%	9.6	78
44	Clay	53	38	48%	7.8	64
45	Doniphan	53	40	42%	9	57
46	Mitchell	53	44	52%	6.1	50
47	Norton	53	58	52%	3.5	27
48	Allen	52	24	46%	10.9	76
49	Cherokee	52	18	45%	12.1	84
50	Logan	52	57	53%	2.9	26
51	Pratt	52	34	55%	6.4	60
52	Scott	52	57	53%	3	32
53	Wilson	52	22	47%	10.2	83
54	Wyandotte	52	31	47%	8.8	75
55	Barton	51	42	51%	6.1	50
56	Nemaha	51	47	37%	8.5	51
57	Phillips	51	53	49%	3.8	40
58	Sumner	51	26	48%	8.5	85
59	Ellsworth	50	36	51%	6.3	60
60	Gove	50	53	54%	2.7	34
61	Ness	50	47	51%	4.5	45
62	Coffey	49	27	41%	10.2	72
63	Jackson	49	41	32%	9.1	59
64	Crawford	48	21	37%	12.1	80
65	Meade	48	39	52%	5.1	57
66	Wallace	47	56	48%	3.5	16
67	Franklin	46	27	33%	10.3	74
68	Pottawatomie	46	40	27%	8.8	62
69	Harvey	45	32	38%	7.9	74
70	Reno	45	33	47%	6.5	69
71	Saline	45	34	44%	6.7	72
72	Jefferson	44	36	26%	9.1	68
73	Osage	44	28	35%	9.8	72
74	Ottawa	44	36	41%	6.7	64
75	Shawnee	43	35	32%	8.6	68
76	Trego	43	48	46%	3.5	43
77	Wichita	43	58	42%	3.2	22
78	Greeley	42	60	39%	3.3	13
79	Leavenworth	42	33	27%	9.2	71
80	McPherson	42	35	36%	7.1	69
81	Miami	42	28	25%	10.2	74
82	Thomas	42	62	41%	2.8	18
83	Butler	41	30	27%	9.2	74
84	Ford	41	42	35%	6.2	51
85	Geary	41	35	23%	8.9	70
86	Linn	41	25	25%	11	76
87	Lyon	41	32	37%	8.6	64
88	Riley	41	38	21%	8.6	65
89	Sheridan	41	56	40%	3.2	28
90	Sherman	41	59	44%	2.4	13
91	Ellis	40	48	31%	5.7	45
92	Johnson	40	30	14%	9.9	73
93	Kiowa	39	37	37%	6.4	55
94	Sedgwick	39	28	32%	7.5	79
95	Grant	38	50	37%	3.5	36
96	Gray	38	48	30%	5.2	44
97	Douglas	37	31	19%	8.9	71
98	Hamilton	36	56	34%	3	22
99	Finney	35	53	21%	3.8	38
100	Haskell	35	49	26%	4.5	40
101	Stanton	35	49	37%	2.8	28
102	Kearny	33	52	32%	2.9	31
103	Seward	32	42	27%	4.3	49
104	Stevens	30	42	30%	3.6	40
105	Morton	26	38	38%	2.5	30

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