Mississippi Dams

6,089 dams tracked by the National Inventory of Dams

Total Dams

6,089

High Hazard

348

5.7%

Poor / Unsatisfactory

273

Average Age

48 yrs

Hazard Classification

High348 (5.7%)
Significant66 (1.1%)
Low4,510 (74.1%)

Condition Assessment

Satisfactory194 (3.2%)
Fair180 (3.0%)
Poor / Unsatisfactory273 (4.5%)
Not Rated5,442 (89.4%)

Federal

48

State

62

Local

649

Private

5,311

All Dams in Mississippi

Showing 4476–4500 of 4,510

Dam NameHeight (ft)YearHazardCondition
Alcorn College Lake Dam

Claiborne County

44—LowNot Rated
Albritton Lake Dam

Pearl River County

331995LowNot Rated
Albert Prevost Pond

Washington County

81970LowNot Rated
Albert Prevost Catfish Pond

Washington County

81970LowNot Rated
Albert Jones Pond Dam

Lauderdale County

12—LowNot Rated
Albert Harris Pond Dam

Copiah County

18—LowNot Rated
Albert Etheridge Lake Dam

Lee County

20—LowNot Rated
Alberta Hills Lake Dam

Claiborne County

25—LowNot Rated
Ainsworth Number 2 Dam

Simpson County

171993LowNot Rated
A Hoda Lake Dam

Hancock County

13—LowNot Rated
A G Taylor Estate Pond Dam

Panola County

20—LowNot Rated
A G Mcinturff Lake Dam

Lamar County

24—LowNot Rated
A G Doss Lake Dam

Monroe County

18—LowNot Rated
A E Britt Pond Dam

Sunflower County

8—LowNot Rated
Addison Dam

Hancock County

101999LowNot Rated
Adams Lake Dam

Hinds County

20—LowNot Rated
Adams Egg Farm Lake Dam

Hinds County

12—LowNot Rated
Adams Egg Farm Lagoon Dam

Simpson County

16—LowNot Rated
Actman Catfish Pond Dam

Tallahatchie County

8—LowNot Rated
Abotlapoota WS Str Y-34-16 Dam

Carroll County

231973LowNot Rated
Abotlapoota WS Str Y-34-15 Dam

Carroll County

301973LowUnsatisfactory
Abotlapoota Watershed Structure Y-34-14 Dam

Carroll County

321970LowNot Rated
A B Mansell Lake Dam

Madison County

10—LowNot Rated
Abiaca Watershed Structure Y-34-45 Dam

Carroll County

281973LowNot Rated
Abiaca Watershed Structure Y-34-43 Dam

Carroll County

191972LowNot Rated
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Data sourced from the National Inventory of Dams (NID). Hazard classification reflects potential consequences of failure, not the likelihood of failure.