Out of 417 ZIP codes with infrastructure data in South Carolina, these areas face the highest estimated risk of water pipe failure based on infrastructure age, funding gaps, and violation history.
| Statistic | Value |
|---|---|
| ZIP codes ranked | 417 |
| Highest risk | NaN% |
| Median risk | NaN% |
| Average risk | NaN% |
| State | South Carolina |
Top 100 Highest Risk ZIP Codes
| Rank | ZIP Code | City | State | Pipe Failure Risk | Risk Level | Safety Score |
|---|---|---|---|---|---|---|
| 1 | 29001 | Alcolu | SC | NaN% | Unknown | — |
| 2 | 29003 | Bamberg | SC | NaN% | Unknown | — |
| 3 | 29006 | Batesburg | SC | NaN% | Unknown | — |
| 4 | 29009 | Bethune | SC | NaN% | Unknown | — |
| 5 | 29010 | Bishopville | SC | NaN% | Unknown | — |
| 6 | 29014 | Blackstock | SC | NaN% | Unknown | — |
| 7 | 29015 | Blair | SC | NaN% | Unknown | — |
| 8 | 29016 | Blythewood | SC | NaN% | Unknown | 82/100 |
| 9 | 29018 | Bowman | SC | NaN% | Unknown | — |
| 10 | 29020 | Camden | SC | NaN% | Unknown | — |
| 11 | 29030 | Cameron | SC | NaN% | Unknown | — |
| 12 | 29031 | Carlisle | SC | NaN% | Unknown | — |
| 13 | 29032 | Cassatt | SC | NaN% | Unknown | — |
| 14 | 29033 | Cayce | SC | NaN% | Unknown | — |
| 15 | 29036 | Chapin | SC | NaN% | Unknown | 79/100 |
| 16 | 29037 | Chappells | SC | NaN% | Unknown | — |
| 17 | 29038 | Cope | SC | NaN% | Unknown | — |
| 18 | 29039 | Cordova | SC | NaN% | Unknown | — |
| 19 | 29040 | Dalzell | SC | NaN% | Unknown | — |
| 20 | 29042 | Denmark | SC | NaN% | Unknown | — |
| 21 | 29044 | Eastover | SC | NaN% | Unknown | — |
| 22 | 29045 | Elgin | SC | NaN% | Unknown | — |
| 23 | 29046 | Elliott | SC | NaN% | Unknown | — |
| 24 | 29047 | Elloree | SC | NaN% | Unknown | — |
| 25 | 29048 | Eutawville | SC | NaN% | Unknown | — |
| 26 | 29051 | Gable | SC | NaN% | Unknown | — |
| 27 | 29052 | Gadsden | SC | NaN% | Unknown | — |
| 28 | 29053 | Gaston | SC | NaN% | Unknown | — |
| 29 | 29054 | Gilbert | SC | NaN% | Unknown | — |
| 30 | 29055 | Great Falls | SC | NaN% | Unknown | — |
| 31 | 29056 | Greeleyville | SC | NaN% | Unknown | — |
| 32 | 29058 | Heath Springs | SC | NaN% | Unknown | — |
| 33 | 29059 | Holly Hill | SC | NaN% | Unknown | — |
| 34 | 29061 | Hopkins | SC | NaN% | Unknown | 72/100 |
| 35 | 29062 | Horatio | SC | NaN% | Unknown | — |
| 36 | 29063 | Irmo | SC | NaN% | Unknown | 81/100 |
| 37 | 29065 | Jenkinsville | SC | NaN% | Unknown | — |
| 38 | 29067 | Kershaw | SC | NaN% | Unknown | — |
| 39 | 29069 | Lamar | SC | NaN% | Unknown | 100/100 |
| 40 | 29070 | Leesville | SC | NaN% | Unknown | — |
| 41 | 29072 | Lexington | SC | NaN% | Unknown | — |
| 42 | 29073 | Lexington | SC | NaN% | Unknown | — |
| 43 | 29074 | Liberty Hill | SC | NaN% | Unknown | — |
| 44 | 29075 | Little Mountain | SC | NaN% | Unknown | — |
| 45 | 29078 | Lugoff | SC | NaN% | Unknown | — |
| 46 | 29079 | Lydia | SC | NaN% | Unknown | — |
| 47 | 29080 | Lynchburg | SC | NaN% | Unknown | — |
| 48 | 29081 | Ehrhardt | SC | NaN% | Unknown | — |
| 49 | 29082 | Lodge | SC | NaN% | Unknown | — |
| 50 | 29101 | Mc Bee | SC | NaN% | Unknown | 100/100 |
| 51 | 29102 | Manning | SC | NaN% | Unknown | — |
| 52 | 29104 | Mayesville | SC | NaN% | Unknown | — |
| 53 | 29105 | Monetta | SC | NaN% | Unknown | — |
| 54 | 29107 | Neeses | SC | NaN% | Unknown | — |
| 55 | 29108 | Newberry | SC | NaN% | Unknown | — |
| 56 | 29111 | New Zion | SC | NaN% | Unknown | — |
| 57 | 29112 | North | SC | NaN% | Unknown | — |
| 58 | 29113 | Norway | SC | NaN% | Unknown | — |
| 59 | 29114 | Olanta | SC | NaN% | Unknown | — |
| 60 | 29115 | Orangeburg | SC | NaN% | Unknown | — |
| 61 | 29118 | Orangeburg | SC | NaN% | Unknown | — |
| 62 | 29122 | Peak | SC | NaN% | Unknown | — |
| 63 | 29123 | Pelion | SC | NaN% | Unknown | — |
| 64 | 29125 | Pinewood | SC | NaN% | Unknown | — |
| 65 | 29126 | Pomaria | SC | NaN% | Unknown | — |
| 66 | 29127 | Prosperity | SC | NaN% | Unknown | — |
| 67 | 29128 | Rembert | SC | NaN% | Unknown | — |
| 68 | 29129 | Ridge Spring | SC | NaN% | Unknown | — |
| 69 | 29130 | Ridgeway | SC | NaN% | Unknown | — |
| 70 | 29133 | Rowesville | SC | NaN% | Unknown | — |
| 71 | 29135 | Saint Matthews | SC | NaN% | Unknown | — |
| 72 | 29137 | Salley | SC | NaN% | Unknown | — |
| 73 | 29138 | Saluda | SC | NaN% | Unknown | — |
| 74 | 29142 | Santee | SC | NaN% | Unknown | — |
| 75 | 29145 | Silverstreet | SC | NaN% | Unknown | — |
| 76 | 29146 | Springfield | SC | NaN% | Unknown | — |
| 77 | 29148 | Summerton | SC | NaN% | Unknown | — |
| 78 | 29150 | Sumter | SC | NaN% | Unknown | — |
| 79 | 29152 | Shaw A F B | SC | NaN% | Unknown | — |
| 80 | 29153 | Sumter | SC | NaN% | Unknown | — |
| 81 | 29154 | Sumter | SC | NaN% | Unknown | — |
| 82 | 29160 | Swansea | SC | NaN% | Unknown | — |
| 83 | 29161 | Timmonsville | SC | NaN% | Unknown | 83/100 |
| 84 | 29162 | Turbeville | SC | NaN% | Unknown | — |
| 85 | 29163 | Vance | SC | NaN% | Unknown | — |
| 86 | 29164 | Wagener | SC | NaN% | Unknown | — |
| 87 | 29166 | Ward | SC | NaN% | Unknown | — |
| 88 | 29168 | Wedgefield | SC | NaN% | Unknown | — |
| 89 | 29169 | West Columbia | SC | NaN% | Unknown | — |
| 90 | 29170 | West Columbia | SC | NaN% | Unknown | — |
| 91 | 29172 | West Columbia | SC | NaN% | Unknown | — |
| 92 | 29175 | Westville | SC | NaN% | Unknown | — |
| 93 | 29177 | White Rock | SC | NaN% | Unknown | — |
| 94 | 29178 | Whitmire | SC | NaN% | Unknown | — |
| 95 | 29180 | Winnsboro | SC | NaN% | Unknown | — |
| 96 | 29201 | Columbia | SC | NaN% | Unknown | 82/100 |
| 97 | 29203 | Columbia | SC | NaN% | Unknown | 81/100 |
| 98 | 29204 | Columbia | SC | NaN% | Unknown | 82/100 |
| 99 | 29205 | Columbia | SC | NaN% | Unknown | 82/100 |
| 100 | 29206 | Columbia | SC | NaN% | Unknown | 81/100 |
Methodology
Infrastructure risk rankings combine four data sources, each weighted equally (25%): (1) EPA Drinking Water Infrastructure Needs Survey (DWINS 2023) — state-level 20-year funding gap per capita for pipe replacement, treatment, and storage; (2) Census ACS housing vintage — percentage of homes built before 1980, when lead solder and galvanized pipes were common; (3) EPA SDWIS violation and enforcement data — system-level compliance history; (4) Lead and Copper Rule indicators — service line material inventories and 90th percentile lead testing results. The combined score is normalized to a 0-100% probability scale.
Data sources: EPA DWINS 2023, Census ACS, EPA SDWIS, Lead and Copper Rule data. Last updated: 2026-08-31.
Frequently Asked Questions
What does pipe failure probability mean?
Pipe failure probability estimates the likelihood of water main breaks, lead contamination from corroded pipes, or service disruptions based on infrastructure age, state funding gaps, violation history, and lead indicators. It is not a prediction of imminent failure, but a risk assessment based on known factors.
How is infrastructure risk calculated?
The risk score combines four equally weighted factors: state-level infrastructure funding gap per capita (from EPA DWINS 2023), housing vintage (Census ACS pre-1980 housing percentage), water system violation and enforcement history (EPA SDWIS), and lead exposure indicators (service line probability and testing results).
What can homeowners do about aging infrastructure?
Test your tap water annually, especially for lead. Check if your home has a lead service line through your water utility. Consider a whole-house water filter (NSF/ANSI 53 certified). Review your water system Consumer Confidence Report for violation history.
Does high risk mean my water is unsafe right now?
Not necessarily. Infrastructure risk indicates long-term vulnerability, not current contamination. However, areas with aging pipes and high violation counts have a statistically higher chance of water quality issues. Regular testing is the best way to verify your water safety.