Historical analysis of U.S. onshore hazardous liquid pipeline accidents triggered by natural hazards

Incidents at U.S. onshore hazardous liquid pipeline systems were analyzed with an emphasis on natural hazards. Incidents triggered by natural hazards (natechs) were identified by keyword-based data mining and expert review supplemented by various data sources. The analysis covered about 7000 incidents in 1986-2012, 3800 of which were regarded as significant based on their consequences. 5.5% of all and 6.2% of the significant incidents were found to be natechs that resulted in a total hazardous substance release of 317,700 bbl. Although there is no trend in the long-term yearly occurrence of significant natechs, importance is found to be increasing due to the overall decreasing trend of the incidents. Meteorological hazards triggered 36% of the significant natechs, followed by geological and climatic hazards with 26% and 24%. While they occurred less frequently, hydrological hazards caused the highest amount of release which is about 102,000 bbl. The total economic cost of significant natechs was 597 million USD, corresponding to about 18% of all incident costs in the same period. More than 50% of this cost was due to meteorological hazards, mainly tropical cyclones. Natech vulnerabilities of the system parts vary notably with respect to natural hazard types. For some natural hazards damage is limited possibly due to implemented protection measures. The geographical distribution of the natechs indicated that they occurred more in some states, such as Texas, Oklahoma, and Louisiana. About 50% of the releases was to the ground, followed by water bodies with 28%. Significant consequences to human health were not observed although more than 20% of the incidents resulted in fires. In general, the study indicated that natural hazards are a non-negligible threat to the onshore hazardous liquid pipeline network in the U.S. It also highlighted problems such as underreporting of natural hazards as incident causes, data completeness, and explicit data limitations.