Forecasting Groundwater Remediation Timeframes: Site‐Specific Temporal Monitoring Results May Not Predict Future Performance
Year: 2023
Type: article
Abstract: At contaminated sites, groundwater monitoring results are commonly used (quantitatively or qualitatively) to predict remediation timeframes. If results are predictive, then there should be a strong positive correlation between attenuation rates for the first half of a temporal monitoring record and attenuation rates for the second half of the same record. We utilized the GeoTracker database to evaluate the power of historical groundwater monitoring results to predict future attenuation rates. For two data sets (petroleum and chlorinated solvent), we found a small negative correlation between the first‐order concentration vs. time attenuation rate observed during the earlier part of the monitoring record and the later part of the monitoring record: benzene—correlation coefficient (r) = −0.11, methyl tert‐butyl ether (MTBE)—r = −0.12, trichloroethene (TCE) = −0.12. For each data set, a small negative correlation between the first‐order attenuation rate observed during the earlier part of the monitoring record and the later part of the monitoring record was also observed for a subset of monitoring records exhibiting the best model fits (R 2 > 0.8), a subset with a statistically significant (p < 0.05) positive attenuation rate for the first half of the monitoring record. For the TCE data set, this negative correlation was also observed for a subset of monitoring records with no change in site remedy during the monitoring period (r = −0.22). Our analysis suggests that the historical concentration vs. time attenuation rate for a contaminant at an individual site or monitoring well is a poor predictor of the future rate.
DOI: 10.1111/gwmr.12609
Institutions: GSI Environmental (United States), Shell (United States)
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,550
Award: G1071967776
OpenAlex ID: W4385065601
