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Title: Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O 2 reduction and denitrification (NO 3 reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF 6, CFCs, 3H, He from 3H (tritiogenic He), 14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO 3 and dissolved gas data to estimate zero order and first order rates of O 2 reductionmore » and denitrification. Results indicated that O 2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O 2 and NO 3 reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O 2 reduction rates. Estimated historical NO 3 trends were similar to historical measurements. Here, results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O 2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.« less
Authors:
 [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [5]
  1. U.S. Geological Survey, Menlo Park, CA (United States)
  2. U.S. Geological Survey, Sacramento, CA (United States)
  3. Univ. of Alabama, Tuscaloosa, AL (United States)
  4. U.S. Geological Survey, East Hartford, CT (United States)
  5. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Report Number(s):
LLNL-JRNL-703499
Journal ID: ISSN 0022-1694
Grant/Contract Number:
AC52-07NA27344
Type:
Accepted Manuscript
Journal Name:
Journal of Hydrology
Additional Journal Information:
Journal Volume: 543; Journal Issue: PA; Journal ID: ISSN 0022-1694
Publisher:
Elsevier
Research Org:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org:
USDOE; National Research Program (NRP); National Water-Quality Assessment (NAWQA) program; USGS; National Science Foundation (NSF)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; Oxygen reduction; Denitrification; Groundwater; Residence time; Multi-model analysis; Regional water quality
OSTI Identifier:
1368022

Green, Christopher T., Jurgens, Bryant C., Zhang, Yong, Starn, J. Jeffrey, Singleton, Michael J., and Esser, Bradley K.. Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA. United States: N. p., Web. doi:10.1016/j.jhydrol.2016.05.018.
Green, Christopher T., Jurgens, Bryant C., Zhang, Yong, Starn, J. Jeffrey, Singleton, Michael J., & Esser, Bradley K.. Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA. United States. doi:10.1016/j.jhydrol.2016.05.018.
Green, Christopher T., Jurgens, Bryant C., Zhang, Yong, Starn, J. Jeffrey, Singleton, Michael J., and Esser, Bradley K.. 2016. "Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA". United States. doi:10.1016/j.jhydrol.2016.05.018. https://www.osti.gov/servlets/purl/1368022.
@article{osti_1368022,
title = {Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA},
author = {Green, Christopher T. and Jurgens, Bryant C. and Zhang, Yong and Starn, J. Jeffrey and Singleton, Michael J. and Esser, Bradley K.},
abstractNote = {Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O2 reduction and denitrification (NO3– reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF6, CFCs, 3H, He from 3H (tritiogenic He), 14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO3– and dissolved gas data to estimate zero order and first order rates of O2 reduction and denitrification. Results indicated that O2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O2 and NO3– reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O2 reduction rates. Estimated historical NO3– trends were similar to historical measurements. Here, results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.},
doi = {10.1016/j.jhydrol.2016.05.018},
journal = {Journal of Hydrology},
number = PA,
volume = 543,
place = {United States},
year = {2016},
month = {5}
}