Investigating the effect of lab bias on long-term stream chemistry data

Long-term (LT) stream chemistry studies are used to examine changes in and responses to the environment. Much of the data collected over long periods of time goes through changes in instrumentation, methods, and personnel potentially resulting in changing values. A data user must understand these me...

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Main Authors: Cindi L. Brown, Chelcy F. Miniat, Jennifer D. Knoepp
Format: Article
Language:English
Published: IWA Publishing 2021-08-01
Series:Hydrology Research
Subjects:
Online Access:http://hr.iwaponline.com/content/52/4/864
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spelling doaj-b0b61d6e35b34fa7ba15b592d5ddd31f2021-10-06T16:59:15ZengIWA PublishingHydrology Research1998-95632224-79552021-08-0152486487510.2166/nh.2021.164164Investigating the effect of lab bias on long-term stream chemistry dataCindi L. Brown0Chelcy F. Miniat1Jennifer D. Knoepp2 USDA Forest Service, Southern Research Station, Coweeta Hydrologic Lab, 3160 Coweeta Lab Road, Otto, NC 28763, USA USDA Forest Service, Rocky Mountain Research Station, 333 Broadway SE, Suite Albuquerque, NM 87102, USA USDA Forest Service, Southern Research Station, Coweeta Hydrologic Lab, 3160 Coweeta Lab Road, Otto, NC 28763, USA Long-term (LT) stream chemistry studies are used to examine changes in and responses to the environment. Much of the data collected over long periods of time goes through changes in instrumentation, methods, and personnel potentially resulting in changing values. A data user must understand these measures of data quality through quality control (QC) results to know with certainty if trends are real or attributable to other factors. We used the Web of Science database search engine to search for LT stream chemistry studies. For each study, we then determined: record or study length; if QC was reported; and if QC was used. We found that 33% of papers reported QC in the method, and 12% presented the QC in the results. Next, we conducted a case study on 46 years of stream chemistry data to evaluate the data with and without the application of QC protocols from two watersheds (WS) at Coweeta Hydrologic Laboratory; WS 7; clear-cut in 1967–77 and adjacent WS 2 which serves as a reference. We focused on nitrogen and sulfur due to their importance in understanding the forest ecosystem response to disturbance (NO3) and acid deposition (SO4). We determined average annual dissolved inorganic nitrogen (DIN) export (NH4 + NO3 = DIN) using three methods for censoring values below the method detection limit (mdl): (1) the found value, (2) the value of zero, and (3) one-half the mdl value. We found that DIN export for WS 2/WS 7 was (1) 66.9/831.4 (g ha−1 yr−1), (2) 45.4/808.0 (g ha−1 yr−1), and (3) 72.1/823.2 (g ha−1 yr−1) using the three censoring methods, and that the export estimate was significantly different for WS 2 but not for WS 7 (P = 0.001). We found that on average stream NH4 concentrations were below the mdl 58% of the time until an instrument change in 1994 resulted in improved mdls resulting in fewer data points below detection. We found increased bias for stream SO4 concentration following an instrumentation change from segmented flow analysis to ion chromatography. As a result, stream SO4 concentration data that were bias-corrected declined more rapidly in WS 2 compared with non-bias-corrected data, but not in WS 7. We conclude that including QC results with LT data is essential to verify data validity and give the data user a full understanding of the results. HIGHLIGHTS Long-term (LT) stream chemistry studies are used to examine environmental changes, but few studies report QA/QC information.; An analysis of 272 LT stream chemistry papers revealed that only 33% reported QC.; A study of 46 years of stream nitrogen export from Coweeta Hydrologic Laboratory showed that incorporating QA/QC data for values below the detection limit resulted in significantly different export estimates.;http://hr.iwaponline.com/content/52/4/864method detectionnitrogenquality controlsulfateuncertainty
collection DOAJ
language English
format Article
sources DOAJ
author Cindi L. Brown
Chelcy F. Miniat
Jennifer D. Knoepp
spellingShingle Cindi L. Brown
Chelcy F. Miniat
Jennifer D. Knoepp
Investigating the effect of lab bias on long-term stream chemistry data
Hydrology Research
method detection
nitrogen
quality control
sulfate
uncertainty
author_facet Cindi L. Brown
Chelcy F. Miniat
Jennifer D. Knoepp
author_sort Cindi L. Brown
title Investigating the effect of lab bias on long-term stream chemistry data
title_short Investigating the effect of lab bias on long-term stream chemistry data
title_full Investigating the effect of lab bias on long-term stream chemistry data
title_fullStr Investigating the effect of lab bias on long-term stream chemistry data
title_full_unstemmed Investigating the effect of lab bias on long-term stream chemistry data
title_sort investigating the effect of lab bias on long-term stream chemistry data
publisher IWA Publishing
series Hydrology Research
issn 1998-9563
2224-7955
publishDate 2021-08-01
description Long-term (LT) stream chemistry studies are used to examine changes in and responses to the environment. Much of the data collected over long periods of time goes through changes in instrumentation, methods, and personnel potentially resulting in changing values. A data user must understand these measures of data quality through quality control (QC) results to know with certainty if trends are real or attributable to other factors. We used the Web of Science database search engine to search for LT stream chemistry studies. For each study, we then determined: record or study length; if QC was reported; and if QC was used. We found that 33% of papers reported QC in the method, and 12% presented the QC in the results. Next, we conducted a case study on 46 years of stream chemistry data to evaluate the data with and without the application of QC protocols from two watersheds (WS) at Coweeta Hydrologic Laboratory; WS 7; clear-cut in 1967–77 and adjacent WS 2 which serves as a reference. We focused on nitrogen and sulfur due to their importance in understanding the forest ecosystem response to disturbance (NO3) and acid deposition (SO4). We determined average annual dissolved inorganic nitrogen (DIN) export (NH4 + NO3 = DIN) using three methods for censoring values below the method detection limit (mdl): (1) the found value, (2) the value of zero, and (3) one-half the mdl value. We found that DIN export for WS 2/WS 7 was (1) 66.9/831.4 (g ha−1 yr−1), (2) 45.4/808.0 (g ha−1 yr−1), and (3) 72.1/823.2 (g ha−1 yr−1) using the three censoring methods, and that the export estimate was significantly different for WS 2 but not for WS 7 (P = 0.001). We found that on average stream NH4 concentrations were below the mdl 58% of the time until an instrument change in 1994 resulted in improved mdls resulting in fewer data points below detection. We found increased bias for stream SO4 concentration following an instrumentation change from segmented flow analysis to ion chromatography. As a result, stream SO4 concentration data that were bias-corrected declined more rapidly in WS 2 compared with non-bias-corrected data, but not in WS 7. We conclude that including QC results with LT data is essential to verify data validity and give the data user a full understanding of the results. HIGHLIGHTS Long-term (LT) stream chemistry studies are used to examine environmental changes, but few studies report QA/QC information.; An analysis of 272 LT stream chemistry papers revealed that only 33% reported QC.; A study of 46 years of stream nitrogen export from Coweeta Hydrologic Laboratory showed that incorporating QA/QC data for values below the detection limit resulted in significantly different export estimates.;
topic method detection
nitrogen
quality control
sulfate
uncertainty
url http://hr.iwaponline.com/content/52/4/864
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