US Long-Term Ecological Research Network

North Temperate Lakes LTER Regional Survey Water Color Scans 2015 - current

Abstract
The Northern Highlands Lake District (NHLD) is one of the few regions in the world with periodic comprehensive water chemistry data from hundreds of lakes spanning almost a century. Birge and Juday directed the first comprehensive assessment of water chemistry in the NHLD, sampling more than 600 lakes in the 1920s and 30s. These surveys have been repeated by various agencies and we now have data from the 1920s (UW), 1960s (WDNR), 1970s (EPA), 1980s (EPA), 1990s (EPA), and 2000s (NTL). The 28 lakes sampled as part of the Regional Lake Survey have been sampled by at least four of these regional surveys including the 1920s Birge and Juday sampling efforts. These 28 lakes were selected to represent a gradient of landscape position and shoreline development, both of which are important factors influencing social and ecological dynamics of lakes in the NHLD. This long-term regional dataset will lead to a greater understanding of whether and how large-scale drivers such as climate change and variability, lakeshore residential development, introductions of invasive species, or forest management have altered regional water chemistry. Color is measured in water samples that are filtered in the field through 0.45 um nucleopore membrane filters. A spectrophotometer is used to quantify color in the lab as absorbance (unitless) at 1 nm intervals between the wavelengths of 200 and 800 nm. Absorbance data are considered suspect for values greater than 2.
Dataset ID
377
Date Range
-
LTER Keywords
Methods
We collect water samples for color at the deepest part of the lakes. The samples are surface water, filtered in the field through 0.45u polycarbonate membrane filters. We run a wavelength scan from 800 to 200nm, using a 5cm rectangular quartz cell in a Beckman Coulter Model DU800 spectrophotometer. Any samples that display absorbance values above 2AU are run again from 400 to 200nm using a 1cm quartz cuvette. Inititally the full range of wavelengths were run again and two values may be found in the database even if the original measurement with the large cuvette did not exceed 2AU. The user should discard values above 2AU and use values from the smaller cuvette instead. All values are given as measurements at the path lenth of the employed cuvette and need to be devided by the cuvette length for a comparable value at a pathlength of 1 cm.

The single beam Beckman Coulter DU800 spec is blanked first on a sample of DI water. Additional blank values are from a scan run on DI after that blanking as a check and are reported alongside the scans but are not subtracted from the scan values.
Version Number
3

Cascade Project at North Temperate Lakes LTER Core Data Carbon 1984 - 2016

Abstract
Data on dissolved organic and inorganic carbon, particulate organic matter, partial pressure of CO2 and absorbance at 440nm. Samples were collected with a Van Dorn sampler. Organic carbon and absorbance samples were collected from the epilimnion, metalimnion, and hypolimnion. Inorganic samples were collected at depths corresponding to 100%, 50%, 25%, 10%, 5%, and 1% of surface irradiance, as well as one sample from the hypolimnion. Samples for the partial pressure of CO2 were collected from two meters above the lake surface (air) and just below the lake surface (water). Sampling frequency: varies; number of sites: 14
Core Areas
Dataset ID
350
Date Range
-
Methods
Detailed field and laboratory protocols can be found in the Cascade Methods Manual, found here: https://cascade.limnology.wisc.edu/public/public_files/methods/CascadeManual1998.pdf
POC, PON and DOC: 1. 100 - 300 ml (Typically ~200mL for PML, 150 metalimnion and 75 – 100 for the hypolimnion) of lake water from each depth was filtered through 153 um mesh to remove large zooplankton. Water was then filtered through a precombusted 25mm GF/F filter (0.7 um pore size) at less than 200 mm Hg pressure. Filters were placed in drying oven at 60 C to dry for at least 48 hours. 20mL of filtered water was stored in a scintillation vial and acidified with 200uL of 2N H2SO4 for DOC analysis. Blank samples for POC and DOC were prepared with deionized water to control for contamination. All samples were sent to the Cary Institute of Ecosystem Studies for analysis.

Version Number
24

Long-term trends and synchrony in dissolved organic matter characteristics in Wisconsin, USA lakes: quality, not quantity, is highly sensitive to climate

Abstract
Dissolved organic matter (DOM) is a fundamental driver of many lake processes. In the past several decades, many lakes have exhibited a substantial increase in DOM quantity, measured as dissolved organic carbon (DOC) concentration. While increasing DOC is now widely recognized, fewer studies have sought to understand how characteristics of DOM (DOM quality) change over time. Quality can be measured in several ways, including the optical characteristics spectral slope (S275-295), spectral ratio (SR), absorbance at 254 nm (a254), and DOC-specific absorbance (SUVA; a254:DOC). However, long-term measurements of quality are not nearly as common as long-term measurements of DOC concentration. We used 24 years of DOC and absorbance data for seven lakes in the North Temperate Lakes Long Term Ecological Research site in northern Wisconsin, USA to examine temporal trends and synchrony in both DOC concentration and quality. We predicted lower SR and S275-295 and higher a254 and SUVA trends, consistent with increasing DOC and greater allochthony. DOC concentration exhibited both significant positive and negative trends among lakes. In contrast, DOC quality exhibited trends suggesting reduced allochthony or increased degradation, with significant long-term increases in SR in three lakes. Patterns and synchrony of DOM quality parameters suggest they are more responsive to climatic variations than DOC concentration. SUVA in particular tended to increase with greater moisture and decrease with drier conditions. These results demonstrate that DOC quantity and quality can exhibit different complex long-term trends and responses to climate components, with important implications for aquatic ecosystems.
Contact
Core Areas
Dataset ID
329
Date Range
-
Methods
Data contained within is derived from data publicly available through the North Temperature Lakes Long Term Ecological Research (NTL-LTER) website at the following url: https://lter.limnology.wisc.edu/. All data is for the upper meter of the water column, collected in the deepest point of the lake. For DOC concentration data and ancillary data such as pH, iron, and total N, please see the NTL-LTER website.
The file dat.w.blank.fin 7_29_16.csv contains the absorbance scans that were used to calculate the spectral metrics (NTL LTER 2012). Samples for absorbance scans were collected approximately quarterly. Absorbance scans were run on a spectrophotometer over the wavelengths from 200-800 nm. In this file, the column value is the raw value for absorbance read directly off the instrument for the corresponding wavelength. The column blank.value is the value of the DI blank taken nearest in time for the corresponding wavelength and cuvette width. The column cor.value is the blank.value column subtracted from the value column. The cor.value column was used in all subsequent analyses and calculations.
The file metrics for_analysis.csv contains the spectral metrics calculated from the absorbance scans as well as select meteorological metrics. ab.254 is raw absorbance measured by the instrument (after correcting for DI blanks), corrected for a 1 m pathlength. lin.slope.275.295 is the slope for the log transformed absorbance scan over the wavelengths 275-295 nm, determined by linear regression. nlin.slope.275.295 is the spectral slope (S275-295) over the wavelengths 275-295 nm, calculated using non-linear regression in R version 3.2.3 (R Core Team 2015), fitting the following equation:
alambda = alambdarefe-S(lambda-lambdaref)
In this equation a is the Naperian absorption coefficient (see below), lambda is the wavelength, lambdaref is the reference wavelength, and S is the spectral slope (nm-1) (Twardowski et al. 2004; Helms et al. 2008). The initial estimate supplied to the non-linear regression procedure was supplied by the value for lin.slope.275.295. lin.slope.350.400 and nlin.slope.350.400 were calculated in a similar fashion, but over the wavelengths 350-400 nm. This calculation yields the spectral slope over the wavelengths 350-400 nm (S350-400). slope.ratio is the slope ratio (SR), the ratio of S275-295 to S350-400 (Helms et al. 2008). ab.254.1cm is similar to ab.254, but is corrected for a 1 cm cuvette width. a254.nap is the Naperian absorption coefficient and is calculated from the equation:
a = 2.303A/l
In this equation, a is the Naperian absorption coefficient, A is raw absorbance measured by the spectrophotomer, and l is the path length (Green and Blough 1994). SUVA was calculated by dividing raw absorbance at 254 nm by the DOC concentration of the DOC sample collected nearest in time to the absorbance sample. SUVA is reported as Ltimesmg C-1timesm-1 (Weishaar et al. 2003).
wk.prcp, mth.prcp, and ninety prcp are precipitation totals for the 7, 30, and 90 days up to and including the sampling date (mm). These data come from the Minocqua, WI station in the Global Historical Climatology Network (GHCN) dataset (available at https://www.ncdc.noaa.gov/data-access/quick-links#ghcn) (Menne et al. 2010).
wk.tmp, mth.tmp, and ninety.tmp are mean values for the mid-daily temperature in the 7, 30, and 90 days up to and including the sampling date (°C). These are from the same data source as the precipitation data.
The l.lev column contains lake level from the NTL LTER website in meters above sea level. wk.insol, mth.insol, and ninety.insol are mean solar insolation incident on a horizontal surface in the 7, 30, and 90 days up to and including the sampling date (kWh/m2/day) (these data were obtained from the NASA Langley Research Center Atmospheric Sciences Data Center NASA/GEWEX SRB Project).
Monthly Palmer Drought Severity Index (PDSI) data corresponding to the study period can be accessed at: ftp://ftp.ncdc.noaa.gov/pub/data/cirs/climdiv/ using StateCode=47 and Division=2. These data were retrieved from the US National Oceanic and Atmospheric Administration (NOAA) National Center for Environmental Information (NCEI). These data were used to relate trends and synchrony in spectral metrics to moisture conditions.
The DOC column contains DOC concentration (mg L-1) for the corresponding sample date, obtained from the NTL LTER website.

Short Name
DOM trends data
Version Number
19

LAGOS - Chlorophyll, TP, and water color summer epilimnetic concentrations and lake and catchment data for inland lakes in WI, MI, NY, and ME – a subset of lake data from LAGOSLimno v.1.040.1

Abstract
This dataset includes lake total phosphorus (TP), true water color, and chlorophyll a (CHLa) concentrations from summer, epilimnetic water samples and is a subset of the larger LAGOS database (Lake multi-scaled geospatial and temporal database, described in Soranno et al. 2015). LAGOS compiles multiple, individual lake water chemistry datasets into an integrated database. We accessed LAGOSLIMNO version 1.040.0 for lake water chemistry data and LAGOSGEO version 1.02 for lake catchment geographic data. In the LAGOSLIMNO database, lake water chemistry data were collected from individual state agency sampling and volunteer programs designed to monitor lake water quality. Water chemistry analyses follow standard lab methods. In the LAGOSGEO database geographic data were collected from national scale geographic information systems (GIS) data layers. Lake catchments, defined as 'The area of land that drains directly into a lake, and into all upstream-connected, permanent streams to that lake exclusive of any upstream lake watersheds for lakes greater than or equal to 10 ha that are connected via permanent streams', were delineated for lakes greater than or equal to 4 ha. Lake-stream connectivity type was assigned to lakes greater than or equal to 4 ha using GIS tools that use the National Hydrology Dataset (See Soranno et al. 2015 for LAGOS geographic processing steps).
A subset of lake and geographic data was created to examine spatial variation in TP and water color relationships with CHLa across broad geographic extents using spatially-varying coefficient models with a Bayesian framework. Lakes were selected that had complete records for summer epilimnetic total TP, true water color, and CHLa. In addition we selected lakes with surface area greater than or equal to 4 ha and less than 10,000 ha to exclude very small and very large lakes from the analyses. The resulting dataset includes 838 lakes in Wisconsin, Michigan, New York, and Maine with 7395 observations. The majority of lakes in the data subset have only one water chemistry observation (~72% of lakes). There are 228 lakes with more than one water chemistry observation taken on different sampling occasions over time (average of 29 observations per lake with repeated measures). The dataset reports the original, individual measurements. The proportion of agriculture and wetlands in the lake catchment were derived from land cover and land use data in the National Land Cover Dataset (2006). For the analyses we withheld ten percent of the observations for model validation and to assess prediction accuracy. The remaining observations were used in the model building steps. The 'dataset' column in the data indicates whether the observation belongs to the model-building ('mb') or hold-out dataset ('h').
Dataset ID
325
Data Sources
Date Range
-
Methods
Limnological water chemistry samples were collected through individual monitoring programs carried out or overseen by state agencies. Water chemistry analyses were performed using standard methods by individual labs. Methods for integrating the disparate state datasets are described in detail in Soranno et al. 2015 Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse, GigaScience20154:28 DOI: 10.1186/s13742-015-0067-4
NTL Keyword
Version Number
14

Fluxes project at North Temperate Lakes LTER: Random lake survey 2004

Abstract
The overarching goal of this project is to understand carbon and nutrient cycles for a landscape on which terrestrial and freshwater systems are intimately connected in multiple and reciprocal ways. In the Northern Highlands region of Wisconsin, they are studying a spatially complex landscape in which water features make up almost half of the land area, with wetlands (27% of land surface) and lakes (13%) both prevalent throughout the region, interspersed in upland forests.Weather and limnological data from a set of 170 lakes in the NHLD samples summer 2004. The sampled lakes were from a random stratified subsample (N=300 of 7588 total) of all the lakes in the NHLD.
Contact
Core Areas
Dataset ID
277
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Hanson PC, Carpenter S, Cardille JA, Coe MT, Winslow LA. 2007. Small lakes dominate a random sample of regional lake characteristics. Freshwater Biology. 52:814-22Lakes were selected from unique Water Body Identification Codes (WBICs). Linear features and water bodies identified as impoundments or stream openings were identified from maps digitised by the Departments of Natural Resources of Michigan and Wisconsin (1 : 24 000 USGS 7.5’ topographic quadrangles) and were excluded. More than 7500 lakes ranging in size from about 0.01 to over 2800 ha remained in the data set. We used a stratified random survey, an approach consistent with the Environmental Monitoring and Assessment Program (EMAP) guidelines (Larsen et al., 1994) of the U.S. Environmental Protection Agency, to select and sample 300 lakes from the data set as follows. All lakes were ordered by area and divided into 20 bins of equal population. From each bin, 15 lakes were chosen at random. Because of logistical issues in travelling to many lakes scattered over a wide geographical region, we clustered lakes into 31 geographically small regions of about 150 km2 each. The order of regions sampled was randomised to reduce correlation of geographic region with time. For any one sampling date we visited only one region, although not all lakes in a region could be visited on a single trip. After all 31 regions were visited, the regions were again selected at random, and lakes previously not visited were sampled. There were 45 sampling days spread between May 20 and August 19. Some lakes that were chosen for sampling could not be visited. Difficulty portaging the sampling gear to a lake or failure to gain access to a lake through private property were reasons for abandoning a sampling effort.Lakes were sampled at their approximate geographic centre. Lake depth and water clarity were measured with a Secchi disk. Our measurement of lake depth was neither a measurement of the maximum nor the mean depth. Because the measurement was made in the middle of the lake and most lakes in the region tend to be bowl shaped, our measurement was probably between mean and maximum depth. Dissolved oxygen (DO) and thermal profiles were obtained from a YSI Model 58 (YSI, Inc., Yellow Springs, OH, U.S.A.) metre (DO air calibrated; temperature calibrated in the laboratory), and the approximate middle of the epilimnion was estimated from the profile. Thermal stratification was calculated from the thermal profile according to the methods listed on the Internet at the North Temperate Lakes Long Term Ecological Research (NTL-LTER) program Web site (http://lter.limnology.wisc.edu). Water samples for later analyses (Table 1, chemical variables) were obtained from the middle of the epilimnion, using a peristaltic pump. For samples that required filtration [dissolved inorganic carbon (DIC), DOC, cations and anions], a 0.45 μm filter was attached in-line. All samples were refrigerated upon returning to the vehicle, and samples for total nitrogen (TN) and total phosphorus (TP) were preserved by acidification. Acid neutralizing capacity (ANC) and pH were determined the day of sampling by Gran alkalinity titration (for ANC) and measurement by pH probe (Accumet 950; Fisher Scientific, Hanover Park, IL U.S.A.). pH was not air equilibrated. DIC and DOC were measured with a carbon analyzer (TOC-V; Shimadzu Scientific Instruments, Columbia, MD, U.S.A.). TN and TP were measured with a segmented flow auto-analyzer (Astoria-Pacific, Inc., Clackamas, OR, U.S.A.). Anions were measured using an ion chromatograph (DX500; Dionex Corporation, Sunnyvale, CA, U.S.A.), and cations using mass spectrometry (ICP-MS; PerkinElmer Life and Analytical Sciences, Shelton, CT, U.S.A.). Details of chemical analyses are available on the Internet at the NTL-LTER Web site listed above.To correct for bias introduced by not sampling all 300 lakes, we replaced missing data using multiple imputation (Levy, 1999). Multiple imputation is a technique for estimating the uncertainty of imputed variables. For each variable for each lake not sampled in a given bin, we chose at random (with replacement) a value from lakes sampled in that bin. We repeated the imputation 1000 times to provide a distribution of estimates for each variable in the lakes not sampled. The distribution mean for each variable in each lake was used in the calculation of the median for the regional lake population. We chose to present the median for the 300 lakes because distributions tended to be highly skewed. For comparison purposes, we also calculated the median from sampled lakes only (i.e. excluding imputed data). The mean cumulative distributions for some variables, including 95% confidence intervals, were plotted from the 1000 cumulative distributions generated by multiple imputation.We fit a Pareto distribution to the regional lake area data set to compare the size distribution of NHLD lakes with those of other regions. We used the maximum likelihood estimator for parameter estimates (Bernardo & Smith, 2000). Of particular interest is the parameter (β) that describes the logarithmic decline in number of lakes with lake area, because this parameter has been used previously (Downing et al., 2006, Table 1) to compare lake area distributions among regions and to estimate the global abundance of lakes.Where indicated, results have been area weighted to reflect the influence of lake size. For correlations, data were transformed (log10) to normalise distributions and linearise relationships. Shoreline development factor (SDF), an index of the irregular shape of lakes, was calculated for each lake according to Kalff (2002). The minimum SDF, 1, indicates a lake is a perfect circle.
NTL Keyword
Version Number
25

Trout Lake USGS Water, Energy, and Biogeochemical Budgets (WEBB) Stream Data 1975-current

Abstract
This data was collected by the United States Geological Survey (USGS) for the Water, Energy, and Biogeochemical Budget Project. The data set is primarily composed of water chemistry variables, and was collected from four USGS stream gauge stations in the Northern Highland Lake District of Wisconsin, near Trout Lake. The four USGS stream gauge stations are Allequash Creek at County Highway M (USGS-05357215), Stevenson Creek at County Highway M (USGS-05357225), North Creek at Trout Lake (USGS-05357230), and the Trout River at Trout Lake (USGS-05357245), all near Boulder Junction, Wisconsin. The project has collected stream water chemistry data for a maximum of 36 different chemical parameters,. and three different physical stream parameters: temperature, discharge, and gauge height. All water chemistry samples are collected as grab samples and sent to the USGS National Water Quality Lab in Denver, Colorado. There is historic data for Stevenson Creek from 1975-1977, and then beginning again in 1991. The Trout Lake WEBB project began during the summer of 1991 and sampling of all four sites continues to date.
Creator
Dataset ID
276
Date Range
-
Maintenance
Completed.
Metadata Provider
Methods
DL is used to represent “detection limit” where known.NOTE (1): Each method listed below corresponds with a USGS Parameter Code, which is listed after the variable name. NOTE (2): If the NEMI method # is known, it is also specified at the end of each method description.NOTE (3): Some of the variables are calculated using algorithms within QWDATA. If this is the case see Appendix D of the NWIS User’s Manual for additional information. However, appendix D does not list the algorithm used by the USGS. If a variable is calculated with an algorithm the term: algor, will be listed after the variable name.anc: 99431, Alkalinity is determined in the field by using the gran function plot methods, see TWRI Book 9 Chapter A6.1. anc_1: 90410 and 00410, Alkalinity is determined by titrating the water sample with a standard solution of a strong acid. The end point of the titration is selected as pH 4.5. See USGS TWRI 5-A1/1989, p 57, NEMI method #: I-2030-89.2. c13_c12_ratio: 82081, Exact method unknown. The following method is suspected: Automated dual inlet isotope ratio analysis with sample preparation by precipitation with ammoniacal strontium chloride solution, filtration, purification, acidified of strontium carbonate; sample size is greater than 25 micromoles of carbon; one-sigma uncertainty is approximately ± 0.1 ‰. See USGS Determination of the delta13 C of Dissolved Inorganic Carbon in Water, RSIL Lab Code 1710. Chapter 18 of Section C, Stable Isotope-Ratio Methods Book 10, Methods of the Reston Stable Isotope Laboratory.3. ca, mg, mn, na, and sr all share the same method. The USGS parameter codes are listed first, then the method description with NEMI method #, and finally DL’s:ca- 00915, mg- 00925, mn- 01056, na- 00930, sr- 01080All metals are determined simultaneously on a single sample by a direct reading emission spectrometric method using an inductively coupled argon plasma as an excitation source. Samples are pumped into a crossflow pneumatic nebulizer, and introduced into the plasma through a spray chamber and torch assembly. Each analysis is determined on the basis of the average of three replicate integrations, each of which is background corrected by a spectrum shifting technique except for lithium (670.7 nm) and sodium (589.0 nm). A series of five mixed-element standards and a blank are used for calibration. Method requires an autosampler and emission spectrometry system. See USGS OF 93-125, p 101, NEMI Method #: I-1472-87.DL’s: ca- .02 mg/l, mg-.01 mg/l, mn-1.0 ug/l, na- .2 mg/l, sr- .5 ug/l4. cl, f, and so4 all share the same method. The USGS parameter codes are listed first, then the method description with NEMI method #, and finally DL’s:cl- 00940, f-00950, so4-00945All three anions (chloride, flouride, and sulfate) are separated chromatographically following a single sample injection on an ion exchange column. Ions are separated on the basis of their affinity for the exchange sites of the resin. The separated anions in their acid form are measured using an electrical conductivity cell. Anions are identified on the basis of their retention times compared with known standards. 19 The peak height or area is measured and compared with an analytical curve generated from known standards to quantify the results. See USGS OF 93-125, p 19, NEMI method #: I-2057.DL’s: cl-.2 mg/l, f-.1 mg/l, so4-.2 mg/lco2: 00405, algor, see NWIS User's Manual, QW System, Appendix D, Page 285.co3: 00445, algor.color: 00080, The color of the water is compared to that of the colored glass disks that have been calibrated to correspond to the platinum-cobalt scale of Hazen (1892), See USGS TWRI 5-A1 or1989, P.191, NEMI Method #: I-1250. DL: 1 Pt-Co colorconductance_field: 00094 and 00095, specific conductance is determined in the field using a standard YSI multimeter, See USGS TWRI 9, 6.3.3.A, P. 13, NEMI method #: NFM 6.3.3.A-SW.conductance_lab: 90095, specific conductance is determined by using a wheat and one bridge in which a variable resistance is adjusted so that it is equal to the resistance of the unknown solution between platinized electrodes of a standardized conductivity cell, sample at 25 degrees celcius, See USGS TWRI 5-A1/1989, p 461, NEMI method #: I-1780-85.dic: 00691, This test method can be used to make independent measurements of IC and TC and can also determine TOC as the difference of TC and IC. The basic steps of the procedure are as follows:(1) Removal of IC, if desired, by vacuum degassing;(2) Conversion of remaining inorganic carbon to CO<sub>2</sub> by action of acid in both channels and oxidation of total carbon to CO<sub>2</sub> by action of ultraviolet (UV) radiation in the TC channel. For further information, See ASTM Standards, NEMI method #: D6317. DL: n/adkn: 00623 and 99894, Organic nitrogen compounds are reduced to the ammonium ion by digestion with sulfuric acid in the presence of mercuric sulfate, which acts as a catalyst, and potassium sulfate. The ammonium ion produced by this digestion, as well as the ammonium ion originally present, is determined by reaction with sodium salicylate, sodium nitroprusside, and sodium hypochlorite in an alkaline medium. The resulting color is directly proportional to the concentration of ammonia present, see USGS TWRI 5-A1/1989, p 327, NEMI method #: 351.2. DL: .10 mg/Ldo: 0300, Dissolved oxygen is measured in the field with a standard YSI multimeter, NEMI Method #: NFM 6.2.1-Lum. DL: 1 mg/L.doc: 00681, The sample is acidified, purged to remove carbonates and bicarbonates, and the organic carbon is oxidized to carbon dioxide with persulfate, in the presence of an ultraviolet light. The carbon dioxide is measured by nondispersive infrared spectrometry, see USGS OF 92-480, NEMI Method #: O-1122-92. DL: .10 mg/L.don: 00607, algor, see NWIS User's Manual, QW System, Appendix D, page 291.dp: 00666 and 99893, All forms of phosphorus, including organic phosphorus, are converted to orthophosphate ions using reagents and reaction parameters identical to those used in the block digester procedure for determination of organic nitrogen plus ammonia, that is, sulfuric acid, potassium sulfate, and mercury (II) at a temperature of 370 deg, see USGS OF Report 92-146, or USGS TWRI 5-A1/1979, p 453, NEMI method #: I-2610-91. DL= .012 mg/L.fe: 01046, Iron is determined by atomic absorption spectrometry by direct aspiration of the sample solution into an air-acetylene flame, see USGS TWRI 5-A1/1985, NEMI method #: I-1381. DL= 10µg/L.h_ion: 00191, algor.h20_hardness: 00900, algor.h20_hardness_2: 00902, algor.hco3: 00440, algor.k: 00935, Potassium is determined by atomic absorption spectrometry by direct aspiration of the sample solution into an air-acetylene flame , see USGS TWRI 5-A1/1989, p 393, NEMI method #: I-1630-85. DL= .01 mg/L.n_mixed: 00600, algor.n_mixed_1: 00602, algor.n_mixed_2: 71887, algor.nh3_nh4: 00608, Ammonia reacts with salicylate and hypochlorite ions in the presence of ferricyanide ions to form the salicylic acid analog of indophenol blue (Reardon and others, 1966; Patton and Crouch, 1977; Harfmann and Crouch, 1989). The resulting color is directly proportional to the concentration of ammonia present, See USGS OF 93-125, p 125/1986 (mg/l as N), NEMI Method #: I-2525. DL= .01 mg/L.nh3_nh4_1: 71846, algor.nh3_nh4_2: 00610, same method as 00608, except see USGS TWRI 5-A1/1989, p 321. DL = .01 mg/L.nh3_nh4_3: 71845, algor.no2: 00613, Nitrite ion reacts with sulfanilamide under acidic conditions to form a diazo compound which then couples with N-1-naphthylethylenediamine dihydrochloride to form a red compound, the absorbance of which is measured colorimetrically, see USGS TWRI 5-A1/1989, p 343, NEMI method #: I-2540-90. DL= .01 mg/L.no2_2: 71856, algor.no3: 00618, Nitrate is determined sequentially with six other anions by ion-exchange chromatography, see USGS TWRI 5-A1/1989, P. 339, NEMI method #: I-2057. DL= .05 mg/L.no3_2: 71851, algor.no32: 00630, An acidified sodium chloride extraction procedure is used to extract nitrate and nitrite from samples of bottom material for this determination(Jackson, 1958). Nitrate is reduced to nitrite by cadmium metal. Imidazole is used to buffer the analytical stream. The sample stream then is treated with sulfanilamide to yield a diazo compound, which couples with N-lnaphthylethylenediamine dihydrochloride to form an azo dye, the absorbance of which is measured colorimetrically. Procedure is used to extract nitrate and nitrite from bottom material for this determination (Jackson, 1958), see USGS TWRI 5-A1/1989, p 351. DL= .1 mg/Lno32_2: 00631, same as description for no32, except see USGS OF 93-125, p 157. DL= .1 mg/L.o18_o16_ratio: 82085, Sample preparation by equilibration with carbon dioxide and automated analysis; sample size is 0.1 to 2.0 milliliters of water. For 2-mL samples, the 2-sigma uncertainties of oxygen isotopic measurement results are 0.2 ‰. This means that if the same sample were resubmitted for isotopic analysis, the newly measured value would lie within the uncertainty bounds 95 percent of the time. Water is extracted from soils and plants by distillation with toluene; recommended sample size is 1-5 ml water per analysis, see USGS Determination of the Determination of the delta (18 O or 16O) of Water, RSIL Lab Code 489.o2sat: Dissolved oxygen is measured in the field with a standard YSI multimeter, which also measures % oxygen saturation, NEMI Method #: NFM 6.2.1-Lum.ph_field: 00400, pH determined in situ, using a standard YSI multimeter, see USGS Techniques of Water-Resources Investigations, book 9, Chaps. A1-A9, Chap. A6.4 "pH," NEMI method # NFM 6.4.3.A-SW. DL= .01 pH.ph_lab: 00403, involves use of laboratory pH meter, see USGS TWRI 5-A1/1989, p 363, NEMI method #: I-1586.po4: 00660, algor, see NWIS User's Manual, QW System, Appendix D, Page 286.po4_2: 00671, see USGS TWRI 5-A1/1989, NEMI method #: I-2602. DL= .01 mg/L.s: 63719, cannot determine exact method used. USGS method code: 7704-34-9 is typically used to measure sulfur as a percentage, with an DL =.01 µg/L. It is known that the units for sulfur measurements in this data set are micrograms per liter.sar: 00931, algor, see NWIS User's Manual, QW System, Appendix D, Page 288.si: 00955, Silica reacts with molybdate reagent in acid media to form a yellow silicomolybdate complex. This complex is reduced by ascorbic acid to form the molybdate blue color. The silicomolybdate complex may form either as an alpha or beta polymorph or as a mixture of both. Because the two polymorphic forms have absorbance maxima at different wavelengths, the pH of the mixture is kept below 2.5, a condition that favors formation of the beta polymorph (Govett, 1961; Mullen and Riley, 1955; Strickland, 1952), see USGS TWRI 5-A1/1989, p 417, NEMI method #: I-2700-85. DL= .10 mg/L.spc: 00932, algor, see NWIS User's Manual, QW System, Appendix D, Page 289.tds: 70300 and 70301, A well-mixed sample is filtered through a standard glass fiber filter. The filtrate is evaporated and dried to constant weight at 180 deg C, see " Filterable Residue by Drying Oven," NEMI method #: 160.1, DL= 10 mg/l. Note: despite DL values occur in the data set that are less than 10 mg/l.tds_1: 70301, algor, see NWIS User's Manual, QW System, Appendix D, Page 289.tds_2: 70303, algor, see NWIS User's Manual, QW System, Appendix D, Page 290.tkn: 00625 and 99892, Block digester procedure for determination of organic nitrogen plus ammonia, that is, sulfuric acid, potassium sulfate, and Mercury (II) at a temperature of 370°C. See the USGS Open File Report 92-146 for further details. DL: .10 mg/L.toc: 00680, The sample is acidified, purged to remove carbonates and bicarbonates, and the organic carbon is oxidized to carbon dioxide with persulfate, in the presence of an ultraviolet light. The carbon dioxide is measured by nondispersive infrared spectrometry, see USGS TWRI 5-A3/1987, p 15, NEMI Method #: O-1122-92. DL=.10 mg/L.ton: 00605, algor, See NWIS User's Manual, QW System, Appendix D, page 286.tp: 00665 and 99891, This method may be used to analyze most water, wastewater, brines, and water-suspended sediment containing from 0.01 to 1.0 mg/L of phosphorus. Samples containing greater concentrations need to be diluted, see USGS TWRI 5-A1/1989, p 367, NEMI method #: I-4607. tp_2: 71886, algor.tpc: 00694, The basic steps of this test method are:1) Conversion of remaining IC to CO2 by action of acid, 2) Removal of IC, if desired, by vacuum degassing, 3) Split of flow into two streams to provide for separate IC and TC measurements, 4) Oxidation of TC to CO2 by action of acid-persulfate aided by ultraviolet (UV) radiation in the TC channel, 5) Detection of CO2 by passing each liquid stream over membranes that allow the specific passage of CO2 to high-purity water where change in conductivity is measured, and 6) Conversion of the conductivity detector signal to a display of carbon concentration in parts per million (ppm = mg/L) or parts per billion (ppb = ug/L). The IC channel reading is subtracted from the TC channel reading to give a TOC reading, see ASTM Standards, NEMI Method #: D5997. DL= .06 µg/L.tpn: 49570, A weighed amount of dried particulate (from water) or sediment is combusted at a high temperature using an elemental analyzer. The combustion products are passed over a copper reduction tube to covert nitrogen oxides to molecular nitrogen. Carbon dioxide, nitrogen, and water vapor are mixed at a known volume, temperature, and pressure. The concentrations of nitrogen and carbon are determined using a series of thermal conductivity detectors/traps, measuring in turn by difference hydrogen (as water vapor), carbon (as carbon dioxide), and nitrogen (as molecular nitrogen). Procedures also are provided to differentiate between organic and inorganic carbon, if desired, see USEPA Method 440, NEMI method #: 440. DL= .01 mg/L.
Short Name
TL-USGS-WEBB Data
Version Number
15
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