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Heidelberg Tributary Loading Program (HTLP) Dataset

<p><strong>This dataset is updated more frequently and can be visualized on NCWQR&#39;s <a href="https://ncwqr-data.org/HTLP/Portal">data portal</a>.</strong></p> <p>If you have any questions, please contact <a href="https://www.heidelberg.edu/directory/laura-johnson">Dr. Laura Johnson</a> or <a href="https://www.heidelberg.edu/directory/nathan-manning">Dr. Nathan Manning</a>.</p> <p>&nbsp;</p> <p>The National Center for Water Quality Research (NCWQR) is a research laboratory at Heidelberg University in Tiffin, Ohio, USA. Our primary research program is the Heidelberg Tributary Loading Program (HTLP), where we currently monitor water quality at 22 river locations throughout Ohio and Michigan, effectively covering ~half of the land area of Ohio.&nbsp; The goal of the program is to accurately measure the total amounts (loads) of pollutants exported from watersheds by rivers and streams. Thus these data are used to assess different sources (nonpoint vs point), forms, and timing of pollutant export from watersheds.&nbsp; The HTLP officially began with high-frequency monitoring for sediment and nutrients from the Sandusky and Maumee rivers in 1974, and has continually expanded since then.&nbsp;&nbsp;&nbsp;&nbsp;</p> <p>Each station where samples are collected for water quality is paired with a US Geological Survey gage for quantifying discharge (<a href="http://waterdata.usgs.gov/usa/nwis/rt">http://waterdata.usgs.gov/usa/nwis/rt</a>).&nbsp; Our stations cover a wide range of watershed areas upstream of the sampling point from 11.0 km2 for the unnamed tributary to Lost Creek to 19,215 km2 for the Muskingum River. These rivers also drain a variety of land uses, though a majority of the stations drain over 50% row-crop agriculture.&nbsp;</p> <p>At most sampling stations, submersible pumps located on the stream bottom continuously pump water into sampling wells inside heated buildings where automatic samplers collect discrete samples (4 unrefrigerated samples/d at 6-h intervals, 1974&ndash;1987; 3 refrigerated samples/d at 8-h intervals, 1988-current). At weekly intervals the samples are returned to the NCWQR laboratories for analysis. When samples either have high turbidity from suspended solids or are collected during high flow conditions, all samples for each day are analyzed. As stream flows and/or turbidity decreases, analysis frequency shifts to one sample per day. At the River Raisin and Muskingum River, a cooperator collects a grab sample from a bridge at or near the USGS station approximately daily and all samples are analyzed. Each sample bottle contains sufficient volume to support analyses of total phosphorus (TP), dissolved reactive phosphorus (DRP), suspended solids (SS), total Kjeldahl nitrogen (TKN), ammonium-N (NH4), nitrate-N and nitrite-N (NO2+3), chloride, fluoride, and sulfate. Nitrate and nitrite are commonly added together when presented; henceforth we refer to the sum as nitrate.&nbsp;</p> <p>Upon return to the laboratory, all water samples are analyzed within 72h for the nutrients listed below using standard EPA methods. For dissolved nutrients, samples are filtered through a 0.45 um membrane filter prior to analysis. We currently use a Seal AutoAnalyzer 3 for DRP, silica, NH4, TP, and TKN colorimetry, and a DIONEX Ion Chromatograph with AG18 and AS18 columns for anions. Prior to 2014, we used a Seal TRAACs for all colorimetry.&nbsp;</p> <p>&nbsp;</p> <p><strong>2017 Ohio EPA Project Study Plan and Quality Assurance Plan</strong></p> <p><strong><a href="https://ncwqr.files.wordpress.com/2019/04/ncwqr-study-plan-20170127-with-addendums.pdf">Project Study Plan</a></strong></p> <p><strong><a href="https://ncwqr.files.wordpress.com/2019/04/quality-assurance-plan_version-6-20170127.pdf">Quality Assurance Plan</a></strong></p> <p>&nbsp;</p> <p><strong>Data quality control and data screening</strong></p> <p>The data provided in the River Data files have all been screened by NCWQR staff. The purpose of the screening is to remove outliers that staff deem likely to reflect sampling or analytical errors rather than outliers that reflect the real variability in stream chemistry. Often, in the screening process, the causes of the outlier values can be determined and appropriate corrective actions taken. These may involve correction of sample concentrations or deletion of those data points.</p> <p>This micro-site contains data for approximately 126,000 water samples collected beginning in 1974. We cannot guarantee that each data point is free from sampling bias/error, analytical errors, or transcription errors. However, since its beginnings, the NCWQR has operated a substantial internal quality control program and has participated in numerous external quality control reviews and sample exchange programs. These programs have consistently demonstrated that data produced by the NCWQR is of high quality.</p> <p>&nbsp;</p> <p><strong>A note on detection limits and zero and negative concentrations</strong></p> <p>It is routine practice in analytical chemistry to determine method detection limits and/or limits of quantitation, below which analytical results are considered less reliable or unreliable. This is something that we also do as part of our standard procedures. Many laboratories, especially those associated with agencies such as the U.S. EPA, do not report individual values that are less than the detection limit, even if the analytical equipment returns such values. This is in part because as individual measurements they may not be considered valid under litigation.</p> <p>The measured concentration consists of the true but unknown concentration plus random instrument error, which is usually small compared to the range of expected environmental values. In a sample for which the true concentration is very small, perhaps even essentially zero, it is possible to obtain an analytical result of 0 or even a small negative concentration. Results of this sort are often &ldquo;censored&rdquo; and replaced with the statement &ldquo;&lt;DL&rdquo; or &ldquo;&lt;2&rdquo;, where DL is the detection limit, in this case 2. Some agencies now follow the unfortunate convention of writing &ldquo;-2&rdquo; rather than &ldquo;&lt;2&rdquo;.</p> <p>Censoring these low values creates a number of problems for data analysis. How do you take an average? If you leave out these numbers, you get a biased result because you did not toss out any other (higher) values. Even if you replace negative concentrations with 0, a bias ensues, because you&rsquo;ve chopped off some portion of the lower end of the distribution of random instrument error.</p> <p>For these reasons, we do not censor our data. Values of -9 and -1 are used as missing value codes, but all other negative and zero concentrations are actual, valid results. Negative concentrations make no physical sense, but they make analytical and statistical sense. Users should be aware of this, and if necessary make their own decisions about how to use these values. Particularly if log transformations are to be used, some decision on the part of the user will be required.</p> <p>&nbsp;</p> <p><strong>Analyte Detection Limits</strong></p> <p><a href="https://ncwqr.files.wordpress.com/2021/12/mdl-june-2019-epa-methods.jpg?w=1024">https://ncwqr.files.wordpress.com/2021/12/mdl-june-2019-epa-methods.jpg?w=1024</a></p> <p>&nbsp;</p> <p><strong>For more information, please visit <a href="https://ncwqr.org/">https://ncwqr.org/</a></strong></p>