Water quality monitoring data and reports
Protecting and restoring water quality is a core mission of the St. Johns River Water Management District. A key component of this work is water quality monitoring and reporting. Monitoring provides a wealth of information that enables the district to make resource decisions based on accurate and timely information. In addition, residents can use the information to acquire a basic knowledge of groundwater, springs and water bodies in which they have an interest. The water quality monitoring program is staffed and managed by the Bureau of Water Resource Information.
The water quality monitoring network at the district was initially designed and implemented in the early 1980s and has since been improved and expanded. The current network is comprised of more than 400 surface water sampling stations located on rivers, streams, lakes, canals, and estuaries, 23 spring stations, and more than 450 groundwater stations throughout the district’s 18-county service area. Stations are sampled for a variety of water quality parameters, including nutrients, major ions and physical measurements, and water quality samples are analyzed using U.S. Environmental Protection Agency (EPA) methods at the district’s laboratory or at various contract labs. In addition, the district maintains more than 20 continuous water quality stations in freshwater, springs and estuaries, collecting real-time water quality data to support district projects.
All data is considered provisional and the district is not liable for any use or misuse of this data. The district reserves the right to make changes in the stored data without notice.
If you have questions concerning this data, please contact the Bureau of Water Resource Information at 800-451‑7106, or by email at firstname.lastname@example.org.
Methods used to generate the 2019 status and trends maps
Water quality data for 209 surface water monitoring stations, 274 Upper Floridan aquifer groundwater monitoring wells and 25 springs monitoring stations located throughout the St. Johns River Water Management District (SJRWMD) were analyzed for status and trends. Water quality status is an indication of the condition of a waterbody for a given analyte or parameter (for example, color or total phosphorus). Water quality trends indicate whether a series of analyte or parameter values is increasing or decreasing over time.
Water quality status
The status assessment period was five years, from Jan. 1, 2014, to Dec. 31, 2018. At least three years of data during the five-year status assessment period were required to complete the status assessment, and the last year had to be 2018. Water quality status is represented by the median of annual median values from the five-year assessment period. Median values were chosen to represent water quality status as they are not greatly skewed by outliers, and thus serve as a robust indicator of central tendency.
Water quality status is indicated by symbol color in the status and trends maps. For surface water analytes and some springs and groundwater analytes, percentiles were assigned to ranked status results. Ranges of percentiles were established (low: 0th–25th percentile, medium: 25th–75th percentiles, high: 75th–100th percentile) and these three ranges are indicated with different shades of blue color, from light to dark. For most of the springs and groundwater analytes, the range is not based on a percentile distribution, but rather a numerical range. Note that all ranges are expressed as low, medium or high relative to each other, and high values do not necessarily indicate poor water quality.
Water quality trends
The trend assessment period was 15 years, from Jan. 1, 2004, to Dec. 31, 2018. At least 10 years of data were required from the 15-year period of record to calculate a trend. The 10-year period of record could be any 10 years within the 15-year period, including periods for which there was a gap in the data, although the last year in the period had to be 2018. Years in the period of record that had more samples than other years were adjusted such that each year was represented by the same number of samples, when possible. Trends were calculated using the nonparametric Mann-Kendall test. A non-seasonal version of the test was used if there were no statistically significant differences between monthly values (Kruskal-Wallis test, p<0.05). A seasonal version of the Mann-Kendall test was used if there were significant differences.
Water quality trends are indicated by symbol shape in the status and trends maps. An up triangle indicates an increasing trend, while a down triangle indicates a decreasing trend. Squares indicate a stable result or a statistically non-significant trend, while circles indicate insufficient data. Trends that are changing more than 5% per year are indicated with a small yellow circle in the trend symbol. Stations may have insufficient data for a variety of reasons. A newly established station that has not been sampled for at least 10 years will have insufficient data for a trend calculation. In some cases, a station will have results for some analytes, but not others. This report does not attempt to analyze the cause or impacts of any trends, nor are the trend results meant to be forecasts. Rather, trends indicate what has happened at the water quality station over the assessment period.
Water quality sample collection and laboratory analysis
Water quality data were derived from samples collected primarily by SJRWMD field staff. For surface water and springs monitoring stations, most samples were “grab” samples, which means that they were collected using a technique of either inverting the sample bottle in the water column or pouring sample water from a separate collection device, such as a Van Dorn sampler, into the sample bottle. “Vertically integrated” samples were also included in the surface water and springs assessments. These samples were obtained with the use of a long sampling tube and indicate water quality over a range of depths. Since most waterbodies in the district are shallow and not stratified, data from all depths were used for the assessment, including vertically integrated samples. The samples for all three water resource types were analyzed using U.S. Environmental Protection Agency (EPA) methods at the district’s laboratory or at various contract labs.
Water quality data preparation
Prior to use in the assessment, sample data were evaluated and filtered in a multi-step process. Important details of this process are outlined below.
- All sample data were analyzed using both SAS and R software.
- Collection, analysis and processing of water quality samples and data can be an error-prone process, and problems can occur. On those rare occasions, the laboratory will associate qualifier codes with the data. In this assessment, qualifier codes were evaluated and any suspect data were omitted. In addition, any quality assurance samples such as duplicates and blanks were omitted.
- Total nitrogen (TN) was calculated for each day of data from the sum of total Kjeldahl nitrogen (TKN) and total nitrate + nitrite (NOx), even if NOx was missing. If TKN was missing, then TN was not calculated. If total NOx was missing, then dissolved NOx was used instead, if it was available. Calculated TN was then added to the data set.
- Hardness was calculated from calcium and magnesium for each day of data and added to the data set.
- Daily median values were calculated for all data to ensure that there was only one value per day. The daily median value closest to the midpoint of each month was used to represent the month for trend calculations.
- Individual station and analyte datasets that contained more than 5% non-detect values were evaluated for status using survival statistics methods and for trends using the Kendall tau correlation coefficient with an Akritas-Theil-Sen regression estimate (Helsel 2005).
- Analytical results were combined with a spatial representation of sampling locations. The interactive maps were created using an Esri ArcGIS Online web application template.
Helsel, Dennis R. 2005. Nondetects and data analysis: statistics for censored environmental data. Hoboken, N.J.: Wiley-Interscience, 250 pp.