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Water Quality Evaluation Section

North Central Region Office

Water Quality Evaluation Section

 

3500 Industrial Blvd.
West Sacramento, CA 95691
(916) 376-9600

Mailing Address:
P.O. Box 942836
Sacramento, CA 94236-0001

 

 

Untitled Document

 Water Quality Evaluation Section

South Delta Monitoring Program Metadata

 

I. Contact Information


Program Manager: Shaun Philippart

Lead contact: David Bosworth
Environmental Scientist
Department of Water Resources
North Central Region Office
3500 Industrial Blvd., West Sacramento 95691
Email:  dboswort@water.ca.gov
Office: (916) 376-9646

Lead contact: Jenna Van Parys
Environmental Scientist
Department of Water Resources - North Central Region Office
3500 Industrial Blvd., West Sacramento 95691
Email:  jvanpary@water.ca.gov
Office: (916) 376-9644

Laboratory:
DWR Bryte Chemical Laboratory
1450 Riverbank Road,
West Sacramento, CA 95605
(916) 375-6008
Sid Fong: Supervisor of Bryte Chemical Laboratory
Email: sfong@water.ca.gov

II. Study Area and Sample Site Objectives

A. General Information

The Department of Water Resources (DWR) has been monitoring water quality as part of the South Delta Temporary Barriers project since 1991 to investigate water quality conditions in the South Delta that may be affected by temporary barrier installations and operations.  The North Central Region Office (NCRO) water quality sampling program consists of two components: 1) bi-monthly discrete sampling; and 2) continuous sampling.  NCRO staff analyzes the data and presents their findings in the water quality chapter of the Temporary Barriers Monitoring Report.  The information collected by this program is also required for compliance with a 401 Water Quality Certification issued by the Central Valley Regional Water Quality Control Board.  For detailed information on the South Delta Improvements Program and the Temporary Barriers Project please visit DWR’s Bay-Delta Office website at http://baydeltaoffice.water.ca.gov/sdb/.  

Historically, DWR conducted discrete sampling on a weekly basis at 10 locations to monitor physical and biological constituents, as well as nutrients.  The objective of this discrete program was and still is to monitor the effects of barrier operations on water quality.  To ensure that adequate data was collected before, after, and during the operational period of the barrier, DWR started discrete sampling two weeks before the barriers were installed and did not conclude until two weeks after all the barriers were removed.  Staff conducted sampling every Tuesday morning to target the time when dissolved oxygen concentrations tend to be lowest.

In 1998, Central District (CD) initiated a pilot program to test the viability of establishing permanent multi-parameter water quality stations in the South Delta to continuously monitor water temperature, pH, dissolved oxygen, specific conductance, and turbidity.  CD established this program to better understand barrier installations in accordance with the following: 1) to determine the feasibility of collecting reliable time-series water quality data; 2) to develop an understanding of dynamic water quality conditions in a tidally influenced system; and 3) to establish and maintain long-term continuous data records in the South Delta for analysis.

This continuous water quality monitoring program began with two stations: Old River at Tracy Wildlife Association and Middle River at Howard Road.  Central District staff determined that the time-series data generated from these two sites was reliable, accurate, and precise when compared to calibration standards and field data.  The success of the pilot program resulted in the decision to expand the continuous monitoring program.  DWR designed this expansion to complement the existing discrete stations.  As a result, CD staff installed continuous monitoring stations at each of the 10 discrete monitoring locations between 2000 and 2006.  After the installation of multi-parameter instruments at the discrete locations was complete, the weekly dissolved oxygen sampling was terminated and monitoring of biological constituents and nutrients was changed from weekly to bi-monthly. 

B. Name and Location Information for Continuous Water Quality Sampling Sites

- South Delta Stations Map

C.  Station Period of Record, Instrumentation, and Parameter Collection History

-South Delta Stations Table

D.  CDEC and Water Data Library Station Codes

-CDEC and WDL Station Codes Table

III. Sampling Frequency

A. Sonde Instrument Sampling

There are a total of 14 South Delta water quality monitoring stations that collect time-series data at 15 minute intervals using a YSI 6600EDS V2-4 internal data logging sonde.  All stations, with the exception of San Joaquin River at Dos Reis (which only collects water temperature and specific conductance data), record a single measurement of water temperature (Cº), dissolved oxygen (%), pH, specific conductance (µS/cm), turbidity (NTU), and chlorophyll (µg/L), within the 15 minute interval.

B. Field Instrument Sampling

Upon each site visitation (can vary from weekly to every 3 weeks), calibrated handheld field instruments are used to sample current water conditions to confirm and compare water quality measurements to the YSI 6600EDS V2-4 continuous monitoring stations.  Water temperature (Cº), pH, and specific conductance (µS/cm) measurements are field verified with an YSI 63 Handheld pH and Conductivity Instrument.  Dissolved oxygen measurements are field verified with a YSI Professional Optical Dissolved Oxygen Meter. Turbidity measurements are field verified with a Hach 2100P Portable Turbidimeter.

C. Discrete Sampling           

Staff collects a chlorophyll a/pheophytin a sample in a plastic quart bottle at 1 meter depth with a Van Dorn sampling device at each site.  The chlorophyll a/pheophytin a  sample and other field measurements are sampled at a 1 meter depth since the YSI 6600 sondes are also sampling at this depth.  During each field run, DWR staff also collects a duplicate chlorophyll a/pheophytin a  sample at one of the stations to test for field and lab precision and repeatability.  Total suspended solids samples are collected at two sites that are operating in conjunction with USGS flow stations: Old River below DMC barrier and Victoria Canal.

IV. Field Methods

A. Field measurements

During each site visit field readings are taken using portable and handheld instruments.  These handheld instruments are calibrated to comply with manufacturers or laboratory specifications.  Field readings are taken and recorded for comparison with YSI sonde data.  Field measurements are taken at each site at a 1meter depth to duplicate depth of deployed YSI sondes. 

YSI 63 Handheld pH and Conductivity Instrument

The YSI 63 Handheld Instrument measures temperature, conductivity, pH, and salinity.  The instrument is calibrated once a month for conductivity and pH is calibrated before each field run.

YSI Professional Optical Dissolved Oxygen Meter

The YSI Professional Optical Dissolved Oxygen meter measures percent saturation and mg/L of dissolved oxygen.  The instrument is checked and calibrated before each field run.

HACH 2100P Portable Turbidimeter

The HACH 2100P turbidimeter measures turbidity optically using the nephelometric principle.  The portable instrument is calibrated every three months using manufactures StablCal standards to assure accuracy.

B. Sample Collection

Staff collects discrete chlorophyll a/pheophytin a, chloride/bromide, and total suspended at 1 meter depth with a Van Dorn at each monitoring station.  One sample field run is duplicated, on a rotating basis, for quality assurance/quality control testing at the lab

C. Sample containers and holding times

The DWR Bryte laboratory supplies all necessary sampling materials to the NCRO Water Quality Evaluation field staff. Requirements for sample containers, preservation techniques, and holding times are found in one of the following references (or later editions): Standard Methods for the Examination of Water and Waste Water, American Public Health Association, et al., 21st Edition; Handbook for Sampling and Sample Preservation of Water and Wastewater, 2005, and 1979 US EPA Manual entitled “Methods for Chemical Analysis of Water and Wastes,” EPA-600/4-79-020.

V. Laboratory Methods

All water quality analyses are conducted by staff at the DWR Bryte Laboratory. Located in West Sacramento, the lab’s primary function is to analyze drinking water, surface water, groundwater, and wastewater. Bryte lab has maintained certification by the Environmental Protection Agency and the California Department of Health Services for water analysis since 1978. It also provides quality assurance, and related technical services.

-Lab Method Chart

VI. Data Management

A. Sonde Data

Post-deployment Quality Assurance


After the YSI 6600 sondes are removed from the field, DWR staff perform the following two procedures to check whether the sondes are still operating properly and measuring accurately:

  1. A post-deployment accuracy check on the day the sondes are removed and before the instruments are cleaned
  2. A comparison between the data measured by the handheld field instruments and the data collected by the sonde at the closest 15 minute time interval

The accuracy of sonde probes while deployed in the field can be negatively affected by probe malfunction, drift away from initial calibration, and/or fouling caused by biological growth on the probe reading surface.  DWR staff perform the post-deployment accuracy check by the following procedure prior to cleaning the sonde probes:

  1. Placing the sonde probes in fresh calibration standards with known values
  2. Operating the sondes in the standards and recording the values the sondes are reading
  3. Rating the values collected during the accuracy check for each constituent as excellent, good, fair, or poor based on their deviation from the calibration standard according to the USGS technical report “Guidelines and Standard Procedures for Continuous Water Quality Monitors-Station Operation, Record Computation, and Data Reporting” (Wagner et al., 2006)
    The ratings obtained from the accuracy check indicate the quality, accuracy, and reliability of the data that the sonde collected while in the field. 

In addition to the post-deployment accuracy check, DWR staff compare the water temperature, specific conductance, pH, dissolved oxygen, and turbidity data measured in the field by the handheld instruments (the YSI-63, YSI Pro-ODO, and HACH 2100P) to the sonde data that is closest in time.  While taking the field measurements, DWR staff attempt to collect the field readings at the same depth that the sonde probes are measuring at (1 meter) and as close to the sonde pipe as possible.  Since the field instruments are calibrated regularly, a large difference between the sonde and field readings could indicate inaccuracy of the sonde data during the deployment period.  DWR staff consider these comparisons between the field and sonde readings and the ratings obtained from the post-deployment accuracy check while assessing data quality when entering the continuous data into the Hydstra database. 

 

Data Quality Assurance/Quality Control (QA/QC)


DWR staff import data files from sondes into the North Central Region Office (NCRO) Hydstra database where additional QA/QC procedures are performed.  In addition to documenting the results of quality assurance procedures discussed in the previous section, staff use the results of these procedures to flag any suspect or unreliable data.  Any obvious outliers in the continuous dataset due to fouling or other factors are flagged as unreliable.  No data that has been determined by DWR staff as suspect or unreliable were used in this chapter; only reliable data of known good quality were used.  The reliable and good quality data in Hydstra are used to populate the Water Data Library where the data for all the continuous sites are available online at http://wdl.water.ca.gov/.

Chlorophyll a estimation


After all of the chlorophyll data was compiled, DWR staff then used the Minitab statistical software to analyze regression relationships for the matched chlorophyll data pairs.  Each of the 13 continuous monitoring locations was analyzed individually since the relationship between lab and sonde data is specific to location.  Each regression analysis generated an equation describing the relationship between sonde and lab chlorophyll data for the particular location.  DWR staff then used these equations to adjust the chlorophyll concentrations from the sonde to more closely represent chlorophyll a concentrations.  The regression analysis procedure is described in the following steps:

  1. A simple linear regression analysis is performed with the sonde data as the explanatory variable (x-variable) and the laboratory data as the response variable (y-variable).  Three assumptions of this parametric regression procedure are: the data follow a linear pattern, the underlying distribution of the data follows a normal or bell-shaped curve distribution, and the variance of the residuals from the regression is constant.  If these three assumptions are met, then the equation from the linear regression analysis can be used to adjust chlorophyll a concentrations.  If not, move on to step #2. 
  2. If the data do not follow a linear pattern, the explanatory variable (sonde data) needs to be transformed so that this assumption is met.  If the variance of the residuals is not constant or the underlying data is not normally distributed, then the response variable (laboratory data) needs to be transformed.  A typical transformation that is effective for this data is the natural logarithm.  Once the response variable is transformed, the regression equation no longer predicts the mean chlorophyll a concentration; it predicts the geometric mean or median.  In order to correct for this, either of two methods can be used:  the Maximum Likelihood Estimator (MLE) or Smearing.  These methods are described more in Step #4.  If it is not possible to transform the data so that the three assumptions of a linear regression are satisfied, then a nonparametric regression needs to be used, which is described in Step #5.
  3. If the equation from either the simple linear regression (Step #1) or the linear regression with transformed data (Step #2) is going to be used, then the seasonal terms, sine and cosine, are added to the regression analysis to determine if they are good predictors of the seasonality of chlorophyll concentrations.  If one or both of the seasonal terms are statistically significant in the analysis, then both terms are added to the regression equation in order to incorporate seasonality into the equation.
  4. MLE is one of the bias correction methods used to estimate the mean concentration when using a regression equation with the response variable transformed to a natural logarithm.  The MLE is calculated by the following equation:
  • MLE = e(0.5*MSE) 

The MSE is the mean squared error in logarithmic units, which is a quantification of the difference between the true data and the data estimated by the regression equation.  The adjusted chlorophyll a data generated by the regression equation with a natural logarithm transformation is then corrected by multiplying the adjusted value by the MLE.  For most of the stations that had a regression equation with data transformed to natural logarithms, the MLE was used as the bias correction factor to estimate the mean chlorophyll a concentrations.  However, for one of the stations the Smearing correction factor was used, since it was the better estimator .  The Smearing factor is calculated by first using the natural exponent (e) to “back-transform” all of the residuals from the regression.  The factor is then the average of all of the “back-transformed” residuals.  Like with the MLE, the adjusted chlorophyll a data is multiplied by the Smearing correction factor to correct the values to the estimated mean concentrations.

If transforming the data doesn’t allow for the assumptions of a linear regression to be attained, then the Theil-Sen line, a nonparametric regression procedure, can be calculated.  Like with the linear regression when the response variable is transformed to the natural logarithm, the Theil-Sen line equation predicts the median chlorophyll a concentration.  However, there is no bias correction factor available to estimate the mean concentrations when using a nonparametric regression procedure.  Therefore, when summarizing chlorophyll a concentrations adjusted with the Theil-Sen equation, averages such as daily or monthly averages cannot be reliably calculated.

The decision to use the MLE or Smearing correction factor was determined by the following procedure.  The sonde chlorophyll data that was matched to the lab chlorophyll data was plugged into the regression equation and then corrected by the MLE factor to provide a predicted sonde chlorophyll concentration.  These predicted values were then matched with their corresponding lab chlorophyll values, and a linear regression was performed on the matching pairs.  The same procedure was used with the Smearing correction factor.  The correction factor that gave a regression equation with a slope closest to one was then used.

B. Field Data

Field measurements are recorded on field data sheets upon each site visitation, and if the station has a discrete grab sample component, the data is then entered into the field module of DWR Bryte Laboratory’s “Flims” database.  Laboratory analyses are performed by DWR Bryte Laboratory on the discrete grab samples and the results are entered into the “FLIMS” database at the lab. For those stations without a discrete sample component, the field data sheets are used for sonde data comparison and archived accordingly.   On a regular basis the data from “Flims” database is loaded into DWR’s Water Data Library (WDL) database for public viewing and access.  Lab results are further archived and used for data report analyses.