Continuous Temperature Sampling and Analysis Plan
Major Lakes Program
CONTINUOUS TEMPERATURE
Sampling and Analysis Plan
_______________________________________________________
Prepared by:
King County Department of Natural Resources & Parks
Water and Land Resources Division
Science and Data Management Section
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_______________________________________________________
November 2005
Name of Project: Major Lakes Program: Continuous Temperature Study
Project Number: 421235
SAP Prepared By: Curtis DeGasperi
King County Department of Natural Resources & Parks
Water and Land Resources Division
Science and Data Management Section
______________________________________________________________________
___________________________________
Curtis DeGasperi, Project Manager
Water and Land Resources Division
____________________________________
Jonathan Frodge, Program Manager
Major Lakes Program
__________________________________
Bob Kruger, Technical Coordinator
King County Environmental Laboratory
___________________________________
Katherine Bourbonais, Laboratory Project Manager
King County Environmental Laboratory
___________________________________
Colin Elliott, QA Officer
King County Environmental Laboratory
1 INTRODUCTION 2
1.1 Study Area 3
1.2 Historical Data Review 3
2 Study Design 9
2.1 Data Recording, Management, and Reporting 15
2.2 Timeline 16
3 PROJECT ORGANIZATION 16
4 DATA QUALITY OBJECTIVES 17
Precision 17
Accuracy and bias 17
Comparability 18
Completeness 18
5 QUALITY CONTROL PROCEDURES 19
6 DATA ANALYSIS PROCEDURES 19
7 PROJECT DELIVERABLES 19
8 REFERENCES 20
List of Tables
Table 1. Thermistor chain deployment design summary. 15
Table 2. Project team members and responsibilities 16
Table 3. Summary of instrument precision, accuracy and response time 18
List of Figures
Figure 1. Major Lakes Program study area, including routine monitoring locations. 4
Figure 2. Historical lake temperature monitoring locations. 5
Figure 3. Example temperature data sets for (A) routine temperature profiling at Lake Washington 0852, (B) RUSS buoy WASHS on Lake Washington, (C) Onset thermistor chain on Lake Washington I-90 floating bridge, and (D) RBR thermistor chain at Lake Sammamish LS02A. 6
Figure 4. Seattle-District Army Corps of Engineers seasonal (May-Oct) temperature and salinity (LL, BB, FB, UB, and GW) and water surface elevation monitoring locations (Kenmore and Lake Washington Ship Canal). 11
Figure 5. Proposed RBR and Onset thermistor chain deployment locations. Current RUSS buoy locations are also shown. 12
Figure 6. RBR thermistor chain deployment design. 13
Figure 7. Lake Washington floating bridge Onset thermistor chain design. 15
Appendix A Field Data Sheet
INTRODUCTION
The largest lakes in the Seattle metropolitan area – Sammamish, Washington, and Union – have been the focus of King County’s (formerly METRO’s) Major Lakes water quality monitoring program (Major Lakes Program) since the late 1960s and early1970s (e.g., King County 2005a, King County 2003, King County 2002, Tomlinson et al. 1977, Isaac et al. 1966). These lakes have also been the focus of a variety of investigations conducted by researchers at the University of Washington (e.g., Edmondson et al. 2003, Welch et al. 1986, Rattray and Shetye 1982). Routine water quality monitoring of Lake Washington by University of Washington (UW) researchers and of all three lakes by King County continues. In the last few years, more specific studies have focused on the movement and trophic interactions of salmonids and other fish species due to the use of these lakes by Endangered Species Act (ESA) listed species of salmon (e.g., Beauchamp et al. 2004). Of particular relevance to the development of this Sampling and Analysis Plan (SAP) is radio and thermistor tagging studies designed to track Chinook and sockeye salmon movements through Lake Washington (e.g., Newell and Quinn 2005). Fish will be equipped this summer (2005) with radio tags and temperature sensors to evaluate their thermal exposure and temperature preferences while migrating through the lake.
Long term changes in the temperature dynamics of the lakes, including a trend of increasing temperatures, and related biological effects have also been identified based on the long term monitoring data collected on Lake Washington (e.g., Hampton 2005, Arhonditsis et al. 2004, Winder and Schindler 2004a, Winder and Schindler 2004b). Arhonditsis et al. (2004) estimated that the surface (0 – 10 m) and whole lake temperatures have increased over the period 1964-1998 by 1.5 (0.0458 oC yr-1) and 0.98 oC (0.0268 oC yr-1), respectively. This long-term trend was best described by a trend of increasing atmospheric long wave radiation – consistent with expectations from human-induced global climate warming (Arhonditsis et al. 2004).
Winder and Schindler (2004b) have been able to show that long term lake warming trends have resulted in extension of the spring-summer stratification period by 25 days over the last 40 years (1962-2002) – mainly due to earlier spring stratification, which occurs about 16 days earlier than it did 40 years ago. In response to earlier stratification, the spring phytoplankton bloom occurs about 19 days earlier than it did in 1962. The timing of the spring peak of Daphnia, the main zooplankton consumer of the spring phytoplankton bloom has not changed in response to the shift in phytoplankton resulting in a reduction in the availability of their food source. This has resulted in a decline in Daphnia abundance, with implications for food supply to upper trophic levels in the lake (Winder and Schindler 2004a).
Edmondson et al. (2003) also hypothesized that the progressive warming of Lake Washington in recent years may be leading to more physically stable conditions during summer that provide a competitive advantage to Microcystis, a blue-green alga or cyanobacterium, which can regulate its buoyancy. This blue-green species is capable of producing neurotoxins and hepatotoxins, with implications for the health of humans and other animals exposed directly through ingestion of water or indirectly via dermal contact (Chorus et al. 2002).
Rising lake temperatures have also been suggested as a possible explanation for the loss of adult sockeye salmon as they migrate through Lake Washington in recent years (Stifler, L., Seattle Post-Intelligencer, July 11, 2005; Cornwall, W., Seattle Times, June 22, 2005). Elevated water temperature in general has been identified as a potentially significant factor in the decline of ESA-listed salmon (Kerwin 2001), although this concern is related more specifically to temperature increases in local streams resulting from clearing of shading vegetation, channel and wetland modifications, and water diversions.
King County is also currently developing hydrodynamic and water quality models of these lakes as part of the county’s Freshwater Program. One goal of this modeling effort is the simulation of temperature dynamics in these lakes and coupling of the hydrodynamic model to a water quality model. These models could be used to evaluate future lake temperature and water quality conditions in response to climate change.
This SAP describes the design of a field sampling program to collect continuous (15 minute frequency) temperature profile data in these lakes that will provide temporal and spatial resolution sufficient to evaluate the timing of seasonal and diurnal lake stratification and destratification, data for coupling fish tracking thermistors with lake temperatures, and support further hydrodynamic model testing and development. The collection of additional temperature data described in this plan will also aid in our understanding of the influence of climate variability and trends on lake temperature specifically and water quality in general.
1 Study Area
The study area includes Lake Sammamish, Lake Washington, and Lake Union (Figure 1).
2 Historical Data Review
Historically, temperature data have been collected on a weekly, bi-weekly, or monthly basis at one or more locations within each lake. A single profile is recorded at a particular location, typically near mid-day, by lowering a recording thermistor to specific depths. More recently, attempts have been made to record temperature profiles at a number of locations in Lake Washington and Sammamish using Remote Underwater Sampling System (RUSS) profilers (maximum of 4 profiles per day at 1 m depth intervals) and strings of continuous temperature sensors deployed from the Lake Washington floating bridges (hourly at 2, 7, 10, 15, 20, 25, 35 and 55 m depths) or suspended from the lake bottom (minimum of 3 minutes at 1 m intervals spanning approximately 3 to 26 m depth or every 8 minutes at 1 m intervals from 3 m to the bottom) (King County unpublished data). The locations where long-term routine profiles and recent continuous data have been collected are shown in Figure 2. Example data sets for each sampling approach for the most recent year of data available are shown in Figure 3.
Each of these approaches to the collection of temperature data has advantages and disadvantages. Routine profiling is a reliable means of collecting temperature data (see Figure 3A), but the temporal resolution (currently 2 profiles per month between March and October) does not provide precise information on the timing of stratification and destratification and practically no information regarding higher frequency temperature fluctuations that occur due to internal waves (seiches) that occur on a daily or sub-daily frequency.
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Figure 1. Major Lakes Program study area, including routine monitoring locations.
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Figure 2. Historical lake temperature monitoring locations.
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Figure 3. Example temperature data sets for (A) routine temperature profiling at Lake Washington 0852, (B) RUSS buoy WASHS on Lake Washington, (C) Onset thermistor chain on Lake Washington I-90 floating bridge, and (D) RBR thermistor chain at Lake Sammamish LS02A.
Note: Black line on each panel identifies the depth of maximum density change above a threshold of 0.1 sigma-t based on the available data to demonstrate the effect of temporal and spatial resolution of temperature data collection on identification of period of days between stratification and destratification and daily average depth of the thermocline.
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Figure 3 (continued). Example temperature data sets for (A) routine temperature profiling at Lake Washington 0852, (B) RUSS buoy WASHS on Lake Washington, (C) Onset thermistor chain on Lake Washington I-90 floating bridge, and (D) RBR thermistor chain at Lake Sammamish LS02A.
Note: Black line on each panel identifies the depth of maximum density change above a threshold of 0.1 sigma-t based on the available data to demonstrate the effect of temporal and spatial resolution of temperature data collection on identification of period of days between stratification and destratification and daily average depth of the thermocline.
The RUSS system has been plagued by vandalism and maintenance problems, due to its high visibility and technical sophistication required for system operations that include solar battery charging and onboard computer and telecommunications equipment. When operational, the RUSS was capable of collecting data over nearly the entire water column and the sampling frequency of 4 times per day captures some of the diel changes in temperature due to internal waves and the development of diurnal thermoclines (see Figure 3B). Although the RUSS program initially consisted of 3 buoys on Lake Washington and 2 buoys on Lake Sammamish, only one buoy was operating on each lake by mid-2005. By mid-June 2005 the last functioning Lake Washington buoy (WASHN) ceased to function and has since been removed. The Lake Sammamish buoy (SAMMS) functioned into late September, but is no longer maintained, although the meteorological station is currently operational.
The Onset™ thermistors that were used on the floating bridges and a few Major Lakes Hydrodynamic Study locations (see below) are relatively inexpensive and reliable. However, these devices require field personnel to occasionally download each thermistor, which can create some difficulties with data file retrieval and tracking. These instruments have been typically set up to measure temperature at 15 minute intervals or less. This sampling frequency captures much of the diel temperature variation, but in some cases some vertical resolution has been sacrificed (see Figure 3C).
Bottom-deployed thermistor chains [Richard Brancker Research (RBR) XR-420-T24] were deployed as part of a hydrodynamic study of Lake Washington and Sammamish (Schock 2002). There was some difficulty with the deployment of the thermistor chains, which caused some of the thermistors to fail. However, it is believed that these problems have been resolved and a thermistor chain deployed in Lake Sammamish since June 26, 2004 has performed well – no thermistors have failed during one full year of deployment time. The major advantage of the RBR thermistors is that they are extremely accurate (±0.002 oC) compared to ±0.2 oC typical of the various Onset thermistors), have very accurate internal clocks (±1 minute yr-1 compared to ±1 minute wk-1 for the Onset Optic Stowaway thermistors), rapid response time (~3 seconds compared to 4 minutes for the Onset Optic Stowaway thermistors) and data are downloaded simultaneously from all thermistors to a single data file. The major disadvantage is that the chains purchased for the hydrodynamic study are only 24 m long. Therefore, sampling at every depth in the deeper parts of Lake Washington can only be accomplished by deploying two offset chains at the deepest locations. An example of RBR data collected at a mid-lake location in Lake Sammamish (LS02A) in 2004 is shown in Figure 3C.
Study Design
The study approach is designed to provide adequate spatial and temporal resolution of continuous temperature data to evaluate the timing of seasonal and diurnal lake stratification and destratification, for coupling fish tracking thermistors with lake temperatures, and support further hydrodynamic model testing and development. These temperature data will also supplement the routine temperature profiling data (King County 2005b) and data collected by the Seattle-District Army Corps of Engineers (Figure 4).
Stations equipped with RBR X-420-T24 thermistor chains located along the main axis of Lake Washington are proposed to provide longitudinal resolution of temperature dynamics (Figure 5). The deployment of RBR X-420 thermistor chains at one location in Lake Sammamish is proposed to characterize the high frequency temperature dynamics of these lakes (Figure 5). A vertical resolution of 1 m is proposed to characterize the vertical temperature dynamics of these lakes. Due to the limitations of the existing RBR equipment, the available RBR thermistor chains will only provide data for 24 m of the water column. The portion of the water column that will be sampled by these thermistor chains will cover depths from approximately 3 to 26 m below the water surface. The RBR deployment design is presented in Figure 6. Each thermistor chain will be equipped with an RBR pressure transducer (DR-1050) so that the depth of each thermistor during each deployment can be determined.
At the proposed northern and southern RBR stations in Lake Washington and in Lake Sammamish, the RBR chains will cover approximately 60 (0804A / NWASH)[1] to 80 (0641A / LS02A) percent of the water column; focused on the depths that encompass the location of the seasonal thermocline. At the proposed mid-lake Lake Washington RBR station (0861A / MIDWAY), a single chain will still cover the seasonal thermocline, but will miss some of the more subtle temperature dynamics in the deeper water column.
RBR thermistors will be set up to record instantaneous temperature at 15-minute intervals on the quarter hour and the pressure transducer will be set up to record instantaneous depth at hourly frequency. Memory and battery life will allow data to be retrieved on approximately a 6 month schedule. This schedule presents the risk of loosing up to 6 months of data at any location, but more frequent retrieval of equipment and data is considered to excessively increase the cost of this program. Multiple stations provide some sampling redundancy along with data collected as part of routine sampling and the RUSS.
To coordinate with the proposed 2005 fish tagging study, data downloads may be somewhat more frequent through October 2005. Thereafter, downloads are planned to follow the 6 month schedule with the next data download planned for sometime in April 2006 unless unforeseen circumstances warrant a schedule change.
No RBR X-420 thermistor chains will be available as a backup, although 2 non-working chains may be reparable depending on availability of maintenance funds and negotiations with RBR. In the event that one of these chains is repaired, it will become a backup for this project. The backup RBR thermistor chain will then be deployed as soon as possible following discovery of a bad thermistor chain. The bad chain will then be sent for servicing if maintenance funds become available and the repaired chain will become the backup. If both chains are repaired, one chain will become a backup and the second chain will be deployed at the mid-lake (0861A / MIDWAY) Lake Washington station to sample the 27 to 50 m water depths.
An Onset™ thermistor chain will be deployed from each floating bridge (SR-520 and I-90) on Lake Washington and from a dock at a relatively deep location on the south end of Lake Union to provide high frequency sampling data from near the water surface to the bottom (Figure 5). On the Lake Washington floating bridges, thermistors will be attached to a line at fixed depths – 2, 4, 6, 8, 10, 12, 15, 20, 25, 30, 35, and 55 m below the water surface. The Lake Union station thermistor chain will be attached to a dock with thermistors at fixed depths of 2, 4, 6, 8, 10, 12 and 14 m. The Onset bridge thermistor chain deployment design is presented in Figure 7. An Onset thermistor chain already deployed at the Hiram M. Chittenden Locks (at fixed depths from 2 to 13 m below the water surface) will be incorporated into this proposed program (Figure 5). Thermistors will be set up to record instantaneous temperatures at 15-minute frequency. Memory and battery life will allow data to be retrieved on approximately a 6 month schedule.
All computers used to synchronize thermistor clocks will be logged into the network and synchronized with local network time in the morning prior to launching and setting thermistors and pressure transducer clocks. The computer time will also be checked against atomic clock time (e.g., ) to verify that the computer clock displays the correct local time. Therefore, time series files will be recorded on the quarter hour in Pacific Daylight or Pacific Standard Time (PDT or PST) depending on the time of deployment. Data management systems will be developed to allow the data recorded in local time to be extracted in a time specified by the user (e.g., UTC, PST, PDT, or local time) or through programming designed to determine if the instrument was launched in PST or PDT.
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Figure 4. Seattle-District Army Corps of Engineers seasonal (May-Oct) temperature and salinity (LL, BB, FB, UB, and GW) and water surface elevation monitoring locations (Kenmore and Lake Washington Ship Canal).
Note: Fish Ladder water quality monitoring location not shown.
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Figure 5. Proposed RBR and Onset thermistor chain deployment locations.
Note: Locations of the two RUSS buoys remaining in mid-2005 are also shown, but these buoys are no longer operational with the exception of a meteorological station on SAMMS.
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Figure 6. RBR thermistor chain deployment design.
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Figure 7. Lake Washington floating bridge Onset thermistor chain design.
The sampling design is summarized in Table 1.
|Table 1. Thermistor chain deployment design summary. |
|Lake Sammamish |
|Locator (Station)a |Water |Northing/Easting c |Equipment d |Number of Depths |
| |Depth | | | |
|0641A (LS02A) |30 |215863 / 1329893 |RBR/RDR |24 |
|SAMMS/ |30 |213515 / 1329640 |RBR/RDR |24 |
|RUSS b | | | | |
|Lake Washington |
|0804A (NWASH) |40 |265514 / 1287012 |RBR/RDR |24 |
|0852B (SR-520) |60 |237499 / 1286500 |Onset |12 e |
|0861A (MIDWAY) |55 |227896 / 1288438 |RBR/RDR |24 |
|0890W (I-90W) |55 |218442 / 1283479 |Onset |12 e |
|0890E (I-90E) |55 |218361 / 1285261 |Onset |12 e |
|0831A (SWASH) |28 |190872 / 1296115 |RBR/RDR |24 |
|Lake Union |
|0522B (SUNION) |14 |234567 / 1269291 |Onset |7 e |
|0512B (Large Lock) |13 |246506 / 1255828 |Onset |8 e |
|a King County Laboratory Information System (LIMS) station Locator and original station name. The LIMS Locator will be used in |
|LIMS to store other water quality data collected at these stations. |
|b SAMMS Remote Underwater Sampling Station (RUSS) buoy does not have a proposed LIMS Locator. |
|c Northing/Easting are in State Plane feet, Washington North, NAD83/91 (HPGN). It is expected that the exact location of each |
|deployment will be within a 30 m radius of these station coordinates due to limitations of wind and wave conditions and deployment |
|logistics. |
|d Proposed sampling frequency for all thermistors is 15 minutes recorded on the quarter hour. Proposed RDR pressure transducer |
|sampling frequency is hourly. |
|e Proposed thermistor depths for the Onset chains deployed on each bridge and the SAMMS RUSS buoy are 2, 4, 6, 8, 10, 12, 15, 20, |
|25, 30, 35 and 50 m. Proposed depths for the Onset chain suspended from a dock in the southern end of Lake Union near station A522|
|are 2, 4, 6, 8, 10, 12, and 14 m. The Onset chain currently deployed at the Hiram M. Chittenden Locks has 8 thermistors suspended |
|from a float at 2, 5, 7, 9, 10, 11, 12, and 13 m water depth. |
1 Data Recording, Management, and Reporting
Data will be downloaded to field laptops using appropriate software and the raw and processed files will be named according to the convention “RBRLLLYYMMDD.* or ONSLLLYYMMDDZZ.*” where RBR or ONS refers to the thermistor type (RDR will be used for the pressure transducer data). LLLL refers to the station locator (e.g., SWASH, YYMMDD refers to the year, month and day of data retrieval (e.g., “050623”) and ZZ refers to the water depth of each Onset thermistor (e.g., “02”). Data files will be copied from the field laptop to a network directory within one day of instrument retrieval and stored in folders labeled by download date (e.g., “Data\MajorLakes\thermistors\_050623”). Standardized file naming and folder structure will facilitate data management and retrieval.
Data will be reviewed to ensure their quality and acceptable data will be loaded into the King County hydrologic database that is now available to the public via a web-based interface ().
2 Timeline
It is proposed that this sampling plan be implemented in August 2005. At a minimum, sampling and analysis will continue through December 2006. At that time, the program should be reevaluated and modified or discontinued based on review of the data collected.
PROJECT ORGANIZATION
Project team members and their responsibilities are summarized in Table 2. All team members are staff of the King County Department of Natural Resources Water and Land Resources Division.
Table 2. Project team members and responsibilities
|Name/Telephone |Title |Affiliation |Responsibility |
|Curtis DeGasperi |Water Quality Engineer |Water and Land Resources |Project manager for the Major Lakes |
|(206) 296-8252 | |Division |Temperature Study, data QA/QC, |
| | | |managemnent, and reporting. |
|Katherine Bourbonais |Laboratory Project |Environmental Laboratory |Coordination of field activities |
|(206) 684-2382 |Manager | | |
|Bob Kruger |Environmental Laboratory |Environmental Laboratory`|Coordination of sampling activities, |
|(206) 684-2323 |Scientist | |field QA/QC, and field analyses. |
|Colin Elliott |Quality Assurance Officer|Environmental Laboratory |Overall project QA/QC. |
|(206) 684-2343 | | | |
|Jonathan Frodge |Senior Water Quality |Water and Land Resources |Program Manager for Major Lakes |
|(206) 296-8018 |Planner |Division |Monitoring Program. |
DATA QUALITY OBJECTIVES
Data quality objectives typically involve specifications of the required precision, accuracy, and tolerable bias of the data. Discussion is also provided that describes the methods used to ensure that the data are representative of the population targeted for sampling, comparable to other similar studies. Methods and procedures used to minimize the loss of usable data are also described.
Precision
Data precision is the degree of agreement among repeated measurements on the same sample (laboratory replicate) or on separate samples collected as close as possible temporally and spatially (field replicate). A measure of precision gives one an idea of how consistent and reproducible your field or laboratory methods are. However, precision does not reflect how “true” or accurate the results are.
Accuracy and bias
Accuracy is a measure of confidence in the data. The smaller the difference between the measurement and the “true” value, the more accurate the results. The pattern of these differences (typically higher or lower) indicate the amount of bias in the results. Results with high precision and low bias are more accurate than results with high bias and precision or high bias and low precision. Results may still be accurate if they have low bias and precision, but there will tend to be a random scatter of results around the true value.
Table 3 provides the manufacturers information on the precision, accuracy, and response time of the thermistors and pressure transducers selected for use in this program.
Other, often neglected, considerations for accuracy are the clock times of the computers used to set the field instrument clocks and the accurate documentation and tracking of either Pacific Standard or Pacific Daylight Time as the starting time when the field instrument is launched. As described above, computer clocks should be synchronized with local network time on the morning of a planned field deployment and checked against atomic clock time and adjustments made as needed. Strict adherence to these protocols will ensure that the RBR clocks are accurate to within a minute of local time over the course of a 6 month deployment. The Onset clocks are less accurate, but still should be accurate to within several minutes over the course of a 6 month deployment.
Another significant consideration is the accuracy with which one can determine the water depth of each thermistor. This will depend on accurate measurements of the Onset thermistor strings built for this program and accurate recording/measurement of the depth below the water surface to the first thermistor. It is hoped that the accuracy of determination of the depth to any particular thermistor be no less than ±10 cm (~4 in).
|Table 3. Summary of instrument precision, accuracy and response time |
|Instrument |Range |Accuracy |Resolution |Response Time |
|Richard Brancker Research (RBR) |
|Thermistor (XR-420-T24) |-5 to 35 oC |±0.002 oC | ................
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