Prepared in cooperation with the U.S. Fish and Wildlife Service

Guidelines for the Collection of Continuous Stream 

Water-Temperature Data in Alaska

U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2014–1182

Guidelines for the Collection of Continuous Stream 

Water-Temperature Data in Alaska

By Ryan C. Toohey, Edward G. Neal, and Gary L. Solin

Prepared in cooperation with the U.S. Fish and Wildlife Service

Open-File Report 2014–1182

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2014

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Suggested citation:

Toohey, R.C., Neal, E.G., and Solin, G.L., 2014, Guidelines for the collection of continuous stream watertemperature data in Alaska: U.S. Geological Survey Open-File Report 2014-1182, 34 p., 

http://dx.doi.org/10.3133/ofr20141182. 

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iii

Contents

Abstract ...................................................................................................................................................................... 1

Introduction................................................................................................................................................................. 2

Purpose and Scope .................................................................................................................................................... 2

Preparation ................................................................................................................................................................. 3

Developing a Study Plan......................................................................................................................................... 3

Site Selection .......................................................................................................................................................... 3

Equipment Selection and Deployment .................................................................................................................... 4

Recording Temperature Sensors ........................................................................................................................ 4

Programming Recording Intervals ....................................................................................................................... 5

Field Instruments................................................................................................................................................. 5

Field Thermometer and Temperature Sensor Accuracy Check Procedures........................................................ 5

Training................................................................................................................................................................... 6

Field Procedures......................................................................................................................................................... 7

Site Selection and Installation Procedures for Continuous Measurement Sensors................................................. 7

Site Visits and Field Measurements........................................................................................................................ 9

Stream Temperature Cross Sections Using the Equal Width Increment Method .............................................. 13

Routine Site Visits ............................................................................................................................................. 13

Record Computation................................................................................................................................................. 14

Data-Processing Procedures ................................................................................................................................ 14

Initial Data Evaluation........................................................................................................................................ 15

Data Corrections ............................................................................................................................................... 22

Final Data Evaluation ........................................................................................................................................ 24

Reporting .............................................................................................................................................................. 24

Station Description ............................................................................................................................................ 25

Station Analysis................................................................................................................................................. 25

Data Reporting .................................................................................................................................................. 26

Data Processing Packages and Database Management...................................................................................... 26

Database Management ..................................................................................................................................... 28

Summary .................................................................................................................................................................. 28

References Cited...................................................................................................................................................... 29

Appendix 1. Photograph showing Example of a Self-Contained Temperature Recording Devise and 

Protective Housing.................................................................................................................................................... 31

Appendix 2. Example of a Station Analysis for Water Temperature on Terror River near Kodiak, Alaska................ 32

Figures

Figure 1. Photograph of Mendenhall River, southeastern Alaska, showing poor mixing conditions during 

winter low-flow conditions because of groundwater inflow near the bank.................................................................. 8

Figure 2. Example of a stream temperature cross section showing the location of vertical temperature 

measurements using the Equal Width Increment method........................................................................................ 10

Figure 3. Example field-inspection sheet for a continuous water-temperature monitoring site showing 

inspection and cross-section survey information ..................................................................................................... 11
iv

Figure 4. Example of smooth diurnal patters in water temperature as taken from a properly functioning water 

temperature recording sensor, Old Tom Creek near Kasaan, Alaska, June–July 2011........................................... 16

Figure 5. Water temperature and repeated burial of temperature sensor at Unuk River below Blue River near 

Wrangell, Alaska, July 16–August 29, 2003............................................................................................................. 17

Figure 6. Raw water temperature values, including erroneous data resulting from sensor dewatering, 

at Kadashan River above Hook Creek near Tenakee, Alaska, June-July 1998....................................................... 18

Figure 7. Raw water-temperature data, including erroneous record of sub-zero water temperatures 

resulting from a sensor frozen in ice, at Upper Earl West Creek near Wrangell, Alaska, December 23, 

2004–January 21, 2005........................................................................................................................................... 20

Figure 8. Water-temperature data taken from a properly functioning temperature sensor on a stream with 

intermittent ice cover at the Situk River near Yakutat, Alaska, December 14, 2008–January 14, 2009................... 21

Figure 9. Two-point variable correction for calibration drift of a temperature sensor at Kenai River at 

Cooper Landing, Alaska, October 26–December 22, 2011...................................................................................... 23

Figure 10. Example of daily maximum, minimum, and mean water temperature taken from an annual

thermograph for Staney Creek near Klawock, Alaska, water year 2006................................................................. 27

Table

Table 1. Typical data problems with stream water temperature sensors................................................................. 15

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

foot (ft) 0.3048 meter (m)

Volume

gallon (gal) 3.785 liter (L) 

gallon (gal) 0.003785 cubic meter (m3) 

gallon (gal) 3.785 cubic decimeter (dm3) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32. 
1 

Guidelines for the Collection of Continuous Stream 

Water-Temperature Data in Alaska 

By Ryan C. Toohey, Edward G. Neal, and Gary L. Solin

Abstract

Objectives of stream monitoring programs differ considerably among many of the academic, 

Federal, state, tribal, and non-profit organizations in the state of Alaska. Broad inclusion of streamtemperature monitoring can provide an opportunity for collaboration in the development of a statewide 

stream-temperature database. Statewide and regional coordination could reduce overall monitoring cost, 

while providing better analyses at multiple spatial and temporal scales to improve resource decisionmaking. Increased adoption of standardized protocols and data-quality standards may allow for 

validation of historical modeling efforts with better projection calibration. For records of stream water 

temperature to be generally consistent, unbiased, and reproducible, data must be collected and analyzed 

according to documented protocols. Collection of water-temperature data requires definition of dataquality objectives, good site selection, proper selection of instrumentation, proper installation of 

sensors, periodic site visits to maintain sensors and download data, pre- and post-deployment 

verification against an NIST-certified thermometer, potential data corrections, and proper 

documentation, review, and approval. A study created to develop a quality-assurance project plan, dataquality objectives, and a database management plan that includes procedures for data archiving and 

dissemination could provide a means to standardize a statewide stream-temperature database in Alaska. 

Protocols can be modified depending on desired accuracy or specific needs of data collected. This 

document is intended to guide users in collecting time series water-temperature data in Alaskan streams

and draws extensively on the broader protocols already published by the U.S. Geological Survey. 
2 

Introduction

Water temperature is one of the most significant factors in the health of a stream ecosystem 

(Stevens and others, 1975; U.S. Geological Survey, 2006a). Depending on the type of stream and its 

location, the natural flora and fauna establish themselves in ranges delineated by temperature. Stream 

temperature affects various fish species populations by influencing physical, chemical, and biological 

water properties (Kyle and Brabets, 2001; Alaska Department of Environmental Conservation, 2012). 

Water temperature also affects invertebrate and aquatic plant growth and can be subject to 

environmental regulation and monitoring by State, Federal, and local agencies. Accurate water 

temperature data are needed to document thermal alterations to the environment caused by natural 

phenomena and human activities (Kelleher and others, 2012). Anthropogenic or natural alterations may 

change timing, magnitude, frequency and (or) duration of water-temperature conditions. Additionally, 

determination of many other important water-quality parameters relies on accurate water temperature 

data. Temperature affects the density of water, the rate of chemical reactions, biological activity and the 

solubility of constituents (such as oxygen) in water, pH, and specific conductance (U.S. Geological 

Survey, 2006b). 

In November 2012, the Western Alaska Landscape Conservation Cooperative, the Northwest 

Boreal Forest Landscape Conservation Cooperative, and the Alaska Climate Science Center hosted a 

stream and lake temperature-monitoring workshop in Anchorage, Alaska (Reynolds and others, 2013). 

Water-temperature data are collected by many of the academic, Federal, state, tribal and non-profit 

organizations in the State of Alaska at different spatial and temporal resolutions

(http://aknhp.uaa.alaska.edu/aquatic-ecology/akoats/). Each one of these entities has its own procedures 

and instrumentation to measure water temperature in Alaskan streams. One of the primary goals of the 

workshop was to discuss the possibility of developing a statewide stream-temperature-monitoring 

program in Alaska with different data contributors. Because of these differences in resolution, 

procedures, and instrumentation, this report was produced o offer adaptable standardized protocols for 

continuous water-temperature monitoring in data measurement, collection, storage, and analysis. For 

Federal fiscal years 2014–15, the Western Alaska Landscape Conservation Cooperative has committed 

to facilitating advancements in water-temperature monitoring and its connections to temperature change, 

other physical and hydrological processes, and biological resources (Reynolds and others, 2013). 

Purpose and Scope

This report describes procedures to collect, process, and report continuous temperature data at 

stream temperature monitoring stations located in various settings in Alaska, with a particular emphasis 

on temperature monitoring in cooler climates. Standardized procedures that could be used by 

organizations to collect and manage continuous temperature data at stream monitoring stations located 

in various settings are described. Many of the protocols in this document are derived from U.S. 

Geological Survey (USGS) National Field Manual, chapter 6.1 (U.S. Geological Survey, 2006a) and 

USGS Techniques and Methods, Book 1, chapter D3 (Wagner and others, 2006). These resources also 

should be referenced for additional data-quality standards and more details in documentation of 

protocols. 
3 

Preparation

Developing a Study Plan

The primary factors to consider in selecting a water-temperature monitoring site are the purpose 

of monitoring and the objectives of data collection. Often, the objective of data collection is selecting a 

location that represents the average condition of a reach. However, another common purpose might be 

to collect water-temperature data at a specific location (that is, where fish spawn, and so on) rather than

a location that simply represents the average condition of the reach. Data collection objectives can 

describe the data methodology, instruments, and type of records. In conjunction with the study purpose, 

data collection objectives should be developed for the amount or duration of data collection (that is, 

1,000 records or 5 years) or the accuracy of the data to be collected (that is, temperature sensors that 

have an accuracy of ≤ 0.2 °C). The data collection objectives should be stated in a quality-assurance 

plan written at the initiation of the project. The preferred quality-assurance plan is one specifically 

written for the study. Quality-assurance plan templates are provided by many different agencies or 

groups (Alaska Department of Environmental Conservation, 2011, Zender, 2014). Alternatively, a

generic plan that describes a region-wide water-temperature data-collection program also can be used. 

All other factors used in the site selection process should be balanced against the purpose and objectives 

of the study (U.S. Geological Survey, 2006a; Wagner and others, 2006). 

Site Selection

Site selection depends on the purpose of the study. The location of the temperature sensor in the 

stream channel may be the most important factor in collecting representative water-temperature data. 

Sites are ideally located where good mixing characteristics assure an even temperature distribution. If 

possible, braided channel reaches, backwater or slough areas, and shallow riffles should be avoided. 

These areas often do not have homogeneous temperature cross-sections or can provide challenges for 

keeping temperature sensors submerged in the water year round. However, another common purpose of 

study includes determining the effect of certain points (that is, tributaries, facilities that discharge water, 

and so on) on stream temperature. For these purposes, the data-quality objective may be to understand 

how mixing of different water bodies occurs. 

Obtaining recorded measurements representative of the water body typically is an important 

data-collection objective. To achieve this objective, the temperature sensor should be placed in a 

location that represents the water body being measured. The sensor should be installed in the stream or 

water body such that recorded water temperature is unaffected by the installation. Cross-section surveys 

of water temperature should be made to determine the most representative location for placement. A site 

should not be selected without first determining that the temperature distribution is uniform throughout 

the cross section. Sufficient measurements must be made at the cross section to determine the degree of 

mixing at the prospective site under different flow conditions and to verify that cross-sectional 

temperature variability does not exceed that needed to meet data collection objectives. Cross-sectional 

temperature variability should be as minimal as possible, but those requirements are ultimately 

determined by the study’s data-quality objectives. Finally, a survey for human, bear, or beaver (or other 

biotic influence) activity may be an additional consideration when locating a sensor. 
4 

Equipment Selection and Deployment 

The selection of a water-temperature monitoring instrument to collect water temperature 

involves three major interrelated elements: (1) the purpose of the data collection, (2) the type of 

installation, and (3) the duration, accuracy, and precision requirements of the data-collection objectives 

(U.S. Geological Survey, 2006a; Wagner and others, 2006). Other factors to consider include sensor 

memory capacity, price, battery life, programming versatility, and durability. General calibration 

procedures for temperature sensors are described in this report. However, because of the large number 

of manufacturers and models, the manufacturers’ instructions and recommendations should be carefully 

followed. Finally, with each new instrument, it is good practice to record calibrations, maintenance, and 

history of use in a log book. 

Recording Temperature Sensors

There are many manufacturers and models of temperature sensors and data loggers. Many of 

these configurations are self-contained units that both measure and record temperature data. In some 

cases, temperature may be measured using a temperature sensor attached to a shore based data logging 

device that can be used to record various environmental parameters. When selecting a temperature 

sensor it is important to consider how the device will be installed and if features of the temperature 

sensor will satisfy data collection objectives. Most manufacturers provide product specifications. 

However, the user should verify the accuracy claimed by the manufacturer for the range of application. 

At a minimum, the data-quality objectives of most temperature-monitoring efforts will likely be met if 

the instruments have an accuracy of ±0.2 °C or less. 

Even durable temperature sensors can be damaged or lost in the harsh environmental conditions 

encountered in most streams. Flood flows often transport large amounts of sediment and debris and are 

capable of scouring study reaches or burying sensors. Similarly, in Alaska’s cold climates, ice break-up 

events can damage or transport sensors that are not suitably secured and protected. Most temperature 

sensors should be in protective housing and have anchors at sites where there is the possibility of loss or 

damage. The type of protective housing will depend on the selected temperature sensor and installation 

method. An example of a typical recording temperature sensor and protective housing are provided in 

appendix 1. Because of their greater precision, submersible temperature sensors mounted in durable 

flow-through housings are preferred over non-submersible temperature sensors installed in sealed 

waterproof housings (Dunham and others (2005). 
5 

Programming Recording Intervals

The recording time interval is determined by the data collection objectives, storage capacity of 

the recorder, time between field visits, and the magnitude of diurnal (daily) temperature fluctuations. 

Desired recording intervals should be defined in the quality-assurance plan prior to temperature sensor 

installation. Longer recording intervals result in reduced temporal resolution that may fail to record the 

actual range of temperature variation at a site. This is particularly important if instantaneous 

measurements of temperature such as the daily maximum or minimum are critical data collection 

objectives. In most cases, a recording interval of 30 minutes should provide adequate resolution to 

determine actual daily maximum and minimum temperature values. A shorter interval of 15 minutes 

might be necessary to provide suitable resolution on smaller rivers and streams that are subject to large 

or rapid variations in temperature. Longer intervals of 60 minutes might be appropriate on larger rivers 

where temperature change could be somewhat slower due to the size of river. In Alaska, monitoring 

sites might be remote with limited site visits; therefore, memory capacity available between site visits 

needs to be sufficient for the data-recording interval. 

Field Instruments

Field temperature sensors are used during site visits to verify that recording sensors are operating 

correctly, to provide an independent check of temperature changes during the site visit, and to make 

cross-sectional surveys to verify that the recording sensor is providing temperature data representative 

of the stream cross section. Digital readout thermistors are the most commonly used device for 

collecting field measurements of water temperature. A thermistor is a type of resistor whose resistance 

varies with temperature. Similar to recording sensors, there are many manufacturers and models of 

digital field thermistors. A suitable field thermistor should have an accuracy of ± 0.2 °C or less. Most 

manufacturers of digital thermistors provide detailed information on the accuracy of their instruments. 

Thermistors that are traceable to National Institute of Standards and Technology (NIST) standards are 

available and reliable. Users should verify the accuracy claimed by the manufacturer for the range of 

application. Regardless of the type of temperature sensor selected for field measurements it should be 

transported in a protective case designed to reduce shock and vibration. 

Field Thermometer and Temperature Sensor Accuracy Check Procedures 

For temperature measurements, an accuracy check at specified temperatures is done using a 

thermometer that is certified by the NIST, is manufacturer-certified as NIST traceable and carries a 

current NIST certification, or is NIST-traceable certified that is no more than 2 years old or still current 

according to the manufacturer. The desired accuracy for the NIST thermometer is ±0.1 °C or less. If a 

field instrument fails the accuracy check (typically agreement within ±0.2 °C of the reference 

instrument), it should not be used. Some thermistors can be calibrated following the manufacturer’s 

instructions and some may need to be returned to the manufacturer if they fail the accuracy check. Field 

instrument checks should be performed at least once every year. More frequent accuracy checks may be 

needed based on manufacturer’s recommendations or to meet data collection objectives. The actual time 

between instrument checks depends on manufacturer recommendations, frequency of thermometer use, 

and the conditions to which it has been subjected during field operations and storage, or if consistent 

differences are noted between a field thermistor and installed temperature sensors. Recording sensors 

should undergo a calibration check prior to and after installation. 
6 

Users can do the annual check of field thermistors an office or laboratory, or can have the checks 

done at an NIST-accredited commercial laboratory. To check a thermistor, test its readings across a 

range of temperatures as described in the instructions for water-bath calibration check procedures. 

Calibration checks should bracket the temperature range expected to be detected in the field. It is 

recommended that the thermistor be checked at five values (a minimum of three) between 0.0 and 40 

°C, which is typically less than or greater than most flowing stream temperature minimums and 

maximums recorded in natural streams. Any digital thermistors checked that differ by more than 0.2 °C 

from the NIST laboratory thermometer should not be used (U.S. Geological Survey, 2006a). 

Accuracy Check Procedures

• Fully submerge the thermistor into a refrigerated water bath. If a commercial refrigerated water bath

is not available, an insulated 5 gal container may be used. A mixing device is required to circulate 

the water in the container. Fill the container with water near the desired temperature and allow the 

temperature of the bath to stabilize for several minutes. When checking recording temperature 

sensors, set the recording interval to 1 minute (or less) and keep the sensors submerged. Keep 

calibration and field temperature sensors submerged throughout the calibration process without 

contacting the sides or bottom of the insulated container. 

• With the water circulating, the water temperature should stabilize. At this point, record the time,

water temperature value measured from the NIST thermometer, and water temperature measured 

from the field thermistor. Compare the NIST thermometer value with each of the temperature 

measuring devices being checked. If a recording temperature sensor does not have a display, then 

complete the comparison after downloading the recorded data. Repeat this step for the three or more 

temperatures to be checked. Record all thermometer readings throughout the warming and cooling 

periods and while maintaining circulation of the water. 

• Check meter batteries periodically for proper voltage when using a thermistor. 

• Record the calibration check data in the instrument log book for each thermometer, including 

thermistor-containing field meters. Maintenance performed or repairs by the manufacturer should be 

noted in the instrument log book. 

Training

Training of field personnel is critical to ensure collection of high quality water-temperature data. 

Training should include data collection methods, procedures, and equipment operation. There are a wide 

variety of temperature data recording devices and thermometers. Field personnel should be trained in 

the data collection activities including operation, programming, and data management tools for each 

type of temperature sensor used. Project leaders and experienced data collection personnel familiar with

continuous water-temperature monitoring should design and conduct the training. 
7 

Field Procedures 

Site Selection and Installation Procedures for Continuous Measurement Sensors

Generally, the most important data collection objective for continuous water-temperature 

monitoring sites is that the temperature sensor records water-temperature data representative of the 

actual stream temperature. Prior to temperature sensor installation, surveys of the cross-sectional 

variability of water temperature are needed to determine if the site can readily provide a representative 

temperature record. Ideally, a number of cross-sectional surveys representing a range of flow and 

seasonal conditions would be collected to determine if discharges or seasonal changes affect spatial 

patterns of water temperature variability at the site prior to the installation of a temperature sensor. For 

reconnaissance purposes, this typically can be done quickly in a small stream by submersing a field 

thermistor in the stream and noting water temperature as the cross section is traversed. After a 

potentially suitable site is identified, detailed and systematic temperature measurements of the cross 

section will be required. Detailed instructions for recording cross-sectional temperature measurements 

are provided in the section, “Site Visits and Field Measurements.” 

Stream cross sections that exhibit good mixing characteristics and even temperature distributions 

during high or moderate flows may have poor mixing and uneven temperature distributions during lowflow periods. For example, figure 1 shows a glacier stream that is laterally stratified during winter lowflow conditions because of warmer groundwater inflow near the bank. This same reach is well mixed 

and thermally homogeneous during the runoff season. Because of these types of conditions, site 

reconnaissance and installation should be conducted during low-flow conditions if possible. 

In addition to having a homogeneous temperature distribution across the monitoring cross 

section, a good monitoring reach should be straight and have a uniformly shaped channel (Rantz and 

others, 1982). There should be no tributaries immediately upstream of the reach unless the purpose of 

the temperature measurements is to look at mixing from different sources. Mean cross-sectional stream 

velocities should be uniform temperature across the section. The water-temperature sensor should be 

located such that it remains submerged under low flow conditions. Ideally, the depth of water over the 

sensor should be at least 1 ft, although this may not always be practical under all flow conditions or in 

smaller streams. The sensor should not be located in a position where it could be frequently buried with 

streambed sediments or have direct exposure to sunlight. If possible, more than one sensor may be 

installed at each monitoring site to ensure redundancy, to minimize data loss resulting from malfunction 

or operator error, and to allow for data comparison. 
8 

Figure 1. Photograph of Mendenhall River, southeastern Alaska, showing poor mixing conditions during winter lowflow conditions because of groundwater inflow near the bank. Photograph by Edward G. Neal, U.S. Geological 

Survey, November 12, 2009. 

Most water-temperature monitoring sites will not have all of the desired physical characteristics 

of an ideal site. The methods used to install the temperature sensor will depend on the type of sensor 

selected and the physical conditions at the monitoring site. For example, positioning the temperature 

sensor in a deep pool may be the best option to assure it remains submerged during all flow conditions. 

Under these circumstances, comparative cross-sectional measurements of water temperature might be 

conducted downstream of the pool across a section that is readily traversed. Field personnel will be 

required to balance desired site characteristics with practical aspects of site access and field data 

collection. 
9 

Site Visits and Field Measurements

To generate accurate and complete water-temperature records, recording temperature sensors 

must be compared periodically to field measurements of water temperature. The primary objective of 

the field measurements is to determine if the recording sensor is representative of the actual water 

temperature; therefore, simultaneous values recorded by the temperature monitoring device and by field 

personnel must be documented. Records from the recording temperature sensor will have to be 

corrected accordingly if significant differences exist between the temperature measured with the field 

thermometer and the recording temperature sensor. The application of corrections is discussed in greater 

detail in the section, “Record Computation.” 

Water temperature should be measured and recorded at least once during each site visit to 

document whether or not a correction to the recorded value is needed. If the sensor appears to be fouled 

or exposed to air, then additional measurements would be needed after these situations are remedied. 

The time and location of the field values should be recorded on the field notes with comparable readings 

from the temperature monitor. Water temperature can change rapidly over time. If it is not possible to 

obtain live readings from the recording temperature sensor, it will be necessary to measure and record 

field values as near as possible to the monitor’s recording intervals. For example, if the monitor records 

at 15 minute intervals it would be important to synchronize field measurements to these same 15 minute 

intervals. It is important to note any differences in field personnel watch time and recorder time, as the 

field values will need to be compared to recorded values to accurately compute the temperature record.

Water temperature should always be measured in situ, and preferably in a location immediately adjacent 

to the recording sensor. Field measurements should be conducted with a thermometer that has had its 

accuracy checked with a NIST thermometer. When measuring the in situ field water temperature during 

sunny conditions, shade the field thermometer from the sun. 

Cross sectional measurements of stream temperature should be conducted twice annually, 

preferably over a range of discharges and seasonal conditions. The Equal Width Increment (EWI) 

method is used to divide a selected stream cross section into increments of equal width. The EWI 

temperature measurement locations are at the midpoint of each width increment. The EWI method 

usually results in a composite temperature value that represents the arithmetic mean of the stream cross 

section being measured. This cross sectional mean value can be compared to readings from the installed 

temperature sensor. Additional discussion and information to assist in selecting sampling locations is 

available in chapter A4 of the USGS National Field Manual (U.S. Geological Survey, 2006b). 

A graphical example of a EWI cross section is provided in figure 2. A field form for recording

field measurements using the EWI method is shown in figure 3. Five measurement locations is the 

minimum for water temperature cross sections using the EWI method, but at least seven measurement 

locations are recommended (U.S. Geological Survey, 2006b). Measurements at additional locations in 

the cross section are suggested when temperature variations in the cross section are greater than 0.2 °C. 

A tagline, non-stretchable cloth or metal measuring tape, or other measuring method is used to obtain 

horizontal distances across the stream. If a distance measuring device is not available to accurately 

measure stream width distances, estimating distances or visually subdividing the stream is preferable 

over no cross-sectional measurements. The location and water temperature measured at each 

measurement location should be noted. The number of cross sections obtained each year should meet 

the stated data collection objectives defined in the quality assurance plan. 
10

Figure 2. Example of a stream temperature cross section showing the location of vertical temperature 

measurements using the Equal Width Increment method. Temperatures are in degrees Celsius (°C).
11

Figure 3. Example field-inspection sheet for a continuous water-temperature monitoring site showing inspection 

and cross-section survey information. 
12

Figure 3.—Continued
13

Only one water temperature value is measured at each increment. This value can be measured at 

mid-depth or as close to the surface as 20 percent of the total depth at each increment. Uniform mixing 

with depth should be checked as part of the site selection process. The depth or location in the 

measurement increment needs to be noted. Many cross sections will be well mixed and have uniform 

water temperatures over the measured depths. Exceptions may include streams that are located near lake 

outlets, have significant groundwater contributions, or are just downstream of a tributary or discharge 

facility. If these types of sites are monitored, they should be routinely checked for uniform mixing. 

Stream Temperature Cross Sections Using the Equal Width Increment Method

• Make cross-sectional water temperature readings (fig. 2) to determine the temperature variability of 

the stream section adjacent, or as close as possible, to the sensor recording water temperature data. 

A hand-held digital thermistor may work well for this purpose. 

• Record the water temperature values from the cross-section, the time that the water temperature was 

observed, the total stream width, the horizontal distance of the reading in the stream, the sampling 

method selected, stream depth, and depth of the water temperature measurement (fig. 3). In cases 

where temperature values increase or decrease within the cross section, repeat measurements to 

confirm or identify problematic readings. 

• In a flowing, shallow stream, wade to the locations where temperature is to be measured. Prevent 

erroneous readings caused by direct solar radiation by standing so a shadow is cast over the field 

thermometer. 

• In a stream that is too deep or swift to wade, measure temperature increments by lowering a 

thermistor probe attached to a weighted cable, line, or rod from a bridge, cableway, or boat. 

• In slow or still-water conditions, measure temperature at multiple depths at several points in the 

cross section to check for vertical temperature stratification.

• Immerse the sensor in the water to the correct depth and hold it there for no less than 60 seconds, or 

according to the manufacturer’s guidelines, until the sensor equilibrates thermally. The sensor must 

be immersed properly while reading the temperature; this might require attaching the thermistor to a 

rod or weighted cable to submerge thermistor to the desired depth. Read the temperature to the 

nearest 0.1 °C for digital thermistor readings. If possible, do not remove the device from the water 

between cross section readings.

Routine Site Visits

After sensors are installed, periodic site visits are recommended to verify that they remain in 

place, are still underwater, and are working properly. Installation problems often can become apparent 

shortly after installation. Even at seemingly ideal locations, sensors sometimes become exposed to air or 

isolated in pools or side channels during low flows. Sensors also may become buried in stream sediment 

or are lost or damaged during high flows. 

The sensor location should be described accurately after installation so that the sensor can be 

recovered over a range of flow conditions as needed. This may involve GPS coordinates, hand drawn 

maps, and a description of lateral distance from multiple recognizable reference points on the stream 

bank. Adequate notes need to be taken to document field conditions. Notes should include sensor 

movement resulting from channel migration or whether or not the temperature sensor housing is filled 

with material or covered by streambed material. Photographs from the same point and oriented in the 

same direction every time may be helpful to detect changes over time and provide an image of site 

conditions. 
14

Data loggers should be downloaded frequently to avoid data loss with additional emphasis 

during autumn flow recessions while they remain easily accessible prior to development of ice cover. 

Frequent downloading, particularly soon after initial deployment, will minimize gaps in the temporal 

record and allow an estimation of any issues with the site or the logger before significant time has been 

wasted. When it is determined that logger is functioning properly and the site is deemed appropriate for 

the type of measurement being made, site visits may be less frequent, but not longer than 1 month 

between visits (except at extremely remote sites). 

During field servicing the recorder and thermistor may need to be serviced and cleaned 

following manufacturer’s instructions. If self-contained temperature sensors are used, they should be 

inspected, data retrieved, and cleaned as needed, then returned to the installed location as found. 

Record Computation

The record-computation process verifies and validates the water-temperature data and 

documents water quality. Accurate field notes and calibration logs are essential in processing the record. 

Ideally, the technician who services the water-temperature monitor computes the data record. The 

primary steps in processing water-temperature record are an initial data evaluation, removal of 

erroneous data, application of data corrections, and a final data evaluation (U.S. Geological Survey, 

2006a; Wagner and others, 2006). The initial data evaluation should begin immediately upon 

completion of the field trip to ensure that all necessary information is available and to check for possible 

instrument malfunctions that may not have been evident in the field. Timely application of data 

corrections and initial computations are essential and can aid in determining if the sensor is functioning 

properly or needs to be replaced. 

Data-Processing Procedures

Water-temperature records should be processed in a timely manner according to the project’s 

quality-assurance plan policies. Complete and accurate field notes are essential and reduce the amount 

of time required to process the data. Corrections to data should not be made unless the cause(s) of 

error(s) can be justified, validated, or explained in the field notes, by comparison with site data from a 

duplicate recorder and information from adjacent stations. Water-temperature data processing typically 

includes five procedures: (1) initial data evaluation, (2) application of data corrections, (3) final data 

evaluation, (4) record computation, and (5) final record review. Wagner and others (2006) suggest a 

sixth procedure that includes evaluation and corrections based on cross-section averaged measurements 

of temperature; however, they note that cross-section corrections may not be applicable for 

environments with poor mixing. In poorly mixed reaches, such as downstream from a tributary, it is 

exceedingly difficult to characterize temperature variability accurately. For the purposes intended for 

these guidelines, the measurements of cross-sectional water temperature should be used to verify that 

temperatures measured at the probe accurately reflect average conditions in the stream, or alternatively, 

to exclude or downgrade the rating of accuracy for a temperature record if persistent differences in 

temperature exist within the cross section.
15

Initial Data Evaluation

Initial data evaluation is used to verify accurate transfer of raw field data to the database, to 

assess continuity and completion of the data record, and to identify and remove erroneous data. 

Standard time-series graphs (temperature/time) of the record should be plotted shortly after field visits 

to confirm accurate transfer of data and to detect any instrument recording or sensor errors. For 

example, the beginning or end of a data file may contain air temperature values that were recorded 

before and after field deployment of the sensor. These values should be deleted. Other values that need 

to be removed include any periods when the water level was below the sensor level. Erroneous data can 

result from various problems with sensors, recorders, and hydrologic or environmental conditions. 

Common sources and solutions for erroneous data are shown in table 1. 

Table 1. Typical data problems with stream water temperature sensors.

Symptom Possible 

problem

Likely solution

Water temperature sensor

Thermistor does 

not read 

accurately

Dirty sensor Clean sensor.

Erratic readings Poor connections 

at monitor or 

sensor

Tighten 

connections.

Monitor slow to 

stabilize

Dirty sensor Clean sensor.

Readings off 

scale

Failure in 

electronics

Replace sensor or 

monitor.

Water temperature data from a properly operating sensor typically yields graphs showing smooth 

diurnal patterns (fig. 4). These patterns result from water warming and cooling with daily changes in 

long- and short-wave radiation and the ambient air temperature. Smooth diurnal patterns should be 

persistent in raw data plots and departures from these patterns should be examined thoroughly. During 

the summer, the temperature data are likely to contain substantial daily oscillations and seasonally high 

maximum temperature values. During winter ice conditions, sensors can be de-watered and either 

encased in ice or in an air space between the channel bottom and the ice. Fluctuations of recorded 

temperature under these icing conditions are less dramatic, and values should remain near 0.0 °C. Air

temperature influences on a dewatered sensor is typically greater with thinner ice cover and may be 

evidenced by recorded temperatures that are well below 0.0 °C; such values do not reflect water 

temperature and should be deleted. Comparisons should be made with nearby stream temperature or 

climate station records when evaluating the data for errors. Deviations or changes in the magnitude of 

daily variation in these patterns typically result from variations in weather patterns such as prolonged 

precipitation events, warm sunny weather, or weather patterns resulting in little change in daily air 

temperature. When recording sensors are operating properly in ice covered streams, the data record

should show prolonged periods of water temperatures close to 0 °C. Although the potential exists for 

natural streams to super cool to temperatures less than 0 °C by 1 or 2 tenths of a degree (Osterkamp, 

1978), a water temperature record indicating prolonged temperatures less than 0 °C may indicate the 

probe has frozen or has been exposed to air and is not accurately measuring the stream temperature. 
16

Figure 4. Example of smooth diurnal patters in water temperature as taken from a properly functioning water 

temperature recording sensor, Old Tom Creek near Kasaan, Alaska, June–July 2011.

The following sections present selected examples of erroneous or problematic water temperature

data. These examples might be common when monitoring stream temperature. The examples are 

intended to illustrate authentic examples of continuous water-temperature data with periods or 

questionable or erroneous data. The examples also provide guidance on how to identify erroneous data 

for removal. 
17

Buried Sensors

One problem inherent with placing a temperature sensor at a single location capable of recording 

water temperature over a large range of flow conditions is that it may be subject to burial as sediment is 

transported through the monitoring reach. Figure 5 shows an example of unedited temperature sensor

data where the sensor was buried in gravel during the summer run-off season. The erroneous data 

resulting from probe burial is recognizable because of the reduction in amplitude of diurnal temperature 

patterns (July 24–29, fig. 5). This example also demonstrates that simply uncovering or clearing the 

sensor may not provide a lasting solution to data collection problems. The sensor was buried again 3 

days after being cleared during a site visit. On a following site visit the probe was relocated to an 

elevated position in the water column; however, there was a risk of being exposed to air when 

streamflow recedes. When operating a temperature monitor on a stream with large seasonal variations in 

stage and sediment transport, it may be necessary to secure additional probes (or probe anchoring 

points), such that the probe can be covered by water at all stages, while remaining uncovered by stream 

sediment.

Figure 5. Water temperature and repeated burial of temperature sensor at Unuk River below Blue River near 

Wrangell, Alaska, July 16–August 29, 2003.
18

Sensors Exposed to Air or Frozen 

Under extreme low-flow conditions, temperature sensors can become exposed to air, encased in 

ice, or isolated from flowing water. A careful evaluation of raw data plots should provide clues to help 

identify these erroneous data and to facilitate edits to the water temperature record. Figure 6 shows an 

example of unedited water temperature data from a sensor exposed to air during summer conditions in 

southeastern Alaska. The large diurnal variations and elevated temperatures are quite evident for July 1–

3, but careful observation suggests sensor exposure to air probably began around the June 18, as 

evidenced by the erratic spikes in otherwise smooth diurnal patterns. For the example shown in figure 6, 

various supplementary data were reviewed to aid in evaluation of the raw temperature data. Data that 

might aid in situations such as these would include stage or streamflow data from the study site or a 

nearby streamgage, air temperature data from the study site, nearby climate data recorded by the 

National Weather Service or any alternate entity collecting climate data. 

Figure 6. Raw water temperature values, including erroneous data resulting from sensor dewatering, at Kadashan 

River above Hook Creek near Tenakee, Alaska, June-July 1998.
19

Clues provided by a hydrograph showing stream stage at the study site could aid in determining 

the dates and times the sensor was exposed to air rather than submerged in water. Therefore, the 

elevation of the sensor relative to streamgage data can and should be recorded. In an example such as 

shown in figure 6, the hydrograph of the study site or that of a neighboring stream should indicate a 

receding hydrograph (declining water levels) prior to the erroneous data record. 

Collecting an accurate water temperature record in streams that have intermittent or continuous 

ice cover during winter months often can be problematic. Ice formation during extreme low flows 

resulting from cold weather can encase the temperature sensor in ice resulting in erroneous temperature 

records. An example of an erroneous temperature data recorded under ice cover conditions on a stream 

where intermittent ice cover is typical is shown in figure 7. In this example of uncorrected temperature 

data, the sensor provides accurate water temperature near 0 °C from December 26 through 

approximately December 31 when the temperature begins to drop below 0 °C. The sensor was 

positioned so that it became encased in shore ice as the flows receded through the middle of January. 

The subzero temperature data were discarded for this period. Although water temperatures can be less 

than 0 °C under certain conditions by 1 or 2 tenths of a degree, the duration of subzero water 

temperatures is typically quite short and usually occurs just prior to ice formation on the surface of a 

stream (Osterkamp, 1978). The handling and correction of subzero water-temperature data can be 

problematic sometimes and specific guidelines are lacking. Subzero water temperature corrections will 

need to be tailored to the type (brand or manufacturer) of recording sensor being used to collect data. 
20

Figure 7. Raw water-temperature data, including erroneous record of sub-zero water temperatures resulting from a 

sensor frozen in ice, at Upper Earl West Creek near Wrangell, Alaska, December 23, 2004–January 21, 2005.
21

Figure 8 provides an example of a properly functioning temperature sensor in a stream that 

typically experiences intermittent ice cover during the winter. In this example, the water temperature 

sensor records temperatures at or near zero for extended periods, with temperatures intermittently 

greater than 0 °C. Streams under continuous ice cover typically exhibit little if any diurnal variation in 

water temperature. When a temperature sensor is functioning properly in an ice-covered stream,

recorded temperatures are typically 0 ± 0.2 °C. 

Figure 8. Water-temperature data taken from a properly functioning temperature sensor on a stream with 

intermittent ice cover at the Situk River near Yakutat, Alaska, December 14, 2008–January 14, 2009. 
22

Data Corrections

Data corrections adjust recorded water-temperature data for sensor calibration drift and sensorfouling errors that may occur during the interval between site visits because of environmental or 

instrumentation effects. Quality-control limits for correcting water-temperature data should be 

established in the study or program quality-assurance plan. Quality-control limits reduce the risk of 

retaining data from a faulty temperature sensor. The USGS uses a maximum allowable limit of 0.2 °C as 

the sum of the absolute values of all applied data corrections. If recorded values differ from the 

corrected values by more than the maximum allowable limit, then those data may be deemed unsuitable 

for use and are not reported or stored in the database. In some cases, a temperature sensor may be 

installed with a programming error, such as an improper slope, offset, or Fahrenheit versus Celsius 

units. If the data can be corrected by application of a constant correction for a known mistake or 

problem, the temperature data should be retained. 

Temperature measurement errors occur primarily from sensor calibration drift and sensor 

fouling. A data correction is required when the sum of the absolute values for fouling and calibration 

drift corrections exceed a specified data-correction threshold. The USGS data-correction threshold for 

water-temperature data corrections is 0.2 °C (Wagner and others, 2006). The USGS data-correction 

thresholds are guidelines. More or less stringent criteria may be needed to meet project or program 

objectives. These guidelines should be stated in the quality-assurance plan for the study or program. 

Measurement error from calibration drift results from electronic drift in the recording sensor 

reading from its previous calibration and is determined by simultaneous comparison of recording 

temperature sensor readings with temperature values measured with a calibrated field thermometer 

during site visits. Corrections can be applied at a constant rate over time of the site visit interval or as 

two-point corrections for non-uniform error that is prorated over time. For water-temperature data, the 

correction most frequently used is the two-point calibration drift over time, based on field visit dates and 

correction values (fig. 9). The corrections to the data between the start and end dates of the correction 

period are linearly interpolated (Wagner and others, 2006). In some instances, a correction for 

calibration drift will be held constant throughout time between site visits, as it is common to find some

recording sensors with a persistent but consistent small error. 

Data corrections typically have a starting date and time delineating the correction interval. The 

dates and times of these intervals usually begin and end on site visit dates. Exact procedures for the 

application of data corrections will depend on the data processing package selected to compute final 

water temperature values. 
23

Figure 9. Two-point variable correction for calibration drift of a temperature sensor at Kenai River at Cooper 

Landing, Alaska, October 26–December 22, 2011.
24

Final Data Evaluation 

Following the application of data corrections, the technician providing quality control for the 

water temperature record should review the data record, check data corrections, and apply any needed 

final corrections. Data used in producing the final water-temperature record should be checked 

thoroughly for completeness and accuracy before final review, approval, and release. Checking and 

reviewing of the water-temperature record should include examination from at least one additional 

technician familiar with the computation of water-temperature records. Two independent reviews should 

help to eliminate most computational errors from the record. To adequately check or review watertemperature records, all field data should be verified for accuracy of transcription from field sheets or 

missing electronic information; all data corrections must be checked to ensure that the correct values

were used; and all dates and numbers in the report for the site should be checked for accuracy.

Accuracy Assessment 

An assessment of the overall accuracy of the water-temperature record can be made using certain

criteria used by USGS (Wagner and others, 2006). The accuracy rating is based on data values recorded 

before any data corrections are made after the record has been evaluated and data corrections applied. 

One of four accuracy classifications ranging from excellent to poor is applied to the record. Excellent 

record is deemed to be accurate within 0.2 °C; good is from 0.2 to 0.5 °C; fair is from 0.5 to 0.8 °C; and 

poor is more than 0.8 °C. This accuracy rating can be different for discrete periods of record based on 

the combined fouling and calibration drift corrections applied to the water-temperature record. A 

decision based on professional judgment should be made as to whether to approve and release poor 

records or when the data quality is not known. 

Rating the accuracy of the record also can be based on an evaluation of the proportion of 

approved and final record, the amount of data corrected, frequency of site visits, and quality-control data 

used to make adjustments to the record. Record that has numerous and inconsistent data corrections may 

indicate the sensor has calibration stability issues that provide less reliable data. The quality rating of the 

record also may be lowered because of frequent gaps in the record. Missing data or data that do not meet 

the criteria for maximum allowable correction limits may have a varied range of effects on the accuracy 

rating of the final data, depending on the situation; the decision to approve and release the data is left to 

the professional judgment of the personnel computing and reviewing the record (U.S. Geological 

Survey, 2006a; Wagner and others, 2006). 

Reporting

Documentation of the data record typically includes a report and analysis with several 

components, including descriptions of the site, the equipment installed, the data collected, and the 

corrections applied. 
25

Station Description

The station description contains information about the location, history, and operation of the 

water-temperature monitoring site. A complete station description should facilitate finding the site and 

executing the tasks necessary for an effective site visit. Changes in location, instrumentation, operation, 

or land use should be recorded in the station description. The frequency of site visits should be recorded 

in the station description. A complete description should be prepared for each monitoring station and 

revised as needed. Contents of the station description may vary from station to station, but should 

include the following: 

• Location of the station; 

• Station history; 

• Drainage area; 

• Channel characteristics; 

• Methods for making temperature measurements; 

• Historical extremes; 

• Cross-section surveys; 

• Purpose of monitoring; 

• Maps, photographs, and permits; 

• Safety hazards, detailed directions to the site, and access remarks. 

Station Analysis

The station analysis presents a concise and accurate summary of site conditions and includes 

how the water-temperature data are compiled and computed. A station analysis should be written for 

each station providing water temperature record (appendix 2). Records of cross-section surveys and 

extreme values should be updated annually in the station analysis. The following compilation of station 

analysis attributes recommended by the USGS was modified from Wagner and others (2006): 

• Measurement locations—Station identifier, year, parameters measured, and measurement and 

recording frequency; 

• Equipment and instrumentation—Type of equipment used and dates sensor or equipment was 

moved or replaced; 

• Site characteristics—Description of the study reach, location of recording sensor, and any 

features that may pertain to the quality of the record; 

• Record—Record of how the raw data were manipulated to generate final record and note any 

missing record and reasons why it was missing. Include data collected but not retained. Include 

rating of accuracy for the period of record; 

• Calibration—Provide documentation of calibration procedures or instrument checks; 

• Computations—Statement of how and why data corrections were applied to the data, list 

extreme data correction values applied to data during the year, and list any abnormal data or data 

corrections; 

• Cross-section surveys—How, where, and when the cross section was measured, the number of 

verticals, and variation (or lack of) of measurements across throughout the cross section; 

• Remarks—Any additional relevant information that does not fit within the other sections; 

• Discussion—Description of patterns within the data and their relation to other datasets or 

significant events; 

• Date and name—Identify preparer, checkers, and reviewers.
26

The station analysis should enable the reader to determine how the record was processed, 

corrections that were applied, and reasons for their application. Rationale used to determine the final 

accuracy ratings for the record also should be included in the station analysis. 

Data Reporting

The desired water-temperature data reporting accuracy should be described in the study purpose, 

data-quality objectives, or program quality-assurance plan. The USGS databases typically report 

temperature measurements rounded to the nearest 0.1 °C (U.S. Geological Survey, 2006a). If finer 

resolution in the data is required, temperatures can be reported to the nearest 0.01 °C, provided that 

instruments are capable of the desired accuracies and the data are reproducible. Operation of continuous 

water-temperature sensors can produce large volumes of data. Instantaneous values throughout the day 

should be recorded, checked for quality control, approved, and released. Depending on the application, a 

graphical display of the data may allow for visual detection of errors and other patterns. 

Criteria or protocols for finalizing and releasing periods of record with data gaps need to be 

defined in the quality-assurance plan. Estimating, interpolation methods and modeling techniques are 

not applied to data gaps. For example, in order for the USGS to compute daily water temperature 

statistics, the following minimum requirements apply (Wagner and others, 2006): 

• To compute a daily mean or median value on days when less than 100 percent of the discrete time 

interval data are collected, both the expected daily maximum and minimum values must be present. 

Reporting daily mean values when less than 100 percent of the unit values are available is a decision 

based on professional judgment and generally is determined by the data capture interval, by data 

trends, knowledge of site characteristics, and the influence of hydrologic events. The station analysis 

should include a discussion of how the judgment was determined. 

Data Processing Packages and Database Management

Exact methods used to edit, process, and report water-temperature data will be largely 

dependent on the data processing package selected for use. The data processing package may originate

from the manufacturer of the temperature sensing equipment, commercially purchased software, opensource software, or be developed in-house. The selection of a data processing package will be a key 

factor in facilitating accurate and efficient computation of water temperature records. A good processing 

package will have the capacity to readily graph time series data on multiple scales, which allows for 

efficient screening, editing, and evaluation of the original data. The capacity to automate linear 

interpolation and proration of data corrections over time is another desired feature of a good data 

processing package. The frequent application of prorated data corrections between site visits is common 

in processing water temperature data and the automation of this process simplifies the computation, 

checking, and review of the final data record. The capacity to round recorded temperature values may be 

another desired attribute of a data processing package. 

In addition to graphing and processing capabilities, it may be desirable to obtain a data 

processing package that readily generates tables of daily maximum, minimum, and mean temperature 

values, as well as monthly and annual mean values (fig. 10). Other desirable attributes of a data 

processing package might include data correction summaries, monthly data summaries, and annual data 

summaries. Although a typical spreadsheet package may have the capacity to generate many of these

summaries and computations, the processes used to generate the desired output can become 

cumbersome and time consuming when computing, checking, and reviewing water temperature record 

for multiple sites. 
27

Figure 10. Example of daily maximum, minimum, and mean water temperature taken from an annual thermograph 

for Staney Creek near Klawock, Alaska, water year 2006. 
28

Database Management

Effectively managing and archiving water temperature records will require a database

management plan. Development of the database management plan will be largely dependent on the 

study or program objectives as well as institutional procedures and requirements of the agency 

collecting the data. Although it is beyond the scope of this document to develop a database management 

plan, what follows are potential factors to consider in the development of a database management 

strategy:

• Data Format—A format for data storage will need to be selected (for example, html, ASCII, 

jpeg, or other formats); 

• Data Access—Determine if the data will be posted on a website or public database or limited to 

specific requests on a case by case basis. How will the data be protected from inadvertent 

changes or loss?; 

• Policies for Distribution—If data are provided for general access, disclaimers or conditions 

regarding the terms of use of the data may need to be provided; 

• Archiving—Data and metadata need to be regularly backed-up, properly indexed, and plans are 

needed to transfer data and metadata to new storage media or devices as technological standards 

or practices change. If data are retained in an internal or external central warehouse for storage, 

the data in question must meet the format requirements of the warehouse. 

Summary 

Producing records of stream water temperature that are generally consistent, comparable, 

unbiased, and reproducible requires that the data are collected and analyzed according to documented 

protocols. This report provides guidelines for developing protocols for the operation of continuous 

water-temperature stations in streams under conditions most common in Alaska. These protocols 

include site and sensor selection considerations, sensor inspection and calibration techniques, field 

procedures, data screening, evaluation, correction, and computation. Additionally, this report provides 

guidelines for stream temperature data reporting, process documentation, and data storage and 

management considerations. The guidelines provided were largely derived from protocols used by the 

U.S. Geological Survey to generate and report continuous water-quality data, but have been targeted to 

suit conditions in Alaska’s cold-water streams and rivers. 
29

References Cited

Alaska Department of Environmental Conservation, 2012, 18 AAC 70 Water quality standards: Alaska 

Department of Environmental Conservation, 

http://dec.alaska.gov/commish/regulations/pdfs/18%20AAC%2070.pdf. 

Alaska Department of Environmental Conservation, 2011, Generic tier 2 quality assurance project plan 

for water quality monitoring sampling and analysis activities: Alaska Department of Environmental 

Conservation, http://dec.alaska.gov/water/wqapp/wqapp_index.htm. 

Dunham, J., Chandler, G., Rieman, B., and Martin, D., 2005, Measuring stream temperature with digital 

data loggers—A user’s guide: U.S. Department of Agriculture Forest Service General Technical 

Report RMRS-GTR-150WWW, 15 p. 

Kelleher, C., Wagener, T., McGuire, K., and Marshall, L., 2012, Investigating controls on the thermal 

sensitivity of Pennsylvania streams: Hydrological Processes, v. 26, p. 771–785, 

http://dx.doi.org/10.1002/hyp.8186. 

Kyle, R.E., and Brabets, T.P., 2001, Water temperature of streams in the Cook Inlet Basin, Alaska and 

implications of climate change: U.S. Geological Survey Water-Resources Investigations Report 01-

4109, 24 p. 

Osterkamp, T.E., 1978, Frazil ice formation–A review: Journal of Hydraulic Engineering, v. 104, iss. 9, 

1,239–1,256 p. 

Rantz, S.E., and others, 1982, Measurement and computation of streamflow—Volume 1, 

Measurement of stage and discharge: U.S. Geological Survey Water-Supply Paper

2175. 

Reynolds, J.H., Murphy, K., and Smith, C., 2013, Alaska stream and lake temperature monitoring 

workshop, Anchorage, Alaska, November 5–6, 2012: Western Alaska Landscape Conservation 

Cooperative, http://westernalaskalcc.org. 

Stevens, H.H., Jr., Ficke, J.F., and Smoot, G.F., 1975, Water temperature—Influential factors, field 

measurement, and data presentation: U.S. Geological Survey Techniques of Water-Resources 

Investigations, book 1, chap. D1, 65 p. 

Wagner, R.J., Boulger, R.W., Jr., Oblinger, C.J., and Smith, B.A., 2006, Guidelines and standard 

procedures for continuous water-quality monitors—Station operation, record computation, and data 

reporting: U.S. Geological Survey Techniques and Methods 1-D3, 94 p. 

U.S. Geological Survey, 2006a, National field manual for the collection of water-quality data: U.S. 

Geological Survey Techniques of Water-Resources Investigations, book 9, chap. A6.1. [Also 

available at http://pubs.water.usgs.gov/twri9A.] 

U.S. Geological Survey, 2006b, National field manual for the collection of water-quality data: U.S. 

Geological Survey Techniques of Water-Resources Investigations, book 9, chap. A4.1. [Also 

available at http://pubs.water.usgs.gov/twri9A.] 

Zender Group, 2014, Blank QAPP Template: Zender Group, accessed January 2014 at 

http://www.zendergroup.org/docs/WQ-Tribal-Temp-QAPP-%202014.doc. 
30

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31

Appendix 1. Photograph showing Example of a Self-Contained Temperature 

Recording Devise and Protective Housing
32

Appendix 2. Example of a Station Analysis for Water Temperature on Terror 

River near Kodiak, Alaska

ATTACHMENT A EXAMPLE STATION ANALYSIS

Station Analysis 

15295700 TERROR R AT MOUTH NR 

KODIAK AK

Responsible Office

U.S. Geological Survey

Anchorage Field Office

1209 Orca St.

Anchorage, AK 99501

LOCATION.--Lat 57°41'41", long 153°09'42" referenced to North American Datum of 1927, in 

SW 1/4 NE 1/4 sec.5, T.29 S., R.24 W., Kodiak Island Borough, AK, Hydrologic Unit 19020701, 

(Kodiak C-4 quad), on Kodiak Island, in Kodiak National Wildlife Refuge, on right bank, 0.9 mi 

upstream from mouth, 7.5 mi downstream from Terror Lake Dam, and 29 mi southwest of 

Kodiak.

SPECIAL NOTE.--Worked by: November 3, 2009

Checked by: February 10, 2010 

Reviewed by: March 9, 2010

EQUIPMENT.--A multiple interface Sutron Accubar pressure sensor, a HIF-rented KPSI 

submersible transducer, a Therm-X 44020 water temperature probe, a tipping bucket 

precipitation gage, and a Design Analysis H-522+ high-data rate data recorder with a GOES 

radio. 

The wooden gage house was replaced by a new fiberglass and aluminum building on August 14, 

1998. The new gage house has additional space for two bunks should personnel get weathered in 

at the site.

GAGE HEIGHT RECORD.--The DCP supplied gage heights for all of the 2009 water year. Gage 

height values were supplied from the Sutron Accubar from October 1, 2008 - June 23, and from 

August 5 - September 30, 2009. The KPSI supplied gage height values from June 23 - August 4. 

The KPSI was intended to be used as a secondary instrument, but DCP logging problems were 

encountered when using two transducers. Data was downloaded to a field computer on most field 

visits and is stored in the database. 
33

WATER QUALITY RECORD.--Type of Station: Daily water temperature station recording at 60 

minute intervals.

Equipment: Therm-X 44020 temperature thermistor housed in a PVC pipe attached to the orifice. 

The lead to the thermistor is housed in flexible conduit and runs to the gage house where it is 

attached to the Design Analysis H-522+ data collection platform. 

Surface water temperature is measured each field visit using a thermometer which has been 

calibrated against a National Bureau of Weights and Measurements thermometer. Field 

thermometers are calibrated twice yearly. 

Location of Probe: Temperature sensor is mounted in a one inch diameter perforated white PVC 

pipe near the orifice on the right bank. Probe was never out of water at low gage heights, but did 

become buried in gravel, resulting in temperatures slightly lower than the actual stream 

temperatures.

Cross Section Measurements: Two cross-section measurements were taken this water year. The 

December 18 cross-section was located 10 feet below the probe due to a large gravel bar 

separating the channel across from the probe at lower stages. The August 4 cross-sectional 

measurement was located directly across from the probe. Cross section data, including date and 

time, location in the cross-section, water temperature, air temperature, stream width, discharge, 

and gage-height were entered into QWDATA. 

The sensor water temperatures and maximum and minimum cross section temperatures are: 

DATE SENSOR TEMP. X-SECTION MAX. TEMP. X-SECTION MIN. TEMP.

12-18-08 1.7 2.0 1.7

 8-04-09 11.9 11.9 11.8 

Record: Recorder provided satisfactory record of stream temperature for the water year. 

Recorder values are rounded to the nearest 0.5 °C. 

Accuracy: Record had a maximum variation of 0.3 °C between field measurements at the probe 

and the recorded values. The probe became buried in gravels late in the 2008 water year. It was 

cleaned and raised to a higher elevation on October 24, 2008, and values were found to be within 

limits. Cross-section temperatures between the recorded values and the cross-section medians 

were within +/- 0.3 °C. The maximum variation within cross-section measurements was 0.3 °C. 

Maximum daily temperature variation observed during the water year was 6.7 °C, occurring June 

10. 
34

 CORRECTION CURVES 

Correction set #1 Sensor fouling correction 2009 Water Year 

 DD 4, Temperature, water (deg C) 

 STARTS AGE ENDS INPUT CORR.

 ------------------------ --- -------------------------- ------- ------- 

PRV: 2008/09/19 12:30:00 AKDT A 6.1 0.5

 As found.

 1 2008/10/24 16:00:00 AKDT L 2.3 0.0

 As found. Raised thermistor abv stream bed.

 2 2008/10/24 16:40:00 AKDT W 2.2 0.3

 As found.

 3 2008/12/18 13:30:00 AKST W 1.4 0.3

 As found, continue correction.

 4 2009/03/31 10:00:00 AKDT W 0.2 0.3

 As found. Continue correction.

 5 2009/06/23 10:00:00 AKDT W 4.6 0.2

 As found.

NXT: 2009/10/19 12:45:00 AKDT W 6.1 0.2

 As found.

REMARKS: Record is considered fair for the water year due to the divided channel across from 

the probe location during low stage. Air temperature from Kodiak was used to help verify water 

temperatures during the year.

EXTREMES FOR CURRENT YEAR: 

MAX 13.0 °C July 11-12.

MIN 0.0 °C Many days during winter.

EXTREMES FOR PERIOD OF DAILY RECORD: 

MAX. RECORD 15.0 °C July 15, 2003

MIN. RECORD 0.0 °C Many days during winter periods.
Publishing support provided by the U.S. Geological Survey 

Science Publishing Network, Tacoma Publishing Service Center

For more information concerning the research in this report, contact the

 Director, Alaska Science Center

U.S. Geological Survey

4210 University Dr

Anchorage, Alaska 99508-4560 

http://alaska.usgs.gov
Toohey and others—Guidelines for the Collection of Continuous Stream Water-Temperature Data in Alaska—Open-File Report 2014-1182

ISSN 2331-1258 (online)

http://dx.doi.org/10.3133/ofr20141182