Forest Service Rocky Mountain Research Station General Technical Report RMRS-GTR-331 March 2015

United States Department of Agriculture

Climate, Snowpack, and Streamflow of 

Priest River Experimental Forest, Revisited

Wade T. Tinkham

Robert Denner

Russell T. Graham
Tinkham, Wade T.; Denner, Robert; Graham, Russell T. 2015. Climate, snowpack, and streamflow of 

Priest River Experimental Forest, revisited. Gen. Tech. Rep. RMRS-GTR-331. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 49 p.

Abstract

The climate record of Priest River Experimental Forest has the potential to provide a century-long 

history of northern Rocky Mountain forest ecosystems. The record, which began in 1911 with the 

Benton Flat Nursery control weather station, included observations of temperature, precipitation, 

humidity, and wind. Later, other observations stations were added to the network and observations 

were expanded to include snow courses and streamflow measurements. The region contains nearly 

all of the dominant forest types within the northern Rocky Mountains, from the xeric ponderosa pine 

forest type, to the highly mesic western red cedar type, with mesic Douglas-fir forests in between. 

Over the last century, the area has experienced an increase in minimum daily temperatures of 2.8 °F, 

while no discernable trend can be seen in the maximum temperatures. This observed increase in 

minimum daily temperature is consistent with changes expected from global warming. The total annual precipitation has not changed over the last century, while the March 1st snowpack at the lower 

elevations within the catchment has declined by over 30%. Although there is no change in total 

precipitation, there has been a 33% increase in average annual stream runoff. This change in runoff 

is attributed to both a shift in streamflow timing, due to earlier snowpack melt, and to large changes 

in tree species composition following the white pine blister rust epidemic in the 1950s. This unique 

dataset has the potential to inform managers and researchers about the changes regional climatic 

water balances may undergo as climate continues to shift.

Authors

Wade T. Tinkham is a Research Scientist, Department of Forest, 

Rangeland, and Fire Sciences, College of Natural Resources, 

University of Idaho, Moscow, Idaho. 

Robert Denner is a Forester, and Russell T. Graham is a Research 

Forester at the USDA Forest Service, Rocky Mountain Research 

Station, Forest and Woodland Ecosystems, Moscow Idaho.

Acknowledgments

This synthesis of Priest River Experimental Forest’s climate record 

would not be possible without the effort from dozens of Forest 

Service personnel who spent countless hours collecting, verifying, 

and archiving this unique dataset. The length of record has been 

maintained because of its inherent value in describing the climatic 

variables of this area; this value has been recognized since the 

establishment of the Experimental Forest. Scientists from other 

agencies and institutions outside the Forest Service have also 

Cover photo: Priest River Experimental Forest Office/Lab; the control weather station is on the right. 

(All photos provided by USDA Forest Service unless otherwise noted.)

made use of the record and contributed to its value. Gratitude 

is extended to Dr. Charlie Luce and Johanna Bell for collation 

and cleaning of early streamflow and meteorological data. The 

analysis of the data in this report was guided by Dr. John Marshall of the University of Idaho. The authors also wish to thank 

the following individuals for their thoughtful and constructive 

suggestions in the preparation of this manuscript: John Abatzoglou, Professor of Meteorology, University of Idaho; Ronald 

Miller, Science Operations Officer, National Weather Service, 

Spokane, Washington; Timothy Link, Professor of Hydrology, 

University of Idaho; William Massman, Atmospheric Scientist, 

Rocky Mountain Research Station, Fort Collins, Colorado; Larry 

Bradshaw, Meteorologist, Rocky Mountain Research Station, Missoula, Montana; L. Scott Baggett, Statistician, Rocky Mountain 

Research Station, Fort Collins, Colorado; Theresa Jain, Research 

Forester, Rocky Mountain Research Station, Moscow, ID; Brandon 

Glaza, Hydrologist, Bonners Ferry Ranger District; Bonners Ferry, 

ID; Abby Lute, Snow and Water Resources Specialist, Natural 

Resources Conservation Service, Boise, Idaho. And special thanks 

to Kathleen Graham for the hours spent proofreading this report. 
Table of Contents

Introduction .............................................................................................................. 1

Description of the Area ........................................................................................... 3

Forest Infrastructure and Data Collection ............................................................. 7

Control Weather Station ............................................................................... 7

Benton Dam Rain Gauge ............................................................................11

Benton Spring Rain Gauge ......................................................................... 12

Snow Courses ............................................................................................ 12

Benton Dam Streamflow ............................................................................. 14

Additional Data Collections ......................................................................... 15

Condensed Climatic Summary............................................................................. 19

Climate Record Trends and Patterns................................................................... 20

Precipitation ................................................................................................ 20

Streamflow .................................................................................................. 24

Temperature ............................................................................................... 29

Discussion ............................................................................................................. 33

Conclusion ............................................................................................................. 38

References ............................................................................................................. 38

Appendix A ............................................................................................................. 40

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 1

Climate, Snowpack, and Streamflow of 

Priest River Experimental Forest, Revisited

Wade T. Tinkham 

Robert Denner 

Russell T. Graham

Introduction ______________________________________________________

For over 100 years Priest River Experimental Forest (PREF), located in the northern 

Panhandle of Idaho, has served as a test site for researchers investigating timber management, wildfire research, genetic variation within conifer species, forest insect and 

pathogen vectors, watershed manipulation, and wildlife habitat (Wellner 1976). Over 

the course of the last century a detailed meteorological record has been collected and 

maintained by Forest Service personnel and collated within the National Climate Data 

Center (NCDC). This dataset is accompanied by 73 years of ongoing streamflow measurements dating back to 1939. These datasets have long been used in investigating the 

role climate plays in controlling the forest composition within PREF, with studies linking 

weather and climate to fire danger (Larsen and Delavan 1922; Hayes 1941; Barrows 

1954; Stockstad and others 1964), climate and forest production (Jemison 1934; Larsen 

1930, 1940; Duursma and others 2007), and snowpack accumulation and ablation in 

watershed management (Stage 1957; Packer 1962; Snyder and others 1975; Haupt 1968).

The climate record was last summarized by Finklin (1983) and included many dayto-day weather observations such as wind speed and cloud cover that have ceased to be 

collected. This paper does not address the character of wind speed as it is not typically 

reported to the National Weather Service (NWS) under the National Observer Network. 

Finklin developed his discussion of wind speed from data collected at the clearcut inflammability station, fire weather observations, the 150-ft weather tower, or the Gisborne 

lookout. Old photos of the control weather station clearly show at least one, if not more, 

anemometers in place. Possibly the data was collected and stored in-house and used in 

fire weather studies. One could surmise that a number of anemometers were installed 

at the control station to test and calibrate for use at regional fire weather stations. An 

automated weather station was installed in 2009 to compliment the manual instruments 

of the control station and has been recording wind speed and direction.

The PREF climate record is particularly valuable due to the lack of climate records 

in this forested region of the United States (Figure 1) and the relatively unique climate 

of this area. Situated east of the Cascade Mountains and west of the Rocky Mountain 

crest, the climate is affected by the Pacific Ocean as well as the large land area that 

weather systems must pass over to reach the site. Climate scientists refer to these effects 

as “maritime” and “continental,” respectively (Finklin 1983). The balance of maritime 

and continental influences at PREF shapes a unique climate that is more similar to southeastern British Columbia than the adjacent Rocky Mountains or Cascades. While the 

Rocky Mountain region generally receives most if its precipitation in January through 

April, PREF receives the bulk of its annual precipitation in November through January.

Persistent snowpack will form even at low elevations in PREF. However, winter 

temperatures at PREF are mild relative to locations on the eastern slopes of the Rocky 

Mountains in Montana due to the moderating effect of maritime climate, making the 

transition from snow accumulation to snow melt, especially at lower elevations, sensitive to small changes in temperature. These kinds of snowpacks have been termed “at 
2 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

risk” of transitioning from snow dominated to rain dominated (Nolin and Daly 2006) 

from climate warming. Previous studies have found trends toward warmer winters 

have caused snow to melt earlier in the spring, shifting the timing of spring floods to 

earlier in the year (Stewart and others 2005). Regional annual streamflow has also been 

shown to have decreased in major rivers across the northwestern United States (Luce 

and Holden 2009).

Within natural resource management, computer models are often employed to 

forecast future conditions or to reconstruct previous events. Examples include models 

of fire frequency and behavior, snow accumulation and ablation, streamflow, species 

distribution, atmospheric carbon sequestration, and forest productivity. These models 

are utilized by natural resource managers in making decisions, improving our long-term 

vision, and in meeting management objectives. Models of this nature serve as a looking glass, helping us view future conditions and allowing us to evaluate management 

trade-offs. Until recently, climate was often ignored within many of these modeling 

exercises, with the common assumption that climate would remain static. Advances in 

climate research over the last 20 years have shifted how we collect, utilize, and think 

about climatic records. For example, the last time climate was summarized at PREF, 

the focus was on the 11-year solar cycle (Finklin 1983) and was largely explained by 

year-to-year variability; long-term climate trends were not widely considered. But if 

climate continues to change along predicted trajectories, natural resource managers will 

be challenged with making decisions about a future that is more and more uncertain and 

in which climate cannot be assumed as static.

Figure 1—PREF in relation to neighboring states and Canada.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 3

This report summarizes the long-term climatic record of PREF, by presenting the 

annual, decadal, and climate “normal” trends between 1911 and 2013. Climate is traditionally defined as an average set of conditions; a 30-year average will be used within 

this report to describe the climate normals, which is an interval used by the NWS and 

other agencies that report long-term climatic data. These data are a useful description 

of the state of the climate during the recorded period and may provide a reasonable 

estimate of conditions in the immediate future, even if climate is gradually changing.

Description of the Area _____________________________________________

PREF occupies 6,382 acres (2,583 ha) within the Idaho Panhandle National Forest, 

in northern Idaho (Figure 1), 12.3 miles north of the town of Priest River, Idaho. Within 

PREF, there are two mountain catchments ranging in elevation from 2,220 to 5,980 ft 

above sea level (677 to 1,823 m). The landscape is occupied by Canyon Creek and 

Benton Creek, two first order headwater streams that flow westward until their confluence with the East Fork of the Priest River and the Priest River, respectively. PREF is 

located at the southern end of the Selkirk Mountains, approximately 120 miles west of 

the Rocky Mountain crest.

Within a half mile area of the headquarters site, forest types can be found that illustrate the entire range of conditions in the region from the xeric southwestern slopes 

to the more mesic northeastern slopes with a highly mesic forest system between 

(Figure 2). Most of the forest types in the northern Rocky Mountains are represented 

within PREF’s boundaries. In the years prior to the 1950s, the forest was dominated 

by western white pine (Pinus monticola), which regenerated following fires dating 

back to 1860. The mature white pine was nearly eliminated by the white pine blister 

rust (Cronartium ribicola) epidemic that struck the region and peaked in the 1950s 

(Maloy 1997). Following the blister rust outbreak, PREF was dominated by two major 

forest types of mixed western larch (Larix occidentalis) and Douglas-fir (Pseudotsuga 

menziesii) or nearly pure Douglas-fir (Wellner 1976). By 2000, the basal area on the 

forest was 35% western redcedar (Thuja plicata), 20% Douglas-fir, and 15% western 

hemlock (Tsuga heterophylla) (Duursma and others 2003). Both western redcedar and 

western hemlock are shade-loving late successional species that established under the 

canopies of the western larch and Douglas-fir and have since become the dominant 

species within the forest.

Except where silvicultural studies and harvests have taken place, the forest has largely 

escaped fire or major harvest disturbances over the last century. This lack of disturbance 

has allowed the western redcedar and western hemlock to become increasingly dominant 

over time. This is particularly true of the Benton Creek watershed (Figure 3), which 

has undergone limited cutting and no significant wildfires since the 1860s. The upper 

watershed above the Benton gauging dam had a narrow “transect” clearcut by a Civilian Conservation Corps crew in 1940 (Figure 3, LiDAR and NAIP images). The Upper 

Benton harvest covered about 95 acres (38 ha) and was situated below the Benton Spring 

snowcourse; cut in 1965 to 1966, it was broadcast burned in 1968. The other harvest 

was the Lower Benton clearcut, which harvested about 110 acres (45 ha) on the north 

and south slopes of lower Benton Creek near the gauging dam. Logging was completed 

in 1968 on the Lower Benton harvest and logging slash was burned in 1969. There has 

been additional stand thinning and harvesting, but they have been mostly reserved to 

the Canyon Creek drainage or kept small enough to not influence water flow in Benton 

Creek at the bottom of the valley.
4 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 2—Two extremes of the forested environment found in PREF. The top photo is the 

highly mesic western redcedar/western hemlock association within the Benton Creek riparian 

zone. Below is a stand of ponderosa pine (Pinus ponderosa) on a dry xeric southwesterly slope 

above Benton Creek.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 5

Figure 3—Maps of PREF, including topographic contours at 300 ft intervals (Top) and LiDAR-derived digital elevation maps 

(Bottom). Locations of infrastructure sites are also overlaid, including climate stations and snow courses. Marked sites include 

the control weather station next to headquarters (HQ), the low-elevation Benton Meadow (BMSC) snowcourse, the Benton Flat 

(BF) nursery, the Benton Dam (BD) streamflow and rain gauges, and the Benton Spring (BS) rain gauge, the Benton Spring 

high elevation snowcourse (BSSC), and the hashed polygon is the 1940 “transect” harvest.
6 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 3 Continued—Maps of PREF, including LiDAR-derived canopy height model (Top; collected in 2002) and National 

Agriculture Imagery Program (NAIP) 0.5 m aerial photograph collected in 2013 (Bottom). The “transect” timber harvest from 

1940 is still visible in both the canopy height model and aerial photograph.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 7

Forest Infrastructure and Data Collection ______________________________

Data presented in this document from sites within PREF include the control weather 

station, Benton dam raingauge, Benton Spring raingauge, Benton Meadow and Benton 

Spring snow surveys, and discharge from Benton gauging dam. Included is a brief discussion of the fire weather observations and the National Atmospheric Deposition Program.

Control Weather Station

Recording of the PREF climate record began in 1911. The NWS assisted with the 

weather station installation, provided instruments, and the protocols for observations 

and reporting. PREF is a member of the National Observation Network, station ID 

#107386. The original control weather station was established in November 1911 

at a site that is now the Benton Flat nursery (Figure 4). In 1916, the instruments 

were moved 1,500 ft (460 m) east at a constant elevation to their present location 

next to the Headquarters Building at latitude 48.3512 N and longitude -116.8355 

W (Figure 5). The station is now located on a slight rise overlooking the Benton 

Creek floodplain at 2,380 ft (726 m) above sea level. While the two sites that the 

weather station has occupied were both clearings of similar topography, the forest edge 

had already moved “much closer” by 1983 and the trees have continued to grow since. 

(This forest encroachment will be discussed in more detail later in this report.) 

Figure 4—The control weather station was originally installed in 1911 in what is now the 

Benton Flat nursery. In 1916 it was moved to its present location about 1,500 ft east and 

adjacent to the Office/Lab. In this view of the nursery site, from L. to R. is an instrument 

shelter housing the minimum and maximum thermometers, anemometers, snow catch 

instrument, and in the foreground and right, a tipping bucket and rain storage canisters.
8 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Temperatures at the weather station are influenced by nighttime inversions, which deliver cool air from upslope into the valley, especially on clear, still summer nights. The 

top of this layer of cool air occurs “a few hundred feet below the 3,800-ft elevation” 

in the summertime (Finklin 1983). Minimum temperatures averaged 4.8 °F (2.7 °C) 

cooler in the valley bottoms (2,700 ft; 823 m) than in the warmer air above (3,800 ft; 

1,159 m) (Hayes 1941). During the daytime, the inversion disappears and the normal 

cooling with elevation returns, with an observed daytime temperature lapse rate of 

4.0 °F/1,000 ft (2.2 °C/305 m) of elevation (Finklin 1983).

As a cooperative venture with the National Weather Service (NWS), daily observations of minimum and maximum temperature, liquid precipitation, and snow depth 

are collected at 1700 hours (Figures 6,7, and 8). Finklin (1983) described and manually tabulated the written records and data collected from magnetic tapes. The NWS 

provides and calibrates the thermometers, rain canisters, and dipsticks. Temperature 

is observed with NWS minimum and maximum thermometers (°F) mounted on a 

Townsend support within a Hazen instrument shelter. Precipitation is measured at 

the control weather station with an NWS 8-inch storage canister and dipstick graduated in inches, tenths, and hundredths. During the summer months, the secondary 

canister is placed within the 8-inch canister and an 8-inch funnel placed over both. 

Figure 5—An overview of the Headquarters site at the Experimental Forest, 1936. The control weather station is 

located at the center of the photo (A). The area left of the weather station, between the driveways, is the site of 

the Benton Meadow snowcourse and the present sample points 1-5. Note the lack of overstory trees within the 

snowcourse site and weather station.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 9

Figure 6—(Top) Interior view of the Hazen instrument shelter (installed 1932, still in service) at the 

control weather station. At the upper left are the National Weather Service minimum and maximum 

thermometers; below is a hygrothermograph that records temperature and humidity. To the right is a 

whirling psychrometer, used to accurately determine humidity and calibrate the hygrothermograph; 

the use of both of these instruments has been discontinued. (Bottom) H. T. Gisborne comparing 

rain gauges at the control weather station, 1936. The small, inexpensive canister on the right was 

developed at PREF for use at Forest Service facilities throughout the region. The gauge in the center 

is an electronic tipping bucket and the canister on the left is a standard Weather Service rain gauge.
10 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 8—Present day control weather station, from left, the Hazen instrument shelter, manual and tipping 

bucket rain gauges, and an automated weather station. The automated weather station was installed in 

2009 and provides hourly and daily measurements of temperature, humidity, solar radiation, wind speed 

and direction, and accumulating snow depth.

Figure 7—A view of the control weather 

station, 1932. In the center foreground is 

the Hazen instrument shelter, housing the 

minimum and maximum thermometers, 

hygrothermograph, and whirling psychrometer. To the left is a Cotton type shelter for 

housing comparative tests of instruments. 

Behind the weather station is the western 

larch “weather tree.” Instruments were 

mounted at the top of the larch to record 

wind speed, temperature, and humidity at 

an elevation above the surrounding forest 

canopy. This data was used for fire weather 

studies. Climbing spikes in the tree enabled 

scientists to reach the top and maintain 

the instruments. The man at the top of the 

"weather tree" is George Jemison, who 

started his career at PREF as a seasonal 

assistant and later went on to become the 

director of the Northern Rocky Mountain 

and Pacific Southwest Research Stations. 

He finished his career as Deputy Chief of 

the Forest Service for Research.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 11

For winter operation, the 8-inch canister stands alone; any 24-hour amount of frozen 

precipitation is moved to the office to thaw while a spare canister is substituted at 

the weather station. The thawed precipitation is poured into a secondary canister 

from which all measurements are taken. Snow fall is measured on the ground as 

both a daily sum and total snowpack accumulation. An NWS dipstick, graduated in 

inches and tenths is used to determine depth of snow. Daily snow accumulation is 

measured on a sheet of plywood painted white, which is then cleared of the snow 

and laid on top of the existing snowpack. Total snowpack is measured daily with a 

permanent staff gage. Thanks to the efforts of Arnold Finklin and others, we were 

able to gather the climate data from NCDC records (http://www.ncdc.noaa.gov/oa/

ncdc.html). The most up-to-date climatic data is available at the Moscow Forestry 

Sciences Lab, Moscow Idaho.

Benton Dam Rain Gauge

Benton Dam and rain gauge are located one mile east of the headquarters site (Figure 3).This record was condensed from a dataset provided by the NCDC, which listed 

the hourly and daily precipitation for Benton Dam from July 1948 to May 1977. Daily 

totals were culled from this dataset to produce monthly and water year totals. From 

1948 to 1977, PREF staff transcribed strip chart data to National Oceanic and Atmospheric Administration Form 79-Id and submitted to the NWS; since 1977, PREF staff 

continued to record the strip chart data and archived the data at PREF and the Moscow 

Forestry Sciences Laboratory (FSL). These data were collected by a Friez dual traverse 

recording rain gauge (Figure 9), with the strip charts analyzed by PREF personnel to 

determine hourly, daily, and monthly totals. The record now extends to 2009; however, 

problems with the rain gauge and unsuccessful efforts to replace it put a temporary hold 

on the data collection. This was remedied when an electronic tipping bucket rain gauge 

was installed in 2010.

Figure 9—Benton Creek gauging dam in 

1948. Behind the deep v-notched weir is the 

Friez dual traverse recording rain gauge. It 

operates on a 7-day chart and clock, from 

which hourly, daily, and monthly totals of 

precipitation were derived.
12 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Benton Spring Rain Gauge

The earliest continuous collection of monthly data at this site began in December 

1960 (Figure 3). The station is equipped with a 10-ft tall tower with an Alter wind shield, 

protecting an 8-inch diameter, 42-inch tall rain storage canister. The rain gauge is located 

in a small clearing at 4,775 ft (1,456 m) in elevation, above Forest Road 597-B between 

sample points 1 and 2 of the Benton Spring snowcourse (Figure 10). Measurements 

are taken on or about the first of the month with a NWS 36-inch dipstick, graduated in 

inches and tenths; these data are archived at the Moscow FSL.

In his earlier summary, Finklin (1983) noted difficulties with accurately estimating 

winter precipitation with the Benton Spring rain gauge and estimated that the measured 

mean annual precipitation of 37 inches (950 mm) should be increased to 42 inches 

(1,070 mm), a 13% increase over the raw value. The correction was based on snow 

accumulation observations from snow surveys on adjacent peaks and justified based 

on the observation that the gauge was located near trees that may have intercepted or 

redistributed snow above the gauge. A photograph in Finklin’s report (Finklin 1983, 

Figure 4B) shows trees immediately behind the gauge. The data presented here for 

Benton Spring are not corrected, but the possibility that they have underestimated real 

precipitation should be kept in mind.

Figure 10—The Benton Spring rain gauge, March 31, 2014, in about 48 inches of snow. 

The Alter wind shield surrounding the canister reduces the effect of wind on the catch of 

precipitation.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 13

Figure 11—Top photo is a view of the snow tube in use. The tubes are graduated in inches for 

measuring the depth of the snowpack and length of the snow core. The soil plug at the cutting tip 

indicates the entire depth of snow was recovered; the plug is removed and depth and core length 

adjusted. The weight of the core determines the water content of the snow. The bottom photo is 

taken at Benton Spring snowcourse, station 4, looking northwesterly over the Priest River valley.
14 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Snow Courses

Two manual snow courses are maintained in cooperation with the Natural Resources 

Conservation Service (NRCS) (Figure 3). The low elevation site, Benton Meadow (2,330ft 

or 710 m) is located just to the west of the control weather station on rolling, old forest 

ground. The Benton Spring snowcourse (Figure 11) runs between 4,770 and 4,870 ft 

(1,454 and 1,485 m) along Forest Road 597-B and occupies a west-southwesterly aspect.

Both snow courses were established in January 1937 and have continuous measurements to the present. A schedule of measurements, as prescribed by the NRCS, begins 

on or about the 1st of January (±2 days) and continues monthly until the 1st of May or 

melt-out, whichever comes first. The snowpack is measured for depth and snow water 

equivalent with a scale and standard snow survey tubes (Figure 11). NRCS protocols 

are followed for all sampling and measurement calculations, as described in USDA 

Agricultural Handbook 169.

Benton Dam Streamflow

Streamflow has been monitored on Benton Creek since 1939, by a concrete dam 

supporting a compound Cipolleti Weir with steel edged crests (Figure 12), located at 

latitude 48.3504 N, longitude -116.8100 W, and 2,660 ft (411 m) in elevation. The dam 

was designed with a concrete barrier down to the underlying bedrock to block any flow 

of water below the surface, forcing all flow through the notch of the weir, where it can 

be measured. The weir has two notches—the reference weir is a deep, narrow notch for 

low flows and a higher, wider notch to monitor high flows (Figure 12). A Boyden hook 

gauge, located in the stilling well, is used to determine the water level above the weirs 

and calibrate the recording instruments.

Figure 12—A recent view of Benton gauging dam when the recording rain gauge (right) was 

still in use. Note the development of the vegetation and the stilling rack placed at the head 

of the weir pool. The rack slows the current entering the pool and provides a calm surface 

for more accurate water level measurements.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 15

At this point in the watershed, Benton Creek is a first-order perennial headwater 

stream. The creek drains a watershed of 950 acres (384 ha) above the dam, reaching east 

to a ridge that forms the top of Gisborne Mountain, at approximately 5,500 ft (1,675 m) 

(Figures 13 and 14). The weir was constructed in 1938 because Harry T. Gisborne, then 

Fire Research Investigator for the research station, “was concerned because not one 

“Little Water” was being gauged or studied in the entire northern Rocky Mountains” 

(Wellner 1976). Early streamflow research at PREF was pioneered by Stage (1957), 

who explored the first 44 years of temperature and precipitation data and 16 years of 

streamflow data. Stage was able to create an early climatic water budget and also demonstrate the linkage between precipitation timing and streamflow discharge.

Streamflow data collection has been performed with a number of different devices 

ranging from mechanical strip charts to electronic water level sensors connected to 

electronic data loggers. The data were collated into a single time series and integrated 

to daily and monthly time steps by Link and Wei (2010) and included (1) a summary of 

paper records, (2) digitized hydrographs, and (3) data from digital recorders. In many 

instances, data gaps occurred in one record, but were filled using data from other recorders. Where overlapping records were available, strong agreement was seen between 

observations. Nonetheless, several gaps remain in the datasets. Significant portions 

(greater than 1 month) of the following years are missing: 1961, 1962, 1970 to 1975, 

1986 to 1988, and 1990.

Additional Data Collections

Throughout PREF’s history, several additional datasets have been collected in conjunction with the century-long climate record. One of the earliest mandated research 

projects by PREF scientists was undertaken in 1916 and attempted to improve 

detection and control of forest fires, emphasizing fire rate of spread, interactions with 

weather, and site conditions. These observations would ultimately lead to PREF being 

the first fire weather observation station within the U.S. Weather Bureau. These stations 

 (Figure 15) were charged with recording and relaying daily relative humidity, wind, 

and lightning activity for the months of May through October for regional radio broadcasts. These observations were collected from two sites in and around PREF from 

1922 until 1978 when they were discontinued. This undertaking was spearheaded 

by Harry T. Gisborne, who was hired in 1922 as the first full time fire scientist 

in the Northern Rocky Mountain Research Station and continued his career in fire 

studies until his death in 1949. Gisborne's efforts resulted in advances in firefighting 

techniques, improved understanding of conditions that promote fires, and the study and 

use of climatology in wildfire applications throughout the United States. Among the 

substantial fire related research accomplishments was the creation of the Model 1 Fire 

Danger Meter in 1932. This breakthrough made it possible to estimate a fire’s rate of 

spread and what actions would be needed to fight it based on physical observations of 

weather and fuels (Brown and Davis 1939). A detailed review of the fire weather data 

collection can be found in Finklin (1983). The fire research pioneered at PREF cleared 

the way and proved the need of a dedicated fire research facility, which would become a 

reality in 1960 with the opening of the Missoula Fire Laboratory in Missoula, Montana.
16 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 14—A contemporary view of Figure 13 of the Benton Creek 

watershed above the gauging dam, 2013. (Google Earth aerial view.)

Figure 13—An overview of the Benton Creek watershed, 1935. The dotted line 

represents the 950-acre (384-ha) drainage that flows over Benton Dam. Note 

the lack of harvest units in this photo. The headquarters site is in the small 

clearing at the bottom of the photo; the bare ground in the lower right quadrant 

resulted from the High Landing wildfire in 1922. (Photo by the 116th Washington 

Air National Guard, Spokane, Washington.)
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 17

More recently, PREF became a member of the National Trends Network (NTN) of the 

National Atmospheric Deposition Program (NADP), with the installation of a precipitation chemistry collection gauge in January, 2003. The program is intended to provide 

a national framework for collecting and disseminating quality-assured atmospheric 

deposition data. Each site in the network is configured with an automated precipitation 

collector and a rain gauge (Figure 16). Site operators follow standard operating procedures 

to ensure data comparability and representativeness throughout the network. Weekly 

composite samples are collected every Tuesday morning and shipped to the Central 

Analytical Laboratory (CAL) at the University of Illinois in Champaign, Illinois, for 

analysis. The CAL performs chemical analysis of the sample and returns the results on 

a monthly basis. Provided sufficient volume is available, samples are analyzed for free 

acidity (H+ as pH), conductance, calcium (Ca2+), magnesium (Mg2+), sodium (Na+), 

potassium (K+), sulfate (SO4

2-), nitrate (NO3-

), chloride (Cl-), bromide (Br-), and ammonium (NH4

+) concentrations. Figure 17 gives an example of the type of data available 

from the NADP system. Following review of the data for completeness and accuracy, 

where equipment failure, sample mishandling, and contamination are flagged, the data 

are made available on the NAPD website. A map indicating NTN sites is available on 

the NADP website, as is the complete data record for each site in the network. The 

analysis results for the PREF NTN Monitoring Location ID02 are archived at PREF 

and the Moscow FSL; they can also be found through links on the NADP website at: 

http://nadp.sws.uiuc.edu/sites/siteinfo.asp?id=ID02&net=NTN.

Figure 15—The fire weather station at PREF, 1962. This site was located on a cleared 

bench west of the county road and present entrance; it is adjacent to the Clear-Cut Inflammability Station. The small instrument shelter on the left housed the scale for weighing 

the fuel moisture sticks, which were placed outside to reflect the changes in humidity 

and fuel moisture. The Cotton instrument shelter housed a hygrothermograph and min/

max thermometers. A small rain canister is at the right, with a 20-ft wind anemometer 

located on the central pole.
18 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 16—The National Atmospheric Deposition Program site in Benton Nursery. The electronic rain gauge 

on the left records the time, duration, and intensity of precipitation events. On the right is the precipitation collector. A heated moisture sensor activates a motor that moves the peaked roof from the wet deposition bucket 

to the dry deposition bucket as precipitation begins. As a rain event ends, the sensor dries, and the roof rotates 

back to cover the wet side bucket.

Figure 17—Example of deposition concentrations from three molecules at the PREF NADP site. The two outlier peaks in the summer of 2003 and 2006 coincide with late summer wildfire smoke emission deposition.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 19

Condensed Climatic Summary _______________________________________

The climate at PREF is controlled by both large scale weather circulation patterns, 

such as the passage of warm and cold fronts, and by smaller-scale effects, such as the 

drainage of cold air downslope at night. Focusing first on the large-scale effects, the 

climate is generally intermediate between the mild climates on the western side of the 

Cascade Mountains and the harsher climate on the eastern side of the Rocky Mountains. 

Temperatures vary throughout the year, with mean monthly temperatures over the past 

century ranging from 24.4 °F (-4.2 °C) in January to 64.6 °F (18.1 °C) in July (Table 1), 

and an average annual temperature during the period of 44.1 °F (6.7 °C).

Seasonal temperatures demonstrate a pattern that is intermediate between the maritime 

conditions on the coast and the continental conditions east of the Rocky Mountains. 

Snow sustaining temperatures can persist within PREF from October until early April 

(Table 1), although temperatures are typically more moderate than those on the east 

side of the Rocky Mountains (Finklin 1983). Temperatures begin to increase by the end 

of April and by late June temperatures resemble those of the greater forested northern 

Rocky Mountains region until the fall storm track returns in early September. While 

summer temperatures rarely drop below 40 °F, below freezing temperatures have occurred in every month. From 1912 to 2013 there was an average of 173 days per year at 

the control station where minimum temperatures stayed above 32 °F (0 °C). The stable 

atmosphere PREF experiences during July, August, and September is attributed to the 

northward movement and weakening of the storm trade and subtropical high over the 

Pacific, which deters mid-latitude cyclones from impacting the region frequently and 

promotes warm, dry conditions in late summer. These persistent dry air masses have 

led to 14 days over the last 102 years with high temperatures over 100 °F (37.8 °C) in 

July and August.

PREF receives an average of 31.4 inches (798 mm) of precipitation annually at the 

control weather station near the station office, but the climate record varies widely 

with outliers ranging from 16.0 to 47.2 inches (406-1,199 mm) per year (Table 2). 

During the winter months, precipitation is carried inland along the jet stream, yielding 

40% of PREF’s annual precipitation during the months of November, December, and 

January (Table 2). The importance of winter precipitation is even more pronounced at 

high elevations within the Benton Creek watershed, where up to 60% of the annual precipitation can come in the form of snow that sometimes lingers into June. The months 

of July, August, and September account for less than 12% of the annual precipitation, 

Table 1—Monthly average and daily extreme temperatures (°F) at the PREF control weather station from 1911 to 2013.

Averages Extremes

Month Daily maximum Daily minimum Monthly Highest Year Lowest Year

 Jan. 30.5 18.3 24.4 50 2003 -33 1950

 Feb. 37.0 20.3 28.7 57 1947 -35 1933

 Mar. 45.6 24.7 35.2 71 2004 -18 1945

 Apr. 57.0 30.2 43.6 88 1934 -1 1936

 May 66.8 37.3 52.1 97 1936 18 1954

 June 73.6 43.4 58.5 97 1912 24 1918

 July 82.8 46.2 64.6 102 1924 29 1917

 Aug. 81.9 44.6 63.3 103 1961 26 1914

 Sept. 71.3 38.3 54.8 97 1988 16 1926/1934

 Oct. 55.8 32.1 44 83 1935/1943 -5 1935

 Nov. 38.9 26.7 32.8 64 1965 -16 1955

 Dec. 31.6 21.3 26.5 55 1933 -36 1968

 Year 56.1 32 44.1 103 Aug. 1961 -36 Dec. 1968
20 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

which is in contrast to areas east of the Rocky Mountain crest, where precipitation is 

more heavily concentrated in the summer and is fueled by monsoonal moisture carried 

northward from the tropics (Whitlock and Bartlein 1993). Northern Idaho is the northernmost stronghold of the summer-dry regime characteristic of northern California and 

the Oregon and Washington Cascades.

Climate Record Trends and Patterns __________________________________

Precipitation

The seasonal precipitation regime that is most typical of the northwestern Rocky 

Mountains has a pronounced dry season developing in July and lasting into September, 

while the bulk of the annual precipitation occurs during the winter months. The dry 

summers and the winter flow of moist maritime air lead to disproportionately high wintertime precipitation totals (Table 3 and Figure 18). This strongly seasonal distribution 

differs from the situation in southern Idaho and in the Yellowstone region east of the 

Continental Divide, where precipitation is more concentrated in the late fall and early 

winter (Whitlock and Bartlein 1993). The PREF control weather station receives an 

average of 31.4 inches with a Standard Deviation (SD) of 5.6 inches (x– = 797.6, SD = 

142.2 mm) annually, with no statistically significant trend in total annual precipitation 

over the last century (Figure 19, p = 0.17). Decadal and climate normal average monthly 

and annual precipitation totals are given in Table 3.

Precipitation accumulation often increases with elevation over short distances, but rates 

of increase can be difficult to predict in a given watershed. The control station (2,380 ft; 

726 m) precipitation gauge, located at the bottom of the drainage, was compared to the 

Benton Spring gauge (4,775 ft; 1,456 m), located about three quarters of the way up 

the watershed (~3 horizontal miles away) (Figures 18, 19, and 20). The strong seasonal 

dependence in precipitation is clear at both sites, with 40% and 37% of the total annual 

precipitation for the control station and Benton Spring station coming from November, 

December, and January, respectively (Figure 19). July, August, and September account 

for 13% of the annual precipitation at the control station and 12% for the Benton Spring 

station. Both gauging stations show very similar distributions of annual precipitation 

with the mean of the Benton Spring distribution being approximately 4.5 inches greater 

than the Control Station (Figure 19).

Table 2—Monthly and daily average and extreme precipitation (inches) at the PREF control weather station from 1911 to 2013.

Snowfall

Monthly Maximum Minimum Daily Daily Maximum Maximum

Month average monthly Year monthly Year average maximum Year Average monthly Year daily Year

Jan. 4.01 8.38 1954 0.27 1985 0.14 1.74 1967 25.7 89 1969 16 1969

Feb. 2.89 6.66 1999 0.20 2005 0.11 1.73 1970 14 53.3 1937 13.5 1948

Mar. 2.85 8.12 2012 0.36 1965 0.10 1.90 1966 6.5 35.2 1951 11 1916

Apr. 2.14 4.53 1955 0.30 1924 0.08 1.50 1982 0.9 10.3 1922 7 1915

May 2.35 7.13 1941 0.37 1937 0.08 3.34 1998 0 3 1943 2 1943

June 2.33 6.84 2012 0.14 1922 0.08 2.91 1992 0 2 1916 2 1916

July 1.03 4.03 1983 0.00 1960/1973 0.04 1.34 1937 0 0 0

 /2003

Aug. 1.13 4.24 1926 0.00 1931/1969 0.04 1.66 1918 0 0 0

Sept. 1.54 7.50 1927 0.01 1990 0.05 1.65 1927 0 1 1971 1 1971

Oct. 2.62 8.31 1947 0.13 1987 0.09 1.75 1951 0.6 9.5 1919 6 1919

Nov. 4.06 10.46 1973 0.11 1929 0.14 2.40 1959 9.9 60.2 1996 14.5 1996

Dec. 4.49 11.22 1933 0.91 1913 0.16 2.21 1951 24.1 68.8 2008 20 1951

Year 31.37 11.22 Dec. T Jul-73 0.09 3.34 May 81.9 89 Jan. 20 Dec. 

 1933 1998 1969 1951
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 21

Table 3—Ten-year (decadal) and 30-year “normal” average precipitation (inches) for the PREF control weather station.

Period Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Annual

Decade

1912-1920a 3.8 3.0 2.8 2.2 2.6 2.0 1.3 1.3 2.0 2.3 4.3 3.5 31.0

1921-1930 3.4 2.8 1.8 1.6 1.7 1.7 0.5 1.3 1.8 2.4 2.8 3.9 25.8

1931-1940 4.6 3.0 2.8 1.9 1.3 1.8 0.7 0.4 1.4 2.9 3.5 5.6 29.9

1941-1950 3.1 3.1 3.2 2.4 2.6 3.3 1.1 0.9 1.6 4.1 4.0 3.8 33.3

1951-1960 5.2 3.4 2.5 2.3 2.4 2.8 0.9 1.4 1.4 2.5 4.3 4.3 33.3

1961-1970 4.9 2.5 2.8 1.9 2.1 2.2 0.8 1.3 1.7 2.5 4.5 4.8 32.0

1971-1980 3.6 3.4 2.2 1.9 2.6 1.4 1.5 1.9 1.5 1.5 4.2 5.0 30.8

1981-1990 3.7 3.1 3.3 2.2 2.4 2.2 1.3 1.4 1.4 1.7 4.8 3.3 30.7

1991-2000 4.2 2.9 2.7 2.5 2.9 2.8 1.5 0.8 1.5 2.5 4.2 4.9 33.5

2001-2010 4.1 1.8 3.3 1.9 2.7 2.5 0.8 1.2 1.4 2.8 4.0 4.6 31.0

2011-2013a 3.7 2.2 5.0 3.6 3.4 4.6 1.2 0.2 0.3 3.5 6.0 4.2 37.9

30 Years

1912-1940 3.92 2.91 2.54 1.91 1.78 1.80 0.82 0.97 1.69 2.57 3.57 4.36 28.86

1921-1950 3.71 2.94 2.62 1.88 1.97 2.28 0.77 0.90 1.69 3.11 3.49 4.59 29.94

1931-1960 4.33 3.14 2.80 2.05 2.22 2.64 0.92 0.92 1.58 3.30 3.91 4.71 32.51

1941-1970 4.43 3.12 2.87 2.14 2.41 2.72 0.95 1.13 1.56 3.25 4.18 4.45 33.21

1951-1980 4.56 3.16 2.57 2.07 2.43 2.15 1.05 1.49 1.53 2.24 4.21 4.78 32.23

1961-1990 3.98 3.02 2.76 2.07 2.37 2.08 1.22 1.47 1.56 1.95 4.40 4.39 31.25

1971-2000 3.72 3.14 2.70 2.24 2.63 2.21 1.41 1.31 1.41 1.92 4.34 4.36 31.38

1981-2010 3.85 2.54 3.06 2.29 2.60 2.48 1.16 1.10 1.36 2.33 4.34 4.26 31.37

a Not full decades.

Figure 18—Monthly average precipitation and snowfall for PREF. The top chart is based 

on 51 years (1961-2012) of precipitation observations at the high elevation Benton Spring 

site. The bottom is based on 101 years (1911-2012) at the control station, with snowfall 

(open bars) plotted against the right axis, which has been scaled proportional to that of 

precipitation (black bars), assuming an average of 1.0 inch water equivalent from 12.0-inch 

snowfall. Error bars represent a 95% confidence interval throughout the time series.
22 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 20—Comparison of annual precipitation 

at high-elevation Benton Spring gauge and 

at lower-elevation control station gauge from 

1961 to 2011. The solid line represents a 1:1 

reference line and the dashed line represents 

a linear fit through the dataset. The regression 

line does not significantly differ from 1 and 

represents an average increase of 13.5% more 

precipitation received at the 4,775-ft elevation 

Benton Spring station compared to the 2,380-ft 

elevation control station.

Figure 19—Annual precipitation totals at 

PREF for both the control station and Benton 

Spring station, showing (A) the temporal variation and (B) distribution of the two stations. 

The control station shows 101 years (1912 to 

2012) of precipitation data, while the Benton 

Spring station shows 51 years (1961 to 2012). 

In order to visualize the difference in distributions, the Benton Spring station record was 

doubled so that it would show approximately 

the same number of records. While the records 

show contrasting trends in their slope, neither 

slope statistically differs from 0.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 23

Analysis shows a consistent increase in annual precipitation along an elevation gradient, with the slope of the regression not differing from 1 (p = 0.32) (Figure 20). This 

consistent increase causes the Benton Spring site to receive on average 4.5 (SE = 0.4) 

inches (x– = 114.3, SE = 10.2 mm) more precipitation in both wet and dry years (Figure 20). In his 1983 report, Finklin proposed that the Benton Spring raingauge was 

underestimating snow accumulation by 13%. If true, that would increase the snowpack 

estimates proportionally, where the proportional increase would be added to the already 

described 4.5-inch increase seen between the sites. The elevation induced precipitation 

gradient yields a 1.8-inch increase in annual precipitation per 1,000 ft of elevation (148 

mm/km). Which is substantially lower than rates reported for the Wind River mountains 

in Wyoming, which was 5.99 inches/1,000 ft (500 mm/km; Fontaine and others 2002), 

Dry Creek Watershed near Boise, Idaho, which was 5.55 inches/1,000 ft (463 mm/km; 

Stratton and others 2009), or the Colorado Front Range, which was 5.39 inches/1,000 ft 

(450 mm/km; Bigler and others 2007).

Although there appears to be no change over time in total precipitation across the 

watershed (Figure 19), cumulative snowfall at the low elevation control station has 

declined at a rate of 0.20 inches per year (SE = 0.10, p = 0.054; 5.1 mm/year) over 

the past century (Figure 21). If the decline in snowpack is summed over 100 years, it 

results in a 24% loss of the mean snowfall (81.9 inches or 2,080.3 mm) over the period. 

While the decline in snowfall is apparent in the statistics, the level of variation in snow 

accumulation (SD = 30 inches or 762 mm) has remained high throughout the climate 

record. In fact, a few heavy snowfall years cause the data to fail the Shapiro-Wilk test 

for normal distribution (p = 0.009), which violates one of the assumptions in linear regression analysis. Transforming the data by taking the natural log solves the problem, 

but this transformed data yields results with less intuitive parameters: -0.0028 per year, 

which compounds into 24% per century.

The low-elevation Benton Meadow snow course rarely accumulates a snowpack 

greater than 20 inches, with peak snow accumulation often in February and a March 

1st snowpack depth averaging 18.6 inches (472.1 mm) (Table 4). In contrast the highelevation Benton Spring snow course often experiences it’s peak snow accumulation in 

March or April and has a March 1st snowpack depth averaging 51.5 inches (1,308.1 mm) 

(Table 4). While the Benton Meadow snowpack annually melts out before May 1st, the 

Benton Spring snowpack typically persists well into May and sometimes into June. 

Figure 21—Cumulative annual snowfall at the low-elevation control station for 

1912 to 2012, with a linear regression line plotted through the data. Over the last 

century cumulative snowfall at the lower elevations of the watershed has declined 

by approximately 20 inches.
24 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

However, when looking at the climate record for both snow courses it becomes apparent 

that snow accumulation at the two sites is changing (Figure 22). At Benton Meadow, 

the data show an 0.11-inch (2.8-mm) per year (p = 0.03) decline in March 1st snow 

depth, suggesting the snowpack is on average 30% shallower than it was in the 1930s. 

This trend holds constant for the snow water equivalent (SWE) data (p = 0.03), with the 

snowpack containing approximately one-third less water than it did on March 1st in the 

1930s. While regression of the March 1st snowpack for the Benton Spring site shows a 

negative slope, there was no significant decline in either snow depth or SWE in any of 

the sampling periods (Figure 22, Table 4).

Streamflow

Collection of streamflow data began in 1939, almost three decades after the 

climate data collection began, currently providing 73 years of data. Benton Creek 

resembles that of a typical hydrograph for most first order mountain streams of the 

western United States. It has a pronounced peak flow occuring during mid-May 

(Julian Date = ~140) averaging 7.19 cubic ft per second (cfs; 0.20 cubic meters per 

second (cms)) (Figures 23, 24) and a historic maximum flow on May 16th, 1997 

of 30.06 cfs (0.85 cms). The hydrologic system also shows the prolonged summer baseflow period, beginning in mid-July and tappering off in December. This 

baseflow corresponds with the temporal lag commonly seen between snowmelt 

and streamflow. Benton Creek streamflow is presented in correlation with daily 

weather observations from the control station within Appendix A. The stream reaches 

its baseflow level in early October (Julian Date = ~275) averaging 0.44 cubic ft 

per second (Figure 23), with a record low of 0.197 cfs (0.006 cms) on October 21st, 1981. 

Table 4—Summary of monthly snow course depth and snow water depth (SWE) in inches for the Benton Spring and Benton 

Meadow snow courses from 1937-2013. Snow depth and SWE equivalent were collected within three days of the 

first of the month and then averaged.

January 1 February 1 March 1 April 1 May 1 June 1

Depth SWE Depth SWE Depth SWE Depth SWE Depth SWE Depth SWE

Benton Spring (4,775 feet)

1937-1946 26.9 7.3 41.2 12.3 50.9 16.7 48.7 18.4 25.7 11.7 0.0 0.0

1947-1956 32.9 9.4 52.8 16.1 63.2 21.8 64.7 24.4 42.6 18.6 1.4 0.8

1957-1966 33.1 8.4 46.0 12.5 50.3 16.2 53.1 19.0 35.7 14.9 0.0 0.0

1967-1976 31.7 8.9 50.4 15.2 58.1 20.0 60.1 22.2 46.5 19.6 3.0 1.3

1977-1986 29.4 7.7 35.7 10.8 44.0 14.8 43.6 15.5 24.7 10.7 0.0 0.0

1987-1996 22.7 6.2 37.6 11.7 41.6 13.8 38.3 14.2 12.4 6.3 0.0 0.0

1997-2006 34.2 10.0 46.5 14.5 52.8 18.2 50.0 19.6 26.8 12.2 1.5 0.8

2006-2013 32.6 9.0 40.5 12.6 50.7 16.6 56.5 20.5 40.0 16.5 0.0 0.0

Overall 30.4 8.3 44.0 13.3 51.5 17.3 51.7 19.2 31.7 13.7 0.8 0.4

Benton Meadow (2,380 feet)

1937-1946 7.7 2.1 17.2 4.4 20.0 6.6 4.1 1.8 0.0 0.0 0.0 0.0

1947-1956 17.2 3.5 24.4 6.1 23.2 7.0 11.5 3.9 0.0 0.0 0.0 0.0

1957-1966 16.8 3.4 21.6 5.6 20.3 6.2 13.1 4.6 0.0 0.0 0.0 0.0

1967-1976 12.6 2.6 21.0 5.1 20.1 6.0 14.7 5.1 0.0 0.0 0.0 0.0

1977-1986 13.8 2.7 17.8 4.2 17.2 5.4 6.4 2.3 0.0 0.0 0.0 0.0

1987-1996 9.1 1.9 13.4 3.6 13.0 4.1 4.8 1.9 0.0 0.0 0.0 0.0

1997-2006 12.0 3.0 17.2 4.6 15.3 4.8 4.7 1.6 0.0 0.0 0.0 0.0

2006-2013 15.7 3.6 20.7 5.1 20.3 6.0 11.0 4.0 0.0 0.0 0.0 0.0

Overall 13.0 2.8 19.1 4.8 18.6 5.8 8.7 3.1 0.0 0.0 0.0 0.0
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 25

Figure 22—Comparison of the 

low elevation Benton Meadow 

(solid line) and high elevation 

Benton Spring (dashed line) snow 

courses from 1937 to 2013. The 

comparisons show the March 1st

(A) snowpack depth and (B) snow 

water equivalent (SWE), where the 

line through each dataset represents a linear regression.

Figure 23—Seasonal distribution 

of streamflow in both cubic feet per 

second (cfs) and cubic meters per 

second (cms) averaged monthly 

since 1939 and daily since 1955 

until early 2012 at the Benton Dam 

gauging station.
26 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

The months of April and May account for 48% of the annual streamflow (Figure 23), 

while September and October contribute less than 4% of the annual total. Evenly 

distributing the average annual runoff across the catchment places 17 inches (431.8 

mm) of water everywere, which is approximately 51% of the average catchment precipitation of 33.6 inches (853.4 mm). The unaccounted for 16.6 inches (421.6 mm) of 

precipitation is apparently removed from the system through evapotransporation or 

lateral subsurface flow processes. The annual runoff depth has increased in variation 

since Finklin (1983) reported a maximum and minimum of 25.3 and 6.0 inches (642.6 

and 152.4 mm), respectively, to a new maximum of 33.5 in 1999 and a minimum of 

4.6 inches (850.9 and 116.8 mm) in 1977.

Similar to the snowfall data presented earlier, streamflow data were log-normally 

distributed, so we log-transformed the data prior to analysis. This transformation reduced 

the influence of a few years with very high or low flows and allowed the distribution 

to pass the Shapiro-Wilk normality test (Figure 25). Streamflow has increased over the 

period of record (p = 0.0043) by 7.38 acre ft per year. When extrapolated over 73 years, 

Figure 24—Benton dam during spring runoff, May 2011; the flat bottom weir on the left is the overflow weir, 0.75 ft 

above the V-notched reference weir on the right. The pool level is 1.161 ft (35.39 cm) above the V-notch, equivalent 

to a discharge rate of 13.1 cfs (0.37 cms).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 27

this compounds to a 33% increase in the average annual runoff total. While there is an 

increase in annual streamflow, it can also be seen that the level of variation increases 

during the last three decades (Figure 26). The greatest variation in monthly streamflow 

occures in April and May, which can be linked to the high level of temperature variation and the influence that it has on snowmelt timing. This high variation also becomes 

apparent when looking at the timing of peak streamflow, which has moved 3.75 days 

per decade earlier or approximately 19 days earlier over the last 50 years (p = 0.0024; 

Figure 27).

Figure 25—Average annual stream flow from 1939 through 2012, log transformed on top 

and presented as the raw data on bottom. Both graphs are plotted with a linear regression 

through the data, showing an approximate 33% increase in streamflow over the 73 years of 

observation.
28 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 27—Timing of peak decadal streamflow over the last 60 years, with a linear regression plotted through the data. The regression shows that peak streamflow has shifted 

3.75 days early each decade.

Figure 26—Averaged decadal streamflow hydrographs (solid line) with a 95% confidence 

interval (dotted line), where the x-axes marks denote the start of the decade. Although it 

appears that annual streamflow is increasing, this shows that the overall level of annual 

variation has also increased in the more recent decades.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 29

Temperature

Throughout the climate record of PREF, the average annual temperature has been 

44.1 °F (6.7 °C), with July being the hottest month with an average daily maximum 

temperature of 82.8 °F (28.2 °C) and January being the coldest with a average daily 

maximum temperature of 30.5 °F (-0.8 °C). While freezing temperatures have occurred 

in every month, they are not common between May and October (Figure 28). A summary 

of decadal and climate normal average monthly temperatures for the control weather 

station at PREF can be found in Table 5.

Table 5—Ten-year (decadal) and 30-year “normal” average monthly temperature (°F) for PREF control weather station.

 Period Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Annual

Decade

1912-1920a 22.8 27.1 33.9 42.9 49.3 56.7 62.8 61.8 52.9 42.5 32.8 25.0 42.5

1921-1930 21.9 27.7 35.4 43.6 51.8 58.5 65.1 63.1 54.0 44.1 33.3 25.5 43.7

1931-1940 24.6 25.0 35.4 44.6 52.8 59.1 65.0 62.8 55.9 45.6 33.6 29.4 44.5

1941-1950 20.3 28.3 33.9 43.8 52.3 57.6 64.1 62.8 55.4 44.8 33.3 26.9 43.6

1951-1960 25.0 28.5 33.4 42.7 52.3 57.9 64.1 61.8 55.2 44.7 31.8 28.4 43.8

1961-1970 24.6 30.0 34.0 42.3 51.6 58.9 64.0 62.9 55.6 44.2 34.3 27.1 44.1

1971-1980 22.1 30.0 35.3 43.6 52.3 59.6 65.4 64.1 56.3 45.3 32.0 27.6 44.5

1981-1990 26.0 27.9 36.7 44.7 52.4 60.0 64.1 63.9 54.4 43.5 32.3 23.4 44.1

1991-2000 26.5 29.5 36.5 44.2 53.2 58.3 64.0 63.4 54.7 42.9 31.8 25.8 44.2

2001-2010 26.8 30.1 35.9 43.7 52.2 59.0 66.2 63.6 54.5 42.6 32.1 25.4 44.3

2011-2013a 25.9 28.6 35.7 42.7 50.8 57.0 65.1 64.0 56.9 44.0 34.1 28.4 44.4

30 Years

1912-1940 23.5 26.8 34.9 43.6 51.4 58.1 64.2 62.6 54.0 44.1 33.1 26.5 43.6

1921-1950 22.8 27.3 35.2 44.2 52.4 58.4 64.9 62.9 54.9 44.8 33.4 27.3 44.0

1931-1960 23.6 27.5 34.3 43.9 52.5 58.2 64.5 62.5 55.3 45.0 33.1 28.0 44.0

1941-1970 23.5 29.1 33.8 43.0 52.1 58.2 64.2 62.7 55.2 44.5 33.0 27.2 43.9

1951-1980 24.1 29.7 34.3 42.8 52.2 58.9 64.6 63.3 55.4 44.6 32.6 27.5 44.1

1961-1990 24.5 29.4 35.4 43.5 52.2 59.3 64.4 63.9 55.3 44.2 33.0 26.0 44.2

1971-2000 24.9 29.4 36.2 44.1 52.6 59.1 64.4 63.9 55.2 43.8 32.2 25.8 44.3

1981-2010 26.3 29.3 36.3 44.1 52.6 59.0 64.7 63.8 54.7 42.9 32.2 25.2 44.3

a Not full decades.

Figure 28—Temperature variation as recorded at the weather station, 1912-2012.
30 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

To look at any possible long-term trends that may be occurring in the climate record 

temperature data, we combined daily temperature data into annual averages. We analyzed 

daily mean temperatures and both the daily maximum temperature, which normally 

occurs sometime in mid-afternoon, and the daily minimum temperature, which normally occurs shortly following sunrise, but before the sun begins to warm the ground 

( Figure 29). Regression analysis showed that neither the daily mean nor daily maximum 

temperatures had changed over the past century, maintaining average value of 43.9 °F 

and 55.9 °F (6.6 °C and 13.3 °C), respectively (Figure 29). In contrast, daily minimum 

temperatures have increased (p < 0.001). If the increase is assumed linear (Figure 29), 

then minimum temperatures have increased by 0.0283 °F (0.0157 °C) per year, or 2.8 °F 

(1.6 °C) per century. Changes in minimum temperatures during the right portion of the 

year can hold serious implications for snowpack energetics and ablation timing and 

growing season length. When looking at Figure 29 it appears that the minimum daily 

temperatures begin to decline during the 1980s. This decline in minimum temperatures 

is supported by using a second order polynomial regression of the data, which resulted 

in an r2

 = 0.36 compared to the linear regressions r2 = 0.23, with both relationships 

being significant (p < 0.001).

When minimum temperature is analyzed by month, the increase in temperature 

was not evenly distributed throughout the year (Figure 30). While every month 

showed a positive increase in minimum temperature with an average increase rate of 

+0.028 (SE = 0.005) °F per year (p = 0.0001), January and February have warmed 

more rapidly than the mean (+0.062 and +0.060 °F per year, SE = 0.013 for both, 

Figure 29—Annual average daily maximum, mean, and minimum temperatures for 1912 to 2012 at the control weather station in PREF, with lines 

of linear (dotted) and polynomial (dashed) regression overlaid. Analyses 

show no change in the maximum and mean daily temperatures, while annual daily average minimum temperatures have increasing by 2.8 °F over 

the last century.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 31

Figure 30—Monthly rate of increase in minimum temperatures from 1911-2012, 

with the average annual increase represented by the horizontal line. Asterisks 

represent rates of change significantly different from the average rate of increase. 

While minimum temperatures increase in every month, the greatest changes occur 

in midwinter and early spring.

p = 0.003 and 0.008, respectively). This would yield net increases of over 6 °F per 

century during these months (Figure 30). In contrast, October and November showed 

no significant change over the period (Standard Error [SE] = 0.013 °F, p = 0.04 for 

both). Comparing Figures 28 and 30, it becomes clear that the two coldest months are 

the ones that have warmed the most. This trend can be seen in Table 5 where winter 

temperatures appear to have become milder over the past four decades.

Finally, we looked at the effect that the increase in minimum temperatures may have 

on other environmental factors, such as the number of frost-free days per year and length 

of snow cover per year. These parameters have strong implications for their influences 

on system production through photosynthesis and economics through frost damage. 

Because it is derived from minimum temperatures, it is not surprising that the trend in 

the probability of frost resembles the trend in minimum temperature, with an increasing rate of approximately 0.2 days per year (Figure 31). Propagating this increase in 

frost-free days over a century shows an increase of 19.6 days per century. When looking 

at which months account for most of this change in frost frequency, it is apparent that 

April and May or the spring shoulder months to the winter weather account for most of 

this change (Figure 32). These two months account for approximately 9 of the 20-day 

difference in frosts over the last century. Along with this, length of snow cover was 

calculated as the number of days per year with at least 1 inch of snow at the control 

weather station (Figure 33). Here we see an inverse relationship with the minimum 

temperature increase, with there being a decline of 0.086 days of snow cover per year 

or 8.6 days less snow cover per century.
32 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 31—Number of frost-free days per year from 1912-2012; a day was counted 

if the minimum temperature did not go below 32 °F (0 °C). The line denotes a 

linear regression and shows that over the last century the growing season length 

has increased by approximately 20 days.

Figure 32—Change in monthly frost frequency from 1912-2012. The horizontal line 

represents the mean change in frost frequency if it was normally distributed across 

all months, with asterisks signifying months that significantly deviate from the mean. 

The decline in frost frequency during April and May influences the timing of peak 

streamflow and snowpack persistence.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 33

Figure 33—Number of days per year with at least 1 inch of snow at the control 

weather station in PREF, with a linear regression plotted through the data. Over 

the last century there has been a decline of approximately 9 days of snow cover.

Discussion _______________________________________________________

Over the period from 1912 to 2012, the climate record from PREF shows several 

signs of climatic warming expressed primarily through increases in the minimum daily 

temperature. This change manifested over the century as (1) decreased snow cover 

days, (2) decreased snow acumulation totals in spite of constant precipitation, (3) earlier 

melting of snowpacks in the spring, (4) earlier peak streamflows due to earlier melting 

of the snowpack, and (5) lower frequency of frosts. Increases in minimum temperature 

were greatest in January and February, but they appeared significant in all months 

except October and November. We also detected a significant long-term increase in 

Benton Creek streamflow from the almost continuous 73-year record. The increase in 

minimum temperatures during the century is what one would expect based on climate 

models (Russo and Sterl 2011) and supports earlier summaries of climate data from 

around the world (Frich and others 2002). Most climate models make predictions of 

future temperatures based on the physical linkage between atmospheric CO2 and temperature, with minimum temperatures being more strongly influenced by atmospheric 

CO2 concentrations than are maximum temperatures. More puzzling was the apparent 

decrease seen in minimum daily temperatures starting around 1980. To further explore 

the downturn in minimum temperatures after 1980, other weather stations within the 

region were analyzed for the same phenomenon. This comparison will distinguish if 

the cooling is in response to the bulk atmosphere, which is to say a “climate” effect, 

rather than a characteristic of the particular spot where the weather station was located, 

which is to say a “microclimate” effect. Three regional stations located between 70 and 

110 miles south of PREF with nearly continuous data back to 1930 were analyzed. For 

each station, 7 years were removed from the records because they presented outliers 

that were not uniformly consistent and doubtful for the region; most of these records 

were in the 1930s, immediately after the weather stations were established and none 

occured after 1980. Regression analysis found similar increases in minimum daily 
34 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

temperatures at each of the stations, but at slightly reduced rates compared to the linear 

fit at PREF (Kellogg, ID +0.023 °F per year, p = 0.027; St. Maries, ID +0.036 °F per 

year, p < 0.01; Wallace, ID +0.031 °F per year, p < 0.01). However, none of these other 

stations showed a decline after 1980. The reduced warming rates for 1981 to 2012 have 

been well documented throughout the region and explained by natural climate variations.

The uniqueness of the pattern leads to questions about the location of the control 

weather station. In particular, there are large trees growing near the station and these 

may have grown tall enough to influence the weather data. For both temperature and 

precipitation measurements, the Environmental Protection Agency (Bennett and others 

1987) recommends that sensors be no closer than four times the obstruction’s height. 

The National Wildfire Coordinating Group (2012) states “Ideally, when dealing with 

tall, dense vegetation the station should be located a distance that is equal to 7 times 

the height of the obstructing vegetation.”

A National Agricultural Imagery Program (NAIP) view of this area, produced in 2009, 

(Figure 34, top photo) clearly illustrates the extent and location of trees in relation to 

the Control weather station and Benton Meadow snowcourse. There are several trees 

over 95 ft (30 m) tall about 50 ft (15 m) northeast of the weather station. There is also a 

closed-canopy forest edge 65 ft (20 m) south of the station; these trees are approximately 

65 ft (20 m) tall and may begin to influence the solar heating and nighttime cooling at 

the station. All of these obstructions are clearly within a distance that could influence 

the accuracy of observations (Bennett and others 1987, NWCG 2012). While Finklin 

(1983) was aware of these issues and discussed them in context of the Benton Spring 

precipitation gauge, he barely mentioned this issue with respect to the headquarters site. 

Certainly, the trees at the headquarters site were much shorter thirty years ago and may 

not have posed an issue at the time. Notably, above average minimum temperatures in 

2012 and 2013 call for a more detailed analysis to assess the influence the land surface 

is having. In the spring of 2012, the vegetation around the weather station and snowcourse was cleared, removing these interfering trees (Figure 33, bottom photo). Further 

work will be needed to see how the weather data responds over the next several years. 

Cutting the trees should allow for a targeted analysis and potential correction to the data 

collected since 1980 (Figure 35). If the trees were indeed the cause of the minimum 

daily temperature downturn in the 1980s, then the temperature increase should resume 

along the trajectory it had established before 1980 and should resemble the data from 

other stations in the region. For our purposes here, we have simply taken the minimum 

temperature data as they were and focused on the long-term increase.

With the biggest increases in minimum temperature occurring in January and February, there are serious linkages to the phase of precipitation with some snowfall shifting 

to rain at low elevations, reducing the snowpack. The relatively warm winters at PREF 

tend to maintain the snowpack at temperatures near 32 °F (0 °C), placing the snowpack 

“at risk” of melting during any warm period (Nolin and Daly 2006). The rise in minimum 

temperature increases the probability that precipitation will come as rain rather than 

snow as demonstrated by the decline in annual snowfall while precipitation remained 

unchanged (Figures 20 and 21). It seems unlikely that the lower-elevation snowpack 

will completely disappear any time soon, but it is at considerable risk of earlier melting and rain on snow events, with the length of time of snow cover having reduced by 

over 8 days in the last century (Figure 33). This warming has also reduced the depth 

and water content of the spring snowpack at low elevation by over 30% (Figure 22). 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 35

Figure 34—(Top) 1.0-m resolution NAIP aerial photo from 2009 of the area surrounding the control station (A) and Benton Meadow snowcourse (B). (Bottom) 

0.5-m resolution NAIP image from 2013 showing the vegetation in the vicinity 

of the control station (A) and Benton Meadow snowcourse (B) after vegetation 

removal in May of 2012.
36 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure 35—Before and after photos of the weather station and the Benton Meadow snowcourse. A selective harvest in May of 2012 removed trees that may have influenced weather 

and snowcourse measurements.

Similar decreases in snowpack water content have been reported across much of the 

western United States (Mote 2003, Mote and others 2005). At PREF, the smaller spring 

snowpacks are accompanied by a shift toward earlier peaks in streamflow (Figure 27), 

may ultimately lengthen the summer dry period. Such shifts toward earlier peaks in 

streamflow are being observed in several parts of North America, but especially in the 

headwaters surrounding the Columbia Basin (Luce and Holden 2009) and in the northern 

Sierra Nevada Mountains (Stewart and others 2005). Of all these interlocking variables, 

only minimum temperatures show a change of direction, starting in 1980. Snowfall, 

snowpack depth, and snow water equivalent all continue to fall throughout the record, 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 37

even with the Benton Meadow snowcourse data (Figure 22) coming from immediately 

adjacent to the control weather station. The lack of change in these variables since 

1980 at or near the control weather station location supports the idea that the minimum 

temperature measurement has been influenced by vegetation or some other variable at 

the headquarters station.

The ecosystems of PREF may see the strongest physiological response to the decrease in frost frequency (Figures 32 and 33). Over the last century April and May 

alone experienced 3.7 and 5.1 fewer days of frost per year, respectively. This change 

occurs at a critical time when days are long, buds are expanding, and soil moisture is 

high. The potential influence this may have on photosynthesis could be significant for 

overall system production (Öquist and Hunter 2003). Separate from photosynthesis, 

tissue susceptibility to frost is also high during periods when new tissues are expanding 

rapidly (Rehfeldt 1989); therefore, the risk of permanent damage to new tissues in May 

would be reduced if frost frequency declines.

The most surprising result of this analysis is the pronounced increase in annual 

streamflow in Benton Creek. This finding contradicts some earlier studies, including 

one conducted in the Pacific Northwest that focused on much larger basins from 1948 to 

2006 (Luce and Holden 2009). These authors found a decrease in mean flow in 58% of 

the rivers for the lowest quartile of years studied, with the smallest basin being 142 km2

and the majority of the decreasing rivers found in the Cascade and northern Rocky 

Mountain ranges. The Benton Creek drainage above Benton Dam is only 3.84 km2

 or 

about 1/37 the size of the smallest catchments considered by Luce and Holden (2009). 

With such strong differences between the hydrograph of this “little water” and the surrounding larger basins, perhaps Harry Gisborne was right about the need to establish 

such a study on a smaller drainage. Other studies have found results similar to Benton 

Creek in small mountian headwater streams thoughout the region (Birsan and others 

2005, Jones 2011).

Understanding how such an increase in streamflow could occur is particularly interesting at PREF because annual precipitation amounts have not changed. The main water 

losses not accounted for are evaporation (including sublimation of snow and interception 

of precipitation by the canopy), transpiration, and deep drainage to aquifers. Canopy 

area is one control over transpiration and interception losses. However, it seems unlikely 

that canopy area has changed enough since 1912 to account for the 33% increase in 

streamflow. The management actions within the catchment, at any given timeframe, 

amount to no more than 10% of the catchment being in a highly disturbed state. It is 

also unlikely that deep drainage would have been modified during this period as it is 

mostly determined by soils and geology.

The most likely cause of the streamflow increase is a reduction in transpiration rate per 

unit area by the canopy. Two possible drivers of this process are (1) a change in species 

composition, and (2) tree height. Species composition has changed substantially since 

1912. The canopy was dominated by western white pine during the early years of the 

record (Wellner and others 1951), but was later replaced by Douglas-fir and western larch 

(Finklin 1983). By 2000, the canopy was reportedly dominated by western red-cedar, 

Douglas-fir, and western hemlock (Duursma and others 2003). The stomatal conductance and transpiration rates per unit leaf area are much lower for the late-successional 

species at the end of this sequence than for the early successional western white pine 

(Pangle 2008). This successional change in species composition will have increased 

water use efficiency and may have reduced the transpiration losses. Secondly, as trees 

grow taller, it becomes more difficult for them to lift water to the canopy. Therefore, 

even within the same species, trees will have reduced conductance and transpiration of 

water per unit leaf area with increased tree height (Koch and others 2004, Pangle 2008). 
38 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

This combination of successional change and height growth could reduce transpiration 

substantially. Utilizing the streamflow record and the Theisien Polygon method of 

distributing precipitation observations from the then sixteen rain gauges, Stage (1957) 

estimated that for 1911 to 1955 there was an average precipitation loss of 69% to 

evapotranspiration, with only 31% seen as streamflow. In 1983, Finklin estimated, by 

difference, that evapotranspiration utilized 60% of the precipitation reaching the forest. 

In 2004, Pangle (2008) directly measured transpiration from trees as utilizing 42% of 

precipitation, which is more in line with the 53% of total precipitation that the 2004 

streamflow accounts for. It would be interesting to extend this comparison to account 

for shrub transpiration over several years.

Conclusion _______________________________________________________

PREF is uniquely positioned within the northern Rocky Mountains and contains a 

diverse wealth of data records, from the climate records and streamflow data to continuous forest inventory observations. This long-term climate record has the potential 

to provide insight into future projections of change within these systems. The potential 

for advancing our understanding of single processes and also coupled interactions, like 

those seen in the change in streamflow, needs to be investigated further.

It is humbling to consider that when Finklin last summarized these data in 1983, climate 

change was just a speck on the horizon. At the time, climate was known to fluctuate but 

it was not expected to undergo directional change; instead, interest was focused on the 

11-year sunspot cycle. In the almost 30 years since then, the accumulating evidence of 

climatic warming has changed the conversation. What is required now is collaboration 

between managers and scientists to develop new means of dealing with the changes 

already being seen on the landscape. The long-term record at PREF can be an important 

tool in this collaboration, but only if maintained, critically evaluated, validated, and applied. PREF data confirm long-term temperature increases and enhance our awareness 

of the potential secondary effects and feedbacks that may result from climate warming 

in this region, including changes in snow hydrology and streamflow volume and timing. PREF’s location at the western edge of the Rocky Mountains, inclusion of low and 

high-elevation snowpack data, limited disturbance history, and its headwater stream 

gauging station provide it with a unique opportunity to serve as our canary in the face 

of climate change within the northern Rocky Mountains.

References _______________________________________________________

Barrows, J.S. 1954. Lightning fire research in the Rocky Mountains. Journal of Forestry. 52:845-847.

Bennett, E.; R. Brode, J. Dicke, R. Eskridge, M. Garrison, J. Irwin, M. Koerber, T. Lockhart, t. Method, S. 

Perkins, R. Wilson. 1987. On-site meteorological program guidance for regulatory modeling applications, 

EPA-450/4-87-013. Research Triangle Park: NC: U.S. Environmental Protection Agency.

Bigler, C., D.G. Gavin, C. Gunning, and T.T. Veblen. 2007. Drought induces lagged tree mortality in a 

subalpine forest in the Rocky Mountains. Oikos. 116:1983–1994.

Birsan, M.-V., P. Molnar, P. Burlando, and M. Pfaundler. 2005. Streamflow trends in Switzerland. Journal 

of Hydrology. 314:312–329.

Brown, A.A. and W.S. Davis. 1939. The fire danger meter for the Rocky Mountain Region. Journal of 

Forestry. 37:552-558.

Duursma, R.A., J.D. Marshall, and A.P. Robinson. 2003. Leaf area index inferred from solar beam transmission in mixed conifer forests on complex terrain. Agricultural and Forest Meteorology. 118:221–236. 

Duursma, R.A., J.D. Marshall, A.P. Robinson, and R.E. Pangle. 2007. Description and test of a simple 

process-based model of forest growth for mixed-species stands. Ecological Modelling. 203:297-311.

Finklin, A.I. 1983. Climate of Priest River Experimental Forest, northern Idaho. Gen. Tech. Rep. INTGTR-159. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range 

Experiment Station. 53 p.

Frich, P., L.V. Alexander, P. Della-Marta, B. Gleason, M. Haylock, A.M.G. Klein Tank, and T. Peterson. 

2002. Observed coherent changes in climatic extremes during the second half of the twentieth century. 

Climate Research. 19:193–212.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 39

Fontaine, T.A., T.S. Cruickshank, J.G. Arnold, and R.H. Hotchkiss. 2002. Development of a snowfallsnowmelt routine for mountainous terrain for the soil-water assessment tool (SWAT). Journal of Hydrology. 262:209-223.

Haupt, H.F. 1968. The generation of spring peak flows by short-term meteorological events. International 

Association of Science Hydrologist Bulletin. 13:65-76.

Hayes, G.L. 1941. Influence of altitude and aspect on daily variation in factors of forest-fire danger. Circ. 

591. Washington, DC: U.S. Department of Agriculture. 38 p.

Jemison, G.M. 1934. The significance of the effect of stand density upon the weather beneath the canopy. 

Journal of Forestry. 32:446-451.

Jones, J.A. 2011. Hydrologic responses to climate change: considering geographic context and alternative 

hypotheses. Hydrologic Processes. 25:1996-2000.

Koch, G.W., S.C. Sillett, G.M. Jennings, and S.D. Davis. 2004. Limits to tree height. Nature. 428:851-854.

Larsen, J.A. 1930. Forest types of the northern Rocky Mountains and their climatic controls. Ecology. 

11:631-672.

Larsen, J.A. 1940. Site factor variations and responses in temporary forest types in northern Idaho. Ecological Monographs. 10:1-54.

Larsen, J.A. and C.C. Delavan. 1922. Climate and forest fires in Montana and northern Idaho, 1909-1919. 

Monthly Weather Review. 50:55-68.

Link, T. and L. Wei. 2010. Priest River Experimental Forest streamflow and climate data digitization. 

Unpublished report on file at: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Moscow, ID. 23 p. Online: http://forest.moscowfsl.wsu.edu/ef/pref/datasets/benton/

Benton_Dam_Draft_Final_Report.pdf.

Luce, C.H. and Z.A. Holden. 2009. Declining annual streamflow distributions in the Pacific Northwest 

United States, 1948–2006. Geophysical Research Letters. 36:16401, doi: 10.1029/2009GL039407.

Maloy, O.C. 1997. White pine blister rust control in North America: a case study. Annual Review of Phytopathology. 35:87-109.

Mote, P.W. 2003. Trends in snow water equivalent in the Pacific Northwest and their climatic causes. 

Geophysical Research Letters. 30:1601, doi: 10.1029/2003GL017258, 2003.

Mote, P.W., A.F. Hamlet, M.P. Clark, and D.P. Lettenmaier. 2005. Declining mountain snowpack in western 

North America. Bulletin of the American Meteorological Society. 39-49.

National Wildfire Coordinating Group (NWCG). 2012. Interagency wildland fire weather station standards 

and guidelines. PMS-426-3. Boise, ID: National Wildfire Coordinating Group. 52 p. 

Nolin, A.W. and C. Daly. 2006. Mapping “at risk” snow in the Pacific Northwest. Journal of Hydrometeorology. 7:1164–1171.

Öquist, G. and N.P.A. Hunter. 2003. Photosynthesis of overwintering evergreen plants. Annual Review of 

Plant Biology. 54:329-355.

Packer, P.E. 1962. Elevation, aspect, and cover effects on maximum snow accumulation in a western white 

pine forest. Forest Science. 8:225-235.

Pangle, R.E. 2008. Transpiration and canopy conductance of mixed species conifer stands in an inland 

Pacific Northwest forest. Ph.D. dissertation, University of Idaho. 199 p.

Rehfeldt, G.E. 1989. Ecological adaptations in Douglas-fir (Pseudotsuga menziesii var. glauca): a synthesis. 

Forest Ecology and Management. 28:203–215.

Russo, S. and A. Sterl. 2011. Global changes in indices describing moderate temperature extremes from the daily 

output of a climate model. Journal of Geophysical Research. 116:D03104, doi: 10.1029/2010JD014727.

Snyder, G.G., H.F. Haupt, and G.H. Belt, Jr. 1975. Clearcutting and burning slash alter quality of stream 

water in northern Idaho. Gen. Tech. Rep. INT-GTR-168. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Forest and Range Experiment Station. 34 p.

Stage, A.R. 1957. Some runoff characteristics of a small forested watershed in Northern Idaho. Northwest 

Science. 31(1):14-27.

Stewart, I.T., D.R. Cayan, and M.D. Dettinger. 2005. Changes toward earlier streamflow timing across 

western North America. Journal of Climate. 18:1136-1155.

Stockstad, D.S. and R.J. Barney. 1964. Conversion tables for use with the national fire-danger rating system 

in the Intermountain area. Res. Note. INT-RN-12. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Forest and Range Experiment Station. 6 p.

Stratton, B.T., V. Sridhar, M.M. Gribb, J.P. McNamara, and B. Narasimhan. 2009. Modeling the spatially 

varying water balance processes in a semiarid mountainous watershed of Idaho. Journal of the American 

Water Resources Association. 45:1390-1408. doi: 10.1111 ⁄ j.1752-1688.2009.00371.x.

Wellner, C.A., R.F. Watt., and A.E. Helmers. 1951. What to see and where to find it on the Priest River 

Experimental Forest. 1951. Misc. Publ. 3, Missoula, MT: U.S. Department of Agriculture, Forest Service, Northern Rocky Mountain Forest and Range Experiment Station. 86 p.

Wellner, C.A. 1976. Frontiers of forestry research—Priest River Experimental Forest, 1911-1976. Ogden, 

UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 148 p.

Whitlock, C. and P.J. Bartlein. 1993. Spatial variations of Holocene climate change in the Yellowstone 

region. Quaternary Research. 39:231-238.
40 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Appendix: Streamflow correlated to other weather variables. ___________

Figure A.1—Benton Creek streamflow correlation with daily snowfall, presented in fifteen year intervals from daily observations collected at the Benton Dam gauging station and control weather station. The data was originally synthesized 

and prepared for a report by Link and Wei (2010).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 41

Figure A.1—Continued
42 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure A.2—Benton Creek streamflow correlation with snowpack depth, presented in fifteen year intervals from daily 

observations collected at the Benton Dam gauging station and control weather station. The data was originally synthesized and prepared for a report by Link and Wei (2010).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 43

Figure A.2—Continued
44 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure A.3—Benton Creek streamflow correlation with precipitation, presented in fifteen year intervals from daily observations collected at the Benton Dam gauging station and control weather station. The data was originally synthesized 

and prepared for report by Link and Wei (2010).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 45

Figure A.3—Continued
46 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure A.4—Benton Creek streamflow correlation with minimum temperature, presented in fifteen year intervals from 

daily observations collected at the Benton Damn gauging station and control weather station. The data was originally 

synthesized and prepared for report by Link and Wei (2010).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 47

Figure A.4—Continued
48 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015

Figure A.5—Benton Creek streamflow correlation with maximum temperature, presented in fifteen year intervals from 

daily observations collected at the Benton Damn gauging station and control weather station. The data was originally 

synthesized and prepared for report by Link and Wei (2010).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-331. 2015 49

Figure A.5—Continued


The U.S. Department of Agriculture (USDA) prohibits discrimination in all of its programs 

and activities on the basis of race, color, national origin, age, disability, and where 

applicable, sex (including gender identity and expression), marital status, familial status, 

parental status, religion, sexual orientation, political beliefs, genetic information, reprisal, 

or because all or part of an individual’s income is derived from any public assistance 

program. (Not all prohibited bases apply to all programs.) Persons with disabilities who 

require alternative means for communication of program information (Braille, large print, 

audiotape, etc.) should contact USDA’s TARGET Center at (202) 720-2600 (voice and 

TDD).

To file a complaint of discrimination, write to: USDA, Assistant Secretary for Civil Rights, 

Office of the Assistant Secretary for Civil Rights, 1400 Independence Avenue, S.W., Stop 

9410, Washington, DC 20250-9410.

Or call toll-free at (866) 632-9992 (English) or (800) 877-8339 (TDD) or (866) 377-8642 

(English Federal-relay) or (800) 845-6136 (Spanish Federal-relay). USDA is an equal 

opportunity provider and employer.

To learn more about RMRS publications or search our online titles:

www.fs.fed.us/rm/publications

www.treesearch.fs.fed.us

Federal Recycling Program Printed on Recycled Paper