Tree ring record of streamflow and drought in the upper Snake River



[1] Tree ring samples collected near the Snake River headwaters were augmented with preexisting tree ring chronologies to create a 415 year reconstruction of upper Snake River streamflow, extending the short instrumental record and providing the first description of multicentury water supply variability in this river. Results indicate that the region's early 21st century drought is severe even in the context of long-term climatic variability and that the instrumental record is representative of low-flow individual years. In terms of overall magnitude, droughts of the recent past are eclipsed by a sustained low-flow period lasting for over 30 years in the early to mid-1600s. A comparison of reconstructed Snake River flow with streamflow reconstructions of the Colorado, Sacramento, and Verde rivers suggests that changes in the predominance of zonal versus meridional atmospheric flow may have influenced drought patterns in the western United States through time.

1. Introduction

[2] The highly regulated upper Snake River is a potential flash point for future water supply crises due to its variability and the growing user demand on its flow [USBR, 2005]. The 1667 km Snake River is one of the largest rivers in the United States, draining a semiarid region that covers 283,000 km2 and includes most of Idaho, as well as portions of Wyoming, Utah, Nevada, Oregon, and Washington. The Snake River's water resources were historically allocated almost entirely for agricultural irrigation [McGuire et al., 2006], leading to stress on the river system as water demands for Endangered Species Act requirements, hydroelectric power generation, municipal supply, and recreational uses have increased [Marston et al., 2005; McGuire et al., 2006; Slaughter and Weiner, 2007]. As the largest tributary of the Columbia River (based on both discharge and watershed size), Snake River streamflow is also important for users further downstream.

[3] Many regions in the western United States (West) have experienced a multiyear drought over the first decade of the 21st century, placing a renewed sense of urgency on water availability issues. The upper Snake River Basin, a hydrologic unit extending from Yellowstone National Park in Wyoming through south central Idaho (Figure 1), has been particularly hard-hit by this drought, registering its lowest 4 year flow period on record from 2001 to 2004. Flows at the Jackson Lake Dam, Wyoming and Heise, Idaho gages were below average (based on the 1911–2009 instrumental period mean) in 7 of 8 years between 2000 and 2007. Although conditions improved in 2008–2009, it is too soon to determine whether the drought period has ended, and low snowpack in 2010 prompted new concerns. With regulations concerning in-stream water for fish habitat recently strengthened, drought conditions are likely to lead to stresses on other users, particularly the agriculture sector [Mote et al., 2003].

Figure 1.

Site map of the Snake River study area. White squares indicate locations of the Snake River streamflow gages reconstructed in this study: Heise (Idaho) and Jackson Lake Dam (Wyoming). The upper Snake River Basin (black dot-dashed line), the Snake River (solid white line), the Columbia River (dotted white line), and tree ring sites used in the final reconstruction model (black circles) are also shown.

[4] The early 21st century drought has raised questions about whether these dry conditions should be considered an extreme event or if this drought is within the range of natural variability and should be included in regular planning. Research incorporating paleoclimate data indicates that the 20th century was an abnormally wet period in this region [Gray and McCabe, 2010], and water managers increasingly acknowledge the need for extended data sources to provide an adequate representation of natural variability in the West's river systems [USBR, 2007]. The reconstruction of annual streamflow from tree rings has long been recognized as an important source of information on multicentury water supply variability [Schulman, 1945; Stockton and Jacoby, 1976]. In the semiarid West, both tree growth and runoff are limited by insufficient soil moisture resulting from lack of precipitation and/or excessive potential evapotranspiration. Streamflow can be reconstructed using tree rings because both tree growth and river discharge are responding to regional precipitation and evapotranspiration patterns [Meko et al., 1995], and streamflow reconstructions have been completed for a number of western rivers [e.g., Graumlich et al., 2003; Gedalof et al., 2004; Meko et al., 2001, 2007; Watson et al., 2009].

[5] The objective of this research is to provide the first long-term record of streamflow in the upper Snake River using dendrochronological techniques. This reconstruction is then used to place the instrumental record (on which current management decisions are based) in the context of longer-term variability and to assess the severity of the early 21st century drought. I also compare the extended Snake River record with streamflow reconstructions of three other western rivers in order to examine synchronicity among the rivers and gain insight into possible climatic controls on drought episodes.

2. Study Area

[6] The headwaters of the Snake River lie in the mountains of western Wyoming (Figure 1), a climatologically complex area associated with a key physiographic influence (i.e., the Rocky Mountains and continental divide, approximately 2400 m in elevation near the Snake River headwaters) and a key geospatial meteorological influence (the shifting latitudinal position of prevailing seasonal storm tracks) [Cayan et al., 1998; Mock, 1996]. The snow-charged Snake River is highly dependent on the 200 mm of orographically induced precipitation received in the headwaters region in an average winter season: the remainder of its route lies primarily in the semiarid Snake River Plain, a broad valley in southern Idaho that receives approximately 300–400 mm of total precipitation per year.

[7] Precipitation in the Snake River Basin is winter moisture dominant from Pacific frontal systems. The low-elevation gap in the Snake River Plain is a preferred route for normal zonal flow of cool season cyclonic disturbances [Bryson and Hare, 1974]. The path of the cyclones is generally west to east, but large waves of alternating low-pressure troughs and high-pressure ridges often alter this pattern. Precipitation from Pacific storms decreases in the Snake River Plain when the Pacific subtropical high begins to strengthen in the spring [Mock, 1996].

[8] In addition to these seasonal hydroclimatic patterns, precipitation, snow accumulation, and streamflow in parts of the West (Figure 2) contain a significant El Niño-Southern Oscillation (ENSO) signal [Cayan et al., 1999]. Western sections of Oregon, Washington, Wyoming, and Montana, as well as northern Idaho, tend to be drier (wetter) than average in winters following El Niño (La Niña) events, while the opposite is true for Arizona, southern California, and parts of New Mexico, Utah, and Nevada. The Snake River Basin covers a large area with a mixed response to ENSO (Figure 2). The headwaters region of the upper Snake River reflects an ENSO signal, but the majority of the Snake River Plain in Idaho does not [Redmond and Koch, 1991; Wise, 2010].

Figure 2.

Reconstructed gages (black and white asterisks) and river basins (black outlines) of the Sacramento River (SacRB), upper Colorado River (UCRB), Verde River (VerRB), and Snake River (SnakeRB). Areas of significant (0.05 level) positive (lighter gray) and negative (darker gray) correlation between June through November SOI and October through March precipitation are shaded.

3. Data and Methods

3.1. Instrumental Streamflow Data

[9] Streamflow records for the Snake River at Jackson Lake Dam, Wyoming (JCK, 1910–2006) and the Snake River near Heise, Idaho (HEII, 1911–2006) were obtained from USBR ( These streamflow records consist of estimated daily average unregulated discharge that has been “naturalized” by USBR to remove the effects of diversions and storage [Wurbs, 2006]. The daily data were aggregated into a water year (1 October to 30 September) total for each year. The water year was chosen as the reconstruction season in order to be useful for water management purposes. The average total water year discharge over the instrumental period was 1281 millions of cubic meters (MCM) at JCK and 6198 MCM at HEII.

3.2. Tree Ring Chronology Development

[10] Both primary (collected by the author) and secondary (provided by other researchers) tree ring data were used in the streamflow reconstruction. Established dendrochronological methods for field sampling and laboratory analysis were followed for chronology development [Stokes and Smiley, 1968; Fritts, 1976]. Tree ring sites for climate studies are chosen based on several key factors: they must reflect a regional climate signal rather than local scale effects, growth at the site must be limited by the climate variable of interest, and the trees must have annual rings that are datable. I sampled 20–40 trees per site at field sites in western Wyoming and eastern Idaho, near the headwaters of the Snake River, collecting two or more cores from each tree using an increment borer.

[11] In the laboratory, cores were mounted and finely sanded. Each core was dated to the calendar year using the established dendrochronological technique of crossdating [Douglass, 1941]. This method of pattern matching allows for the identification of false and locally absent rings and for accurate dating. The individual rings of each dated core were measured to 0.001 mm. The dated and measured series were checked for dating and measurement errors by standardizing a set of site chronologies, creating a master chronology, and correlating segment lengths of each core to the master chronology through comparison of annual ring widths using the program COFECHA [Holmes, 1983]. The cores were then processed in ARSTAN [Cook, 1985], detrended with a cubic spline two-thirds the length of the series to remove the trend toward smaller ring widths as the tree size increases in diameter, standardized, and combined to form site chronologies.

[12] In order to create the most robust possible pool of predictor chronologies, additional chronologies in the region were acquired from other researchers (see Table 1) and the International Tree Ring Data Bank ( These data were obtained in raw ring width measurement format and subjected to the same chronology development process described in the preceding paragraph. Tree ring time series are often autocorrelated due to biological processes that carry over from year to year (e.g., multiyear needle retention in conifers) [Fritts, 1976]. In this study, significant autocorrelation in all chronologies was removed using autoregressive-moving average (ARMA) filtering [Box and Jenkins, 1970], and the resulting residual chronologies were used for further analyses.

Table 1. Metadata for Tree Ring Sites Used in the Reconstruction Model
Site CodeContributorSpeciesLatitudeLongitudeElevation (m)Start YearEnd YearMean SensitivityInterseries Correlation
FMTS. GrayDouglas fir42.96−109.772300150720060.310.76
HRITeton Science SchoolLimber pine43.30−110.672000150520060.290.59
RDHE. WiseLimber pine43.62−110.442300132220060.270.61

3.3. Reconstruction Model Selection and Analysis

[13] Predictor sites were limited to chronologies covering (at minimum) the 1600–2005 time period in order to extend the reconstruction. Each tree ring chronology was tested for significant correlation with the instrumental streamflow record over the entire period (1911–2006) and in a split sample test (1911–1957 and 1958–2006). Site chronologies that were significantly correlated with streamflow over the whole period (p < 0.05) and over the split half periods (p < 0.10) were retained for further analyses. Chronologies lagged 1 year forward and backward were also tested as potential predictors to account for differences in timing between the tree growing season and the water year. These were treated as separate variables and subjected to the same significance testing.

[14] A linear multiple-regression model was selected using an iterative fitting (through a forward stepwise procedure) and cross-validation process, allowing in additional predictors that improved model calibration without overfitting the model. The selected model consisted of three site chronologies: a Pinus flexilis (limber pine) site collected by the author, a Pseudotsuga menziesii (Douglas fir) chronology provided by Stephen Gray of the University of Wyoming, and a Pinus flexilis site collected by the Teton Science School in Jackson, Wyoming (Table 1). The model was used to reconstruct water year streamflow for the 1591–2005 time period. I limited the reconstruction to this 415 year time period in order to ensure sufficient sample depth (Figure 3). Extreme low-flow individual years and periods were calculated based on a cutoff of two standard deviations (SD) below mean flow. Moving average filters of varying lengths were applied to examine longer-term wet and dry periods. Multiyear, low-flow events were delineated based on consecutive years of below-mean flow.

Figure 3.

Sample depth through time (number of individual trees) for the tree ring chronologies used in the reconstruction model, 1591–2005 (see Table 1 for site metadata).

3.4. Comparison With Other Streamflows and Climate Indices

[15] Past studies have shown that snowpack and streamflow tend to be out of phase in northern and southern areas of the West [Meko and Stockton, 1984; Cayan, 1996]. This has been attributed in part to ENSO-related modulation of synoptic scale patterns in storm track position and storm intensity: in El Niño years, there tend to be low-latitude storm tracks across the West and increased moisture in the southwest, while higher-latitude storm systems during La Niña conditions favor increased precipitation in the northwest [Cayan et al., 1999]. This sets up a dipole pattern of out-of-phase hydroclimatic anomalies between the northwest and southwest United States.

[16] To examine this contrasting response pattern, I compared Snake River streamflow over the instrumental and reconstructed periods to streamflow records in three previously reconstructed rivers: the Verde River [Meko and Hirschboeck, 2008], the Sacramento River [Meko et al., 2001], and the upper Colorado River [Meko et al., 2007]. The upper Snake River and the Verde River lie in the northern and southern ENSO response regions, respectively, while the Sacramento and upper Colorado rivers are located in a region with a mixed ENSO signal (Figure 2). Reconstructed streamflow data for these rivers, obtained from TreeFlow (, were compared to Snake River streamflow using correlations and by examining the synchronicity of high- and low-flow years. Following Meko and Stockton [1984], the probability of synchronous and asynchronous wet and dry years (based on >1 or <−1 SD from the mean) occurring by chance was tested using a binomial model,

equation image

where Pm is the probability that the observed opposition or synchronicity of streamflow is by chance, n is the sample size (the number of dry or wet years in the Snake River), m is the number of dry or wet years in the comparison river, and p is the probability of a wet or dry streamflow year in the Snake River over the entire period of the reconstruction. Averaged June–November southern oscillation index (SOI) values from the University of East Anglia ( were also correlated with streamflow over the 1911–2006 Snake River instrumental period.

4. Results and Discussion

4.1. Reconstruction Model

[17] Comparative statistics of reconstructed and instrumental streamflow and model calibration and validation statistics for the JCK and HEII gages are shown in Tables 2 and 3. The reconstruction models for the JCK and HEII gages incorporated the same three site chronologies, and the gages are highly correlated (r > 0.96, p < 0.01) over both the instrumental period and in their reconstructed flows. Because of this similarity and the fact that HEII incorporates a greater percentage of the overall flow in the upper Snake River, this lower gage will be the focus of the following results and discussion.

Table 2. Descriptive Statistics for Observed and Reconstructed Snake River Water Year Streamflow (MCM) at Jackson Lake Dam, Wyoming (JCK), and Near Heise, Idaho (HEII)
JCK Observed1910–2008128112455852306314
JCK Reconstructed1591–2005127312916041917225
HEII Observed1911–2008619860953186106091478
HEII Reconstructed1591–200561676254288295161089
Table 3. Calibration and Validation Statistics for Streamflow Reconstruction Modelsa
GagePredictor Sites (Lag)r2radj2F Levelp ValueSERERMSEPortmanteau Q (p)
  • a

    SE, standard error of the estimate; RE, reduction of error statistic; RMSE, root mean square error. RE and RMSE are based on cross validation. SE and RMSE are measured in units of total water year flow (MCM).

JCKHRI(0)/FMT(−1)/RDH(0)0.560.5539.310.002120.522188.72 (0.56)
HEIIHRI(0)/FMT(−1)/RDH(0)0.630.6250.520.009270.5995011.85 (0.30)

[18] The reconstruction model is fairly robust, explaining 62% of the variance in the instrumental record after adjustment for degrees of freedom (Table 3). While this is less than the predictive power of some southwestern streamflow reconstructions like the Colorado River at Lees Ferry, AZ (r2 up to 0.84) [Woodhouse et al., 2006], it compares favorably to northwestern reconstructions, including the Yellowstone River (radj2 = 0.52) [Graumlich et al., 2003], the Columbia River (r2 = 0.35) [Gedalof et al., 2004], the Oldman River (radj2 = 0.37) [Axelson et al., 2009], and the Wind River (radj2 = 0.38) [Watson et al., 2009]. Although the model is able to capture low flows and moderately high flows well, very high flow years such as 1997 (which is an extreme outlier in the instrumental record) are underpredicted by the tree ring model (Figure 4).

Figure 4.

Modeled (gray) and observed (black) total water year streamflow (MCM) for the Snake River near Heise, Idaho, 1911–2005.

[19] The reduction of error (RE) statistic [Fritts, 1976], which can range from −∞ to 1, is greater than 0 (0.59), signifying that the model has predictive skill (Table 3). The root mean square error (RMSE) from the cross validation is close to the standard error (SE) of the calibration period, indicating that the model skill is not a product of overfitting. Regression residuals are normally distributed. Statistical tests for first-order autocorrelation (based on the Durbin-Watson test) and trend in the residuals indicate that neither is significantly present (p < 0.05).

4.2. Streamflow and Drought in the Upper Snake River

[20] The 415 year reconstruction of streamflow in the upper Snake River extends from A.D. 1591 to 2005 (Figure 5). This reconstruction lengthens the instrumental record by over 300 years, allowing a comparison of instrumental records with longer-term variability. The instrumental period is representative of individual extreme low-flow years. Years in the historical record such as 1977 and 2001 are quite severe even in the context of the longer-term record: with <60% of mean flow, these years rank among the top 10 low-flow years of the reconstruction. The more severe individual years in the reconstruction (Table 4) are not outside of the range of variability that would be expected from the instrumental record; however, regression models tend to bias reconstructed flows toward the calibration-period mean [Meko et al., 2007]. Low-flow individual years are distributed fairly evenly over each century of the reconstructed record (Table 4).

Figure 5.

Reconstructed total water year streamflow (MCM), Snake River near Heise, Idaho, 1591–2005 (gray), with reconstruction 85th, 50th, and 15th percentiles (top to bottom; solid horizontal lines), RMSE (dotted horizontal lines), and 11 year moving average (thick black line).

Table 4. Upper Snake River Reconstructed n Year Means Two Standard Deviations or More Below Period Meana
1 Year5 Year11 Year21 Year
YearWater Year Flow (MCM)PeriodAverage Water Year Flow (MCM)PeriodAverage Water Year Flow (MCM)PeriodAverage Water Year Flow (MCM)
  • a

    Instrumental period years are in bold.

16953729    1639–16595694
19003943    1885–19055699

[21] While individual extreme low-flow years are of concern, long-term periods of drought can be particularly taxing for water systems. Decadal variability in the reconstructed streamflow record was examined through the application of 5, 11, and 21 year moving average filters to the yearly time series (Table 4) and to standardized values of the yearly time series (Figure 6). The 1930s Dust Bowl drought is a severe period even in the context of the longer-term record: the 1930s rank high amongst the driest periods when examined over multiple time scales (Table 4).

Figure 6.

Eleven year moving average of standardized (anomaly) values in reconstructed total water year streamflow, Snake River near Heise, Idaho. Gray shading represents periods above mean flow; black signifies periods below mean.

[22] Instrumental period droughts are eclipsed by conditions in the early to mid-1600s reconstructed flow. This period was severe in both magnitude and duration, dominating the record of drought periods (Table 4). Low-flow conditions were sustained over a long time period, with below-mean flow in 24 of the 34 years between 1626 and 1659 (Figure 6). This drought period has been documented in several other paleoclimate records in the West. Reconstructions of precipitation (A.D. 1226–2001) [Gray et al., 2004] and Palmer Drought Severity Index (A.D. 1405–2001) [MacDonald and Tingstad, 2007] in northeastern Utah identified this early to mid-1600s period as one of the most severe droughts on record in the Uinta Basin. LaMarche [1974], in a study of tree ring records from California bristlecone pines, identified the beginning of this drought period (∼1620s) as the time of a climatic regime shift from cool moist to cool dry. Using tree ring reconstructions of the Palmer Drought Severity Index, Fye et al. [2003] identified a “1930s Dust Bowl-like” drought from 1626 to 1634 that was centered over the Snake River headwaters and extended southwest across Utah, Nevada, and California.

[23] Unbroken periods of dry conditions can be particularly challenging for water resource management. Consecutive years of below-mean flow lasted in length from 2 to 7 years over the reconstructed record (Figure 7). The longest (7 year) periods occurred during the early 17th and 18th centuries. Examined this way, the 21st century drought would fall into the 6 year category (2000–2005), as it was interrupted by moderate flow in 2006. Over the past 415 years, there were six other periods in the record with consecutive low-flow periods as long as or longer than the early 21st century drought.

Figure 7.

Consecutive year periods of below-mean flow in the reconstructed record of the Snake River near Heise, Idaho.

4.3. Synchronicity Between Western Rivers

[24] A dipole pattern of contrasting north-south anomalies in Western precipitation, streamflow, and snowpack records has been noted in previous research and attributed in part to ENSO-related modification of the prevailing storm track position [Redmond and Koch, 1991; Cayan, 1996; Dettinger et al., 1998]. Results from this study indicate that streamflow in the upper Snake River and the Verde River do have nearly equal, but opposite, correlations with SOI over the instrumental period (r = 0.35 and −0.32, respectively; p < 0.01), while the upper Colorado and Sacramento rivers do not have a significant ENSO signal. A north-south, out-of-phase relationship does not dominate the reconstructed streamflow records, however. Over the instrumental period, upper Snake River streamflow was significantly correlated with flow in both the upper Colorado and Sacramento rivers but had neither a positive nor negative correlation with the Verde River (Table 5). Over the longer period available from the reconstructed flows of the four rivers, the upper Snake River maintained a positive, significant relationship with the upper Colorado and Sacramento rivers and also has a low, but significantly positive, correlation with the Verde River (Table 5).

Table 5. Correlations Between Streamflow in the Snake River Near Heise, Idaho, and the Colorado, Sacramento, and Verde Riversa
 Instrumental 1911–2005Reconstructed
  • a

    p < 0.01 for all values. NS, not significant.


[25] All four rivers have had periods of synchronous and asynchronous flow (Figure 8). The strong and extended pluvial period across much of the West in the early 20th century is reflected in the records of all rivers in this study, though with an earlier peak in the Sacramento River record. This wet period coincided with much of the water development in the West, including the creation of the Colorado River Compact in 1922 [Stockton and Jacoby, 1976] and the initial construction of the Jackson Lake Dam in the headwaters of the Snake River in 1906. The 1930s Dust Bowl drought severely impacted northerly areas in the West and was the most extreme drought in the Snake and Sacramento rivers' instrumental records, but the upper Colorado and Verde rivers were more severely impacted by the 1950s drought. The upper Snake River was out of phase with the Verde River in the mid-1600s and mid-1800s (Figure 8). Correlation between flows in the upper Snake and the Sacramento and Verde rivers was highest in the 1700s (Table 5), a period characterized by low ENSO activity [Braganza et al., 2009] that was previously noted as a period of joint drought in the Sacramento and Blue river basins [Meko and Woodhouse, 2005]. In the latter half of the 20th century, a time characterized by unusually high ENSO activity [Gergis and Fowler, 2009], the Snake and Verde rivers have been particularly asynchronous (Figure 8c).

Figure 8.

Eleven year moving averages of standardized reconstructed water year total streamflow for (a–c) the Snake River near Heise, Idaho (gray), (a) the Colorado River at Lees Ferry (black), (b) the Sacramento River four rivers index (black), and (c) the Verde River below Tanglewood Creek (black). Gage locations are shown in Figure 2.

[26] Over the 1591–2005 reconstruction period, the percentage of years with simultaneous above- or below-average flows in the Snake and Verde rivers (52%) was approximately equal to the percentage of years with flows of opposite signs in the two rivers (48%). There were more episodes of synchronous high flow (>+1 SD) or low flow (<−1 SD) in the Snake and Verde rivers (24 occurrences in the 415 year record) than events with high flow in one of the rivers and low flow in the other (15 occurrences) (Table 6). On the basis of a binomial model, the probability that these synchronous and asynchronous flows occurred by chance ranged from 0.03 to 0.14 (Table 6). The Snake and Verde rivers had a greater percentage of asynchronous flow than occurred between the Snake and Colorado rivers (7 of 415 years) or the Snake and Sacramento rivers (5 of 387 years). In the 387 year overlapping record of all four reconstructions, there were just nine occurrences of synchronous high- or low-flow conditions (based on 1 SD) in all four rivers (Table 6), but flow in the four rivers was of the same sign (above or below average) in 30% of individual years.

Table 6. High- and Low-Flow Years in the Snake and Verde Riversa
 Asynchronous YearsSynchronous Years
Snake River>+1 SD<−1 SD>+1 SD<−1 SD
Verde River<−1 SD>+1 SD>+1 SD<−1 SD
  • a

    SD, standard deviation; Pm, probability of occurrence by chance.

  • b

    Sacramento and Colorado rivers > +1 SD.

  • c

    Sacramento and Colorado rivers < −1 SD.

 1971 17871990

[27] The shifts between synchronous and dipole patterns in Western streamflow may be associated with two distinct modes of variation noted previously in research on instrumental precipitation and streamflow patterns [Sellers, 1968; Meko and Stockton, 1984]: (1) north-south fluctuations in storm track position that result in dominantly zonal flow and a dipole pattern of hydroclimatic variability and (2) east-west shifts in atmospheric pressure systems that result in meridional flow and West wide synchronicity. North-south zonal fluctuations have been attributed to ENSO-related shifts in the prevailing storm track position. Strong and persistent cool season meridional flow can result from atmospheric blocking caused by the failure of the Pacific subtropical high to retreat from its summer position [Carrera et al., 2004], as well as from changes in the strength and amplitude of the Pacific North American pattern (PNA) [Wallace and Gutzler, 1981]. A positive PNA pattern, characterized by a strong Aleutian low, ridging in the eastern Pacific and western United States, and a deep trough in the eastern United States, has been linked to snow deficits over the West in winter [Cayan, 1996] and low-flow conditions in western rivers over the instrumental period [Meko and Stockton, 1984].

[28] It is likely that both modes of variation have impacted drought in the Snake River Basin. Precipitation and streamflow in the headwaters of the Snake River have a modest but significant ENSO signal in the instrumental period, although this may also have been a time period of higher frequency and more extreme ENSO activity [Gergis and Fowler, 2009] relative to the previous three centuries. On the basis of spatial drought patterns in the four rivers, there are indications of a zonal flow pattern during two of the most severe droughts in the Snake River record (the 1630s and the 1930s), which were much less severe in the Verde River record. The Snake River's low-flow period in the early 1700s, which was long lasting but less severe in magnitude, is replicated in the flow of all four rivers and may be indicative of drought conditions resulting from persistent meridional flow.

5. Conclusions

[29] This study presented the first long-term record of streamflow in the Snake River, one of the West's largest rivers and a vital source of water for the Pacific Northwest. Results indicate that 20th and 21st century drought patterns are generally representative of the longer-term record. Individual low-flow years in 1977 and 2001 and the longer-term 1930s Dust Bowl drought meet or exceed the magnitude of dry periods in the extended reconstructed period. In terms of overall severity, though, the instrumental record does not contain a drought of the extent seen in the mid-1600s. Twenty-four of 34 years in the 1626–1659 time period had below-average flow, including periods of six and seven consecutive below-mean years (1626–1632 and 1642–1647). During the most severe period from 1626 to 1647, 17 of 22 years (77%) were below-normal flow. This type of event could represent a new “worst-case scenario” for water planning in the upper Snake River.

[30] In the context of longer-term variability in the upper Snake River, the early 21st century drought is severe in terms of both single low-flow years and consecutive years of below-mean flow. The 5 year period from 2000 to 2004 was the second driest in the 415 year record. Despite above-average flows in 2006, 2008, and 2009, this is an ongoing drought. With only 70% of the mean flow, 2007 was another very dry year, and regional snowpack in 2010 was again low. The degree to which this drought matches or exceeds severe droughts in the long-term record cannot be determined until its overall duration is known.

[31] River systems across the West, including the Colorado, Sacramento, Verde, and Snake rivers examined in this study, have had shared pluvial and droughts periods that may be related to atmospheric blocking, strong ridge-trough patterns, and changes in storm track position. Robust reconstructions of synoptic scale atmospheric patterns are needed to distinguish ENSO-related signals from other driving forces of hydroclimatic variability. Drought forecasting for the upper Snake River would also be improved through better understanding of year-to-year variations in the PNA and other short-term synoptic conditions that can significantly impact moisture delivery to the region.


[32] The Teton Science School and Stephen Gray provided two of the tree ring chronologies used in this study. I thank Erica Bigio and Troy Knight for their assistance with field work and Rex Adams, David Meko, and Connie Woodhouse for providing valuable guidance on the project. This research was supported by Society for Women Geographers' Pruitt National Fellowship, Margaret Trussell Scholarship from the Association of Pacific Coast Geographers, Association of American Geographers dissertation award and by United States Environmental Protection Agency (EPA) under the Science to Achieve Results (STAR) Graduate Fellowship Program. EPA has not officially endorsed this publication, and the views expressed herein may not reflect the views of EPA.