1. Introduction
Globally droughts pose significant social and ecological threats in part because of limited water availability in rivers and streams (Harding et al. 1995; Heim 2002; Lake 2003; Golladay et al. 2004; Bond et al. 2008; van Dijk et al. 2013; van Lanen et al. 2016). Reduced streamflow during drought in the western United States has wide ranging effects, which can impact society and ecosystems as a result of their severity and spatial extent (Cayan et al. 2010; Dettinger et al. 2015). While seasonal drought is a regular feature of the climate in much of the western United States, changes in the frequency, timing, magnitude, or spatial extent of droughts would compel adaptive changes in human water use and could further jeopardize aquatic biota and ecosystems because of decreased streamflow (Chang and Bonnette 2016; Gleick 2016). Regional variation of streamflow responses to meteorologic drought is important for assessing vulnerability as part of drought planning and management.
Pervasive drought across the western United States during 2015 provides a case for examining streamflow vulnerability to low spring snowpack, a dry spring, and a dry summer under warm temperatures. Above-normal temperatures and below-normal precipitation enveloped much of the western United States during 2015 (Fosu et al. 2016; Mote et al. 2016; National Centers for Environmental Information 2016; Harpold et al. 2017). January–March 2015 temperatures generally were more than 4°C above normal west of −105° latitude and below-normal precipitation extended from coastal California and Oregon across to the Sierra Nevada, the Cascades, the Great Basin, and the central Rocky Mountains (National Centers for Environmental Information 2016). Early spring snowpack was exceptionally low (Mote et al. 2016). As the spring progressed, the region of below-normal precipitation shifted north into the Olympic and North Cascade Ranges, and northern Rocky Mountains, while temperatures more than 2°C above normal persisted over the Pacific Coast states, Great Basin, and northern Rockies.
The National Weather Service Climate Prediction Center (2018) forecast drought conditions in the spring 2015, leaving regional water managers to ask: how would streamflow respond to a warm, dry spring, particularly where winter precipitation may have been near normal? The objectives for this analysis are to examine spatial variation in streamflow responses across the western United States to the amount, form, and seasonal timing of precipitation during 2015 and compare approaches for assessing streamflow vulnerability to drought, for example, from long-range (+3 month) quantitative precipitation forecasts.
Streamflow responses to meteorological drought (Heim 2002) are conditioned on the seasonal characteristics of a particular drought and the capacity of river basins to store water, which lead to variation in the runoff response across river systems and among different types drought (Risbey and Entekhabi 1996; Andreadis and Lettenmaier 2006; Safeeq et al. 2014; Stoelzle et al. 2014; Solder et al. 2016; Harpold et al. 2017). In a general vulnerability framework (Turner et al. 2003), streamflow in a river is vulnerable to drought because of the combination of its sensitivity to precipitation and the river’s exposure to precipitation deficits. Sensitivity generally indicates how much water is stored in a river basin over time scales longer than the drought and vulnerability represents streamflow responses during a particular drought. The vulnerability of streamflow to drought is essential for predicting long-term impacts from climate change on water resources in the region (Dai 2013; Overpeck 2013; Diffenbaugh et al. 2015; Cooper et al. 2016), but also for near-term forecasting of water availability used to invoke drought management actions such as switching water supplies from surface water to groundwater, curtailing water uses, or leasing water rights to maintain in-stream flows (Glantz 1982; Seattle Public Utilities 2006; California State Water Resources Control Board 2015; Cronin 2015).
Drought vulnerability assessment must specify a functional form for streamflow responses to precipitation (Safeeq et al. 2014). If the difference between annual precipitation and streamflow is relatively constant year-to-year, streamflow has a zero-order relation to precipitation and streamflow deficits during a drought year can be estimated from precipitation deficits for the year. Alternatively, if the ratio of streamflow to precipitation is relatively constant year-to-year, streamflow has a first-order relation precipitation and streamflow during a drought year scales linearly with precipitation. Methodological bias in vulnerability assessment associated with aridity is a key issue in the western United States because of the range of environments, which spans from deserts to rain forests and can lead to divergent conclusions regarding vulnerability (Andreadis and Lettenmaier 2006; Safeeq et al. 2014). Bias of low-order models may limit their utility for assessing river vulnerability to extreme drought and these limits should be known before applying such model.
2. Data and analytical methods
Streamflow responses to precipitation and snowpack during 2015 are examined at 324 streamflow gauges operated by the U.S. Geological Survey on rivers in the contiguous United States draining to the Pacific Ocean or the Great Basin (Konrad et al. 2018; supplemental material S1). Multiple linear regression models are applied to account for the spatial variation in seasonal streamflow as a result of spatial variation in the amount and form of precipitation: autumn is defined as October–December (OND), winter is January–March (JFM), spring is April–June (AMJ), and summer is July–September (JAS). The results indicate the comparative effects of the form and amount of seasonal precipitation. The vulnerability of streamflow to the 2015 drought is assessed using at-site “normative” models that compare the relations between streamflow and precipitation during 2015 to the relations for a “normal” water year.
a. Datasets
Gauges were included in the analysis if daily streamflow records were available for at least 10 years from water year (WY) 1981 to WY 2015 and the gauge was active in 2015 (U.S. Geological Survey 2017). Gauges were excluded from the analysis if they are downstream of large dams, extensive diversions, point discharges, or land uses likely to alter streamflow (Falcone 2011, Table 1). More than half of the gauges had 35 years of record. Streamflow was aggregated monthly, seasonally, or annually, divided by the drainage area at the gauge and is reported as runoff Q (mm).
Criteria for low-likelihood of anthropogenically altered streamflow. Data from Falcone (2011).
Mean annual precipitation
Snowpack and runoff data were not available for the complete climate normal period at all sites, so normal spring snow water equivalent (SWEN) is the median annual 1 April SWE for 2005–15 and normal water-year runoff
Uncertainty in
Significant downward bias in precipitation was evident in wet basins where normal runoff exceeded normal precipitation. Bias is a structural issue for interpolated precipitation data in the western United States because of the lack of high-elevation observations (Henn et al. 2018). Xia (2008) reported bias in PRISM precipitation of ~150 mm at 600 mm yr−1. Precipitation values were inflated by a factor of 1.25 presuming the bias scales linearly with precipitation. Adjusted
b. Spatial variation in seasonal runoff during the 2015 drought
Multiple meteorological factors contributed to the 2015 drought in the western United States. The effects of seasonal precipitation and spring snowpack on spatial variation in seasonal runoff were evaluated using multiple linear regression (R Core Team 2018). This approach presumes that cross-site deviation of runoff from its cross-site mean value is related to cross-site variation in precipitation and snowpack. Models were developed separately for distinct hydroclimatic strata to account for potential differences in the responses of seasonal runoff related to gross variation across the region in climatologies, 2015 weather, and dominant runoff mechanisms. The use of strata helps resolve the effects of specific factors that may not be important in all rivers (e.g., snowpack in rain-dominant systems).
The hydroclimatic strata were defined by the seasonal distribution of normal water-year streamflow (Table 2). Five strata with distinct seasonal timing and sources of runoff were identified: 1) spring snowmelt, 2) snow–rain transition, which has high winter and spring runoff, 3) winter rain, 4) autumn–winter rain, and 5) summer rain (Fig. 1). Final assignments of rivers were examined by location, mean basin elevation, and normal snow water equivalent on 1 April as a fraction of normal precipitation. The strata are used to summarize differences in seasonal responses to drought, which may be related to either dominant runoff mechanisms or spatial patterns of precipitation during 2015.
Hydroclimatic strata for analysis of seasonal runoff. Autumn is October–December, winter is January–March, spring is April–June, and summer is July–September.
Distributions of normal seasonal runoff for five hydroclimatic strata in the western United States.
Citation: Journal of Hydrometeorology 20, 7; 10.1175/JHM-D-18-0121.1
The coefficients
c. Runoff in June and August in rivers with normal WY 2015 precipitation
The comparative effects of rain and snow on runoff in June and August 2015 independent of water-year precipitation were examined in rivers where WY2015 precipitation was near normal (
d. Normative models for streamflow vulnerability to the 2015 drought
Normative models that quantify runoff responses to precipitation deficits in relation to “normal” conditions at a site provide a simple approach for assessing the vulnerability of streamflow to drought. The functional form of runoff responses to precipitation deficits in normative models influences how drought vulnerability is represented and, thus, both the assessment and prediction of vulnerability. Two normative models using zero- and first-order relations for runoff responses to precipitation are compared to the responses observed during 2015. Both models are simply at-site empirical relations between normal runoff and precipitation. As such, they can be applied easily in any river with observed precipitation and runoff to assess or predict drought responses presuming the relation would hold for a drought.
In this case, the first-order model leads to
Either normative model [Eqs. (5) and (6)] represents a tractable approach for estimating water-year runoff from quantitative forecasts of water-year precipitation that could be updated seasonally, but neither model is expected to provide precise estimates of runoff during a drought. Summer runoff in particular is likely sensitive to factors other than water-year precipitation (Milly 1994) including evapotranspiration, precipitation from convective storms, and interannual water storage in groundwater, snow, ice, lakes, or reservoirs.
3. Results
Water-year streamflow for 2015 was below normal in 87% of the rivers in this analysis but was not as pervasively low as many recent droughts (e.g., 1977, 1987, 1988, 1990, 1992, 1994, and 2001) when water-year streamflow was less than the 25th annual percentile for the median site (Fig. 2). The defining characteristic of hydrologic drought in 2015 was the spatial extent of low spring and summer streamflows across the western United States (Fig. 3). Spring 2015 streamflow was at the 5th percentile of annual values for the median gauge with at least 50 years of record from 1951 to 2015 (n = 166) and summer 2015 streamflow was at the 8th percentile.
Median values of annual percentiles of water-year, spring, and summer streamflow for 166 gauges in the western United States with at least 50 years of record.
Citation: Journal of Hydrometeorology 20, 7; 10.1175/JHM-D-18-0121.1
Runoff for June–August 2015 as a percentile of annual values for 1981–2015.
Citation: Journal of Hydrometeorology 20, 7; 10.1175/JHM-D-18-0121.1
Runoff responses to the 2015 drought had distinct seasonal patterns among the hydroclimatic strata that generally converged on below-normal summer runoff across the region (Fig. 4). The winter rain stratum, which extends across California, Arizona, and southern Oregon, had initial responses in winter when runoff was 0.47 of normal for the median site. In contrast, winter runoff was above normal for the median site in snow stratum and normal for the median site in snow–rain transition stratum. The drought resistance of the snow and transitional strata during winter is likely because precipitation fell as rain rather than snow during autumn and winter and snow that melted during the winter in response to warm temperatures. By the spring 2015, runoff was below normal for all strata (Fig. 4) except the summer rain stratum and remained below normal through the summer across the region. Most rivers recovered from the drought by the autumn 2015 when runoff was close to normal for all strata.
Distributions of seasonal runoff for 2015 as a fraction of normal for five hydroclimatic strata in the western United States.
Citation: Journal of Hydrometeorology 20, 7; 10.1175/JHM-D-18-0121.1
a. Effects of the amount and form of seasonal precipitation on spatial variation in seasonal runoff
Precipitation and its transseasonal storage in snowpack accounted for most of the variation in seasonal runoff during WY 2015 across the western United States with the exception of the summer rain stratum (Table 3). The influence of seasonal precipitation and spring snowpack diminish over time with the strongest effects on runoff in the same season. Winter runoff had significant effects from autumn–winter rain and snowmelt in all strata (coefficients ranging from 0.25 to 0.36 and
Summary of linear regression models for seasonal runoff during WY 2015. Autumn is October–December 2014, winter is January–March 2015, spring is April–June 2015, and summer is July–September 2015
The spring runoff models had
Summer runoff models generally accounted for less of the variation in runoff (
b. June and August runoff in rivers with near-normal precipitation for water year 2015
While runoff as a fraction of normal in June and August 2015 was significantly correlated with WY 2015 precipitation as fraction of normal (Kendall rank correlation of 0.30 and 0.26, respectively,
WY 2015 precipitation with (a) June 2015 and (b) August 2015 runoff and SWE on 1 April 2015 with monthly runoff in rivers with near-normal WY 2015 precipitation for (c) June 2015 and (d) August 2015. Rectangles in (a) and (b) comprise rivers where WY 2015 precipitation was near normal (±10%). Box and whiskers represent the 10th, 25th, 50th, 75th, and 90th percentiles of monthly runoff for rain-dominant sites.
Citation: Journal of Hydrometeorology 20, 7; 10.1175/JHM-D-18-0121.1
In rain-dominant rivers with near-normal WY 2015 precipitation, runoff as a fraction of normal in June and August 2015 had cross-river median values of 0.77 and 0.69 respectively (Figs. 5c,d). In comparison, June and August 2015 runoff in snow-dominant and transitional rivers with near-normal WY 2015 precipitation had median values of 0.56 and 0.63 of normal respectively. Snowpack had a significant effect on the variation in median June runoff as a fraction of normal across snow-dominant and transitional rivers,
Runoff deficits were common during August in both snow- and rain-dominant rivers even where water-year precipitation was near normal. While snowpack had a significant effect on median June runoff, its effect on median August runoff was not significant. Likewise, August runoff deficits in snow and snow–rain transition rivers were not more severe as a fraction of normal than the deficits in rain-dominant rivers where water-year precipitation was close to normal.
c. Vulnerability of runoff to drought
The zero- and first-order normative models for streamflow responses to precipitation lead to divergent assessments of drought vulnerability. For the zero-order model, the difference between precipitation and runoff for WY 2015,
Ratios of (a) WY runoff to WY precipitation and (b) July–September runoff to WY precipitation. The 1:1 line represents a precipitation elasticity of runoff, E = 1.
Citation: Journal of Hydrometeorology 20, 7; 10.1175/JHM-D-18-0121.1
Comparison of model errors.
The first-order model of runoff as a constant fraction of precipitation [Eq. (6)] provides more accurate and less biased estimates of runoff for WY 2015 than the zero-order model [Eq. (5); Table 4]. The performance of the first-order model reflects ratios of runoff-to-precipitation for WY 2015
The ratio of summer runoff to WY precipitation was generally less in 2015 than in normal years (Fig. 6b). For the median site,
4. Discussion
Across the western United States, streamflow during the spring and summer of 2015 generally was lower than in any drought over the last half century (Fig. 2). The spatial extent of spring runoff deficits (Fig. 3) resulted from the combination of below-normal precipitation in winter and spring that affected both snow- and rain-dominant rivers. Paradoxically, most snow-dominant rivers had more winter runoff than normal (1.6 for the median river, Fig. 4) because of precipitation falling as rain during the autumn and winter and midwinter snowmelt. Overall, however, low snowpack and the lack of spring rainfall led to lower spring and early summer runoff even in rivers with near-normal WY 2015 precipitation (Fig. 5c).
Runoff during the spring and summer 2015 was below normal in most rivers regardless of their hydroclimatic strata (Fig. 4). Above-normal temperatures and a corresponding increase in potential evapotranspiration may have contributed to below-normal spring and summer streamflow (Das et al. 2011; Williams et al. 2015; Diffenbaugh et al. 2015; Marlier et al. 2017) particularly in rivers with near-normal water-year precipitation (Figs. 5c,d), but precipitation deficits still had significant effects on spring and summer runoff (Mao et al. 2015; Cooper et al. 2016; Table 3). While, snow-dominant rivers were vulnerable to the 2015 drought because of low spring snowpack, snow-dominant rivers were not more vulnerable than rain-dominant rivers (Fig. 4) because of the pervasively dry spring.
The seasonal distribution of precipitation across the western United States (Cayan 1996; Mock 1996) produces distinct provinces where summer streamflow is vulnerable to particular types of drought. In provinces where summer typically is dry (e.g., coastal California), the vulnerability of summer streamflow primarily is controlled by exposure to low precipitation during winter. In contrast, both the Pacific Northwest and desert Southwest can receive substantial precipitation in the spring or summer. In these provinces, water-year precipitation is an incomplete measure of drought exposure for summer runoff, so accurate forecasts of spring and summer precipitation are necessary for forecasting runoff during a drought. Likewise, summer runoff responses to climate change will depends on accurate prediction of changes in seasonal precipitation.
The warm and dry winter and spring in 2015 across the western United States were linked through common control by sea surface temperature and atmospheric flow (Bond et al. 2015; Fosu et al. 2016; Mote et al. 2016), but winter and spring meteorology is not strongly coupled across the western United States in all years (Cayan et al. 1998). The strength of this coupling depends on the persistence of sea surface temperatures and atmospheric flow promoting warm and dry conditions from late fall through the spring (Dettinger 2013; Seager et al. 2015), which is critical for forecasting hydrologic droughts that encompass the region (Glantz 1982; Wood et al. 2015; Newman et al. 2016) and predicting their frequency in the future (Dettinger et al. 2011; Dai 2013). Forecasting summer hydrologic drought, however, can focus on precipitation for specific seasons that vary by province such as winter for the Sierra Nevada in California (Diffenbaugh et al. 2015; Mao et al. 2015), winter and spring in the Pacific Northwest (Glantz 1982; Cooper et al. 2016), and summer in the desert Southwest (Adams and Comrie 1997; Cayan et al. 1998).
Years with lower snowpack in the spring are likely to become more frequent across the western United States (Mote et al. 2005; Barnett et al. 2008), so spring and summer precipitation remain key uncertainties for predicting either summer runoff vulnerability to drought and the frequency, magnitude, and extent of extensive hydrologic droughts in the western United States. WY 2015 provides only weak evidence about the response of summer streamflow to variation in spring precipitation [Eq. (4), Table 3], which was pervasively low across the region. Rain-dominant rivers with near-normal precipitation typically had below-normal summer runoff in 2015 (Fig. 5) and summer 2015 runoff was generally a smaller fraction of water-year precipitation than in normal years in most rivers (Fig. 6b). The vulnerability of summer streamflow in snow-dominant rivers during a year with low snowpack but a wet spring remains an open and relevant question for assessing potential impacts from climate change in the western United States (Glantz 1982; Dettinger 2013; Cooper et al. 2016; Easterling et al. 2017; Gershunov et al. 2017).
The first-order model based on the normal ratio of runoff to precipitation
5. Conclusions
Streamflow was exceptionally low in the spring and summer of 2015 across much of the western United States because of the combination of low precipitation and snowpack that exploited the sensitivity of both rain-dominant and snow-dominant basins. Streamflow responses to the 2015 drought were generally consistent with a first-order model based on the at-site ratio of normal runoff to normal water-year precipitation, which is equivalent to a precipitation elasticity of runoff, E = 1. Greater vulnerability (lower runoff and E > 1) was indicated by bias in the model particularly in arid basins and during summer. A model that accommodates E > 1 is necessary for more accurate assessment of streamflow responses to extreme drought. Summer streamflow for much of the western United States depends on spring and summer precipitation, so prediction of streamflow responses during drought will depend on accurate forecasts of spring and summer precipitation. While lower spring snowpack in response to climate change will likely to reduce late spring and early summer runoff from snowmelt, late summer streamflow in many rivers will depend on changes in spring and summer precipitation.
Acknowledgments
U.S. Geological Survey and the National Oceanic and Atmospheric Administration National Integrated Drought Information System funded this investigation. My colleagues Jim Bartolino, Tana Haluska, Theresa Olsen, Dina Selah, and Kara Watson with the U.S. Geological Survey helped compile data used in the analysis.
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