Interannual Streamflow Variability Research Articles

Tree Rings as Proxies of Historical Runoff in a National Park in Northern Mexico: A Major Ecosystem Service Provider

A dendrochronological network of conifers (Pinus leiophylla, Pinus cembroides, Pinus engelmannii) was developed in the Cumbres de Majalca National Park (CMNP) in Chihuahua, Mexico, to reconstruct historical runoff patterns and examine the impact of ocean–atmosphere phenomena. The CMNP plays a vital role as a runoff source for Conchos River tributaries and groundwater recharge for Chihuahua City and nearby populations. The ring-width chronologies displayed a common signal from 1859 to 2021, with the highest association found between P. engelmannii and P. leiophylla (r = 0.65) and the lowest between P. cembroides and P. engelmannii (r = 0.55). The first principal component explained 75.7% of the variance, and among the species, P. leiophylla exhibited the highest correlation (0.624, p < 0.05) with the accumulated streamflow records from the previous November to July, allowing the construction of a bootstrapped model for runoff reconstruction. The reconstructed streamflow spanned from 1859 to 2014, with an average of 2.732 × 108 m3. Periods of low runoff occurred in 1860–1880, 1940–1960, and 1994–2014, while extreme wet years with high runoff occurred in 1865, 1884, and 1987. The interannual streamflow variability correlated significantly with ENSO indices (SOI, MEI, TRI, and sea surface temperature anomalies), particularly during the winter–spring seasons, indicating that warm phases of the ENSO increased precipitation and runoff. The analysis of return periods revealed probabilities for specific runoff volumes, enabling stakeholders to use the information to develop effective strategies for sustainable water allocation and utilization in the region.

Multi‐Year Controls on Groundwater Storage in Seasonally Snow‐Covered Headwater Catchments

AbstractSeasonally snow‐covered catchments in the western United States supply water to growing populations as both annual snowmelt‐driven streamflow and multi‐year groundwater recharge. Although interannual variability in streamflow is driven largely by precipitation, runoff efficiency (the ratio of streamflow to precipitation) in individual catchments varies by 50% or more. Recent work suggests that interannual variability in groundwater storage, inferred from winter baseflow, is a primary control on runoff efficiency, highlighting a need to quantify both the time scales on which groundwater storage varies and the hydro‐climatic drivers of storage. Using over a century of daily stream discharge data from 10 seasonally snow‐covered catchments in northern Utah, we find that temporal variability in winter baseflow, an index of groundwater storage, measured from mean daily January discharge, exhibits a 2–5‐ and 12–15‐year periodicity, driven by regional precipitation patterns and snowmelt dynamics. Specifically, multiple linear regression (MLR) modeling using antecedent hydro‐climatic variables demonstrates that winter baseflow (groundwater storage) was positively related to 3–4 years of antecedent annual precipitation, negatively related to the previous year's mean annual temperature, and positively related to 1–4 antecedent years of snowmelt rate and duration. Because antecedent baseflow (groundwater storage) is strongly related to runoff efficiency, these results suggest that more frequent and longer droughts in a future climate will reduce surface water supplies faster than otherwise expected. More broadly, these results highlight the importance of including the influence of antecedent climate on groundwater storage when modeling and managing water supplies from seasonally snow‐covered catchments.

Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation

Copula functions have been widely used in stochastic simulation and prediction of streamflow. However, existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months. To address this limitation, this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations. This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas. The up-to-down sequential method, which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach, was used to determine the structures of multivariate D-vine copulas. The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station, the inflow control station of the Longyangxia Reservoir in the Yellow River Basin. The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow. This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.

Decreases in Mean Annual Streamflow and Interannual Streamflow Variability Across Snow‐Affected Catchments Under a Warming Climate

AbstractIt has been found that a decreased fraction of precipitation falling as snow in a warmer climate significantly affects streamflow. Here, based on observations from 631 catchments over the contiguous United States, we proposed a framework to investigate the first‐order and second‐order hydro‐climatic relationships between annual streamflow and snowfall fraction. Results show that in addition to the mean annual streamflow, the interannual streamflow variability will also decrease with lower snowfall fraction in the context of warming. The positive relationship between streamflow variability and snowfall fraction may result from the asymmetric hydrological effects of snowfall in the wet and dry years. To our knowledge, it is the first attempt to detect the role of snowfall on the streamflow variability. This study provides new understandings of the second‐order hydro‐climatic effects, and these findings will facilitate decisions for water resource management in a changing climate.

The Influence of Atmosphere‐Ocean Phenomenon on Water Availability Across Temperate Australia

AbstractLinks between climate variability modes, rainfall, and streamflow are important for understanding the trajectories of change and dynamics in water availability. In this study, we examined the influence of the El Nino Southern Oscillation, Indian Ocean Dipole, Southern Annular Mode, and Interdecadal Pacific Oscillation modes on interannual variations in rainfall and streamflow in four hydroclimate regions. We also explored the link between climate variability modes and extreme rainfall and streamflow years. Climate mode indices, rainfall, and streamflow data from 1975 to 2018 were analyzed for 92 predominately forested catchments located across temperate Australia. Climate modes had divergent influences on streamflow and rainfall between and within regions. Across temperate Australia, a higher proportion of interannual variation in rainfall was explained by climate modes than for streamflow, indicating factors other than atmosphere‐ocean phenomena are important in determining interannual streamflow variability. Extremes in rainfall and streamflow across regions were related to the co‐occurrence of climate modes, with a stronger relationship between teleconnections and low rainfall/streamflow years than high rainfall/streamflow years. The study provides new insights into the regional drivers of hydrological extremes and consolidates our understanding of the role of teleconnections on water availability in the temperate zone of Australia.

Evaluation of Streamflow under Climate Change in the Zambezi River Basin of Southern Africa

The Zambezi River basin is the fourth largest basin in Africa and the largest in southern Africa, comprising 5% of the total area of the continent. The basin is extremely vulnerable to climate change effects due to its highly variable climate. The purpose of this study was to evaluate the impact of climate change on streamflow in one of the sub-basins, the Kabombo basin. The multi- global climate model projections were used as input to the Soil Water Assessment Tool (SWAT) hydrological model for simulation of streamflow under RCP 4.5 and RCP 8.5 climate scenarios. The model predicted an annual streamflow increase of 85% and 6% for high uncertainty and strong consensus, respectively, under RCP 8.5. The model predicted a slightly reduced annual streamflow of less than 3% under RCP 4.5. The majority of simulations indicated that intra-annual and inter-annual streamflow variability will increase in the future for RCP 8.5 while it will reduce for the RCP 4.5 scenario. The predicted high and moderate rise in streamflow for RCP 8.5 suggests the need for adaptation plans and mitigation strategies. In contrast, the streamflow predicted for RCP 4.5 indicates that there may be a need to review the current management strategies of the water resources in the basin.

Informing Stochastic Streamflow Generation by Large-Scale Climate Indices at Single and Multiple Sites

Despite the existence of several stochastic streamflow generators, not much attention has been given to representing the impacts of large-scale climate indices on seasonal to interannual streamflow variability. By merging a formal predictor selection scheme with vine copulas, we propose a generic approach to explicitly incorporate large-scale climate indices in ensemble streamflow generation at single and multiple sites and in both short-term prediction and long-term projection modes. The proposed framework is applied at three headwater streams in the Oldman River Basin in southern Alberta, Canada. The results demonstrate higher skills than existing models both in terms of representing intra- and inter-annual variability, as well as accuracy and predictability of streamflow, particularly during high flow seasons. The proposed algorithm presents a globally relevant scheme for the stochastic streamflow generation, where the impacts of large-scale climate indices on streamflow variability across time and space are significant.

Relative impacts of climate change and land cover change on streamflow using SWAT in the Clackamas River Watershed, USA

Abstract To understand the spatial–temporal pattern of climate and land cover (CLC) change effects on hydrology, we used three land cover change (LCC) coupled scenarios to estimate the changes in streamflow metrics in the Clackamas River Watershed in Oregon for the 2050s (2040–2069) and the 2080s (2070–2099). Coupled scenarios, which were split into individual and combined simulations such as climate change (CC), LCC, CLC change, and daily streamflow were simulated in the Soil and Water Assessment Tool. The interannual variability of streamflow was higher in the lower urbanized area than the upper forested region. The watershed runoff was projected to be more sensitive to CC than LCC. Under the CLC scenario, the top 10% peak flow and the 7-day low flow are expected to increase (2–19%) and decrease (+9 to −20 cm s), respectively, in both future periods. The center timing of runoff in the year is projected to shift 2–3 weeks earlier in response to warming temperature and more winter precipitation falling as rain. High streamflow variability in our findings suggests that uncertainties can stem from both climate models and hydrologic model parameters, calling for more adaptive water resource management in the watershed.

Temporal streamflow reduction and impact on the salt dynamics of the São Francisco River Estuary and adjacent coastal zone (NE/Brazil)

During the past decades, the São Francisco River basin encountered substantial changes due to intensive human activities such as river regularization and damming, and more recently, climate change. As a result, a decrease of streamflow in the lower São Francisco River sector has received considerable attention due to its drastic geomorphological and hydrodynamic changes. This study presents a detailed investigation on the changes of streamflow and its effect on spatiotemporal migration of estuarine plume along the São Francisco coastal zone from 1994 to 2017 based on salinity and water temperature extracted from HYCOM numerical modeling.The progressive saltwater intrusion from in situ observation for 2005 and 2017, is analyzed. The results show two distinct periods with substantial inter-annual variability of streamflow during the period from 1994 to 2011 and accentuated decreasing trends from the second semester of 2012 onwards, and discontinuous periodicities from later 2012 due to the extreme hydrological events of droughts. The spatiotemporal variability in salinity and water temperature on the coastal zone revealed a severe retraction of the estuarine plume due to the low streamflow rates, which started after the second semester of 2012, and the presence of Tropical Surface Waters (TSW, S > 35.9 g/kg) closer to the river mouth, shifting the previous estuarine mixing zone from the coastal region to inward areas of the estuary. The continuous penetration of saltwater towards inner areas of the São Francisco estuary (∼10 km upstream from estuary mouth) is attributed to the decline of water flow supply from the river upper reaches due to the extreme drought events and water conservation measures. These changes may lead to potential ecological and human problems due to persistent high salinity above the limit for human consumption (S > 0.5 g/kg) from the estuary mouth to the limits of local cities along the river.

Evaluation of Routed-Runoff from Land Surface Models and Reanalyses Using Observed Streamflow in Chinese River Basins

Previous studies have demonstrated that offline land surface models (LSMs) and global hydrological models (GHMs) can reasonably reproduce streamflow in large river basins. Global reanalyses supply fine spatiotemporal runoff estimates, but they are not fully intercompared and evaluated in China. This study assesses the routed-runoff from five offline LSM/GHM runs (VIC-CN05.1, CLM-CFSR, CLM-ERAI, CLM-MERRA, and CLM-NCEP) and three reanalysis datasets (ERAI/Land, JRA55, and MERRA-2) against the gauged streamflow (26 stations) in major Chinese river basins during 1980–2008. The Catchment-based Macro-scale Floodplain model (CaMa-Flood) is employed to route those runoff datasets to the hydrological stations. Four statistical quantities, including the correlation coefficient (R), standard deviation (STD), Nash-Sutcliffe efficiency coefficient (NSE), and relative error (RE), along with a ranking method, are used to quantify the quality of those products. The results show that the spatial patterns of both modeled and observed streamflow in summer are similar, but their magnitudes are different. Except for MERRA-2, the other products can reproduce well the interannual variability of streamflow in both the Yangtze and Yellow River basins. All products generally underestimate the magnitude and variance of monthly streamflow, while VIC-CN05.1 and JRA55 are closer to observations compared to other products. The correlation coefficients for all products are overall larger than 0.61, with the highest value (0.85) from VIC-CN05.1. In addition to CLM-MERRA, MERRA-2, and CLM-NCEP with relatively small precipitation, other products can simulate peak flow well with positive NSEs up to 0.41 (ERAI/Land). Considerable uncertainties exist among the eight products at the Yellow River outlet, which might be because the LSMs ignore frequent human activities. Based on the above statistics, performances of the eight runoff products are ranked in descending order as follows: VIC-CN05.1, ERAI/Land, JRA55, CLM-CFSR, CLM-ERAI, MERRA-2, CLM-MERRA, and CLM-NCEP, which provides a reference for flood/hydro-logical drought warning and hydroclimatic research in the future.

Streamflow variability and the role of snowmelt in a marginal snow environment

ABSTRACT Snowmelt in alpine regions supports hydroelectric power generation, water supply, and agricultural production. These regions are warming, and the impact on streamflow of changes in precipitation and the proportion falling as snow is of interest. We investigate the seasonality and interannual variability of streamflow in the Australian Alps, a key location due to the marginal snowpack with winter air temperatures close to 0°C, and focus on a small subalpine catchment with properties representative of an important part of the broader snow-affected region. Streamflow was highly responsive to precipitation inputs with little autocorrelation observed. Water years were divided into four hydrological seasons based on the mean properties of normalized cumulative inflows. The spring snowmelt season accounted for the greatest proportion of annual inflows (mean = 39 percent). However, correlations between seasonal and annual inflows were only significant in the other three seasons, and winter inflows were the most important contributor to annual variability. The present snowpack is highly variable and sensitive to synoptic-scale influences. Although significant future reductions in snow-covered area have been predicted, we find that water resources are more susceptible to observed declines in total precipitation and likely increases in evapotranspiration than to a shift to proportionally less snowfall.

The compensating effect of glaciers: Characterizing the relation between interannual streamflow variability and glacier cover

AbstractMeltwater from glaciers is not only a stable source of water but also affects downstream streamflow dynamics. One of these dynamics is the interannual variability of streamflow. Glaciers can moderate streamflow variability because the runoff in the glacierized part, driven by temperature, correlates negatively with the runoff in the non‐glacierized part of a catchment, driven by precipitation, thereby counterbalancing each other. This is also called the glacier compensation effect (GCE), and the effect is assumed to depend on relative glacier cover. Previous studies found a convex relationship between streamflow variability and glacier cover of different glacierized catchments, with lowest streamflow variability at a certain optimum glacier cover. In this study, we aim to revisit these previously found curves to find out if a universal relationship between interannual streamflow variability and glacier cover exists, which could potentially be used in a space‐for‐time substitution analysis. Moreover, we test the hypothesis that the dominant climate drivers (here precipitation and temperature) switch around the suggested optimum of the curve. First, a set of virtual nested catchments, with the same absolute glacier area but varying non‐glacierized area, were modelled to isolate the effect of glacier cover on streamflow variability. The modelled relationship was then compared with a multicatchment data set of gauged glacierized catchments in the European Alps. In the third step, changes of the GCE curve over time were analysed. Model results showed a convex relationship and the optimum in the simulated curve aligned with a switch in the dominant climate driver. However, the multicatchment data and the time change analyses did not suggest the existence of a universal convex relationship. Overall, we conclude that GCE is complex due to entangled controls and changes over time in glacierized catchments. Therefore, care should be taken to use a GCE curve for estimating and/or predicting interannual streamflow variability in glacierized catchments.

Interdependent effects of climate variability and forest cover change on streamflow dynamics: a case study in the Upper Umvoti River Basin, South Africa

Streamflow dynamics are sensitive to both climate variability and land use change. However, estimating their separate and combined effects remains a research challenge. In South Africa, streamflow dynamics are important not only for irrigated agriculture but also for many rural communities that depend on streamflow for domestic water supply. In this paper, we analysed the effects of pine, wattle and eucalyptus plantation cover change vis-a-vis the effects of inter-annual climate variability on streamflow dynamics of the Upper Umvoti River in South Africa from 1994 to 2016. We modelled inter-annual variability in streamflow by precipitation, temperature and plantation cover using the Bayesian inference. We mapped plantation cover from Landsat satellite imagery. We found strong evidence for an interaction between temperature range and plantation cover net change on streamflow. Specifically, the plantation effect weakened under conditions of high-temperature range anomalies. We explain this interaction with a shift in soil water repellency and interception capacity within the plantation area under a changing temperature range, with important implications for the formation of surface runoff. Previous studies have assumed that the effects of climate variability and plantation cover change on streamflow dynamics are independent. Our results call this assumption into question. Hence, climate and land cover interdependencies should be accounted for in future statistical and process-based modelling studies.

On the Effect of Nonlinear Recessions on Low Flow Variability: Diagnostic of an Analytical Model for Annual Flow Duration Curves

AbstractPredicting the proportion of the water year a given stream will remain at or above various flow thresholds is critically important for making sound water management decisions. Flow duration curves (FDCs) succinctly capture this information using all data available over some historical period, while annual flow duration curves (AFDCs) instead use data from each individual water year. Analyzing the population of AFDCs, and in particular the tails of this distribution, can allow water managers to better prepare for years with extreme streamflow conditions. However, long time series of observations are necessary to capture interannual streamflow variations and are problematic to obtain in rapidly changing and poorly gauged catchments. By incorporating a process‐based model to construct AFDCs based on daily rainfall statistics and flow recession characteristics, the proposed approach is a first step toward addressing this challenge. Results indicate that prediction performance varies substantially across flow quantiles and that the current model fails to properly capture the interannual variability of low flows. Numerical analyses attributed these errors to nonlinearity in storage‐discharge relation, rather than cross‐scale streamflow correlations and non‐Poissonian rainfall, explaining the origin of commonly observed heavy‐tailed behavior in low flow quantiles. We present a case study on hydroelectric power generation, showing that faithfully capturing both interannual streamflow variability and recession nonlinearity has important implications for installation profitability.

Moisture transport associated with large precipitation events in the Upper Colorado River Basin

Interannual streamflow variability poses numerous water supply forecasting and management challenges for mountain snowpack‐sourced basins across the western United States. Previous studies have shown that substantial proportions of annual precipitation occur during relatively few large precipitation events (LPEs) and consequently, such events tend to be significant predictors of streamflow for many basins, including the Upper Colorado River Basin (UCRB). While some primary pathways of atmospheric moisture transport, particularly atmospheric rivers, have been linked with extreme precipitation events across the western United States, this study seeks to expand on this knowledge by quantifying the relationships between moisture transport regimes, LPEs, and streamflow observed in the UCRB. A climatological analysis of integrated vapour transport, via a self‐organizing maps synoptic classification procedure, is used to identify geographic regimes of moisture transport that lead to LPEs, as observed at snow telemetry sites across the UCRB headwaters. Trajectory analyses are also calculated to further characterize LPE‐inducing atmospheric river pathways by subbasin in the UCRB. Results indicate that LPEs throughout the basin most commonly coincide with amplified trough patterns, which advect Pacific moisture into the UCRB from the southwest, through Southern California and the Four Corners region; patterns that are positively correlated to streamflow. LPEs occurring in northern portions of the UCRB exhibit a secondary corridor, featuring west to east‐oriented moisture transport, in association with zonal to meridional flow regimes. Highly amplified ridges over the region rarely lead to LPEs, as such patterns deflect or suppress moisture from the UCRB. These results suggest that climate projections of future enhanced meridional flow aloft will lead to continued streamflow variability in the UCRB.

On the Sensitivity of Annual Streamflow to Air Temperature

AbstractAlthough interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration ( ), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness ( /P) at an annual time scale is identical to that linking interbasin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently.

Catchment water storage variation with elevation

One of the most important functions of catchments is the storage of water. Catchment storagebuffers meteorological extremes and interannual streamflow variability, controls the partitioningbetween evaporation and runoff, and influences transit times of water. Hydrogeological data toestimate storage are usually scarce and seldom available for a larger set of catchments. This studyfocused on storage in prealpine and alpine catchments, using a set of 21 Swiss catchments comprising different elevation ranges. Catchment storage comparisons depend on storage definitions.This study defines different types of storage including definitions of dynamic and mobile catchment storage. We then estimated dynamic storage using four methods, water balance analysis,streamflow recession analysis, calibration of a bucket‐type hydrological model Hydrologiska Byrans Vattenbalansavdelning model (HBV), and calibration of a transfer function hydrographseparation model using stable isotope observations. The HBV model allowed quantifying the contributions of snow, soil and groundwater storages compared to the dynamic catchment storage.With the transfer function hydrograph separation model both dynamic and mobile storage wasestimated. Dynamic storage of one catchment estimated by the four methods differed up toone order of magnitude. Nevertheless, the storage estimates ranked similarly among the 21catchments. The largest dynamic and mobile storage estimates were found in high‐elevationcatchments. Besides snow, groundwater contributed considerably to this larger storage.Generally, we found that with increasing elevation the relative contribution to the dynamic catchmentstorage increased for snow, decreased for soil, but remained similar for groundwater storage.

Tracking Interannual Streamflow Variability with Drought Indices in the U.S. Pacific Northwest

Abstract Drought indices are often used for monitoring interannual variability in macroscale hydrology. However, the diversity of drought indices raises several issues: 1) which indices perform best and where; 2) does the incorporation of potential evapotranspiration (PET) in indices strengthen relationships, and how sensitive is the choice of PET methods to such results; 3) what additional value is added by using higher-spatial-resolution gridded climate layers; and 4) how have observed relationships changed through time. Standardized precipitation index, standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index, and water balance runoff (WBR) model output were correlated to water-year runoff for 21 unregulated drainage basins in the Pacific Northwest of the United States. SPEI and WBR with time scales encompassing the primary precipitation season maximized the explained variance in water-year runoff in most basins. Slightly stronger correlations were found using PET estimates from the Penman–Monteith method over the Thornthwaite method, particularly for time periods that incorporated the spring and summer months in basins that receive appreciable precipitation during the growing season. Indices computed using high-resolution climate surfaces explained over 10% more variability than metrics derived from coarser-resolution datasets. Increased correlation in the latter half of the study period was partially attributable to increased streamflow variability in recent decades as well as to improved climate data quality across the interior mountain watersheds.

The Impact of “Man-Made Hydrological Drought” on Plant Species Abundance in the Low-Flow Channel Downstream from the Matawin Dam, Quebec

The interannual variability of streamflow affects the composition and species richness of vegetation in low-flow channels and alluvial plains. Although climate conditions in 2003 and 2004 were nearly identical, large differences in streamflow were observed downstream from the Matawin dam. These differences resulted in numerous days without flow (no water release) during the growing period (May to August) in 2003, leading to man-made hydrological drought. While this drought had no effect on abiotic variables (grain-size distribution and nutrient concentrations in sediments), a significant decrease in the number of terrestrial species was observed in 2004 (year without drought) relative to 2003 (drought year) on three sand bars studied. This decrease is interpreted to result from prolonged submergence of the sites in 2004. Principal component analysis highlighted the effect of individual sites (first principal component) and of the interannual variability of streamflow (second component) on the number of species. The study suggests that, from a flow management standpoint, it is advisable to release enough water downstream from the dam during the growing season to prevent low-flow channel colonization by invasive terrestrial species.

Eastern U.S. summer streamflow during extreme phases of the North Atlantic oscillation

AbstractNumerous studies have suggested streamflow discharge in the conterminous U.S. has been increasing, particularly in the east starting in the latter half of the 20th century. Northern Hemisphere (NH) hydroclimatic variability has been connected to shifts in large‐scale atmospheric teleconnection patterns. This study ascertained the spatial and temporal influences of the extreme phases of the North Atlantic Oscillation (NAO) on interannual streamflow variability across the eastern U.S. during the summer season. We also assessed the presence of any delayed streamflow responses to NAO configurations during previous spring (March‐April‐May) and winter (December‐January‐February) seasons across the study area. Methods of inquiry included the use of various statistical and compositing analyses applied to records of mean daily summer streamflow obtained from the Hydro‐Climatic Data Network between 1950 and 2010. Results of this study suggest that summer streamflow across eastern U.S. may be related to and thus potentially predicted from the NAO up to three seasons in advance, information of significant hydrologic consequences for the area. Depending upon the season and geographic location, the relationships may be both linear and nonlinear in nature and may be masked by the presence of temporal trends in the index. Summer streamflow across the eastern U.S., in general, displays greatest response to the negative phase of the NAO during the previous winter and the concurrent summer seasons. Geographically, the greatest potential for predictability exists across the Northeast where cohesive responses to NAO exist in all three seasons, winter, spring, and summer.