Regional and Temporal Differences in Nitrate Trends Discerned from Long‐Term Water Quality Monitoring Data

Riverine nitrate (NO₃) is a well‐documented driver of eutrophication and hypoxia in coastal areas. The development of the elevated river NO₃ concentration is linked to anthropogenic inputs from municipal, agricultural, and atmospheric sources. The intensity of these sources has varied regionally, through time, and in response to multiple causes such as economic drivers and policy responses. This study uses long‐term water quality, land use, and other ancillary data to further describe the evolution of river NO₃ concentrations at 22 monitoring stations in the United States (U.S.). The stations were selected for long‐term data availability and to represent a range of climate and land‐use conditions. We examined NO₃ at the monitoring stations, using a flow‐weighting scheme meant to account for interannual flow variability allowing greater focus on river chemical conditions. River NO₃ concentration increased strongly during 1945‐1980 at most of the stations and have remained elevated, but stopped increasing during 1981‐2008. NO₃ increased to a greater extent at monitoring stations in the Midwest U.S. and less so at those in the Eastern and Western U.S. We discuss 20th Century agricultural development in the U.S. and demonstrate that regional differences in NO₃ concentration patterns were strongly related to an agricultural index developed using principal components analysis. This unique century‐scale dataset adds to our understanding of long‐term NO₃ patterns in the U.S.     

Observed Changes in Climate and Streamflow in the Upper Rio Grande Basin

Observed streamflow and climate data are used to test the hypothesis that climate change is already affecting Rio Grande streamflow volume derived from snowmelt runoff in ways consistent with model‐based projections of 21st‐Century streamflow. Annual and monthly changes in streamflow volume and surface climate variables on the Upper Rio Grande, near its headwaters in southern Colorado, are assessed for water years 1958–2015. Results indicate winter and spring season temperatures in the basin have increased significantly, April 1 snow water equivalent (SWE) has decreased by approximately 25%, and streamflow has declined slightly in the April–July snowmelt runoff season. Small increases in precipitation have reduced the impact of declining snowpack on trends in streamflow. Changes in the snowpack–runoff relationship are noticeable in hydrographs of mean monthly streamflow, but are most apparent in the changing ratios of precipitation (rain + snow, and SWE) to streamflow and in the declining fraction of runoff attributable to snowpack or winter precipitation. The observed changes provide observational confirmation for model projections of decreasing runoff attributable to snowpack, and demonstrate the decreasing utility of snowpack for predicting subsequent streamflow on a seasonal basis in the Upper Rio Grande Basin.     

Historical Groundwater Trends in Northern New England and Relations with Streamflow and Climatic Variables

Water‐level trends spanning 20, 30, 40, and 50 years were tested using month‐end groundwater levels in 26, 12, 10, and 3 wells in northern New England (Maine, New Hampshire, and Vermont), respectively. Groundwater levels for 77 wells were used in interannual correlations with meteorological and hydrologic variables related to groundwater. Trends in the contemporary groundwater record (20 and 30 years) indicate increases (rises) or no substantial change in groundwater levels in all months for most wells throughout northern New England. The highest percentage of increasing 20‐year trends was in February through March, May through August, and October through November. Forty‐year trend results were mixed, whereas 50‐year trends indicated increasing groundwater levels. Whereas most monthly groundwater levels correlate strongly with the previous month's level, monthly levels also correlate strongly with monthly streamflows in the same month; correlations of levels with monthly precipitation are less frequent and weaker than those with streamflow. Groundwater levels in May through August correlate strongly with annual (water year) streamflow. Correlations of groundwater levels with streamflow data and the relative richness of 50‐ to 100‐year historical streamflow data suggest useful proxies for quantifying historical groundwater levels in light of the relatively short and fragmented groundwater data records presently available.     

Relative Effects of Climate and Water Use on Base‐Flow Trends in the Lower Klamath Basin1

Abstract: Since the 1940s, snow water equivalent (SWE) has decreased throughout the Pacific Northwest, while water use has increased. Climate has been proposed as the primary cause of base‐flow decline in the Scott River, an important coho salmon rearing tributary in the Klamath Basin. We took a comparative‐basin approach to estimating the relative contributions of climatic and non‐climatic factors to this decline. We used permutation tests to compare discharge in 5 streams and 16 snow courses between “historic” (1942‐1976) and “modern” (1977‐2005) time periods, defined by cool and warm phases, respectively, of the Pacific Decadal Oscillation. April 1 SWE decreased significantly at most snow courses lower than 1,800 m in elevation and increased slightly at higher elevations. Correspondingly, base flow decreased significantly in the two streams with the lowest latitude‐adjusted elevation and increased slightly in two higher‐elevation streams. Base‐flow decline in the Scott River, the only study stream heavily utilized for irrigation, was larger than that in all other streams and larger than predicted by elevation. Based on comparison with a neighboring stream draining wilderness, we estimate that 39% of the observed 10 Mm³ decline in July 1‐October 22 discharge in the Scott River is explained by regional‐scale climatic factors. The remainder of the decline is attributable to local factors, which include an increase in irrigation withdrawal from 48 to 103 Mm³/year since the 1950s.     

Use of Hydrologic Landscape Classification to Diagnose Streamflow Predictability in Oregon

We implement a spatially lumped hydrologic model to predict daily streamflow at 88 catchments within the state of Oregon and analyze its performance using the Oregon Hydrologic Landscape (OHL) classification. OHL is used to identify the physio‐climatic conditions that favor high (or low) streamflow predictability. High prediction catchments (Nash‐Sutcliffe efficiency of (NS) > 0.75) are mainly classified as rain dominated with very wet climate, low aquifer permeability, and low to medium soil permeability. Most of them are located west of the Cascade Mountain Range. Conversely, most low prediction catchments (NS < 0.6) are classified as snow‐dominated with high aquifer permeability and medium to high soil permeability. They are mainly located in the volcano‐influenced High Cascades region. Using a subset of 36 catchments, we further test if class‐specific model parameters can be developed to predict at ungauged catchments. In most catchments, OHL class‐specific parameters provide predictions that are on par with individually calibrated parameters (NS decline < 10%). However, large NS declines are observed in OHL classes where predictability is not high enough. Results suggest higher uncertainty in rain‐to‐snow transition of precipitation phase and external gains/losses of deep groundwater are major factors for low prediction in Oregon. Moreover, regionalized estimation of model parameters is more useful in regions where conditions favor good streamflow predictability.     

Reconstructions of Columbia River Streamflow from Tree‐Ring Chronologies in the Pacific Northwest,USA

We developed Columbia River streamflow reconstructions using a network of existing, new, and updated tree‐ring records sensitive to the main climatic factors governing discharge. Reconstruction quality is enhanced by incorporating tree‐ring chronologies where high snowpack limits growth, which better represent the contribution of cool‐season precipitation to flow than chronologies from trees positively sensitive to hydroclimate alone. The best performing reconstruction (back to 1609 CE) explains 59% of the historical variability and the longest reconstruction (back to 1502 CE) explains 52% of the variability. Droughts similar to the high‐intensity, long‐duration low flows observed during the 1920s and 1940s are rare, but occurred in the early 1500s and 1630s‐1640s. The lowest Columbia flow events appear to be reflected in chronologies both positively and negatively related to streamflow, implying low snowpack and possibly low warm‐season precipitation. High flows of magnitudes observed in the instrumental record appear to have been relatively common, and high flows from the 1680s to 1740s exceeded the magnitude and duration of observed wet periods in the late‐19th and 20th Century. Comparisons between the Columbia River reconstructions and future projections of streamflow derived from global climate and hydrologic models show the potential for increased hydrologic variability, which could present challenges for managing water in the face of competing demands.     

Streamflow Changes in the South Atlantic,United States During the Mid‐ and Late 20th Century1

Abstract: Repeated severe droughts over the last decade in the South Atlantic have raised concern that streamflow may be systematically decreasing, possibly due to climate variability. We examined the monthly and annual trends of streamflow, precipitation, and temperature in the South Atlantic for the time periods: 1934‐2005, 1934‐1969, and 1970‐2005. Streamflow and climate (temperature and precipitation) trends transitioned ca. 1970. From 1934 to 1969, streamflow and precipitation increased in southern regions and decreased in northern regions; temperature decreased throughout the South Atlantic. From 1970 to 2005, streamflow decreased, precipitation decreased, and temperature increased throughout the South Atlantic. It is unclear whether these will be continuing trends or simply part of a long‐term climatic oscillation. Whether these streamflow trends have been driven by climatic or anthropogenic changes, water resources management faces challenging prospects to adapt to decadal‐scale persistently wet and dry hydrologic conditions.     

Estimating Lag to Peak between Rainfall and Peak Streamflow with a Mixed‐Effects Model

We test the use of a mixed‐effects model for estimating lag to peak for small basins in Maine (drainage areas from 0.8 to 78 km²). Lag to peak is defined as the time between the center of volume of the excess rainfall during a storm event and the resulting peak streamflow. A mixed‐effects model allows for multiple observations at sites without violating model assumptions inherent in traditional ordinary least squares models, which assume each observation is independent. The mixed model includes basin drainage area and maximum 15‐min rainfall depth for individual storms as explanatory features. Based on a remove‐one‐site cross‐validation analysis, the prediction errors of this model ranged from ?42% to +73%. The mixed model substantially outperformed three published models for lag to peak and one published model for centroid lag for estimating lag to peak for small basins in Maine. Lag to peak estimates are a key input to rainfall–runoff models used to design hydraulic infrastructure. The improved accuracy and consistency with model assumptions indicates that mixed models may provide increased data utilization that could enhance models and estimates of lag to peak in other regions.     

Precipitation Amount and Intensity Trends Across Southwest Saudi Arabia

This study examines precipitation accumulation and intensity trends across a region in southwest Saudi Arabia characterized by distinct seasonal weather patterns and mountainous terrain. The region is an example of an arid/semiarid area faced with maintaining sustainable water resources with a growing population. Annual and seasonal trends in precipitation amount were examined from 29 rain gages divided among four geographically unique regions from 1945/1946 to 2009. Two of the regions displayed significantly declining annual trends over the time series using a Mann‐Kendall test modified for autocorrelation (α < 0.05). Seasonal analysis revealed insignificant declining trends in at least two of the regions during each season. The largest and most consistent declining trends occurred during wintertime where all regions experienced negative trends. Several intensity metrics were examined in the study area from four additional stations containing daily data from 1985 to 2011. Intensity metrics included total precipitation, wet day count, simple intensity index, maximum daily annual rainfall, and upper/lower precipitation distribution changes. In general, no coherent trends were found among the daily stations suggesting precipitation is intensifying across the study area. The work represents the first of its size in the study area, and one of few in the region due to the lack of available long‐term data needed to properly examine precipitation changes.     

Projected Changes in Discharge in an Agricultural Watershed in Iowa

Our improved capability to adapt to the future changes in discharge is linked to our capability to predict the magnitude or at least the direction of these changes. For the agricultural United States Midwest, too much or too little water has severe socioeconomic impacts. Here, we focus on the Raccoon River at Van Meter, Iowa, and use a statistical approach to examine projected changes in discharge. We build on statistical models using rainfall and harvested corn and soybean acreage to explain the observed discharge variability. We then use projections of these two predictors to examine the projected discharge response. Results are based on seven global climate models part of the Coupled Model Intercomparison Project Phase 5 and two representative concentration pathways (RCPs 4.5 and 8.5). There is not a strong signal of change in the discharge projections under the RCP 4.5. However, the results for the RCP 8.5 point to a stronger changing signal related to larger projected increases in rainfall, resulting in increased trends, in particular, in the upper part of the discharge distribution (i.e., 60th percentile and above). Examination of two hypothetical agricultural scenarios indicates that these increasing trends could be alleviated by decreasing the extent of the agricultural production. We also discuss how the methodology presented in this study represents a viable approach to move forward with the concept of return period for engineering design and management in a nonstationary world.     

Contrasting Lumped and Distributed Hydrology Models for Estimating Climate Change Impacts on California Watersheds1

Maurer, Edwin P., Levi D. Brekke, and Tom Pruitt, 2010. Contrasting Lumped and Distributed Hydrology Models for Estimating Climate Change Impacts on California Watersheds. Journal of the American Water Resources Association (JAWRA) 46(5):1024–1035. DOI: 10.1111/j.1752-1688.2010.00473.x Abstract: We compare the projected changes to streamflows for three Sierra Nevada rivers using statistically downscaled output from 22 global climate projections. The downscaled meteorological data are used to drive two hydrology models: the Sacramento Soil Moisture Accounting model and the variable infiltration capacity model. These two models differ in their spatial resolution, computational time step, and degree and objective of calibration, thus producing significantly different simulations of current and future streamflow. However, the projected percentage changes in monthly streamflows through mid-21st Century generally did not differ, with the exceptions of streamflow during low flow months, and extreme low flows. These findings suggest that for physically based hydrology models applied to snow-dominated basins in Mediterranean climate regimes like the Sierra Nevada, California, model formulation, resolution, and calibration are secondary factors for estimating projected changes in extreme flows (seasonal or daily). For low flows, hydrology model selection and calibration can be significant factors in assessing impacts of projected climate change.     

Climatic Fluctuations and Forecasting of Streamflow in the Lower Colorado River Basin1

Abstract:  Water‐resource managers need to forecast streamflow in the Lower Colorado River Basin to plan for water‐resource projects and to operate reservoirs for water supply. Statistical forecasts of streamflow based on historical records of streamflow can be useful, but statistical assumptions, such as stationarity of flows, need to be evaluated. This study evaluated the relation between climatic fluctuations and stationarity and developed regression equations to forecast streamflow by using climatic fluctuations as explanatory variables. Climatic fluctuations were represented by the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and Southern Oscillation Index (SOI). Historical streamflow within the 25‐ to 30‐year positive or negative phases of AMO or PDO was generally stationary. Monotonic trends in annual mean flows were tested at the 21 sites evaluated in this study; 76% of the sites had no significant trends within phases of AMO and 86% of the sites had no significant trends within phases of PDO. As climatic phases shifted in signs, however, many sites had nonstationary flows; 67% of the sites had significant changes in annual mean flow as AMO shifted in signs. The regression equations developed in this study to forecast streamflow incorporate these shifts in climate and streamflow, thus that source of nonstationarity is accounted for. The R² value of regression equations that forecast individual years of annual flow for the central part of the study area ranged from 0.28 to 0.49 and averaged 0.39. AMO was the most significant variable, and a combination of indices from both the Atlantic and Pacific Oceans explained much more variation in flows than only the Pacific Ocean indices. The average R² value for equations with PDO and SOI was 0.15.     

Air‐Water Temperature Relationships in the Trout Streams of Southeastern Minnesota's Carbonate‐Sandstone Landscape

Carbonate‐sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface‐water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater‐fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air‐water temperature relationships for 40 GWFS in southeastern Minnesota. A 40‐stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R² of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface‐water dominated streams. Regression models for streams with high R² values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater‐fed systems, but will do so at a slower rate than surface‐water dominated systems. A regression model of intercept vs. slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs. management strategies to protect trout streams.     

Streamflow Response to Climate as Influenced by Geology and Elevation1

Mayer, Timothy D. and Seth W. Naman, 2011. Streamflow Response to Climate as Influenced by Geology and Elevation. Journal of the American Water Resources Association (JAWRA) 47(4):724‐738. DOI: 10.1111/j.1752‐1688.2011.00537.x Abstract: This study examines the regional streamflow response in 25 predominately unregulated basins to warmer winter temperatures and snowpack reductions over the last half century in the Klamath Basin of California and Oregon. Geologic controls of streamflow in the region result in two general stream types: surface‐dominated and groundwater‐dominated basins. Surface‐dominated basins were further differentiated into rain basins and snowmelt basins on the basis of elevation and timing of winter runoff. Streamflow characteristics and response to climate vary with stream type, as discussed in the study. Warmer winter temperatures and snowpack reductions have caused significantly earlier runoff peaks in both snowmelt and groundwater basins in the region. In the groundwater basins, the streamflow response to changes in snowpack is smoothed and delayed and the effects are extended longer in the summer. Our results indicate that absolute decreases in July‐September base flows are significantly greater, by an order of magnitude, in groundwater basins compared to surface‐dominated basins. The declines are important because groundwater basins sustain Upper Klamath Lake inflows and mainstem river flows during the typically dry summers of the area. Upper Klamath Lake April‐September net inflows have decreased an estimated 16% or 84 thousand acre‐feet (103.6 Mm³) since 1961, with the summer months showing proportionately more decline. These changes will exacerbate water supply problems for agriculture and natural resources in the region.     

Changes in Patterns of Streamflow From Unregulated Watersheds in Idaho,Western Wyoming,and Northern Nevada1

Clark, Gregory M., 2010. Changes in Patterns of Streamflow From Unregulated Watersheds in Idaho, Western Wyoming, and Northern Nevada. Journal of the American Water Resources Association (JAWRA) 46(3):486-497. DOI: 10.1111/j.1752-1688.2009.00416.x Abstract: Recent studies have identified a pattern of earlier spring runoff across much of North America. Earlier spring runoff potentially poses numerous problems, including increased risk of flooding and reduced summer water supply for irrigation, power generation, and migratory fish passage. To identify changing runoff patterns in Idaho streams, streamflow records were analyzed for 26 U.S. Geological Survey gaging stations in Idaho, western Wyoming, and northern Nevada, each with a minimum of 41 years of record. The 26 stations are located on 23 unregulated and relatively pristine streams that drain areas ranging from 28 to >35,000 km². Four runoff parameters were trend tested at each station for both the period of historical record and from 1967 through 2007. Parameters tested were annual mean streamflow, annual minimum daily streamflow, and the dates of the 25th and 50th percentiles of the annual total streamflow. Results of a nonparametric Mann-Kendall trend test revealed a trend toward lower annual mean and annual minimum streamflows at a majority of the stations, as well as a trend toward earlier snowmelt runoff. Significant downward trends over the period of historical record were most prevalent for the annual minimum streamflow (12 stations) and the 50th percentile of streamflow (11 stations). At most stations, trends were more pronounced during the period from 1967 through 2007. A regional Kendall test for water years 1967 through 2007 revealed significant regional trends in the percent change in the annual mean and annual minimum streamflows (0.67% less per year and 0.62% less per year, respectively), the 25th percentile of streamflow (12.3 days earlier), and the 50th percentile of streamflow (11.5 days earlier).     

The Impact of Asynchronicity on Event‐Flow Estimation in Basin‐Scale Hydrologic Model Calibration1

Abstract: The calibration of basin‐scale hydrologic models consists of adjusting parameters such that simulated values closely match observed values. However, due to inevitable inaccuracies in models and model inputs, simulated response hydrographs for multiyear calibrations will not be perfectly synchronized with observed response hydrographs at the daily time step. An analytically derived formula suggests that when timing errors are significant, traditional calibration approaches may generally underestimate the total event‐flow volume. An event‐adaptive time series is developed and incorporated into the Nash‐Sutcliffe Efficiency objective function to diagnose the potential impact of event‐flow synchronization errors. Test sites are the 50 km² Subwatershed I of the Little River Experimental Watershed (LREWswI) in southeastern Georgia, and the 610 km² Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma, with the Soil and Water Assessment Tool used as the hydrologic model. Results suggest that simulated surface runoff generation is 55% less for LREWswI when the daily time series is used compared with when the event‐adaptive technique is used. Event‐flow generation may also be underestimated for LWREW, but to a lesser extent than it may be for LREWswI, due to a larger portion of the event flow being lateral flow.     

Climate Change,Atmospheric Rivers,and Floods in California – A Multimodel Analysis of Storm Frequency and Magnitude Changes1

Dettinger, Michael, 2011. Climate Change, Atmospheric Rivers, and Floods in California – A Multimodel Analysis of Storm Frequency and Magnitude Changes. Journal of the American Water Resources Association (JAWRA) 47(3):514‐523. DOI: 10.1111/j.1752‐1688.2011.00546.x Abstract: Recent studies have documented the important role that “atmospheric rivers” (ARs) of concentrated near‐surface water vapor above the Pacific Ocean play in the storms and floods in California, Oregon, and Washington. By delivering large masses of warm, moist air (sometimes directly from the Tropics), ARs establish conditions for the kinds of high snowlines and copious orographic rainfall that have caused the largest historical storms. In many California rivers, essentially all major historical floods have been associated with AR storms. As an example of the kinds of storm changes that may influence future flood frequencies, the occurrence of such storms in historical observations and in a 7‐model ensemble of historical‐climate and projected future climate simulations is evaluated. Under an A2 greenhouse‐gas emissions scenario (with emissions accelerating throughout the 21st Century), average AR statistics do not change much in most climate models; however, extremes change notably. Years with many AR episodes increase, ARs with higher‐than‐historical water‐vapor transport rates increase, and AR storm‐temperatures increase. Furthermore, the peak season within which most ARs occur is commonly projected to lengthen, extending the flood‐hazard season. All of these tendencies could increase opportunities for both more frequent and more severe floods in California under projected climate changes.     

Decreased Runoff Response to Precipitation,Little Missouri River Basin,Northern Great Plains,USA

High variability in precipitation and streamflow in the semiarid northern Great Plains causes large uncertainty in water availability. This uncertainty is compounded by potential effects of future climate change. We examined historical variability in annual and growing season precipitation, temperature, and streamflow within the Little Missouri River Basin and identified differences in the runoff response to precipitation for the period 1976‐2012 compared to 1939‐1975 (n = 37 years in both cases). Computed mean values for the second half of the record showed little change (<5%) in annual or growing season precipitation, but average annual runoff at the basin outlet decreased by 22%, with 66% of the reduction in flow occurring during the growing season. Our results show a statistically significant (p < 0.10) 27% decrease in the annual runoff response to precipitation (runoff ratio). Surface‐water withdrawals for various uses appear to account for <12% of the reduction in average annual flow volume, and we found no published or reported evidence of substantial flow reduction caused by groundwater pumping in this basin. Results of our analysis suggest that increases in monthly average maximum and minimum temperatures, including >1°C increases in January through March, are the dominant driver of the observed decrease in runoff response to precipitation in the Little Missouri River Basin.     

Changes in Hydrology of the Ganges Delta of Bangladesh and Corresponding Impacts on Water Resources

The Ganges Delta in Bangladesh is an example of water‐related catastrophes in a major rural river basin where limitations in quantity, quality, and timing of available water are producing disastrous conditions. Water availability limitations are modifying the hydrologic characteristics especially when water allocation is controlled from the upstream Farakka Barrage. This study presents the changes and consequences in the hydrologic regime due to climate‐ and human‐induced stresses. Flow duration curves (FDCs), rainfall elasticity, and temperature sensitivity were used to assess the pre‐ and post‐barrage water flow patterns. Hydrologic and climate indices were computed to provide insight on hydro‐climatic variability and trend. Significant increases in temperature, evapotranspiration, hot days, heating, and cooling degree days indicate the region is heading toward a warmer climate. Moreover, increase in high‐intensity rainfall of short duration is making the region prone to extreme floods. FDCs depict a large reduction in river flows between pre‐ and post‐barrage periods, resulting in lower water storage capacity. The reduction in freshwater flow increased the extent and intensity of salinity intrusion. This freshwater scarcity is reducing livelihood options considerably and indirectly forcing population migration from the delta region. Understanding the causes and directions of hydrologic changes is essential to formulate improve water resources management in the region.     

Implications of Upstream Flow Availability for Watershed Surface Water Supply across the Conterminous United States

Although it is well established that the availability of upstream flow (AUF) affects downstream water supply, its significance has not been rigorously categorized and quantified at fine resolutions. This study aims to fill this gap by providing a nationwide inventory of AUF and local water resource, and assessing their roles in securing water supply across the 2,099 8‐digit hydrologic unit code watersheds in the conterminous United States (CONUS). We investigated the effects of river hydraulic connectivity, climate variability, and water withdrawal, and consumption on water availability and water stress (ratio of demand to supply) in the past three decades (i.e., 1981–2010). The results show that 12% of the CONUS land relied on AUF for adequate freshwater supply, while local water alone was sufficient to meet the demand in another 74% of the area. The remaining 14% highly stressed area was mostly found in headwater areas or watersheds that were isolated from other basins, where stress levels were more sensitive to climate variability. Although the constantly changing water demand was the primary cause of escalating/diminishing stress, AUF variation could be an important driver in the arid south and southwest. This research contributes to better understanding of the significance of upstream–downstream water nexus in regional water availability, and this becomes more crucial under a changing climate and with intensified human activities.