Spatial and temporal patterns in low streamflows were investigated for 183 streamgages located in the Chesapeake Bay Watershed for the period 1939–2013. Metrics that represent different aspects of the frequency and magnitude of low streamflows were examined for trends: (1) the annual time series of seven‐day average minimum streamflow, (2) the scaled average deficit at or below the 2% mean daily streamflow value relative to a base period between 1939 and 1970, and (3) the annual number of days below the 2% threshold. Trends in these statistics showed spatial cohesion, with increasing low streamflow volume at streamgages located in the northern uplands of the Chesapeake Bay Watershed and decreasing low streamflow volume at streamgages in the southern part of the watershed. For a small subset of streamgages (12%), conflicting trend patterns were observed between the seven‐day average minimum streamflow and the below‐threshold time series and these appear to be related to upstream diversions or the influence of reservoir‐influenced streamflows in their contributing watersheds. Using multivariate classification techniques, mean annual precipitation and fraction of precipitation falling as snow appear to be broad controls of increasing and decreasing low‐flow trends. Further investigation of seasonal precipitation patterns shows summer rainfall patterns, driven by the Atlantic Multidecadal Oscillation, as the main driver of low streamflows in the Chesapeake Bay Watershed.

In the Central United States, the Arkansas darter (Etheostoma cragini) is listed as a threatened fish species by the State of Kansas. Survival of the darter is threatened by loss of habitat caused by changing streamflow conditions, in particular flow depletion. Future management of darter populations and habitats requires an understanding of streamflow conditions and how those conditions may have changed over time in response to natural and anthropogenic factors. In Kansas, streamflow alteration was assessed at 9 U.S. Geological Survey streamgages in 6 priority basins with no pronounced long‐term trends in precipitation. The assessment was based on a comparison of observed (O) and predicted expected (E) reference conditions for 29 flow metrics. The O/E results indicated a likely or possible diminished flow condition in 2 basins; the primary cause of which is groundwater‐level declines resulting from groundwater pumping for irrigated agriculture. In these 2 basins, habitat characteristics adversely affected by flow depletion may include stream connectivity, pools, and water temperature. The other 4 basins were minimally affected, or unaffected, by flow depletion and therefore may provide the best opportunity for preservation of darter habitat. Through the O/E analysis, anthropogenic streamflow alteration was quantified and the results will enable better‐informed decisions pertaining to the future management of darters in Kansas.

There is a great deal of interest in the literature on streamflow changes caused by climate change because of the potential negative effects on aquatic biota and water supplies. Most previous studies have primarily focused on perennial streams, and there have been only a few studies examining the effect of climate variability on intermittent streams. Our objectives in this study were to (1) identify regions of similar zero-flow behaviour and (2) evaluate the sensitivity of intermittent streams to historical variability in climate in the USA. This study was carried out at 265 intermittent streams by evaluating (1) correlations among time series of flow metrics (number of zero-flow events, the average of the central 50% and largest 10% of flows) with climate (magnitudes, durations and intensity) and (2) decadal changes in the seasonality and long-term trends of these flow metrics. Results identified five distinct seasonality patterns in the zero-flow events. In addition, strong associations between the low-flow metrics and historical changes in climate were found. The decadal analysis suggested no significant seasonal shifts or decade-to-decade trends in the low-flow metrics. The lack of trends or changes in seasonality is likely due to unchanged long-term patterns in precipitation over the time period examined. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Hydro-ecological stream classificationthe process of grouping streams by similar hydrologic responses and, by extension, similar aquatic habitathas been widely accepted and is considered by some to be one of the first steps towards developing ecological flow targets. A new classification of 1543 streamgauges in the contiguous USA is presented by use of a novel and parsimonious approach to understand similarity in ecological streamflow response. This novel classification approach uses seven fundamental daily streamflow statistics (FDSS) rather than winnowing down an uncorrelated subset from 200 or more ecologically relevant streamflow statistics (ERSS) commonly used in hydro-ecological classification studies. The results of this investigation demonstrate that the distributions of 33 tested ERSS are consistently different among the classification groups derived from the seven FDSS. It is further shown that classification based solely on the 33 ERSS generally does a poorer job in grouping similar streamgauges than the classification based on the seven FDSS. This new classification approach has the additional advantages of overcoming some of the subjectivity associated with the selection of the classification variables and provides a set of robust continental-scale classes of US streamgauges. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

S1 Hydrologic units: additional explanation of terminology,

Runoff-based indicators of terrestrial water availability are appropriate for humid regions, but have tended to limit our basic hydrologic understanding of drylands – the dry-subhumid, semiarid, and arid regions which presently cover nearly half of the global land surface. In response, we introduce an indicator framework that gives equal weight to humid and dryland regions, accounting fully for both vertical (precipitation + evapotranspiration) and horizontal (groundwater + surface-water) components of the hydrologic cycle in any given location – as well as fluxes into and out of landscape storage. We apply the framework to a diverse hydroclimatic region (the conterminous USA) using a distributed water-balance model consisting of 53 400 networked landscape hydrologic units. Our model simulations indicate that about 21% of the conterminous USA either generated no runoff or consumed runoff from upgradient sources on a mean-annual basis during the 20th century. Vertical fluxes exceeded horizontal fluxes across 76% of the conterminous area. Long-term-average total water availability (TWA) during the 20th century, defined here as the total influx to a landscape hydrologic unit from precipitation, groundwater, and surface water, varied spatially by about 400 000-fold, a range of variation ~100 times larger than that for mean-annual runoff across the same area. The framework includes but is not limited to classical, runoff-based approaches to water-resource assessment. It also incorporates and reinterprets the green- and blue-water perspective now gaining international acceptance. Implications of the new framework for several areas of contemporary hydrology are explored, and the data requirements of the approach are discussed in relation to the increasing availability of gridded global climate, land-surface, and hydrologic data sets.

ABSTRACTAn approach is presented in this study to aid water‐resource managers in characterizing streamflow alteration at ungauged rivers. Such approaches can be used to take advantage of the substantial amounts of biological data collected at ungauged rivers to evaluate the potential ecological consequences of altered streamflows. National‐scale random forest statistical models are developed to predict the likelihood that ungauged rivers have altered streamflows (relative to expected natural condition) for five hydrologic metrics (HMs) representing different aspects of the streamflow regime. The models use human disturbance variables, such as number of dams and road density, to predict the likelihood of streamflow alteration. For each HM, separate models are derived to predict the likelihood that the observed metric is greater than (‘inflated’) or less than (‘diminished’) natural conditions. The utility of these models is demonstrated by applying them to all river segments in the South Platte River in Colorado, USA, and for all 10‐digit hydrologic units in the conterminous United States. In general, the models successfully predicted the likelihood of alteration to the five HMs at the national scale as well as in the South Platte River basin. However, the models predicting the likelihood of diminished HMs consistently outperformed models predicting inflated HMs, possibly because of fewer sites across the conterminous United States where HMs are inflated. The results of these analyses suggest that the primary predictors of altered streamflow regimes across the Nation are (i) the residence time of annual runoff held in storage in reservoirs, (ii) the degree of urbanization measured by road density and (iii) the extent of agricultural land cover in the river basin. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling.

Factors controlling the partitioning of old and new water contributions to stream flow were investigated for three events in four catchments (three of which were nested) at Sleepers River Research Watershed in Danville, Vermont. In the 1993 snowmelt period, two-component isotopic hydrograph separations showed that new water (meltwater) inputs to the stream ranged widely from 41 to 74%. and increased with catchment size (41 to 11 125 ha) (with one exception) and with open land cover (0-73%). Peak dissolved organic carbon concentrations and relative alkalinity dilution in stream water ranked in the same order among catchments as the new water fractions, suggesting that new water followed shallow flow paths. During the 1994 snowmelt, despite similar timing and magnitude of melt inputs, the new-water contribution to stream flow ranged only from 30 to 36% in the four catchments. We conclude that the uncommonly high and variable new water fractions in streamwater during the 1993 melt were caused by direct runoff of meltwater over frozen ground, which was prevalent in open land areas during the 1993 winter. In a high-intensity summer rainstorm in 1993. new water fractions were smaller relative to the 1993 snowmelt, ranging from 28 to 46%, but they ranked in the identical catchment order. Reconciliation of the contrasting patterns of new-old water partitioning in the three events appears to require an explanation that invokes multiple processes and effects, including:1. topographically controlled increase in surface-saturated area with increasing catchment size; 2. direct runoff over frozen ground; 3. low infiltration in agriculturally compacted soils; 4. differences in soil transmissivity, which may be more relevant under dry antecedent conditions.These data highlight some of the difficulties faced by catchment hydrologists in formulating a theory of runoff generation at varying basin scales. Copyright (C) 2002 John Wiley Sons, Ltd.

A method for estimation of mean baseflow residence time in watersheds from hydrograph runoff recession characteristics was developed. Runoff recession characteristics were computed for the period 1993–96 in the 2 km 2 Winnisook watershed, Catskill Mountains, southeastern New York, and were used to derive mean values of subsurface hydraulic conductivity and the storage coefficient. These values were then used to estimate the mean baseflow residence time from an expression of the soil contact time, based on watershed soil and topographic characteristics. For comparison, mean baseflow residence times were calculated for the same period of time through the traditional convolution integral approach, which relates rainfall δ 18 O to δ 18 O values in streamflow. Our computed mean baseflow residence time was 9 months by both methods. These results indicate that baseflow residence time can be calculated accurately using recession analysis, and the method is less expensive than using environmental and/or artificial tracers. Published in 2002 by John Wiley & Sons, Ltd.

Annual minimum, median, and maximum daily streamflow for 400 sites in the conterminous United States (U.S.), measured during 1941–1999, were examined to identify the temporal and spatial character of changes in streamflow statistics. Results indicate a noticeable increase in annual minimum and median daily streamflow around 1970, and a less significant mixed pattern of increases and decreases in annual maximum daily streamflow. These changes in annual streamflow statistics primarily occurred in the eastern U.S. In addition, the streamflow increases appear as a step change rather than as a gradual trend and coincide with an increase in precipitation.

In this study, 1:250,000- and 1:24,000-scale digital soil databases for Kansas were compared statistically and spatially. The soil attributes used in this comparison were soil permeability, percent clay, and hydrologic group. Results indicate that, although the two databases were correlated, the potential exists for substantial site-specific variability between them. The largest differences between the two databases typically are in and along the stream networks. With distance away from the stream networks, the mean differences generally stabilize. The results also indicate the possibility of systematic bias between the two databases that varies with landscape position. For applications using mean soil attribute values, the two soil databases usually yield similar values for the three soil attributes analyzed, especially for areas of 25 km(2) (9.7 mi(2)) or larger. However, for applications where more detailed information on soil variability and the spatial pattern of soil properties within the landscape is required, such as for studies focused on small areas or areas in and along stream networks, the two soil databases are sufficiently different such that using one or the other may result in substantially different results.

Observed (1895-1999) trends in climatic moisture conditions in the conterminous United States (US) characterized by (1) annual precipitation minus annual potential evapotranspiration (PMPE), (2) annual surplus (water that eventually becomes streamflow), and (3) annual deficit (the amount of water that must be supplied by irrigation to grow vegetation at an optimum rate) are examined. The sensitivity of moisture conditions across the conterminous US to increases in temperature also are examined. Results indicate that there have been statistically significant trends in PMPE, annual surplus, and annual deficit for some parts of the conterminous US. Most of the significant trends in PMPE have been increasing trends primarily in the eastern US. Annual surplus also has increased over the eastern US, whereas the magnitudes of annual deficit have decreased. For the conterminous US as a whole, there has been a statistically significant increase in PMPE and annual surplus; however, there is no significant trend in annual deficit. Results also indicate that PMPE and annual deficit in the warmest regions of the conterminous US are most sensitive to increases in temperature. The high sensitivity of PMPE and annual deficit in these regions to increases in temperature is related to the relation between temperature and the saturation vapor pressure of air. The increases in potential evapotranspiration for a given change in temperature are larger for high temperatures than for low temperatures. The regions with the highest sensitivity of annual surplus to increases in temperature are the humid regions of the country. In these regions, annual surplus is large and increased potential evapotranspiration, resulting from increased temperature, has a significant effect on reducing annual surplus. In the dry regions of the country, annual surplus is so low that increases in potential evapotranspiration only result in small decreases in annual surplus.

Topographic characteristics computed from 100- and 1000-m resolution digital elevation model (DEM) data are compared for 50 locations representing varied terrain in the conterminous USA. The topographic characteristics are three parameters used extensively in hydrological research and modelling - slope (S), specific catchment area (A(s)) and a wetness index computed as the logarithm of the specific catchment area divided by slope [ln(A(s)/S)]. Slope values computed from 1000-m DEMs are smaller than those computed from 100-m DEMs; specific catchment area and the wetness index are larger for the 1000-m DEMs compared with the 100-m DEMs. Most of the differences between the 100- and 1000-m resolution DEMs can be attributed to terrain-discretization effects in the computation of the topographic characteristics and are not the result of smoothing or loss of terrain detail in the coarse data. In general, the terrain-discretization effects are greatest on flat terrain with long length-scale features, and the smoothing effects are greatest on steep terrain with short length-scale features. For the most part, the differences in the average values of the topographic characteristics computed from 100- and 1000-m resolution DEMs are predictable; that is, biases in the mean values for the characteristics computed from a 1000-m DEM can be corrected with simple linear equations. Copyright (C) 2000 John Wiley & Sons, Ltd.

The hydrologic concepts needed in a water-balance model to estimate the spatial variation in mean annual runoff for the 344 climate divisions in the conterminous United States (U.S.) were determined. The concepts that were evaluated were the climatic supply of water (precipitation), climatic demand for water (potential evapotranspiration), seasonality in supply and demand, and soil-moisture-storage capacity. Most (91%) of the spatial variability in mean annual runoff for the climate divisions in the conterminous U.S, was explained by the spatial variability of mean annual precipitation minus mean annual potential evapotranspiration. When soil-moisture-storage capacity and seasonality in supply and demand were added to the water balance, the explained variance in mean annual runoff increased slightly, and the error in estimated mean annual runoff decreased significantly. Adding soil-moisture-storage capacity and seasonality in supply and demand provided the most improvement in areas where seasonal supply and demand are out of phase.

ABSTRACT: The effects of potential climate change on mean annual runoff in the conterminous United States (U.S.) are examined using a simple water‐balance model and output from two atmospheric general circulation models (GCMs). The two GCMs are from the Canadian Centre for Climate Prediction and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HAD). In general, the CCC GCM climate results in decreases in runoff for the conterminous U.S., and the HAD GCM climate produces increases in runoff. These estimated changes in runoff primarily are the result of estimated changes in precipitation. The changes in mean annual runoff, however, mostly are smaller than the decade‐to‐decade variability in GCM‐based mean annual runoff and errors in GCM‐based runoff. The differences in simulated runoff between the two GCMs, together with decade‐to‐decade variability and errors in GCM‐based runoff, cause the estimates of changes in runoff to be uncertain and unreliable.

The effects of basin size on low-flow stream chemistry and subsurface contact time were examined for a part of the Neversink River watershed in southern New York State. Acid neutralizing capacity (ANC), the sum of base cation concentrations (SBC), pH and concentrations of total aluminum (Al), dissolved organic carbon (DOC) and silicon (Si) were measured during low stream flow at the outlets of nested basins ranging in size from 0.2 to 166.3 km(2). ANC, SBC, pH, Al and DOC showed pronounced changes as basin size increased from 0.2 to 3 km(2), but relatively small variations were observed as basin size increased beyond 3 km(2). An index of subsurface contact time computed from basin topography and soil hydraulic conductivity also showed pronounced changes as basin size increased from 0.2 to 3 km(2) and smaller changes as basin size increased beyond 3 km(2). These results suggest that basin size affects low-flow stream chemistry because of the effects of basin size on subsurface contact time. (C) 1997 by John Wiley & Sons, Ltd.

This study examines the statistical Likelihood of detecting a trend in annual runoff given an assumed change in mean annual runoff, the underlying year-to-year variability in runoff, and serial correlation of annual runoff. Means, standard deviations, and lag-1 serial correlations of annual runoff were computed for 585 stream gages in the conterminous United States, and these statistics were used to compute the probability of detecting a prescribed trend in annual runoff. Assuming a Linear 20% change in mean annual runoff over a 100 yr period and a significance level of 95%, the average probability of detecting a significant trend was 28% among the 585 stream gages. The largest probability of detecting a trend was in the northwestern U.S., the Great Lakes region, the northeastern U.S., the Appalachian Mountains, and parts of the northern Rocky Mountains. The smallest probability of trend detection was in the central and southwestern U.S., and in Florida. Low probabilities of trend detection were associated with low ratios of mean annual runoff to the standard deviation of annual runoff and with high lag-1 serial correlation in the data.

Single flow direction (sfd) and multiple flow direction (mfd) algorithms were used to compute the spatial and statistical distributions of the topographic index used in the watershed model TOPMODEL. An sfd algorithm assumes that subsurface flow occurs only in the steepest downslope direction from any given point; an mfd algorithm assumes that subsurface flow occurs in all downslope directions from any given point. The topographic index in TOPMODEL is ln (a/tan β), where In is the Napierian logarithm, a is the upslope area per unit contour length, and tan β is the slope gradient. The ln (a/tanβ) distributions were computed from digital elevation model (DEM) data for locations with diverse topography in Arizona, Colorado, Louisiana, Nebraska, North Carolina, Oregon, Pennsylvania, Tennessee, Vermont, and Virginia. The means of the ln (a/tan β) distributions were higher when the mfd algorithm was used for computation compared to when the sfd algorithm was used. The variances and skews of the distributions were lower for the mfd algorithm compared to the sfd algorithm. The differences between the mfd and sfd algorithms in the mean, variance, and skew of the ln (a/tan β) distribution were almost identical for the various DEMs and were not affected by DEM resolution or watershed size. TOPMODEL model efficiency and simulated flow paths were affected only slightly when the ln (a/tan β) distribution was computed with the sfd algorithm instead of the mfd algorithm. Any difference in the model efficiency and simulated flow paths between the sfd and mfd algorithms essentially disappeared when the model was calibrated by adjusting subsurface hydraulic parameters.