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Changes in climate are driving an intensification of the hydrologic cycle and leading to alterations of natural streamflow regimes. Human disturbances such as dams, land-cover change, and water diversions are thought to obscure climate signals in hydrologic systems. As a result, most studies of changing hydroclimatic conditions are limited to areas with natural streamflow. Here, we compare trends in observed streamflow from natural and human-modified watersheds in the United States and Canada for the 1981–2015 water years to evaluate whether comparable responses to climate change are present in both systems. We find that patterns and magnitudes of trends in median daily streamflow, daily streamflow variability, and daily extremes in human-modified watersheds are similar to those from nearby natural watersheds. Streamflow in both systems show negative trends throughout the southern and western United States and positive trends throughout the northeastern United States, the northern Great Plains, and southern prairies of Canada. The trends in both natural and human-modified watersheds are linked to local trends in precipitation and reference evapotranspiration, demonstrating that water management and land-cover change have not substantially altered the effects of climate change on human-modified watersheds compared with nearby natural watersheds.

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters.

We run a comparative study of ecohydrological models of streamflow probability distributions (pdfs), p(Q), derived by Botter et al. (2007a, 2009), against field data gathered in different hydrological contexts. Streamflows measured in several catchments across various climatic regions of northeastern Italy and the United States are employed. The relevance of the work stems from the implied analytical predictive ability of hydrologic variability, whose role on stream and riparian ecological processes and large‐scale management schemes is fundamental. The tools employed are analytical models of p(Q) (and of the related flow duration curve, D(Q)) derived by coupling suitable storage‐discharge relations with a stochastic description of streamflow production through soil moisture dynamics, and are expressed as a function of few macroscopic rainfall, soil, vegetation and geomorphological parameters. In this work we compare the performances of a recent version of the model (which includes the effects of nonlinear subsurface storage‐discharge relations) to those provided by the linear version through the application of the models to 13 test catchments belonging to various climatic and geomorphic contexts. A general agreement between predicted and observed daily streamflows pdfs is shown, though differences emerge between the linear and the nonlinear approaches. In particular, by including the effects of a nonlinear storage‐discharge relation the model accuracy is shown to increase with respect to the linear scheme in most examined cases. We show that this is not simply attributable to the added parameter but corresponds to a proper likelihood increase. The nonlinear model is shown to exhibit three basic forms for p(Q) (monotonically decreasing with an atom of probability in Q = 0, bell‐shaped with the mode close to zero, bell‐shaped with the mode close to the mean), corresponding to different hydrologic regimes which are clearly detectable in field data. Inferences on the nonlinear character of the relation between subsurface storage and discharge from observed p(Q) are finally drawn.

The number of high-capacity wells has increased substantially in the state of Wisconsin, United States, and concerns have been raised about their impact on both groundwater levels and streamflow. At the same time, Wisconsin’s annual precipitation and temperature have been trending upward over the last 30 years and both are predicted to increase into the middle of the twenty-first century. The study demonstrates the simultaneous effects of climate change and groundwater withdrawal from high-capacity wells by employing two simulation models: the Soil & Water Assessment Tool (SWAT) and the USGS Modular Hydrologic Model (MODFLOW). SWAT was used to simulate the change in the recharge rate, and MODFLOW was then used to simulate the change in hydraulic head. The SWAT model predicted that future increases in Wisconsin’s annual precipitation (5%) will cause increases in both groundwater recharge (16.7%) and streamflow (14.1%). The future increases in temperature (≈ 3 °C), however, are predicted to leave the state with a net deficit in both streamflow (− 23.4%) and groundwater recharge (− 19.6%). In addition, the MODFLOW model predicted a mean head elevation decrease of over 2 m due to changes in the climate and an additional decrease (≈ 3 m) in groundwater elevation surrounding high-capacity wells due to predicted increases in annual withdrawal rate.

Soil and Water Assessment Tool (SWAT) is a river basin scale model widely used to study the impact of land management practices in large, complex watersheds. Even though model output uncertainties are generally recognized to affect watershed management decisions, those uncertainties are largely ignored in model applications. The uncertainties of SWAT simulations are quantified using various methods, but simultaneous attempt to calibrate a model so as to reduce the uncertainty are seldom done. This study aims to use an uncertainty reduction procedure that helps calibrate the SWAT model. The shuffled complex evolutionary metropolis algorithm for uncertainty analysis is employed for this purpose, and is demonstrated using the data from the St. Joseph River basin, USA. The values of the performance indices, the r2 and the Nash–Sutcliffe efficiency (NSE) for the simulations during calibration period was found to be 0.81 (same for r2 and NSE) and 0.79 for validation period indicating a good simulation by the model. The results also indicate that the algorithm helps reduce the uncertainty (percentage of coverage = 62% and average width = 19.2 m3/s), and also identifies the plausible range of parameters that simulate the processes with less uncertainty. The confidence bands of simulations are obtained that can be employed in making uncertainty-based decisions on watershed management practices.

In coming decades, higher annual temperatures, increased growing season length, and increased dormant season precipitation are expected across the northeastern United States in response to anthropogenic forcing of global climate. We synthesized long‐term stream hydrochemical data from the Sleepers River Research Watershed in Vermont, United States, to explore the relationship of catchment wetness to stream nitrate and DOC loadings. We modeled changes in growing season length and precipitation patterns to simulate future climate scenarios and to assess how stream nutrient loadings respond to climate change. Model results for the 2070–2099 time period suggest that stream nutrient loadings during both the dormant and growing seasons will respond to climate change. During a warmer climate, growing season stream fluxes (runoff +20%, nitrate +57%, and DOC +58%) increase as more precipitation (+28%) and quick flow (+39%) occur during a longer growing season (+43 days). During the dormant season, stream water and nutrient loadings decrease. Net annual stream runoff (+8%) and DOC loading (+9%) increases are commensurate with the magnitude of the average increase of net annual precipitation (+7%). Net annual stream water and DOC loadings are primarily affected by increased dormant season precipitation. In contrast, decreased annual loading of stream nitrate (−2%) reflects a larger effect of growing season controls on stream nitrate and the effects of lengthened growing seasons in a warmer climate. Our findings suggest that leaching of nitrate and DOC from catchment soils will be affected by anthropogenic climate forcing, thereby affecting the timing and magnitude of annual stream loadings in the northeastern United States.

Water resource management requires knowledge of the natural variability in streamflow over multiple time scales. Reconstructions of streamflow derived from moisture-sensitive trees extend, in both time and magnitude, the variability provided by relatively short gage records. In this study, we present a network of 14 annual streamflow reconstructions, 300-600 years long, for gages in the Upper Colorado and South Platte River basins in Colorado generated from new and existing tree-ring chronologies. Gages for the reconstruction were selected on the basis of their importance to two of the largest Colorado Front Range water providers, who provided the natural flow data for the calibration with tree-ring data. The reconstruction models explain 63-76% of the variance in the gage records and capture low flows particularly well. Analyses of the reconstructions indicate that the 20th century gage record does not fully represent the range of streamflow characteristics seen in the prior two to five centuries. Multi-year drought events more severe than the 1950s drought have occurred, notably in the 19th century, and the distribution of extreme low flow years is markedly uneven over the past three centuries. When the 14 reconstructions are grouped into Upper Colorado, northern South Platte, and southern South Platte regional flow reconstructions, the three time series show a high degree of coherence, but also time-varying divergences that may reflect the differential influence of climatic features operating in the western U.S. These reconstructions are currently being used by water managers to assess the reliability of water supply systems under a broader range of conditions than indicated by the gage records alone. [PUBLICATION ABSTRACT]

Slope–area analysis and the integral approach have both been widely used in stream profile analysis. The former is better at identifying changes in concavity indices but produces stream power parameters with high uncertainties relative to the integral approach. The latter is much better for calculating channel steepness. Limited work has been done to couple the advantages of the two methods and to remedy such drawbacks. Here we show the merit of the log-transformed slope–area plot to determine changes in concavities and then to identify colluvial, bedrock and alluvial channels along river profiles. Via the integral approach, we obtain bedrock channel concavity and steepness with high precision. In addition, we run bivariant linear regression statistic tests for the two methods to examine and eliminate serially correlated residuals because they may bias both the estimated value and the precision of stream power parameters. We finally suggest that the coupled process, integrating the advantages of both slope–area analysis and the integral approach, can be a more robust and capable method for bedrock river profile analysis.

With predicted alterations in climate and land use, managing water resources is of the utmost importance, especially in areas such as the United States (U.S.) Coastal Plain where extensive connections exist between surface and groundwater systems. These changes create the need for models that effectively assess shifting hydrologic regimes and, in that context, we examine the performance of the Soil and Water Assessment Tool (SWAT) in a low-gradient, shallow-aquifer-dominated watershed of the U.S. Coastal Plain using a gridded reanalysis dataset. We evaluate accuracy, uncertainty, and parameter sensitivity by comparing observed and predicted streamflow at two gaging stations and assess model predictions for yearly average runoff (SURQ), percolation (PERC), and sediment loss (SYLD). Streamflow performance was acceptable during calibration (NSE = 0.67 and 0.60) and very good during validation (NSE = 0.84 and 0.91). Model predictions for SURQ, PERC, and SYLD coincided with expected ranges for this region. Parameters related to shallow aquifer properties or groundwater were highly sensitive, which indicates the need for continued study of spatial and temporal variability within the sub-surface components of these hydrologic systems. Our findings highlight the applicability of this reanalysis dataset for modeling hydrologic processes in poorly gaged watersheds and adds to the body of research that seeks to develop effective assessment tools for shallow-aquifer-dominated systems. Our methodology can effectively assist watershed managers in establishing baseline rates of hydrologic processes as is crucial with future predicted shifts in hydrologic regimes due to land-use alteration and climate change.