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At least 91 records · Page 5Linked to original sources

Mineralogy, morphology, and textural relationships in coatings on quartz grains in sediments in a quartz-sand aquifer

Mineralogical studies of coatings on quartz grains and bulk sediments from an aquifer on Western Cape Cod, Massachusetts, USA were carried out using a variety of transmission electron microscopy (TEM) techniques. Previous studies demonstrated that coatings on quartz grains control the adsorption properties of these sediments. Samples for TEM characterization were made by a gentle mechanical grinding method and focused ion beam (FIB) milling. The former method can make abundant electron-transparent coating assemblages for comprehensive and quantitative X-ray analysis and the latter technique protects the coating texture from being destroyed. Characterization of the samples from both a pristine area and an area heavily impacted by wastewater discharge shows similar coating textures and chemical compositions. Major constituents of the coating include Al-substituted goethite and illite/chlorite clays. Goethite is aggregated into well-crystallized domains through oriented attachment resulting in increased porosity. Illite/chlorite clays with various chemical compositions were observed to be mixed with goethite aggregates and aligned sub-parallel to the associated quartz surface. The uniform spatial distribution of wastewater-derived phosphorus throughout the coating from the wastewater-contaminated site suggests that all of the coating constituents, including those adjacent to the quartz surface, are accessible to groundwater solutes. Both TEM characterization and chemical extraction results indicate there is a significantly greater amount of amorphous iron oxide in samples from wastewater discharge area compared to those from the pristine region, which might reflect the impact of redox cycling of iron under the wastewater-discharge area. Coating compositions are consistent with the moderate metal and oxy-metalloid adsorption capacities, low but significant cation exchange capacities, and control of iron(III) solubility by goethite observed in reactive transport experimental and modeling studies conducted at the site.

Massachusetts↗

Factors influencing ground-water recharge in the eastern United States

Ground-water recharge estimates for selected locations in the eastern half of the United States were obtained by Darcian and chloride-tracer methods and compared using statistical analyses. Recharge estimates derived from unsaturated-zone (RUZC) and saturated-zone (RSZC) chloride mass balance methods are less variable (interquartile ranges or IQRs are 9.5 and 16.1 cm/yr, respectively) and more strongly correlated with climatic, hydrologic, land use, and sediment variables than Darcian estimates (IQR = 22.8 cm/yr). The unit-gradient Darcian estimates are a nonlinear function of moisture content and also reflect the uncertainty of pedotransfer functions used to estimate hydraulic parameters. Significance level is <0.001 for nearly all explanatory variables having correlations with RUZC of <-0.3 or >0.3. Estimates of RSZC were evaluated using analysis of variance, multiple comparison tests, and an exploratory nonlinear regression (NLR) model. Recharge generally is greater in coastal plain surficial aquifers, fractured crystalline rocks, and carbonate rocks, or in areas with high sand content. Westernmost portions of the study area have low recharge, receive somewhat less precipitation, and contain fine-grained sediment. The NLR model simulates water input to the land surface followed by transport to ground water, depending on factors that either promote or inhibit water infiltration. The model explains a moderate amount of variation in the data set (coefficient of determination = 0.61). Model sensitivity analysis indicates that mean annual runoff, air temperature, and precipitation, and an index of ground-water exfiltration potential most influence estimates of recharge at sampled sites in the region. Soil characteristics and land use have less influence on the recharge estimates, but nonetheless are significant in the NLR model. ?? 2006 Elsevier B.V. All rights reserved.

Journal of Hydrology↗

Historical changes in New York State streamflow: Attribution of temporal shifts and spatial patterns from 1961 to 2016

To better understand the effects of climate change on streamflow, the hydrologic response to both temperature and precipitation needs to be examined at the mesoscale. New York State provides a hydrologically diverse mesoscale region, where sub-regional clusters of watersheds may respond differently to changes in temperature and in seasonal precipitation rates. Connections between streamflow and climate were examined for 97 gaging stations across the state and surrounding areas, for a historical period of 56 years of daily average streamflow. Gages were grouped into clusters if their mean annual discharge rates were strongly correlated to one another. Within each cluster, sharp temporal changes in discharge, or change points, were identified. These change points clustered both spatially and by flow regime, with low, medium, and high flows increasing around 1970 for much of the state consistent with other studies in the region. A step increase in Catskill low flows in 2003 coincides with increases in summer precipitation, and is consistent with a positive correlation between summer precipitation and annual low flows. Our results support previous studies that have shown that streamflow at this mesoscale is strongly tied to precipitation, and the strength of that connection is modulated by land cover, geographic position, and seasonal moisture conditions. Across the state, the winter-spring center of volume date has moved earlier along with increasing January streamflow rates, the result of warmer winter temperatures and an increased proportion of precipitation as rain. The transition to a post-1970s pluvial period also coincided with more frequent peak over threshold flows statewide, and this wetter period has continued to the present day.

New York↗

Chlorine-36 in groundwater of the United States: Empirical data

Natural production of the radionuclide chlorine - 36 ( 36 Cl) has provided a valuable tracer for groundwater studies. The nuclear industry, especially the testing of thermonuclear weapons, has also produced large amounts of 36 Cl that can be detected in many samples of groundwater . In order to be most useful in hydrologic studies, the natural production prior to 1952 should be distinguished from more recent artificial sources. The object of this study was to reconstruct the probable preanthropogenic levels of 36 Cl in groundwater in the United States . Although significant local variations exist, they are superimposed on a broad regional pattern of 36 Cl/Cl ratios in the United States . Owing to the influence of atmospherically transported ocean salt, natural ratios of 36 Cl/total Cl are lowest near the coast and increase to a maximum in the central Rocky Mountains of the United States .

Hydrogeology Journal↗

Mechanisms of Devils Lake’s responses to recent climatic wetting: Insights from a physically based hydrologic model

Study region Devils Lake Basin of the Northern Great Plains (NGP) region, North Dakota, USA Study focus Understanding the mechanism of Devils Lake’s responses and basin-wide hydrologic change under a wet-climatic regime using a process-based and cold region hydrologic model. New hydrologic insights Model results illustrate that three distinct hydroclimatic periods occurred during the study: Water Years 2002–05, 2006–11, and 2012–18. Following a brief time of contraction and growth, the latter two periods provide a complete picture of a wetting to drying cycle during an overall wetting regime. From 2006–2011, Devils Lake (DL) grew primarily due to lateral inflow, driven by strong precipitation and high frozen soil content leading up to the 2011 floods. In addition, during wet years, the snowmelt streamflow from the eastern and central parts of the DL Basin contributes significantly to lake growth compared to the western part. By contrast, from 2012 to 18, DL entered a contraction period, dominated by evaporation losses and anthropogenic flood control operations. Contributors to upstream drying included low precipitation, minimal snowpack accumulation, slightly lower frozen soil ratios, and minimal snowmelt runoff.

North Dakota↗

Determining climate change management priorities: A case study from Wisconsin

A burgeoning dialogue exists regarding how to allocate resources to maximize the likelihood of long-term biodiversity conservation within the context of climate change. To make effective decisions in natural resource management, an iterative, collaborative, and learning-based decision process may be more successful than a strictly consultative approach. One important, early step in a decision process is to identify priority species or systems. Although this promotes the conservation of select species or systems, it may inadvertently alter the future of non-target species and systems. We describe a process to screen terrestrial wildlife for potential sensitivity to climate change and then use the results to engage natural resource professionals in a process of identifying priorities for monitoring, research, and adaptation strategy implementation. We demonstrate this approach using a case study from Wisconsin. In Wisconsin, experts identified 23 out of 353 species with sufficient empirical research and management understanding to inform targeted action. Habitat management and management of hydrological conditions were the common strategies for targeted action. Although there may be an interest in adaptation strategy implementation for many species and systems, experts considered existing information inadequate to inform targeted action. According to experts, 40% of the vertebrate species in Wisconsin will require near-term intervention for climate adaptation. These results will inform state-wide conservation planning as well as regional efforts.

Wisconsin↗

Benchmark dataset of historical annual peak floods classified by causal mechanisms for select US river basins

Considering the causal mechanisms of floods can improve estimates of flood recurrence intervals given that certain flood types can be associated with higher magnitude and more damaging floods. However, few verified datasets of flood types are available to validate the semiautomated and automated classification algorithms needed to apply flood-typing across large hydrologically diverse regions. To address this gap, a benchmark dataset of manually classified flood types was compiled for 1,763 annual maximum flood peaks from 18 stream gauges in six different river basins across the conterminous United States from 1851 to 2022. Within each basin, three representative stream gauges were selected for manual flood typing. A flexible classification framework is introduced that facilitates flood typing across hydrologically diverse regions and accommodates unique combinations of weather and antecedent watershed conditions specific to each region. Floods were manually typed by domain experts using multiple lines of evidence to identify a primary surface water input of each flood (rainfall, snowmelt, or both) and, if relevant, associated storm type and secondary causal mechanisms characterizing antecedent watershed conditions. Across all the study basins, 49% of historical annual maximum flood peaks were attributable to rainfall, 28% to snowmelt, 22% to mixed precipitation, and 1% could not be assigned to a mechanism due to missing or incomplete data. The proposed flood-typing schema supports varying levels of flood typing specificity required for mixed population flood-frequency analysis, flood-type-specific design hydrographs, water quality response studies, and additional applications. This detailed, manually determined benchmark dataset serves as a resource that can be used developing and validating automated or machine learning-based algorithms capable of operationalizing expanded flood peak information.

conterminous United States↗

Validation of a stream and riparian habitat assessment protocol using stream salamanders in the southwest Virginia coalfields

Within the central Appalachia Coalfields, the aquatic impacts of large-scale land uses, such as surface mining, are of particular ecological concern. Identification and quantification of land use impacts to aquatic ecosystems are a necessary first step to aid in mitigation of negative consequences to biota. However, quantifying physical environmental quality such as stream and riparian habitat often can be quite difficult, particularly when there is time or fiscal limitations. As such, standard protocols such as the U.S. EPA’s Stream Habitat Rapid Bioassessment Protocol have been established to be cost- and time-effective. This protocol estimates ten different stream and riparian conditions on a scale of 0 to 20. Unfortunately, using estimations can be problematic because of large potential variation in the scoring depending on differences in training, experience, and opinion of the personnel doing the estimations. In order to help negate these biases and provide a simplified process, the U.S. Army Corps of Engineers (USACE) developed a functional assessment for streams that measures 11 stream and riparian variables along with watershed land use to calculate three different scores, a hydrology score, biogeochemical score, and habitat score. In our study, we examined the correlation of stream salamander presence and abundance to the three USACE scores. In the summer of 2013, we visited 70 sites in the southwest Virginia Coalfields multiple times to collect salamanders and quantify stream and riparian microhabitat parameters. Using occupancy and abundance analyses, we found strong relationships among three Desmognathus spp. and the USACE Habitat FCI score. Accordingly, the Habitat FCI score provides a reasonable assessment of physical instream and riparian conditions that may serve as a surrogate for understanding the community composition and integrity of aquatic salamander in the region.

Virginia↗

A comparison between generalized least squares regression and top-kriging for homogeneous cross-correlated flood regions

Spatial cross-correlation among flood sequences impacts the accuracy of regional predictors. Our study investigates this impact for two regionalization procedures, generalized least squares (GLS) regression and top-kriging (TK), which deal with cross-correlation in two fundamentally different ways and therefore might be associated with different accuracy and uncertainty of predicted flood quantiles. We perform a Monte Carlo experiment based on a dataset of annual maximum flood series for 20 catchments in a hydrologically homogeneous region. Based on a log-Pearson type III parent distribution, we generate 3000 realizations of the region with different degrees of cross-correlation. For each realization, GLS and TK are applied in leave-one-out cross-validation to predict at-site flood quantiles. Our study shows that (a) TK outperforms GLS when catchment area is the only catchment descriptor used for predicting “true” population (theoretical) flood quantiles, regardless of the level of cross-correlation, and (b) GLS and TK perform similarly when multiple catchment descriptors are used.

Hydrological Sciences Journal↗

Population dynamics of the threatened Oregon spotted frog before and after drought mitigation

Amphibians are among the most sensitive taxa to climate change, and species inhabiting arid and semiarid landscapes at the extremes of their range are especially vulnerable to drought. The Jack Creek, Oregon, USA, population of Oregon spotted frogs ( Rana pretiosa ) faces unique challenges because it occupies the highest elevation site in the species' extant range and one that has been transformed by loss of American beavers ( Castor canadensis ), which historically maintained open water. We evaluated the effects of drought mitigation (addition of excavated ponds) on relationships between local and regional water availability, inactive legacy beaver dams, and Oregon spotted frog population dynamics in the Jack Creek system. We conducted egg mass surveys and capture-mark-recapture sampling at a treatment reach with excavated ponds and 3 reference reaches over 13 years; surveys spanned a period before and after pond excavation at the treatment and 1 primary comparison reference reach. We analyzed data using a combination of robust design capture-mark-recapture estimators and generalized linear mixed models to characterize population dynamics. Adult Oregon spotted frog survival was approximately 19.5% higher at the treatment reach than the primary reference reach during the study period. Annual survival was most strongly associated with late summer vegetation greenness, a proxy for water availability, and males had higher survival than females. Among the 4 study reaches, the treatment reach consistently had higher late summer vegetation greenness, and the hydrology functioned more independently of regional precipitation patterns relative to the reference reaches; however, these dynamics were not linked to pond excavation. Breeding was concentrated in 2 legacy beaver ponds that were deepened by excavation during the study compared to an unexcavated beaver pond, 2 excavated ponds without legacy beaver dams, and 9 reference ponds. These results point to the benefit of enhancing existing beaver structures and indicate that management actions aimed at maintaining surface water for breeding in spring and saturated soils and ponded water for adults in late summer would benefit this unique population of Oregon spotted frogs in the face of drought.

Oregon↗

Basis and methods of NASA airborne topographic mapper lidar surveys for coastal studies

This paper provides an overview of the basic principles of airborne laser altimetry for surveys of coastal topography, and describes the methods used in the acquisition and processing of NASA Airborne Topographic Mapper (ATM) surveys that cover much of the conterminous US coastline. This form of remote sensing, also known as "topographic lidar", has undergone extremely rapid development during the last two decades, and has the potential to contribute within a wide range of coastal scientific investigations. Various airborne laser surveying (ALS) applications that are relevant to coastal studies are being pursued by researchers in a range of Earth science disciplines. Examples include the mapping of "bald earth" land surfaces below even moderately dense vegetation in studies of geologic framework and hydrology, and determination of the vegetation canopy structure, a key variable in mapping wildlife habitats. ALS has also proven to be an excellent method for the regional mapping of geomorphic change along barrier island beaches and other sandy coasts due to storms or long-term sedimentary processes. Coastal scientists are adopting ALS as a basic method in the study of an array of additional coastal topics. ALS can provide useful information in the analysis of shoreline change, the prediction and assessment of landslides along seacliffs and headlands, examination of subsidence causing coastal land loss, and in predicting storm surge and tsunami inundation.

Journal of Coastal Research↗

Regional regression models of watershed suspended-sediment discharge for the eastern United States

Estimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1–8, exhibited prediction R 2 values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.

Journal of Hydrologic Engineering↗

Generalized additive regression models of discharge and mean velocity associated with direct-runoff conditions in Texas: Utility of the U.S. Geological Survey discharge measurement database

A database containing more than 17,700 discharge values and ancillary hydraulic properties was assembled from summaries of discharge measurement records for 424 U.S. Geological Survey streamflow-gauging stations (stream gauges) in Texas. Each discharge exceeds the 90th-percentile daily mean streamflow as determined by period-of-record, stream-gauge-specific, flow-duration curves. Each discharge therefore is assumed to represent discharge measurement made during direct-runoff conditions. The hydraulic properties of each discharge measurement included concomitant cross-sectional flow area, water-surface top width, and reported mean velocity. Systematic and statewide investigation of these data in pursuit of regional models for the estimation of discharge and mean velocity has not been previously attempted. Generalized additive regression modeling is used to develop readily implemented procedures by end-users for estimation of discharge and mean velocity from select predictor variables at ungauged stream locations. The discharge model uses predictor variables of cross-sectional flow area, top width, stream location, mean annual precipitation, and a generalized terrain and climate index (OmegaEM) derived for a previous flood-frequency regionalization study. The mean velocity model uses predictor variables of discharge, top width, stream location, mean annual precipitation, and OmegaEM. The discharge model has an adjusted R-squared value of about 0.95 and a residual standard error (RSE) of about 0.22 base-10 logarithm (cubic meters per second); the mean velocity model has an adjusted R-squared value of about 0.67 and an RSE of about 0.063 fifth root (meters per second). Example applications and computations using both regression models are provided. - See more at: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0000635#sthash.jhGyPxgZ.dpuf

Journal of Hydrologic Engineering↗

Size distributions of Arctic waterbodies reveal consistent relations in their statistical moments in space and time

Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km 2 (100 m 2 ) to 1 km 2 . We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size ( R 2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic.

Alaska↗

Change points in annual peak streamflows: Method comparisons and historical change points in the United States

Change-point, or step-trend, detection is an active area of research in statistics and an area of great interest in hydrology because change points may be evidence of natural or anthropogenic changes in climatic, hydrologic, or landscape processes. A common change-point technique is the Pettitt test; however, many change-point methods are now available and testing of methods has been limited. This study investigated eight methods for detecting change points in the location (central tendency, seven methods) and scale (dispersion or spread, one method) of annual peak streamflows, using simulated data with and without change points, and peak-streamflow series from basins with known large additions of reservoir storage. Parametric methods tested, including a Bayesian one, did not perform well, even when transforming peak streamflows to approximate normality by using logarithms. Nonparametric methods other than the Pettitt test allow for more than one change point but have an unacceptable number of false positives. Based on the results of our methods comparisons, we used the Pettitt and the Mood tests to find change points in location and scale, respectively, in thousands of streamgage records in the conterminous United States. Change points in location (median) and scale are abundant, with the changes in median peak streamflow showing regional patterns, as well as a strong increased streamflow signal around 1970. The changes in scale of peak streamflows are dominated more by temporal than spatial patterns; more streamgages had decreases in scale in earlier decades than recent decades and more streamgages had increases in scale occurring in recent decades than earlier decades.

Journal of Hydrology↗

Introduction to the special issue on “Understanding and predicting change in the coastal ecosystems of the northern Gulf of Mexico”

The coastal region of the northern Gulf of Mexico owes its current landscape structure to an array of tectonic, erosional and depositional, climatic, geochemical, hydrological, ecological, and human processes that have resulted in some of the world's most complex, dynamic, productive, and threatened ecosystems. Catastrophic hurricane landfalls, ongoing subsidence and erosion exacerbated by sea-level rise, disintegration of barrier island chains, and high rates of wetland loss have called attention to the vulnerability of northern Gulf coast ecosystems, habitats, built infrastructure, and economy to natural and anthropogenic threats. The devastating hurricanes of 2005 (Katrina and Rita) motivated the U.S. Geological Survey Coastal and Marine Geology Program and partnering researchers to pursue studies aimed at understanding and predicting landscape change and the associated storm hazard vulnerability of northern Gulf coast region ecosystems and human communities. Attaining this science goal requires increased knowledge of landscape evolution on geologic, historical, and human time scales, and analysis of the implications of such changes in the natural and built components of the landscape for hurricane impact susceptibility. This Special Issue of the Journal of Coastal Research communicates northern Gulf of Mexico research results that (1) improve knowledge of prior climates and depositional environments, (2) assess broad regional ecosystem structure and change over Holocene to human time scales, (3) undertake process studies and change analyses of dynamic landscape components, and (4) integrate framework, climate, variable time and spatial scale mapping, monitoring, and discipline-specific process investigations within interdisciplinary studies.

Journal of Coastal Research↗

Patterns and drivers of atmospheric river precipitation and hydrologic impacts across the western United States

Atmospheric rivers (ARs) significantly influence precipitation and hydrologic variability in many areas of the world, including the western United States. As ARs are increasingly recognized by the research community and the public, there is a need to more precisely quantify and communicate their hydrologic impacts, which can vary from hazardous to beneficial depending on location and on the atmospheric and land surface conditions prior to and during the AR. This study leverages 33 years of atmospheric and hydrologic data for the western United States to 1) identify how water vapor amount, wind direction and speed, temperature, and antecedent soil moisture conditions influence precipitation and hydrologic responses (runoff, recharge, and snowpack) using quantile regression and 2) identify differences in hydrologic response types and magnitudes across the study region. Results indicate that water vapor amount serves as a primary control on precipitation amounts. Holding water vapor constant, precipitation amounts vary with wind direction, depending on location, and are consistently greater at colder temperatures. Runoff efficiencies further covary with temperature and antecedent soil moisture, with precipitation falling as snow and greater available water storage in the soil column mitigating flood impacts of large AR events. This study identifies the coastal and maritime mountain ranges as areas with the greatest potential for hazardous flooding and snowfall impacts. This spatially explicit information can lead to better understanding of the conditions under which ARs of different precipitation amounts are likely to be hazardous at a given location.

Journal of Hydrometeorology↗

Trends in snowmelt-related streamflow timing in the conterminous United States

Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940–2014 and 1960–2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (<1600 m) basins in the West, predominantly located in the Northwest, had median earlier WSCVD by 6.8 days (1940–2014, 0.9 days/decade) and 3.4 days (1960–2014, 0.6 days/decade). Streamflow timing at high-elevation (⩾1600 m) basins in the West had median earlier WSCVD by 4.0 days (1940–2014, 0.5 days/decade) and 5.2 days (1960–2014, 0.9 days/decade). Trends toward earlier WSCVD in the Northwest were not statistically significant, differing from previous studies that observed many large and (or) significant trends in this region. Much of this difference is likely due to the sensitivity of trend tests to the time period being tested, as well as differences in the streamflow timing metrics used among the studies. Mean February–May air temperature was significantly correlated with WSCVD at 100 percent of the study gages (field significant, p < 0.0001), demonstrating the sensitivity of WSCVD to air temperature across snowmelt dominated basins in the U.S. WSCVD in high elevation basins in the West, however, was related to both air temperature and precipitation yielding earlier snowmelt-related streamflow timing under warmer and drier conditions.

Journal of Hydrology↗