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At least 685 records · Page 38Linked to original sources
USGS2012

Simulation of climate change in San Francisco Bay Basins, California: Case studies in the Russian River Valley and Santa Cruz Mountains

As a result of ongoing changes in climate, hydrologic and ecologic effects are being seen across the western United States. A regional study of how climate change affects water resources and habitats in the San Francisco Bay area relied on historical climate data and future projections of climate, which were downscaled to fine spatial scales for application to a regional water-balance model. Changes in climate, potential evapotranspiration, recharge, runoff, and climatic water deficit were modeled for the Bay Area. In addition, detailed studies in the Russian River Valley and Santa Cruz Mountains, which are on the northern and southern extremes of the Bay Area, respectively, were carried out in collaboration with local water agencies. Resource managers depend on science-based projections to inform planning exercises that result in competent adaptation to ongoing and future changes in water supply and environmental conditions. Results indicated large spatial variability in climate change and the hydrologic response across the region; although there is warming under all projections, potential change in precipitation by the end of the 21st century differed according to model. Hydrologic models predicted reduced early and late wet season runoff for the end of the century for both wetter and drier future climate projections, which could result in an extended dry season. In fact, summers are projected to be longer and drier in the future than in the past regardless of precipitation trends. While water supply could be subject to increased variability (that is, reduced reliability) due to greater variability in precipitation, water demand is likely to steadily increase because of increased evapotranspiration rates and climatic water deficit during the extended summers. Extended dry season conditions and the potential for drought, combined with unprecedented increases in precipitation, could serve as additional stressors on water quality and habitat. By focusing on the relationship between soil moisture storage and evapotranspiration pressures, climatic water deficit integrates the effects of increasing temperature and varying precipitation on basin conditions. At the fine-scale used for these analyses, this variable is an effective indicator of the areas in the landscape that are the most resilient or vulnerable to projected changes. These analyses have shown that regardless of the direction of precipitation change, climatic water deficit is projected to increase, which implies greater water demand to maintain current agricultural resources or land cover. Fine-scale modeling provides a spatially distributed view of locations in the landscape that could prove to be resilient to climatic changes in contrast to locations where vegetation is currently living on the edge of its present-day bioclimatic distribution and, therefore, is more likely to perish or shift to other dominant species under future warming. This type of modeling and the associated analyses provide a useful means for greater understanding of water and land resources, which can lead to better resource management and planning.

California↗
USGS1983

Map showing outcrops of basaltic rocks of early Quaternary and Tertiary age, Basin and Range province, Southern California

This map report is one of a series of geologic and hydrologic maps covering all or parts of States within the Basin and Range province of the western United States. The map reports contain detailed information on subjects that characterize the geohydrology of the province, including the ground-water hydrology/ ground-water quality, surface distribution of selected rock types, tectonic conditions, areal geophysics, Pleistocene lakes and marshes, and mineral and energy resources. This is a part of the U.S. Geological Survey's program for geologic and hydrologic evaluation of the province to identify prospective regions for further study relative to isolation of high-level nuclear waste (Bedinger, Sargent, and Reed, 1984). This map was prepared from published geologic maps and reports utilizing the project guidelines defined in Sargent and Bedinger (1984). As used in this study, basaltic rocks include basaltic andesite and basalt. The map shows the known occurrences of basaltic rocks largely of Tertiary age. Locally, however, where basalts of Quaternary age were not differentiated from those of Tertiary age, the younger basalts have been included on the map. The Description of Map Units includes the geologic and, if available, radiometric age; lithology; thickness where available; and sources of data for the basaltic units in outlined and numbered areas within the counties of the study area. No information was available on the rock outcrops that are unnumbered. The listed radiometric ages do not necessarily represent the entire age range of a unit.

California↗
USGS2025

Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management

The San Joaquin Valley (SJV) of California is one of the world’s most productive agricultural regions. Reliance on groundwater has led to some of the greatest rates of human-induced land subsidence in the world in the 20th century, as well as more recently. The United States Geological Survey (USGS) has recently developed an integrated surface–subsurface hydrologic model, the Central Valley Hydrologic Model 2 (CVHM2), that represents the major components of the hydrologic system of California’s Central Valley. In this study, CVHM2 was applied as a decision support tool while simulating various management strategies to mitigate the land subsidence caused by the extraction of groundwater. CVHM2 was extended through to 2073 and applied to simulate management scenarios in terms of three primary drivers and their impact on subsidence along the Delta–Mendota Canal (DMC), a critical piece of infrastructure in the western SJV. The drivers considered were agricultural water demands, managed aquifer recharge (MAR), and changes in future climate. The results show that future subsidence is most sensitive to water demands, second most sensitive to future changes in climate, and relatively insensitive to MAR when it is applied as a surface application in the western SJV. However, we demonstrate via proof-of-concept scenarios that the MAR is capable of arresting subsidence when implemented via injection below the Corcoran Clay Member of the Tulare Formation instead of as a surface application. We also examine the uncertainty that is the result of climate variability and how to use the tool to identify the most appropriate strategies to constrain future subsidence to acceptable levels.

California↗
USGS2002

Ecological dynamics of wetlands at Lisbon Bottom, Big Muddy National Fish and Wildlife Refuge, Missouri

The study documented the interaction between hydrology and the biological dynamics within a single spring season at Lisbon Bottom in 1999. The study goal was to provide information necessary for resource managers to develop management strategies for this and other units of the Big Muddy National Fish and Wildlife Refuge. Researchers studied the hydrology, limnology, and biological dynamics of zooplankton, macroinvertebrates, fish and waterbird communities. Lisbon Bottom is one of several parcels of 1993 flood-damaged land that was purchased from willing sellers by the U.S. Fish and Wildlife Service as part of the Big Muddy National Fish and Wildlife Refuge. Lisbon Bottom is a loop bend in the river near Glasgow in Howard County, Missouri between approximately river mile (RM) 213 to RM 219. Flooding at Lisbon in 1993 and 1995 breeched local levees and created a diverse wetland complex.

Missouri↗
USGS2006

Analysis of the surface hydrology in a regional climate model

This paper discusses the surface hydrology of a multi‐year simulation of present day climate over the United States (US) conducted with a regional climate model (RegCM) nested within a general circulation model (GCM). The RegCM, which is run with a 60 km gridpoint spacing is interactively coupled with a state‐of‐the‐art surface physics package that includes full surface hydrology calculations (the Biosphere‐Atmosphere Transfer Scheme or BATS). The hydrologic budgets of ten regional drainage basins in the US are analysed. Model results are compared with available observations and with results from previous modelling experiments to evaluate the feasibility of using nested RegCM/GCM models for hydrology studies. In our experiment, the model captures the basic seasonality of the basin hydrologic budgets, although the simulated precipitation amounts are too high over the western US and too low over the eastern US. As a result, runoff, snow cover and soil water content are underestimated over the eastern US basins, while evaporation and runoff are overestimated in some of the western US basins. Topographically induced characteristics of precipitation, snow cover and runoff are well simulated over the mountainous western regions. Also well captured is the inter‐basin variation of hydrologic budgets which occurs in response to different climatic settings. The springtime snowmelt and peak runoff season generally occurs in the model earlier in the year than is observed. Although our work indicates that the coupled regional modelling system can be useful in applications to hydrological studies, results from this experiment indicate that better accuracy in the simulation of regional climatic variables and more detailed representation of some hydrologic processes would be required before the coupled modelling system could be used to provide accurate assessments of hydrologic responses to climate change.

Quarterly Journal of the Royal Meteorological Soci↗
USGS2012

Linking urbanization to the Biological Condition Gradient (BCG) for stream ecosystems in the Northeastern United States using a Bayesian network approach

Urban development alters important physical, chemical, and biological processes that define urban stream ecosystems. An approach was developed for quantifying the effects of these processes on aquatic biota, and then linking those effects to endpoints that can be used for environmental management. These complex, interacting systems are challenging to model from a scientific standpoint. A desirable model clearly shows the system, simulates the interactions, and ultimately predicts results of management actions. Traditional regression techniques that calculate empirical relations between pairs of environmental factors do not capture the interconnected web of multiple stressors, but urban development effects are not yet understood at the detailed scales required to make mechanistic modeling approaches feasible. Therefore, in contrast to a fully deterministic or fully statistical modeling approach, a Bayesian network model provides a hybrid approach that can be used to represent known general associations between variables while acknowledging uncertainty in predicted outcomes. It does so by quantifying an expert-elicited network of probabilistic relations between variables. Advantages of this modeling approach include (1) flexibility in accommodating many model specifications and information types; (2) efficiency in storing and manipulating complex information, and to parameterize; and (3) transparency in describing the relations using nodes and arrows and in describing uncertainties with discrete probability distributions for each variable. In realization of the aforementioned advantages, a Bayesian network model was constructed to characterize the effect of urban development on aquatic macroinvertebrate stream communities through three simultaneous, interacting ecological pathways affecting stream hydrology, habitat, and water quality across watersheds in the Northeastern United States. This model incorporates both empirical data and expert knowledge to calculate the probabilities of attaining desired aquatic ecosystem conditions under different urban stress levels, environmental conditions, and management options. Ecosystem conditions are characterized in terms of standardized Biological Condition Gradient (BCG) management endpoints. This approach to evaluating urban development-induced perturbations in watersheds integrates statistical and mechanistic perspectives, different information sources, and several ecological processes into a comprehensive description of the system that can be used to support decision making. The completed model can be used to infer which management actions would lead to the highest likelihood of desired BCG tier achievement. For example, if best management practices (BMP) were implemented in a highly urbanized watershed to reduce flashiness to medium levels and specific conductance to low levels, the stream would have a 70-percent chance of achieving BCG Tier 3 or better, relative to a 24-percent achievement likelihood for unmanaged high urban land cover. Results are reported probabilistically to account for modeling uncertainty that is inherent in sources such as natural variability and model simplification error.

Scientific Investigations Report↗
USGS2021

Spatial patterns and drivers of nonperennial flow regimes in the contiguous United States

Over half of global rivers and streams lack perennial flow, and understanding the distribution and drivers of their flow regimes is critical for understanding their hydrologic, biogeochemical, and ecological functions. We analyzed nonperennial flow regimes using 540 U.S. Geological Survey watersheds across the contiguous United States from 1979 to 2018. Multivariate analyses revealed regional differences in no-flow fraction, date of first no flow, and duration of the dry-down period, with further divergence between natural and human-altered watersheds. Aridity was a primary driver of no-flow metrics at the continental scale, while unique combinations of climatic, physiographic and anthropogenic drivers emerged at regional scales. Dry-down duration showed stronger associations with nonclimate drivers compared to no-flow fraction and timing. Although the sparse distribution of nonperennial gages limits our understanding of such streams, the watersheds examined here suggest the important role of aridity and land cover change in modulating future stream drying.

contiguous United States↗
USGS2025

Interrogating process deficiencies in large-scale hydrologic models with interpretable machine learning

Large-scale hydrologic models are increasingly being developed for operational use in the forecasting and planning of water resources. However, the predictive strength of such models depends on how well they resolve various functions of catchment hydrology, which are influenced by gradients in climate, topography, soils, and land use. Most assessments of hydrologic model uncertainty have been limited to traditional statistical methods. Here, we present a proof-of-concept approach that uses interpretable machine learning techniques to provide post hoc assessment of model sensitivity and process deficiency in hydrologic models. We train a random forest model to predict the Kling–Gupta efficiency (KGE) of National Water Model (NWM) and National Hydrologic Model (NHM) streamflow predictions for 4383 stream gauges in the conterminous United States. Thereafter, we explain the local and global controls that 48 catchment attributes exert on KGE prediction using interpretable Shapley values. Overall, we find that soil water content is the most impactful feature controlling successful model performance, suggesting that soil water storage is difficult for hydrologic models to resolve, particularly for arid locations. We identify nonlinear thresholds beyond which predictive performance decreases for NWM and NHM. For example, soil water content less than 210 mm, precipitation less than 900 mm yr −1 , road density greater than 5 km km −2 , and lake area percent greater than 10 % contributed to lower KGE values. These results suggest that improvements in how these influential processes are represented could result in the largest increases in NWM and NHM predictive performance. This study demonstrates the utility of interrogating process-based models using data-driven techniques, which has broad applicability and potential for improving the next generation of large-scale hydrologic models.

conterminous United States↗
USGS2012

The influence of reservoirs, climate, land use and hydrologic conditions on loads and chemical quality of dissolved organic carbon in the Colorado River

Longitudinal patterns in dissolved organic carbon (DOC) loads and chemical quality were identified in the Colorado River from the headwaters in the Rocky Mountains to the United States-Mexico border from 1994 to 2011. Watershed- and reach-scale climate, land use, river discharge and hydrologic modification conditions that contribute to patterns in DOC were also identified. Principal components analysis (PCA) identified site-specific precipitation and reach-scale discharge as being correlated with sites in the upper basin, where there were increases in DOC load from the upstream to downstream direction. In the lower basin, where DOC load decreased from upstream to downstream, sites were correlated with site-specific temperature and reach-scale population, urban land use and hydrologic modification. In the reaches containing Lakes Powell and Mead, the two largest reservoirs in the United States, DOC quantity decreased, terrestrially derived aromatic DOC was degraded and/or autochthonous less aromatic DOC was produced. Taken together, these results suggest that longitudinal patterns in the relatively unregulated upper basin are influenced by watershed inputs of water and DOC, whereas DOC patterns in the lower basin are reflective of a balance between watershed contribution of water and DOC to the river and loss of water and DOC due to hydrologic modification and/or biogeochemical processes. These findings suggest that alteration of constituent fluxes in rivers that are highly regulated may overshadow watershed processes that would control fluxes in comparable unregulated rivers. Further, these results provide a foundation for detailed assessments of factors controlling the transport and chemical quality of DOC in the Colorado River.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2022

Integrating urban planning and water management through green infrastructure in the United States-Mexico border

Creating sustainable, resilient, and livable cities calls for integrative approaches and collaborative practices across temporal and spatial scales. However, practicability is challenged by institutional, social, and technical complexities and the need to build collective understanding of integrated approaches. Rapid urbanization along the United States-Mexico border, fueled by industrialization, trade, and migration, has resulted in cities confronted with recurrent flooding risk, extended drought, water pollution, habitat destruction and systemic vulnerabilities. The international border, which separates natural and built ecosystems, is both a challenge and an opportunity, making a unique social and institutional setting ideal for testing the integration of urban planning and water management. Our research focuses on fusing multi-functional and multi-scalar green infrastructure to restore ecosystem services through a strategic binational planning process. This paper describes this planning process, including the development and application of both a land suitability analysis and a hydrological model to optimally site green infrastructure in the Nogales, Arizona, United States—Nogales, Sonora, Mexico, cross border region. We draw lessons from this process and stakeholder feedback focused on the potential for urban green infrastructure, to allow for adaptation and even transformation in the face of current and future challenges such as limited resources, underdeveloped governance, bordering, and climate change. In sum, a cross border network of green infrastructure can provide a backbone to connect this transboundary watershed while providing both hydrological and social benefits.

Frontiers in Water↗
USGS2020

Hydrologic monitoring networks in the Death Valley Regional Flow System, Nye County, Nevada and Inyo County, California

Introduction Water is an important resource in the arid southwest region of the United States where there is a limited supply of surface water and groundwater. In the Death Valley regional groundwater flow system (DVRFS) in southern Nevada and eastern California, groundwater is the main source of supply for agricultural, commercial, and domestic water needs. For over four decades, the United States Geological Survey (USGS) Nevada Water Science Center (NVWSC) has assisted environmental programs with the collection of hydrologic information within the DVRFS. Three hydrologic networks, managed in cooperation with local (Nye County, Nev., and Inyo County, Calif.) and federal (Bureau of Land Management, Fish and Wildlife Service, National Park Service, U.S. Department of Energy National Nuclear Security Administration) agencies, are used to actively monitor wells and springs in the region.

California, Nevada↗
USGS2011

Effects of model layer simplification using composite hydraulic properties

Groundwater provides much of the fresh drinking water to more than 1.5 billion people in the world (Clarke et al., 1996) and in the United States more that 50 percent of citizens rely on groundwater for drinking water (Solley et al., 1998). As aquifer systems are developed for water supply, the hydrologic system is changed. Water pumped from the aquifer system initially can come from some combination of inducing more recharge, water permanently removed from storage, and decreased groundwater discharge. Once a new equilibrium is achieved, all of the pumpage must come from induced recharge and decreased discharge (Alley et al., 1999). Further development of groundwater resources may result in reductions of surface water runoff and base flows. Competing demands for groundwater resources require good management. Adequate data to characterize the aquifers and confining units of the system, like hydrologic boundaries, groundwater levels, streamflow, and groundwater pumping and climatic data for recharge estimation are to be collected in order to quantify the effects of groundwater withdrawals on wetlands, streams, and lakes. Once collected, three-dimensional (3D) groundwater flow models can be developed and calibrated and used as a tool for groundwater management. The main hydraulic parameters that comprise a regional or subregional model of an aquifer system are the hydraulic conductivity and storage properties of the aquifers and confining units (hydrogeologic units) that confine the system. Many 3D groundwater flow models used to help assess groundwater/surface-water interactions require calculating ?effective? or composite hydraulic properties of multilayered lithologic units within a hydrogeologic unit. The calculation of composite hydraulic properties stems from the need to characterize groundwater flow using coarse model layering in order to reduce simulation times while still representing the flow through the system accurately. The accuracy of flow models with simplified layering and hydraulic properties will depend on the effectiveness of the methods used to determine composite hydraulic properties from a number of lithologic units.

Florida↗
USGS1986

National water summary 1985: Hydrologic events and surface-water resources

The surface-water resources of the United States, the focal point for this National Water Summary, are extensively developed and managed to provide water supplies, hydroelectric power, navigation, recreational opportunities, and sufficient instream flows to maintain fish and wildlife habitats and adequate water quality. Surface water represents 77 percent of the Nation's total freshwater withdrawals, 65 percent of public supplies, 74 percent of self- supplied industries, excluding thermoelectric power generation, and 60 percent of irrigation. In only 10 States does surface water provide less than half of the total withdrawals.

Water Supply Paper↗
USGS2026

A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States

Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.

contiguous United States↗
USGS2012

Hydrologic, vegetation, and soil data collected in selected wetlands of the Big River Management area, Rhode Island, from 2008 through 2010

The Rhode Island Water Resources Board planned to develop public water-supply wells in the Big River Management Area in Kent County, Rhode Island. Research in the United States and abroad indicates that groundwater withdrawal has the potential to affect wetland hydrology and related processes. In May 2008, the Rhode Island Water Resources Board, the U.S. Geological Survey, and the University of Rhode Island formed a partnership to establish baseline conditions at selected Big River wetland study sites and to develop an approach for monitoring potential impacts once pumping begins. In 2008 and 2009, baseline data were collected on the hydrology, vegetation, and soil characteristics at five forested wetland study sites in the Big River Management Area. Four of the sites were located in areas of potential drawdown associated with the projected withdrawals. The fifth site was located outside the area of projected drawdown and served as a control site. The data collected during this study are presented in this report.

Rhode Island↗
USGS2018

The role of a non-native tree in riparian vegetation expansion and channel narrowing along a dryland river

Along rivers, native and invasive species may establish and persist on active channel bedforms as part of channel narrowing. Using historical aerial photography and dendrochronology, we quantified spatial and temporal patterns of narrowing and vegetation expansion, including native Fremont cottonwood (Populus fremontii) and non‐native Russian olive (Elaeagnus angustifolia), along the largely unregulated Escalante River in south‐western United States. Russian olive establishment was examined with respect to hydrologic and climate variables. Narrowing along the Escalante River was initiated during a mid‐20th century drought. Cottonwood rapidly colonized higher, bar surfaces between the 1950s and 1981. Small numbers of Russian olive established in moist sites during this period as the channel narrowed by nearly 80%. After 1981, there was no obvious cottonwood establishment but low channel bars and banks were rapidly colonized by Russian olive. Hydroclimate predictors were equivocal but exponential growth of this large‐seeded, shade‐tolerant species lagged its introduction by 30 years, apparently because of delayed reproductive maturity, limited seed availability, and widespread availability of favourable establishment sites following initial channel narrowing. Sediment trapping, levee formation, and modification of channel form by dense, channel‐edge bands of Russian olive progressively limited new establishment sites and by 2000, recruitment declined sharply. Our results have implications for management of non‐native tree invasions along arid‐region rivers, including identification of low, moist, active channel bars where the establishment and physical impacts of Russian olive appear to be most pronounced and where focused management efforts are likely to be most effective.

Utah↗