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Results for “Bulletin of Seismological Society of America”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,663 records · Page 74Linked to original sources
USGS1993

Ground-water quality near an inactive landfill and sludge-spreading area, Tallahassee, Florida

Ground-water quality of a 120-acre area encompassing an inactive landfill southwest of Tallahassee, Florida, was assessed by installing and sampling 21 monitoring wells. Sludge from a municipal sewage-treatment plant was also applied to the land surface near the landfill site. Water samples were collected from the 21 monitoring wells from June 1987 through September 1990 and analyzed for concentrations of major ions, nitrogen species, trace metals, field measurements, and more than 140 organic constituents. Water quality in the Upper Floridan aquifer at the study site was compared to background water quality in other areas of Leon County. Ground-water quality of the study site was evaluated by the location of wells sampled in relation to the landfill and the sludge-spreading areas. Results of nonparametric statistical analysis indicated that potassium and nitrite plus nitrate as nitrogen concentrations in water samples from wells completed in the Upper Floridan aquifer at the study site were significantly different at the 5 percent probability level from those in samples from background wells completed in this aquifer in Leon County. Median potassium concentrations were 0.4 mg/L (milligrams per liter) in water from wells at the study site and 0.7 mg/L in water from background wells in Leon County. Median nitrite plus nitrate concentrations were 6.48 mg/L in water samples from wells at the study site and 0.51 mg/L in water samples from background wells. Graphical comparison of the water quality characteristics in water from six categories of wells; upgradient, landfill, adjacent to the landfill, downgradient onsite, downgradient offsite, and background Leon County, indicated that sodium, bicarbonate, sulfate, iron, manganese, and dissolved solids concentrations and specific conductance values were highest within the landfill. Upgradient and downgradient well categories include wells in areas affected by sludge spreading. Localized reducing conditions were indicated in a downgradient area by median iron concentrations of 930 and 30 ug/L (micrograms per liter) in samples from wells only 5 feet apart. Nitrite plus nitrate concentrations were lowest in water from wells in the landfill compared to water from the other categories. Concentrations of most trace elements and organic compounds were mostly below detection limits, although State maximum contaminant levels of 1 ug/L for benzene and vinyl chloride and 3 ug/L for tetrachloroethene were exceeded in 14 samples. Concentrations of sodium, potassium, chloride, sulfate, nitrite plus nitrate, total organic and ammonia nitrogen, and ammonia nitrogen in ground water were statistically analyzed in areas affected by sludge-spreading and other areas. Only nitrite plus nitrate and chloride concentrations were significantly different between the two areas. Median nitrite plus nitrate and chloride concentrations in sludge-spreading areas were 6.9 mg/L and 2.9 mg/L, respectively, compared to 1.1 mg/L and 1.8 mg/L in other areas.

Florida↗
USGS2024

The SCEC/USGS community stress drop validation study using the 2019 Ridgecrest earthquake sequence

We introduce a community stress drop validation study using the 2019 Ridgecrest, California, earthquake sequence, in which researchers are invited to use a common dataset to independently estimate comparable measurements using a variety of methods. Stress drop is the change in average shear stress on a fault during earthquake rupture, and as such is a key parameter in many ground motion, rupture simulation, and source physics problems in earthquake science. Spectral stress drop is commonly estimated by fitting the shape of the radiated energy spectrum, yet estimates for an individual earthquake made by different studies can vary hugely. In this community study, sponsored jointly by the U. S. Geological Survey and Southern/Statewide California Earthquake Center, we seek to understand the sources of variability and uncertainty in earthquake stress drop through quantitative comparison of submitted stress drops. The publicly available dataset consists of nearly 13,000 earthquakes of M1 to 7 from two weeks of the 2019 Ridgecrest sequence recorded on stations within 1-degree. As a community study, findings are shared through workshops and meetings and all are invited to join at any time, at any interest level.

Seismica↗
USGS2024

Framework for implementing damping scaling factors in U.S. Geological Survey National Seismic Hazard Models

Traditionally, probabilistic seismic hazard analysis (PSHA) has focused on calculating ground motion hazard curves for elastic, 5%-damped pseudo spectral accelerations, Sa(T,5%), which are used as the basis for engineering design parameters and targets for ground motion selection and modification. However, structures and geotechnical systems can exhibit a wide range of damping ratios both above and below the 5% level, depending on the construction material, structural system, nonstructural elements, or subsurface soil properties. When spectral parameters at such damping levels are required for certain applications, 5%-damped accelerations have traditionally been extracted from PSHA-based hazard curves and adjusted outside of the hazard integral using damping scaling factors (DSF) such as those from Newmark & Hall (1982). Recent advances in the development of more rigorous and comprehensive damping scaling models (e.g., Rezaeian et al., 2014; Rezaeian et al., 2021) have allowed for the modeling of means and standard deviations of DSFs as functions of earthquake source and path properties for crustal, intraslab, and subduction interface tectonic environments. These DSF models can be applied to ground motion model (GMM) estimates of Sa(T,5%) for a given earthquake rupture scenario to produce a corresponding mean and standard deviation Sa at a specified damping ratio β, Sa(T,β). In this study, the DSF models of Rezaeian et al. (2014) and Rezaeian et al. (2021) are implemented within the U.S. Geological Survey National Seismic Hazard Model (NSHM) PSHA framework to calculate probabilistic hazard curves for spectral accelerations at damping ratios from 0.5% to 30%. The DSF models are applied directly to the mean and standard deviation of Sa(T,5%) predictions from each GMM in the NSHM logic tree. Resulting hazard curves and uniform hazard and risk spectra for Sa(T,β) are presented for several geographic locations and compared with corresponding spectra estimated using current design practices by applying the same DSFs outside of the PSHA calculation. Key differences between the two methods for estimating Sa(T,β) are discussed, and potential strategies are presented for the implementation and usage of the hazard-consistent Sa(T,β) in building codes. Comparing the results to those from DSFs used in current design practices that are mainly based on Newmark & Hall (1982) is not explored in this study.

Conference Paper↗
USGS2025

Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20

We present an assessment of water supply across the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico covering water years 2010–20. Our analysis drew on two national hydrologic models, the National Hydrologic Model Precipitation-Runoff Modeling System and the Weather Research and Forecasting model hydrologic modeling system. Both models produced estimates of streamflow, evapotranspiration, soil moisture, snow water equivalent, and other hydrologic states and fluxes. The models were driven by the bias-adjusted 4-kilometer-resolution, long-term regional hydroclimate simulation over the conterminous United States dataset (CONUS404). We assessed spatial and temporal error distributions by comparing monthly simulations at the 12-digit hydrologic unit code and regional scale from both models against external benchmarking datasets. Results showed that average annual rainfall across the CONUS was 857 millimeters per year for the period of analysis, with water year 2012 the driest year (729 millimeters) and water year 2019 the wettest year (995 millimeters). Key interannual variability results included the following: (1) the California–Nevada hydrologic region had the highest variability in precipitation and snow accumulation, and (2) the Texas hydrologic region was among hydrologic regions with the highest variability in precipitation. We related interannual variability in precipitation to storage volumes in soil moisture, snow water equivalent, and lakes and reservoirs to highlight areas with little storage and large year-to-year variability in precipitation. These areas included the Southern High Plains, Central High Plains, Texas, Souris–Red–Rainy, Mississippi Embayment, and Midwest regions. Our analysis of groundwater-level data showed that several of these areas overlap aquifers where groundwater levels were considerably lower than historical averages, including the Colorado Plateaus aquifers, the Rio Grande aquifer system, and the Central and Southern regions of the High Plains aquifer. Many of these lowered groundwater levels are continuations of decades-long declines from overpumping that started well before the assessment period. The resulting water budgets and their analyses provide a high-resolution foundational assessment of the mean state and variability of the terrestrial hydrologic cycle across the CONUS and Alaska, Hawaii, and Puerto Rico to support a wide range of water resource management applications.

Professional Paper↗
USGS2025

Spatiotemporal variations in strain release and seismic rupture in multifault systems: An example from Panamint Valley, southeastern California

Geometrically complex, multifault ruptures have been observed in recent, damaging earthquakes in southeastern California, sparking renewed efforts to identify physical conditions that promote or inhibit fault discontinuity-spanning coseismic ruptures. The likelihood of ruptures propagating across fault discontinuities is thought to be partly controlled by fault geometries, rupture direction, and the history of strain release. However, these parameters vary in space and time over multiple earthquake cycles, making it difficult to forecast the likelihood that an earthquake on one fault will trigger rupture on a nearby fault. Here we use tectono-geomorphic mapping of a geometrically complex fault zone in Panamint Valley, southeastern California, to assess spatiotemporal variations of paleo-rupture patterns and geometries of fault discontinuities over multiple earthquake cycles. First, we identify ten generations of late Pleistocene to Holocene alluvium using geomorphic parameters and luminescence dating to constrain ages of alluvium and bracket late Holocene earthquake timing. Then, we quantify slip kinematics using high-resolution structure from motion digital surface models. We find the Panamint Valley transtensional relay (PVTR) hosted four late Holocene earthquakes, bracketed to ~5.8–3.4 ka, ~3.8–2.2 ka, ~2.4–0.6 ka, and ~0.64–0.16 ka, with ~0.6–1.1 m of slip per event, correlative to Mw ≈ 6.7–6.9 earthquakes. Additionally, we find similarities in earthquake timing on the Ash Hill, PVTR, and Panamint Valley faults and similarities in the slip magnitude and slip kinematics between the Ash Hill and PVTR faults, implying that the PVTR may co-rupture with nearby faults. Paleo-rupture patterns indicate that seismogenic strain transfer may occur through the PVTR, along different combinations of fault segments and jump distances, over multiple earthquake cycles. These data highlight the utility of tectono-geomorphic mapping in evaluating paleo-rupture patterns and suggest that the PVTR may act to propagate and/or arrest rupture between the Ash Hill and Panamint Valley faults.

California↗
USGS2025

Constraining large magnitude event source and path effects using ground motion simulations

The purpose of this study is to use ground motion simulations to investigate ways in which source and path effects for large magnitude events can be represented in non-ergodic GMMs. While we initially developed computation techniques using CyberShake simulations, the range of magnitudes and source-site combinations is not adequate to replicate what is observed empirically. We therefore designed a new ground motion simulation study, which includes earthquakes with a large range of magnitudes distributed uniformly on a fault plane, and sites covering a large range of rupture distances and azimuths. After running a large suite of simulations (M4-M7), we then develop a non-ergodic GMM with the simulation data. We find that the within-site residuals are dominated by the radiation pattern, rupture directivity, and slip patterns. Next, we modify an existing rupture directivity model to fit and remove the observed radiation pattern and rupture directivity from the residuals. We also minimize the contributions of slip patterns by averaging the within-site residuals among multiple source realizations. Finally, after removing the source effects from the within-site residuals, we compare the path effects computed with different magnitude groups using two approaches. The first approach only considers the small events that have the same shortest path to a site with the large events, while the second approach considers all small events on the fault plane. The results indicate that the path effects of large events cannot be satisfactorily approximated with that of small events using either approach.

Conference Paper↗
USGS2025

Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California

The area surrounding the Salinas Valley groundwater basin in Monterey and San Luis Obispo Counties of California is a highly productive agricultural area, contributes significantly to the local economy, and provides a substantial portion of vegetables and other agricultural commodities to the Nation. This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides significant volumes of agricultural products not just for California but the entire United States. Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface water and groundwater resources in the valley. This has resulted in water management challenges in the Salinas Valley that are predominantly related to distribution of water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. To deal with the distribution issue, historically water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface water supplies are insufficient. Availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand on groundwater and surface water resources throughout the Salinas Valley has resulted in undesirable effects of unsustainable water use, such as surface water depletion, groundwater level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface water and groundwater resources. To meet water demands and reduce undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and a variable climate. To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resource Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley Hydrogeologic system called the Salinas Valley System Model. The Salinas Valley Geologic Framework was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The Salinas Valley Watershed Model simulates the entire Salinas River watershed. Monthly surface water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.

EarthArXiv↗
USGS2025

Fiber-imaged supershear dynamics in the 2024 Mw 7 Mendocino Fault earthquake

Fault structure and rupture physics are deeply intertwined, and observations of this coupling are critical for understanding earthquake behavior. Rupture propagation is observable at fine scales using dense seismic networks. Fiber-optic sensing allows for long-term deployments of ultradense arrays that enable high-resolution measurements of infrequent, large earthquakes. We recorded the 2024 moment magnitude ( M w ) 7 Mendocino Fault earthquake with a nearby fiber-optic array and imaged its behavior with seismic beamforming. The rupture propagated to the east at subshear velocity; stagnated near the Mendocino Triple Junction, a zone of structural complexity; and subsequently transitioned to supershear velocity. The correlation between source physics and structure shows how lithospheric heterogeneity affects first-order characteristics of earthquake ruptures. Our results also demonstrate the potential for fiber-optic sensing to improve real-time estimation of key parameters for early warning.

California↗
USGS2024

Near-real-time earthquake-induced fatality estimation using crowdsourced data and few-shot large-language models

When a damaging earthquake occurs, immediate information about casualties (e.g., fatalities and injuries) is critical for time-sensitive decision-making by emergency response and aid agencies in the first hours and days. Systems such as the Prompt Assessment of Global Earthquakes for Response (PAGER) by the U.S. Geological Survey (USGS) were developed to provide a forecast of such impacts within about 30 min of any significant earthquake globally. However, existing disaster-induced human loss estimation systems often rely on early casualty reports manually retrieved from global traditional media, which are labor-intensive, time-consuming, and have significant time latencies. Recent approaches use keyword matching and topic modeling to identify human casualty-relevant information from social media but tend to be error-prone when dealing with complex semantics in multi-lingual text data and parsing dynamically changing and conflicting human death and injury numbers shared by various unvetted sources in social media platforms. In this work, we introduce an end-to-end framework to significantly improve the timeliness and accuracy of global earthquake-induced human loss forecasting using multi-lingual, crowdsourced social media. Our framework integrates (i) a hierarchical casualty extraction model built upon large language models, prompt design, and few-shot learning to retrieve quantitative human loss claims from social media, (ii) a physical constraint-aware, dynamic-truth discovery model that discovers the truthful human loss from massive noisy and potentially conflicting human loss claims, and (iii) a Bayesian updating loss projection model that dynamically updates the final loss estimation using discovered truths. We test the framework in real-time on a series of global earthquake events in 2021 and 2022 and show that our framework effectively automates the retrieval of casualty information faster but with comparable accuracy to those now retrieved manually by the USGS. The code associated with this work is made available at: https://github.com/SusuXu-s-Lab/Hierarchical-Earthquake-Casualty-Information-Retrieval

International Journal of Disaster Risk Reduction↗
USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗
USGS2025

Overcoming the data limitations in landslide susceptibility modelling

Data-driven models widely used for assessing landslide susceptibility are severely limited by the landslide and environmental data needed to create them. They rely on inventories of past landslide locations, which are difficult to collect and often nonrepresentative. Furthermore, susceptibility maps are most needed in regions without the means to assemble an inventory. To overcome these challenges, we develop a method for assessing shallow landslide susceptibility based on a probabilistic morphometric analysis of the landscape’s topography, rather than the characteristics of landslides. The model assumes that hillslopes with higher relief and gradient compared to the surrounding landscape are more prone to landslides. We demonstrate the superior performance of this approach over contrasting data-driven models across the northwestern United States. As our morphometric model only requires elevation data, it overcomes the major limitations of data-driven models and facilitates the creation of effective susceptibility models in areas where it was previously unfeasible.

Oregon, Washington↗
USGS2026

Navigating uncertainty and competing objectives: Spring chinook salmon recovery in the upper Willamette river

Globally, anadromous fish populations are threatened with extinction due to multiple factors, including river impoundments that block migration, widespread alteration of physical habitat, temperature, and flow regimes, commercial and recreational harvest, changes in biological communities, and long-term climate trends. In this synthesis, we describe how physical and biological factors, policy and law, and public resource allocation affect management of spring-run Chinook Salmon ( Oncorhynchus tshawytscha ) in the Upper Willamette River (UWR), Oregon, USA. Efforts to restore salmon populations often involve trade-offs, for example, water management decisions must account for flood control, agricultural and municipal water use, and management of other species. UWR Chinook Salmon recovery efforts are also governed by multiple laws, policies, and action agencies that in some cases have incongruent objectives. Competing and conflicting objectives, combined with uncertainty regarding the outcomes of proposed management actions, create significant challenges for decision makers. Resource limitations, regulatory constraints, and incongruent objectives have created challenges for managers in the UWR, but opportunities exist for improved adaptive management and collaboration, which could build trust and engagement among stakeholders and ultimately support the successful implementation of decision tools. A suite of decision support tools that have been used in the Willamette River basin and elsewhere across the range of Pacific salmon have the potential to enhance decision processes. These tools can be effective when decision makers and stakeholders commit to long-term, collaborative utilization of the tools for decision making, and when available resources and regulatory environments are conducive to implementation and adaptive refinement of both the decision-support tools and management plans. The general biological and institutional principles discussed for UWR Chinook Salmon in this work apply more generally to populations of anadromous fishes across their range, especially to populations in highly regulated river systems.

Oregon↗
USGS2025

Divide and conquer: Separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process – the probability of the existence of a seismic phase (detection probability) and the probability of correctly identifying the phase arrival time (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labeled phase arrival time, and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks) and the height of the peaks are taken as “probability” of the picks. Here, we show that this “probability” represents neither the detection nor the timing probabilty because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multi-class classifier to obtain a probability mass function to address the timing probability. This new approach makes the deep learning-based phase picking process more interpretable and gives us options to logically control seismic monitoring workflows.

Geophysical Journal International↗
USGS2025

Simulated hydrologic responses to proposed wastewater-returnflow scenarios in Falmouth, Massachusetts

The Cape Cod aquifer is the sole source of drinking water for communities on Cape Cod, Massachusetts, including the Town of Falmouth, where the aquifer is currently threatened by contamination from septic-system-derived nitrogen. To address this problem, the Town is proposing to sewer areas of Falmouth, treat the wastewater at the Town’s Main Wastewater Treatment Facility (a nitrogen removing/tertiary treatment facility), and discharge the treated wastewater to an ocean outfall pipe in Nantucket Sound. The U.S. Geological Survey, in cooperation with the Town of Falmouth, updated a three-dimensional steady-state groundwater flow model to represent current (defined as 2019–23) average hydrologic conditions and to simulate the long-term average freshwater hydrologic response to two wastewater-return-flow scenarios. Scenario 1 involves the sewering of all properties south of Route 28 in Falmouth, which approximates the Town’s possible sewer expansion over the next 20–30 years. Scenario 2 involves sewering of all properties in Falmouth to demonstrate the maximum potential effect of sewering on the aquifer. Overall, the simulated hydrologic response of water-table altitudes and streamflow in both scenarios was relatively small compared to fluctuations from natural recharge. In scenario 1, the water-table altitude decreased by about 0.1 feet south of Route 28, where the conversion to municipal sewers removed wastewater-return flow from onsite septic systems. The water-table altitude decreased by about 0.1–0.2 feet over a larger area in Falmouth under town-wide sewering in scenario 2. The greatest decrease in water-table altitude in both scenarios occurred near the Main Wastewater Treatment Facility, with a decrease of about 1.1 feet in scenario 1 and about 1.3 feet in scenario 2. Simulated decreases in streamflow also were estimated for six selected streams in Falmouth and Mashpee. In both scenarios, the largest simulated decreases in streamflow were at the Coonamessett River, which is the closest stream to the Main Wastewater Treatment Facility. In scenario 1, the average annual decrease in flow at the Coonamessett River was 0.1 cubic feet per second, a 1.1 percent decrease from current (2019–23) conditions. In scenario 2, streamflow at the Coonamessett River decreased by 0.6 cubic feet per second, a 5.4 percent decrease from current (2019–23) conditions.

Massachusetts↗
USGS2025

Scoping decision-maker needs and science availability to support regional natural capital accounting in the U.S. Colorado River Basin

Natural capital accounting has the potential to yield important policy insights at multiple scales, but there remains a disconnect between regional-scale natural capital accounts and their use for informing policy. In this paper, we propose a roadmap that could lead to the creation of policy-relevant regional accounts, with steps split across an initial scoping phase and a subsequent development phase. We demonstrate the scoping steps in action with an application to the Colorado River Basin (“Basin”), a large watershed in the southwestern United States (U.S.) that has faced aridification and substantial high-profile tradeoffs around the use of its water and other natural resources. Drawing on prior U.S. Geological Survey science co-production efforts, we conducted a series of eight discussion sessions with 41 scientists and science representatives whose work is relevant to Basin water, riparian and riverine ecosystems, upland ecosystems and energy and minerals. We summarise participants' thoughts on key topics and economic linkages, their insights and questions of interest and their recommendations on existing scientific data sources and gaps. We evaluate the suitability of the available data for construction of System of Environmental-Economic Accounting (SEEA) Central Framework and SEEA Ecosystem Accounting accounts, including those for land, water, forests, energy and minerals and ecosystems (covering extent, condition and ecosystem services). We present a series of lessons learned during the scoping phase, as well as lessons that could be relevant for future practitioners engaging in the development phase. The information can help guide the development of timely and relevant regional-scale environmental-economic accounts in the U.S. and beyond.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2024

Identifying transportation data and system needs for a Federal lands transportation data platform

Executive Summary Modern transportation and land-use planning efforts include information from many sources to address topics such as safety, efficiency, commercial, and social needs. This wide breadth of topics provides opportunities for collaboration and development of common tools for diverse users. In many cases, different information systems provide the spatial data and geographic content necessary for transportation and land-use planners to consider multiple lines of evidence. The Federal Highway Administration Office of Federal Lands Highway (FLH) and Federal Land Management Agency partners use detailed spatial and quantitative data to inform transportation decisions. However, logistic challenges to data sharing exist because data are often managed by separate agencies; data-exchange frameworks and interagency data agreements are insufficient; and consistency from aggregated data requires maintenance, coordination, and supporting infrastructure. The FLH and U.S. Geological Survey collaboratively examined (1) use and availability of spatial data for transportation planning and (2) a possible mechanism to use more shared and consistent data in a common planning environment. The goals of this collaborative effort were to describe data needs from the perspective of planners and to identify opportunities for shared data resources. Results presented here focus on two workshops and a subsequent investigation of data and tools available from partner agencies. The objectives of this report are to (1) describe information used in transportation planning with geographic data; (2) identify spatially explicit data that inform transportation plans and could be shared among all partners; and (3) describe current platforms, planning and administrative opportunities, and potential barriers to developing an integrated planning tool. Key information and data needs were identified in three major classes: system, user, and influential factors. System data are parts of the transportation network and information about the condition of individual segments and the network. User data provide details about the function of the system and insights into potential needs; for example, user trips between source and destinations inform road and network demands that can lead to congestion and safety issues (in the future, user data might also include scenarios and projections based on land-use plans). Influential data represent social and environmental factors that influence transit demands and network conditions. These factors could be popular locations or seasonal events that influence demand and congestion; wildlife habitat or migration intersections that affect safety and management priorities; or geologic features that influence hazards, maintenance, and safety. Responses described here provide specific information for web-tool design and give a framework for interagency communication and cooperation to address specific information needs for integrated planning. Existing web-mapping and web-services, and the data that inform them, are also described. Commonly, these data are created and published by one agency, and the core users are outside of that agency; for example, threatened species distributions are published by the U.S. Fish and Wildlife Service for consideration by planners in advance of National Environmental Policy Act (42 U.S.C. 4321 et seq.) evaluation. This report is provided to inform FLH leaders and Federal Land Management Agency partners by articulating user needs and requirements for integrated planning tool(s). Programmers creating a secure web-based data-sharing platform (with data-viewing, -analysis and -download functions) can use the information presented here to organize data and user interfaces. This integrated perspective can help FLH and Federal Land Management Agency partners develop transportation networks that better serve the needs of people in local communities and across States and the Nation.

Open-File Report↗
USGS2026

Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2017–22

The Cedar River alluvial aquifer is the source of drinking water in Cedar Rapids, Iowa. Production wells are completed in the alluvial aquifer approximately 40 to 80 feet below land surface. The City of Cedar Rapids and the U.S. Geological Survey have studied the groundwater-flow system and water quality of the aquifer in the vicinity of Cedar Rapids since 1992. Results of these studies documented hydrologic conditions, water quality, and geochemistry of the alluvial aquifer and interactions with the Cedar River. Water-quality samples were collected for studies involving well field monitoring, trends, source-water protection, groundwater geochemistry, surface-water–groundwater interaction, and pesticides in groundwater and surface water. Water quality was analyzed for dissolved major ions (boron, bromide, calcium, chloride, fluoride, iron, magnesium, manganese, potassium, silica, sodium, sulfate, and total dissolved solids), dissolved nutrients (ammonia as nitrogen, ammonia plus organic nitrogen as nitrogen, nitrite plus nitrate as nitrogen, nitrite as nitrogen, orthophosphate as phosphorus, and phosphorus), dissolved organic carbon, and selected pesticides. Physical characteristics (alkalinity, dissolved oxygen, pH, specific conductance, and water temperature) were measured on site and recorded for each water sample collected. This report presents the results of routine water-quality data-collection activities from October 2017 through September 2022. Methods of data collection, quality assurance, water-quality analyses, and statistical procedures are presented. Data include the results of water-quality analyses from quarterly sampling from monitoring wells, production wells, two water treatment plants, and the Cedar River at Blairs Ferry Road at Palo, Iowa, streamgage (U.S. Geological Survey station number 05464420), as well as monthly nutrient sampling from the Cedar River and Morgan Creek near Covington, Iowa, streamgage (U.S. Geological Survey station number 05464475).

Iowa↗