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Using probability difference to compare streamflow information of alternatives for efficient operation of monitoring networks

Efficient operation of streamflow monitoring networks requires investments in technology and labor that provide the greatest benefits from available resources. Economic analyses comparing the costs and benefits from different types of alternatives for monitoring have not been practical to implement. Streamflow information provides a generic measure of benefits that can be incorporated into operational decisions as an objective for monitoring networks. A methodology for comparing how accuracy, monitoring period, and monitoring instead of modeling affects streamflow information is developed from information-theoretic approaches for network design but contributes three novel features: (1) a probability-difference model for conditional probability of monotonically paired variables, (2) explicit discounting of unverified information that may exceed the accuracy of streamflow records, and (3) run analysis to account for non-stationarity in streamflow probabilities. Application of the methodology to the U.S. Geological Survey streamflow monitoring network indicates the value of monitoring period to reduce the uncertainty of streamflow probabilities and, thus, increase streamflow information. The methodology has important limitations, particularly for sites with non-perennial streamflow, but demonstrates that probability difference could be used to evaluate operational alternatives to increase the efficiency of monitoring networks.

PLOS Water

REDPy: A Python tool for automated repeating earthquake detection and visualization

Detecting and cataloging seismic events are among the most fundamental tasks in seismology. Many standardized tools for these tasks exist, including the open‐source package repeating earthquake detector in Python (REDPy). REDPy generates an organized catalog of seismic events from continuous waveform data, in which events are automatically separated into groups (“families”) by their waveform similarity through cross‐correlation. REDPy also automatically generates various outputs that allow a user to visualize important trends in the catalog, which may be used in real time or in retrospective analyses to allow rapid identification of interesting features. The code was designed for near‐real‐time volcano monitoring but is applicable across a broad range of use cases in seismology and seismoacoustics. In this article, the utility and performance of REDPy are demonstrated on two highly seismogenic volcanic eruption sequences: the onset of the dome‐building eruption of Mount St. Helens, Washington, from 2004 to 2005, and the entirety of the summit caldera collapse sequence of Kīlauea, Hawai‘i, in 2018. This article is meant to be a companion to the documentation of the code; in addition to detailing the basic required inputs, script functionality, and resulting outputs, the reasonings behind several important design decisions are also discussed.

Seismological Research Letters

Developments in African industrial minerals for renewable energy

Introduction Africa is emerging as a leading source for minerals used in the manufacture of batteries for electric vehicles and in other renewable energy applications. New graphite, lithium, and rare-earth mines have or could be opened in African countries from 2017 through 2026. Estimates of production capacities for graphite, lithium, and rare-earth mines for 2023 and beyond are based upon supply-side assumptions, such as announced plans for new capacity construction and bankable feasibility studies, as well as projected trends that could affect current producing facilities in 2023 and planned new facilities projected to come online by 2026. Forward-looking information, including estimates of future production capacities, graphite flake distributions, and timing of the start of operations, are subject to risk factors and uncertainties that could cause actual events or results to differ significantly from expected outcomes. Projects listed in this report are presented as an indication of industry plans and are not a U.S. Geological Survey (USGS) prediction of what will take place. Only projects with planned startup dates are included in this report; ther graphite, lithium, and rare-earth projects in Africa without startup dates were known to be in various stages of development but are not included in this fact sheet.

Fact Sheet

Reconnaissance of potential alternate water supply sources for the City of Gary, West Virginia

Seven potential sources of water, consisting of free-flowing discharge from abandoned coal mines at six locations and one abandoned flooded underground coal mine air shaft, were sampled for chemical analysis to assess the quality of the groundwater emanating from the seven mine sources. The six free-flowing mine discharge sources were also assessed for discharge by current-meter measurements on two separate occasions. The U.S. Geological Survey assessed these seven sources to provide information to the City of Gary, West Virginia (W. Va.), and the City of Gary’s consulting engineer with groundwater-quality and flow data to allow them to assess the seven sites as potential alternate sources of water for the City of Gary to augment its existing supply. For the six sites where discharge could be measured, discharge ranged from a minimum of 0.082 cubic feet per second (ft 3 /s) to a maximum of 3.685 ft 3 /s. Of the six sites measured, only two, Harmon Branch at Thorpe, W. Va. (USGS site 372201081303501) and the abandoned public-supply water wells near Havaco, W. Va. (USGS site 372358081344601), had discharge in excess of 1.00 ft 3 /s. Discharge from the abandoned public supply wells was 3.685 ft 3 /s on September 20, 2023, and 2.888 ft 3 /s on October 16, 2023, and discharge from Harmon Branch at Thorpe, W. Va., was 1.049 ft 3 /s on September 22, 2023, and 1.038 ft 3 /s on October 17, 2023. Discharge in the abandoned underground mine air shaft (USGS site 372224081340901) could not be assessed, but the air shaft drains an abandoned mine that likely contains water stored in approximately 1.7 square miles (mi 2 ) of abandoned underground coal mines in the Pocahontas No. 3 coal seam, and possibly an additional 0.9 mi 2 of leakage from the overlying Pocahontas No. 4 coal seam. Discharge for the six sites measured for the study was measured during a period between September 20 and October 18, 2023, and corresponded to the 12th to the 15th percentile of flow-duration statistics for the Tug Fork downstream of Elkhorn Creek at Welch, W. Va. streamgage (USGS site 03212750). Water-quality data for the seven sites sampled overall were acceptable with respect to drinking water standards. Of the 203 constituents analyzed, only a few failed to meet applicable U.S. Environmental Protection Agency (EPA) drinking water standards. Iron exceeded the 300 micrograms per liter (μg/L) secondary maximum contaminant level (SMCL) at only 1 of the 7 sites (14.3 percent) sampled. Iron concentrations ranged from a minimum of less than (<) 5.00 μg/L to a maximum of 724 μg/L with a median concentration of 7.62 μg/L. Manganese exceeded the 50.0 μg/L SMCL at 2 of the 7 sites (28.6 percent) sampled. Manganese concentrations ranged from a minimum of 1.93 μg/L to a maximum of 271 μg/L with a median concentration of 4.03 μg/L. No sites sampled exceeded the arsenic maximum contaminant level (MCL) of 10 μg/L. Arsenic concentrations ranged from a minimum of <0.100 μg/L to a maximum of 2.35 μg/L with a median arsenic concentration of 0.200 μg/L. None of the seven sites sampled for selenium for this study exceeded the EPA MCL of 50.0 μg/L. Selenium concentrations ranged from a minimum of <0.050 μg/L to a maximum of 5.26 μg/L with a median concentration of 3.21 μg/L. All seven sites were sampled for volatile organic compounds (VOCs), semivolatile organic compounds (SVOCs), and polychlorinated biphenyls (PCBs), but most had concentrations below the detection limit. Of the 10 PCB compounds analyzed for the seven sites sampled, none contained detectable concentrations of PCBs or Aroclor compounds. Of the 44 SVOCs analyzed at each of the seven sites sampled, only 1 SVOC, acenaphthene, was detected, at a concentration of 0.02 μg/L. Of the 96 VOCs analyzed, from each of the seven sites sampled, only two were found at detectable concentrations. Trichloromethane was detected only at 1 of the 7 (14.3 percent) sites sampled at a concentration of 0.027 μg/L, and benzene was detected at the same site and 3 additional sites (4 of the 7 sites or 57.1 percent of the sites sampled) at concentrations of 0.028, 0.029, 0.021, and 0.035 μg/L, but none exceeded the EPA MCL for benzene of 5.00 μg/L. Total coliform bacteria are ubiquitous in the environment, and their presence only suggests the potential for contamination by near-surface processes. Escherichia coli ( E. coli ) bacteria are derived from either human or animal fecal material and can be an indicator of potential contamination by pathogenic bacteria or viruses. Total coliform bacteria were detected at all 7 sites sampled at concentrations ranging from 17.5 to greater than (>) 2,420 most probable number per 100 mL (MPN/100 mL) of sample, with a median total coliform concentration of 1,553 MPN/100 mL. Escherichia coli bacteria were detected at 4 of the 7 sites sampled at concentrations ranging from <1 to 11.9 MPN/100 mL, with a median E. coli concentration of 5.1 MPN/100 mL.

West Virginia

Satellite interferometry landslide detection and preliminary tsunamigenic plausibility assessment in Prince William Sound, southcentral Alaska

Regional mapping of actively deforming landslides, including measurements of landslide velocity, is integral for hazard assessments in paraglacial environments. These inventories are also critical for describing the potential impacts that the warming effects of climate change have on slope instability in mountainous and cryospheric terrain. The objective of this study is to identify slow-moving landslides in the Prince William Sound region, southcentral Alaska, United States, which has had rapid deglaciation since the mid-1800s, and assess their tsunamigenic plausibility. We use an automated time series persistent scatterer interferometric synthetic aperture radar processing method with 7 years of Sentinel-1 data (2016–22) to identify 43 slow-moving slopes with average velocities ranging from approximately 0.2 to 21 millimeters per year. Landslide presence is confirmed using aerial imagery and previous landslide inventory records. We assess the tsunamigenic plausibility of the landslides using empirically derived estimates of landslide mobility based on modeled landslide volumes. Of the identified landslides, our preliminary analysis suggests that 11 have tsunamigenic potential if they were to fail rapidly and catastrophically. Although our estimate of tsunamigenic plausibility is preliminary and can be refined with additional observations and analyses, it can be used to prioritize ongoing and future hazard assessment, surveillance, and research efforts.

Alaska

CRESCENT earthquake dynamic rupture, earthquake cycle, and tsunami code verification platform

Physics-based simulations are critical for understanding natural hazards. The increasing complexity of numerical codes requires benchmark exercises to verify that different computational methods yield consistent results when solving the same governing equations. Here, we present an open-access web platform designed for the verification of earthquake dynamic rupture, seismic cycle, and tsunami simulations. The platform architecture utilizes a modular, serverless backend on Amazon Web Services (AWS) to provide scalable file processing and visualization. A lightweight static web application provides a secure interface for uploading and managing results, while the browser-based data visualization enables interactive analysis of time series and surface grid data. By using structured JavaScript Object Notation (JSON) text files to define benchmark structures, the system remains fully extensible, allowing the addition of new scenarios without modifying the underlying software logic. The platform hosts the "The Tsunami Problem Versions" (TTPV) 1 & 2, two benchmarks for 3D fully coupled earthquake dynamic rupture and tsunami generation, and provides a framework for earthquake cycle models. This community resource aims to build trust in numerical simulations and facilitate long-term collaborative code verification as modeling software continues to evolve.

Seismica

Aboveground carbon stocks across a hydrological gradient: Ghost forests to non-tidal freshwater forested wetlands

Upper estuarine forested wetlands (UEFWs) play an important role in the sequestration of atmospheric carbon (C), which is facilitated by their position at the boundary of terrestrial and maritime environments but threatened by sea level rise. This study assessed the change in aboveground C stocks along the estuarine–riverine hydrogeomorphic gradient spanning salt-impacted freshwater tidal forested wetlands to freshwater forested wetlands in seasonally tidal and nontidal landscape positions. Standing stocks of C in forested wetlands were measured along two major coastal river systems, the Winyah Bay in South Carolina and the Savannah River in Georgia (USA), replicating and expanding a previous study to allow the assessment of change over time. Aboveground C stocks on these systems averaged 172.9 Mg C ha −1 , comparable to those found in UEFWs across the globe and distinct from the terrestrial forested ecosystems they are often considered to be a part of during large-scale C inventory efforts. Groundwater salinity conditions as low as 1.3 ppt were observed in conjunction with losses of aboveground C. When viewed in context alongside expected sea level rise and corresponding saltwater intrusion estimates, these data suggest a marked decrease in aboveground C stocks in forested wetlands situated in and around tidal estuaries.

Georgia, South Carolina

Compositional and structural mapping of Northwest Africa 15507 angrite

Angrite meteorites represent interesting sampling of planetary crustal environments. Quench-textured angrites with strong crystal zoning originated from the shallow surface region, with evidence of reducing conditions during solidification. Plutonic angrites have more coarse-grained igneous and metamorphic textures with comparatively less zoning and are interpreted as having equilibrated at greater depth. Plutonic angrites contain the minerals magnetite Fe 3 O 4 comprised of Fe 2+ and Fe 3+ , and rhönite, where Fe 3+ is required by inspection of mineral stoichiometry. NWA 15507 is a plutonic angrite with a microgabbroic texture (mean grainsize ∼1.4 mm) composed of zoned Al-Ti-augite, Ca-bearing olivine, anorthite, with accessory kirschsteinite, rhönite, hercynite, low-Ni kamacite, merrillite, Ti-free magnetite and troilite [ 1 ]. Rhönite analyzed by electron-probe microanalysis (EPMA) has the formula Ca 2.04 (Mg 0.32 Fe 2+ 4.25 Fe 3+ 0.47 Ti 0.33 Al 0.61 )(Si 3.74 Al 2.26 )O 20 , where Fe 3+ was estimated by stoichiometric analysis. During preliminary cathodoluminescence (CL) analysis, complex subgrain and oscillatory zoning was observed in the anorthite. In this study we use a combined approach of electron probe microanalysis (EPMA), cathodoluminescence (CL), electron-backscatter diffraction (EBSD), and laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) to further investigate the anorthite and distribution of Fe 3+ in NWA 15507.

Microscopy and Microanalysis

Groundwater tracing used to delineate recharge areas and map karst groundwater pathways for subterranean streams at Oregon Caves National Monument and Preserve

Oregon Caves National Monument and Preserve in southwestern Oregon is a 4,554-​acre area managed by the National Park Service that is home to several cave systems, including Oregon Caves, which is the longest cave in Oregon, with 3.03 miles of mapped passages. Because of the interconnected nature of karst hydrologic systems, it is critical to understand the areas that can influence water quality and quantity in karst environments. Toward this goal, dye tracing was conducted by the U.S. Geological Survey from 2021 to 2024 to better understand the pathways that karst groundwater follows at Oregon Caves National Monument and Preserve and to delineate recharge areas for two caves, Oregon Caves and Cave Next Door. During the project, eight dye injections were conducted, delineating a 0.51-​square-​mile recharge area for Oregon Caves and a 0.69-​square-​mile recharge area for Cave Next Door. Additionally, the study helped to identify three resurgences associated with Oregon Caves that were previously unknown and showed that the recharge areas for the two caves were distinct from one another. The dye traces also illuminated some unique recharge characteristics of the karst at Oregon Caves, including a high variance in karst groundwater velocities, retention within the karst aquifers, and a significant diffuse-​flow component.

Oregon

Total uncertainty quantification in inverse solutions with deep learning surrogate models

We propose an approximate Bayesian method for quantifying the total uncertainty in inverse partial differential equation (PDE) solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations, PDE, and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then, we randomize the MAP objective function and obtain samples of the posterior distribution by minimizing different realizations of the objective function. We test the proposed framework by comparing it with the iterative ensemble smoother and deep ensembling methods for a nonlinear diffusion equation with an unknown space-dependent diffusion coefficient. Among other applications, this equation describes the flow of groundwater in an unconfined aquifer. Depending on the training dataset and ensemble sizes, the proposed method provides similar or more descriptive posteriors of the parameters and states than the iterative ensemble smoother method. Deep ensembling underestimates uncertainty and provides less-informative posteriors than the other two methods. Our results show that, despite inherent uncertainty, surrogate models can be used for parameter and state estimation as an alternative to the inverse methods relying on (more accurate) numerical PDE solvers.

Journal of Computational Physics

Uncertainty in ground-motion-to-intensity conversions significantly affects earthquake early warning alert regions

We examine how the choice of ground‐motion‐to‐intensity conversion equations (GMICEs) in earthquake early warning (EEW) systems affects resulting alert regions. We find that existing GMICEs can underestimate observed shaking at short rupture distances or overestimate the extent of low‐intensity shaking. Updated GMICEs that remove these biases would improve the accuracy of alert regions for the ShakeAlert EEW system for the West Coast of the United States. ShakeAlert uses ground‐motion prediction equations (GMPEs), which calculate spatial distributions of peak ground acceleration (PGA) and peak ground velocity (PGV) from earthquake source estimates, combined with GMICEs to translate GMPE output into modified Mercalli intensity (MMI). We find significant epistemic uncertainty in alert distances; near‐source MMI estimates from different GMICEs can differ by over 1 MMI unit, and MMI extents used for public EEW alerts can differ by hundreds of kilometers for larger magnitude earthquakes ( M ∼6.5+). We use a catalog of “Did You Feel It?” shaking reports to evaluate how well GMICEs predict observed shaking. Our preferred GMICE is the one that computes MMI using PGV for high intensities and transitions to using PGA for nondamaging intensities. These results motivate updating GMICE relationships more generally, including in ShakeMap applications.

The Seismic Record

Morphodynamics of snow barchans at Concordia Station, Antarctica

Barchans are crescent-shaped dunes that form and migrate under unimodal wind regimes in areas of low sediment availability. While sand barchan morphodynamics has been extensively studied, snow barchans remain poorly documented. Here, using hourly time-series images taken near Concordia Station, Antarctica, we measure the sizes (lengths 0.3 m to 13 m, widths 0.4 m to 7.5 m) and migration rates (0.13 m h −1 to 3.5 m h −1 ) of 44 populations of snow barchans during 2017–2022. We compare this dataset with established height–velocity and length-width relationships for sand barchans in both air and water. Our results show that snow barchans follow the same scaling as sand barchans, allowing us to estimate a characteristic sintering (bonding of snow particles) time of about one day. This sintering process limits the size of snow barchans when active, reduces their aspect ratios, and, once wind falls below the transport threshold, explains their preservation over a few years. During wind events, migrating barchans are too small to maintain their shape and orientation, making them highly responsive to fluctuations in wind direction. Thus, studying snow barchans improves understanding of an elementary bedform encountered in multiple environments and also of the surface properties of snow on different timescales, offering insights into snow accumulation and wind-blown snow in ice cores.

Geomorphica

A diatom-based quantitative sea-ice proxy for the Bering and Chukchi seas

Sea ice affects Earth's climate system on both regional and global scales. Its incorporation into climate can be used to achieve more accurate predictions of future climate. However, instrumental records of sea-ice concentration do not extend earlier than 1978. In an effort to extend this record, we constructed a proxy using the generalized additive model based on relative abundances of five easy-to-identify diatom species found in sediment samples across the Bering and Chukchi seas. Here we present the first quantitative diatom-based sea-ice proxy developed for Beringia. The developed proxy has been applied to two sediment cores in the Bering Sea ranging from 0 to 25.7 ka (HLY0204 51JPC) and 369 to 430 ka (IODP Exp 323 Site U1345) and one in the Chukchi Sea ranging from 2.7 to 10 ka (HLY0204 24JPC). The obtained reconstructions of sea-ice concentrations are similar, but not identical to previously published qualitative and nearby records based on other proxies. Because our results are quantitative, they can be incorporated into regional climate models. The proxy is publicly available as an R Shiny application (app) and can be applied to any diatom count from marine sediments in the region.

Bering Sea, Chukchi Sea

Uncertainty and spatial correlation in station measurements for mb magnitude estimation

The body‐wave magnitude (⁠⁠) is a long‐standing network‐averaged, amplitude‐based magnitude used to estimate the magnitude of seismic sources from teleseismic observations. The U.S. Geological Survey National Earthquake Information Center (NEIC) relies on in its global real‐time earthquake monitoring mission. Although waveform modeling‐based moment magnitudes are the modern standard to characterize earthquake size, is important because (1) in many cases, waveform modeling is not possible (e.g., low signal‐to‐noise events), (2) is applicable over a broad range of magnitudes, ∼M 4–7, and (3) there is a many decades‐long history of estimating magnitudes. We use the NEIC Preliminary Determination of Epicenters earthquake catalog to investigate the uncertainty in NEIC station measurements. We show that measurements are spatially correlated, which can bias event ⁠, and we describe an empirical relation between this spatial correlation and station‐to‐station distance. We further describe an approach to mitigate bias from the spatial correlation. Accounting for the spatial covariance of observations can change the event from −0.15 to 0.07 units (10th to 90th percentile) for smaller events (⁠⁠). These smaller events have the largest standard deviations ranging from 0.05 to 0.15 units (10th to 90th percentile).

The Seismic Record

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation

Reconnaissance of the occurrence of agricultural chemicals in ground water in Haywood, Lake, Obion and Shelby Counties, Tennessee

Data on the occurrence of agricultural chemicals in ground wafer in Tennessee are sparse. The surficial alluvial aquifer is an important source of domestic water supply in West Tennessee, and potentially is subject fo contamination from the application of agricultural chemicals in the area. Nineteen shallow wells completed in the alluvial aquifers in areas of high density agricultural use were sampled in the winter and again in the summer of 1988 to ascertain the occurrence of agricultural chemical in ground water. Although no triazine herbicides or organophosphorus insecticides were detected in any of the wells sampled, elevated nitrite plus nitrate (as nitrogen) concentrations were detected. Results from the winter sampling period indicate a range of nitrite plus nitrate (as nitrogen) concentrations of less than 0.1 to 7.8 milligrams per liter with a median concentration of 2.6 milligrams per liter. Results from the summer sampling period indicate a range of nitrite plus nitrate (as nitrogen) concentrations of less than 0.1 to 8.9 milligrams per liter, median, 2.5 milligrams per liter. The highest concentrations occurred in the shallowest wells, and, in one instance, in a shallow well near a heavily irrigated field.

Tennessee

Transmissivity and water quality of water-producing zones in the intermediate aquifer system, Sarasota County, Florida

The intermediate aquifer system is an important water source in Sarasota County, Florida, because the quality of water in it is usually better than that in the underlying Upper Floridan aquifer. The intermediate aquifer system consists of a group of up to three water-producing zones separated by less-permeable units that restrict the vertical movement of ground water between zones. The diverse lithology, that makes up the intermediate aquifer system, reflects the variety of depositional environments that occurred during the late Oligocene and Miocene epochs. Slight changes in the depositional environment resulted in aquifer heterogeneity, creating both localized connection between water-producing zones and abrupt culmination of water-producing zones that are not well documented. Aquifer heterogeneity results in vertical and areal variability in hydraulic and water-quality properties. The uppermost water-producing zone is designated producing zone 1 but is not extensively used because of its limited production capability and limited areal extent. The second water-producing zone is designated producing zone 2, and most of the domestic- and irrigation-supply wells in the area are open to this zone. Additionally, producing zone 2 is utilized for public supply in southern coastal areas of Sarasota County. Producing zone 3 is the lowermost and most productive water-producing zone in the intermediate aquifer system. Public-supply well fields serving the cities of Sarasota and Venice, as well as the Plantation and Mabry Carlton Reserve well fields, utilize producing zone 3. Heads within the intermediate aquifer system generally increase with aquifer depth. However, localized head-gradient reversals occur in the study area, coinciding with sites of intense ground-water withdrawals. Heads in producing zones 1, 2, and 3 range from 1 to 23, 0.2 to 34, and 7 to 42 feet above sea level, respectively. Generally, an upward head gradient exists between producing zones 3 and 2. However, an upward head gradient between producing zones 2 and 1 does not consistently occur throughout Sarasota County, probably the result of greater ground-water withdrawals from producing zone 2 than from producing zone 1. The transmissivity of the intermediate aquifer system is spatially variable. Specific-capacity data from selected wells penetrating producing zones 2 and 3, were used to estimate transmissivity. Estimated transmissivity values for producing zones 2 and 3 range from about 100 to 26,000 feet squared per day and from about 1,300 to 6,200 feet squared per day, respectively. Because the capacity of specific water-producing zones is highly variable from site to site, estimating the performance of a specific water-producing zone as a water resource is difficult. Water samples collected during the study were analyzed for major-ion concentrations. Generally, bicarbonate type water from rock interaction occurs in northern Sarasota County; enriched calcium-magnesium-sulfate type water from deeper aquifers occurs in central Sarasota County; and sodium-chloride type water from saltwater mixing occurs in southern Sarasota County. In some areas of northern Sarasota County, the major-ion concentrations in water are lower in producing zone 2 than in producing zone 1. Major-ion concentrations in water are higher in producing zone 3 throughout the study area. A major objective of the study was to evaluate hydraulic and water-quality data to determine distinctions that could be used to characterize a particular producing zone. However, data indicate that both hydraulic and water-quality properties are highly variable within and between zones, and are more related to the degree of connection between and areal extent of water-producing zones than to aquifer depth and distance from the coast.

Florida

Road salt collection and redistribution at an urban rain garden on sandy soil, Gary, Indiana

Rain gardens installed as green infrastructure to divert storm runoff from entering combined sewers also collect dissolved constituents and particulates. An urban rain garden in northwestern Indiana, USA, was continuously monitored from November 2019 to May 2021 to evaluate the fate of dissolved constituents entering the rain garden in runoff. Physical and chemical properties of soils in the rain garden were also monitored, along with underlying groundwater. Linear regression models relating specific conductance to chloride concentration indicated that the 0.0371-ha (3998 square feet) rain garden collected approximately 1490 kg (3285 pounds) of road salt from the surrounding 0.2228 ha (24,500 square feet) of impervious surfaces. Soils and groundwater were seasonally affected by road salt application but carryover from year to year was not indicated. Rain garden soil permeability (5.20 × 10 −5 to 9.72 × 10 −5 m/s) remained unchanged during the study period and soil organic carbon generally increased under native vegetation. The results suggest that a rain garden built on sandy soil can divert substantial quantities of runoff and dissolved constituents from combined sewers; however, chloride is transported to sub-infrastructure groundwater that eventually discharges to adjacent waterways with concentrations lower than those observed in runoff.

Indiana