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Effects of climate on temporal variability in streamflow and salinity in the Upper Colorado River Basin
Study Region The Upper Colorado River Basin, a critical water source for more than 40 million people in the western United States. Study Focus Potential decreasing streamflow and elevated salinity concentrations threaten this resource. Climate variability has a large and well-studied effect on streamflow in the basin; however, the effect on salinity loading is less understood. This study investigates how snowpack dynamics, precipitation volume, and air temperature affect both streamflow and salinity at the basin scale from water years 1986–2021. New Hydrological Insights for the Region Climate variables explained 54 % of streamflow variability and 40 % of salinity variability across the basin. Both streamflow and salinity yields have declined in response to climate variability, but their response occurs on different timescales. Streamflow is more sensitive to snowpack, whereas salinity yields respond more strongly to antecedent precipitation. The delayed response of salinity yields may obscure the effects of both climate variability and salinity control measures. Residual analysis identified subbasins where the climate-salinity relation deviated from basin-wide patterns, suggesting that possible anthropogenic or other watershed processes may influence salinity loading in these areas. These novel findings underscore the importance of accounting for climate variability when evaluating long-term trends in streamflow and salinity.
Rethinking hyporheic flow and transient storage to advance understanding of stream-catchment connections
Although surface water and groundwater are increasingly referred to as one resource, there remain environmental and ecosystem needs to study the 10 m to 1 km reach scale as one hydrologic system. Streams gain and lose water over a range of spatial and temporal scales. Large spatial scales (kilometers) have traditionally been recognized and studied as river-aquifer connections. Over the last 25 years hyporheic exchange flows (1-10 m) have been studied extensively. Often a transient storage model has been used to quantify the physical solute transport setting in which biogeochemical processes occur. At the longer 10 m to 1 km scale of stream reaches it is now clear that streams which gain water overall can coincidentally lose water to the subsurface. At this scale, the amounts of water transferred are not necessarily significant but the exchanges can, however, influence solute transport. The interpretation of seemingly straightforward questions about water, contaminant, and nutrient fluxes into and along a stream can be confounded by flow losses which are too small to be apparent in stream gauging and along flow paths too long to be detected in tracer experiments. We suggest basic hydrologic approaches, e.g., measurement of flow along the channel, surface and subsurface solute sampling, and routine measurements of the water table that, in our opinion, can be used to extend simple exchange concepts from the hyporheic exchange scale to a scale of stream-catchment connection.
Satellite telemetry: A new tool for wildlife research and management
The U.S. Fish and Wildlife Service and the Alaska Department of Fish and Game have cooperated since 1984 to develop and evaluate satellite telemetry as a means of overcoming the high costs and logistical problems of conventional VHF (very high frequency) radiotelemetry systems. Detailed locational and behavioral data on caribou ( Rangifer tarandus ), polar bears ( Ursus maritimus ), and other large mammals in Alaska have been obtained using the Argos Data Collection and Location System (DCLS). The Argos system, a cooperative project of the Centre National d'Études Spatiales of France, the National Oceanic and Atmospheric Administration, and the National Aeronautics and Space Administration, is designed to acquire environmental data on a routine basis from anywhere on earth. Transmitters weighing 1.6-2.0 kg and functioning approximately 12-18 months operated on a frequency of 401.650 MHz. Signals from the transmitters were received by Argos DCLS instruments aboard two Tiros-N weather satellites in sun-synchronous, nearpolar orbits. Data from the satellites were received at tracking stations, transferred to processing centers in Maryland and France, and made available to users via computer tape, printouts, or telephone links. During 1985 and 1986, more than 25,000 locations and an additional 28,000 sets of sensor data (transmitter temperature and short-term and long-term indices of animal activity) were acquired for caribou and polar bears. Locations were calculated from the Doppler shift in the transmitted signal as the satellite approached and then moved away from the transmitter. The mean locational error for transmitters at known locations (n - 1,265) was 829 m; 90% of the calculated locations were within 1,700 m of the true location. Caribou transmitters provided a mean of 3.1 (+5.0. SD) locations per day during 6h of daily operation, and polar bear transmitters provided 1.7 (+6.9SD) locations during 12h of operation every third day. During the first 6 months of operation, the UHF (ultra-high frequency) signal failed on three of 32 caribou transmitters and 10 of 36 polar bear transmitters. A geographic information system (GIS) incorporating other databases (e.g., land cover, elevation, slope, aspect, hydrology, ice distribution) was used to analyze and display detailed locational and behavioral data collected via satellite. Examples of GIS applications to research projects using satellite telemetry and examples of detailed movement patterns of caribou and polar bears are presented. This report includes documentation for computer software packages for processing Argos data and presents developments, as of March 1987, in transmitter design, data retrieval using a local user terminal, computer software, and sensor development and calibration.
Estimation of evapotranspiration by reed canarygrass using field observations and model simulations
Reed canarygrass (Phalaris arundinacea) commonly invades meadow wetlands, effectively dominating water use and outcompeting native plants. Objectives of this study were to (i) estimate daily, seasonal and annual water use by reed canarygrass using shallow water table fluctuations; and (ii) calibrate the ALMANAC (Agricultural Land Management Alternative with Numerical Assessment Criteria) model to accurately simulate water uptake by this grass. Using a groundwater well, the water table under an area in Iowa dominated by reed canarygrass was monitored hourly. Differences between water level measurements taken each hour were averaged to determine the hourly water table change in each month. Using these estimates of water use, the ALMANAC model was then calibrated to simulate plant transpiration values close to these water table use rates. Average monthly calculated daily plant water use rates were 3.3 mm d-1 in July and 2.3-2.8 mm d-1 in May, June, August, and September. Simulated bimonthly values for measured water use and plant transpiration simulated by the ALMANAC model differed by 14% or less. From May to October the mean ratio of measured to simulated values was 94%. Thus, the similarity between simulated plant transpiration and water use from the water table showed promise that this process-based model can realistically simulate water use under such grassland systems. ?? 2007 Elsevier B.V. All rights reserved.
Ground and surface temperature variability for remote sensing of soil moisture in a heterogeneous landscape
At the Little River Watershed (LRW) heterogeneous landscape near Tifton Georgia US an in situ network of stations operated by the US Department of Agriculture-Agriculture Research Service-Southeast Watershed Research Lab (USDA-ARS-SEWRL) was established in 2003 for the long term study of climatic and soil biophysical processes. To develop an accurate interpolation of the in situ readings that can be used to produce distributed representations of soil moisture (SM) and energy balances at the landscape scale for remote sensing studies, we studied (1) the temporal and spatial variations of ground temperature (GT) and infra red temperature (IRT) within 30 by 30 m plots around selected network stations; (2) the relationship between the readings from the eight 30 by 30 m plots and the point reading of the network stations for the variables SM, GT and IRT; and (3) the spatial and temporal variation of GT and IRT within agriculture landuses: grass, orchard, peanuts, cotton and bare soil in the surrounding landscape. The results showed high correlations between the station readings and the adjacent 30 by 30 m plot average value for SM; high seasonal independent variation in the GT and IRT behavior among the eight 30 by 30 m plots; and site specific, in-field homogeneity in each 30 by 30 m plot. We found statistical differences in the GT and IRT between the different landuses as well as high correlations between GT and IRT regardless of the landuse. Greater standard deviations for IRT than for GT (in the range of 2-4) were found within the 30 by 30 m, suggesting that when a single point reading for this variable is selected for the validation of either remote sensing data or water-energy models, errors may occur. The results confirmed that in this landscape homogeneous 30 by 30 m plots can be used as landscape spatial units for soil moisture and ground temperature studies. Under this landscape conditions small plots can account for local expressions of environmental processes, decreasing the errors and uncertainties in remote sensing estimates caused by landscape heterogeneity.
Groundwater-Surface water interactions research: Past trends and future directions
Interactions between groundwater and surface water sustain groundwater-dependent ecosystems and regulate river temperature and biogeochemical cycles, amongst many other processes. These interactions occur in freshwater environments including rivers, springs, lakes, and wetlands, and in coastal environments via tidal pumping, submarine groundwater discharge, and seawater intrusion. Here, we explore groundwater-surface water interactions research using bibliometric analyses of titles, abstracts, and keywords from 20,275 journal papers published between 1970 and 2023 extracted from Scopus. Analyses show that research into groundwater-surface water interactions is highly multi-disciplinary, with growing contributions from the social and biological sciences. The number of groundwater-surface water interactions papers is rapidly increasing with over 1200 papers published per year since 2020. Drawing on our data-driven approach and expert knowledge, we synthesise current research trends and identify critical future research directions. Despite the thousands of papers on groundwater-surface water interactions, important processes are still difficult to quantify or predict at meaningful spatial scales to inform water-resources management. We see benefits in future groundwater-surface water interactions research focusing on: (1) using new technologies including internet-of-things-based sensors, uncrewed vehicles, and remote-sensing approaches for data collection to inform groundwater-surface water interactions at large scales, (2) seeking approaches to upscale site-specific findings to better inform management, and (3) continuing the movement towards multi-disciplinary investigations to better inform the understanding of groundwater-surface water interactions and processes that will enable better management outcomes.
Multi-level slug tests in highly permeable formations: 2. Hydraulic conductivity identification, method verification, and field applications
Using the developed theory and modified Springer-Gelhar (SG) model, an identification method is proposed for estimating hydraulic conductivity from multi-level slug tests. The computerized algorithm calculates hydraulic conductivity from both monotonic and oscillatory well responses obtained using a double-packer system. Field verification of the method was performed at a specially designed fully penetrating well of 0.1-m diameter with a 10-m screen in a sand and gravel alluvial aquifer (MSEA site, Shelton, Nebraska). During well installation, disturbed core samples were collected every 0.6 m using a split-spoon sampler. Vertical profiles of hydraulic conductivity were produced on the basis of grain-size analysis of the disturbed core samples. These results closely correlate with the vertical profile of horizontal hydraulic conductivity obtained by interpreting multi-level slug test responses using the modified SG model. The identification method was applied to interpret the response from 474 slug tests in 156 locations at the MSEA site. More than 60% of responses were oscillatory. The method produced a good match to experimental data for both oscillatory and monotonic responses using an automated curve matching procedure. The proposed method allowed us to drastically increase the efficiency of each well used for aquifer characterization and to process massive arrays of field data. Recommendations generalizing this experience to massive application of the proposed method are developed.Using the developed theory and modified Springer-Gelhar (SG) model, an identification method is proposed for estimating hydraulic conductivity from multi-level slug tests. The computerized algorithm calculates hydraulic conductivity from both monotonic and oscillatory well responses obtained using a double-packer system. Field verification of the method was performed at a specially designed fully penetrating well of 0.1-m diameter with a 10-m screen in a sand and gravel alluvial aquifer (MSEA site, Shelton, Nebraska). During well installation, disturbed core samples were collected every 0.6 m using a split-spoon sampler. Vertical profiles of hydraulic conductivity were produced on the basis of grain-size analysis of the disturbed core samples. These results closely correlate with the vertical profile of horizontal hydraulic conductivity obtained by interpreting multi-level slug test responses using the modified SG model. The identification method was applied to interpret the response from 474 slug tests in 156 locations at the MSEA site. More than 60% of responses were oscillatory. The method produced a good match to experimental data for both oscillatory and monotonic responses using an automated curve matching procedure. The proposed method allowed us to drastically increase the efficiency of each well used for aquifer characterization and to process massive arrays of field data. Recommendations generalizing this experience to massive application of the proposed method are developed.
Application of continuous seismic reflection methods to hydrologic studies
Oil and gas exploration and engineering studies in water‐covered areas routinely use continuous seismic profiling techniques to obtain subsurface geologic information. Such profiling also can be used effectively in hydrologic studies to define the geologic framework of aquifer systems, to locate hydrologic boundaries, and in some places, to interpret the lithologic character of aquifers and confining beds. High‐resolution continuous seismic profiling, through the use of nonexplosive sound sources, can be used to produce continuous records that require little data processing before hydrogeologic interpretation. High‐resolution tuned transducer, minisparker, Uniboom, and small airgun systems operating from small boats in shallow water are capable of transmitting energy that can penetrate up to a hundred meters of earth materials. The resulting analog records of the reflected seismic signal closely resemble geologic sections. Surveys on the Housatonic River in Connecticut and Massachusetts, and on the Connecticut River, in water from 1 to 10 meters deep, have defined the bedrock surface beneath 60 meters of stratified drift. Seismic‐reflection profiling also was used to determine the extent and thickness of recent lake‐bottom deposits in two Connecticut lakes. Surveys along 90 kilometers of river channels in the Sarasota‐port Charlotte, Florida, area defined in detail the stratigrapahy and continuity of the shallow aquifers.
Global change impacts on mangrove ecosystems
Mangroves are tropical/subtropical communities of primarily tree species that grow in the intertidal zone. These tidal forests are important coastal ecosystems that are valued for a variety of ecological and societal goods and services. Major local threats to mangrove ecosystems worldwide include clearcutting and trimming of forests for urban, agricultural, or industrial expansion; hydrological alterations; toxic chemical spills; and eutrophication. In many countries with mangroves, much of the human population resides in the coastal zone, and their activities often negatively impact the integrity of mangrove forests. In addition, eutrophication, which is the process whereby nutrients build up to higher than normal levels in a natural system, is possibly one of the most serious threats to mangroves and associated ecosystems such as coral reefs. Scientists with the U.S. Geological Survey (USGS) at the National Wetlands Research Center are working to more fully understand global impacts on these significant ecosystems. Changes in climate and other factors may also affect mangroves, but in complex ways. Global warming may promote expansion of mangrove forests to higher latitudes and accelerate sea-level rise through melting of polar ice or steric expansion of oceans. Changes in sea level would alter flooding patterns and the structure and areal extent of mangroves. Climate change may also alter rainfall patterns, which would in turn change local salinity regimes and competitive interactions of mangroves with other wetland species. Increases in frequency or intensity of tropical storms and hurricanes in combination with sea-level rise may alter erosion and sedimentation rates in mangrove forests. Another global change factor that may directly affect mangrove growth is increased atmospheric carbon dioxide (CO 2 ), caused by burning of fossil fuels and other factors. Elevated CO 2 concentration may increase mangrove growth by stimulating photosynthesis or improving water use efficiency, but the consequences of this growth enhancement for the ecosystem are unknown.
Magnitude and Frequency of Rural Floods in the Southeastern United States, through 2006: Volume 2, North Carolina
Reliable estimates of the magnitude and frequency of floods are required for the economical and safe design of transportation and water-conveyance structures. A multistate approach was used to update methods for estimating the magnitude and frequency of floods in rural, ungaged basins in North Carolina, South Carolina, and Georgia that are not substantially affected by regulation, tidal fluctuations, or urban development. In North Carolina, annual peak-flow data available through September 2006 were available for 584 sites; 402 of these sites had a total of 10 or more years of systematic record that is required for at-site, flood-frequency analysis. Following data reviews and the computation of 20 physical and climatic basin characteristics for each station as well as at-site flood-frequency statistics, annual peak-flow data were identified for 363 sites in North Carolina suitable for use in this analysis. Among these 363 sites, 19 sites had records that could be divided into unregulated and regulated/ channelized annual peak discharges, which means peak-flow records were identified for a total of 382 cases in North Carolina. Considering the 382 cases, at-site flood-frequency statistics are provided for 333 unregulated cases (also used for the regression database) and 49 regulated/channelized cases. The flood-frequency statistics for the 333 unregulated sites were combined with data for sites from South Carolina, Georgia, and adjacent parts of Alabama, Florida, Tennessee, and Virginia to create a database of 943 sites considered for use in the regional regression analysis. Flood-frequency statistics were computed by fitting logarithms (base 10) of the annual peak flows to a log-Pearson Type III distribution. As part of the computation process, a new generalized skew coefficient was developed by using a Bayesian generalized least-squares regression model. Exploratory regression analyses using ordinary least-squares regression completed on the initial database of 943 sites resulted in defining five hydrologic regions for North Carolina, South Carolina, and Georgia. Stations with drainage areas less than 1 square mile were removed from the database, and a procedure to examine for basin redundancy (based on drainage area and periods of record) also resulted in the removal of some stations from the regression database. Flood-frequency estimates and basin characteristics for 828 gaged stations were combined to form the final database that was used in the regional regression analysis. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations that can be used for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance flows for rural ungaged, basins in North Carolina, South Carolina, and Georgia. The final predictive equations are all functions of drainage area and the percentage of drainage basin within each of the five hydrologic regions. Average errors of prediction for these regression equations range from 34.0 to 47.7 percent. Discharge estimates determined from the systematic records for the current study are, on average, larger in magnitude than those from a previous study for the highest percent chance exceedances (50 and 20 percent) and tend to be smaller than those from the previous study for the lower percent chance exceedances when all sites are considered as a group. For example, mean differences for sites in the Piedmont hydrologic region range from positive 0.5 percent for the 50-percent chance exceedance flow to negative 4.6 percent for the 0.2-percent chance exceedance flow when stations are grouped by hydrologic region. Similarly for the same hydrologic region, median differences range from positive 0.9 percent for the 50-percent chance exceedance flow to negative 7.1 percent for the 0.2-percent chance exceedance flow. However, mean and median percentage differences between the estimates from the previous and curre
Controls of stream chemistry and fish populations in the Neversink watershed, Catskill Mountains, New York
The Neversink Watershed Study was initiated in 1991 to develop an understanding of the key natural processes that control water quality within the forested, 166 km 2 (64 mi 2 ), Neversink River watershed; part of the New York City drinking water supply system, in the Catskill Mountain region of New York. The study entailed (1) hydrological investigations of water movement from the atmosphere to streams, (2) biogeochemical investigations of nitrogen and calcium, important nutrients in forest and aquatic ecosystems whose availability has been altered by acidic deposition, (3) an investigation of elevational patterns in atmospheric deposition, and (4) fisheries investigations to determine the relative importance of physical habitat and acidic deposition in controlling the abundance and diversity of fish species in the watershed. This report summarizes the results of these investigations, which have also been presented, in detail, in peer-reviewed technical articles and reports that are cited throughout the text.
Hydrochemical characterization of groundwater in the Akyem area, Ghana
The Akyem area is a small farming community located in southeastern Ghana. Groundwater samples from wells in the area were analyzed for concentrations of the major ions, silica, electrical conductivity and pH. The objective was to determine the main controls on the hydrochemistry of ground-water. Mass balance modeling was used together with multivariate R-mode hierarchical cluster analysis to determine the significant sources of variation in the hydrochemistry. Two water types exist in this area. The first is influenced most by the weathering of silicate minerals from the underlying geology, and is thus rich in silica, sodium, calcium, bicarbonate, and magnesium ions. The second is water that has been influenced by the effects of fertilizers and other anthropogenic activities in the area. Mineral speciation and silicate mineral stability diagrams suggest that montmorillonite, probably derived from the incongruent dissolution of feldspars and micas, is the most stable silicate phase in the groundwaters. The apparent incongruent weathering of silicate minerals in the groundwater system has led to the enrichment of sodium, calcium, magnesium and bicarbonate ions as well as silica, leading to the supersaturation of calcite, aragonite, dolomite and quartz. Stability in the montmorillonite field suggests restricted flow conditions and a long groundwater residence time, leading to greater exposure of the rock to weathering. Cation exchange processes appear to play minor roles in the hydrochemistry of groundwater.
Restoration and revegetation associated with control of saltcedar and Russian olive: Chapter 7
Rationales for controlling or eliminating saltcedar and Russian olive from sites, river reaches, or entire streams include implicit or explicit assumptions that natural recovery or applied restoration of native plant communities will follow exotic plant removal (McDaniel and Taylor, 2003; Quimby and others, 2003). The vegetation that replaces saltcedar and Russian olive after treatment (“replacement vegetation”), with or without restoration actions, strongly influences the extent to which project objectives are successfully met. It is often assumed or implied that saltcedar and Russian olive removal alone is “restoration,” and many reports equate restoration success with areal extent of nonnative plants treated (for example, Duncan and others, 1993). However, removal of nonnative species alone does not generally constitute restoration. In this chapter, the term “restoration” refers to conversion of saltcedar- and Russian olive-dominated sites to a replacement vegetation type that achieves specific management goals and helps return parts of the system to a desired state. The degree to which a site is “restored” following removal of saltcedar or Russian olive typically depends upon a range of factors, such as (1) the site’s potential for restoration (such as extant soil conditions, site hydrology), (2) the direct and indirect effects of removal (for example, mechanical impacts to the site, effects of herbicides on nontarget vegetation), (3) the efficacy of restoration activities (for example, grading, reseeding, pole planting), and (4) the maintenance of processes that support native vegetation and prevent re-colonization by nonnative communities over the long term. This chapter summarizes and synthesizes the published literature on the topic of restoring native riparian vegetation following saltcedar and Russian olive control or removal. Most of the studies reviewed here are from saltcedar removal, revegetation, and river restoration projects in semiarid and arid parts of the Western United States. The paucity of literature on Russian olive prevents thorough evaluation of specific considerations for restoration following Russian olive removal; however, a few field studies are highlighted. Furthermore, the basic principles of restoration following vegetation removal and the considerations and lessons learned from saltcedar case studies are broadly applicable to sites across the Western United States. We begin with a brief discussion of planning and objective setting. Next, we discuss site factors and context, which are important to consider when selecting and prioritizing sites for restoration. We then review and synthesize the literature on restoration approaches and methods or combinations of methods to apply to particular sites. Throughout this chapter, we highlight what is known on the topics of restoring soils, vegetation, and site conditions following nonnative species removal, as well as future research needs.
Temporal coherence of two alpine lake basins of the Colorado Front Range, USA
1. Knowledge of synchrony in trends is important to determining regional responses of lakes to disturbances such as atmospheric deposition and climate change. We explored the temporal coherence of physical and chemical characteristics of two series of mostly alpine lakes in nearby basins of the Colorado Rocky Mountains. Using year-to-year variation over a 10-year period, we asked whether lakes more similar in exposure to the atmosphere be-haved more similarly than those with greater influence of catchment or in-lake processes. 2. The Green Lakes Valley and Loch Vale Watershed are steeply incised basins with strong altitudinal gradients. There are glaciers at the heads of each catchment. The eight lakes studied are small, shallow and typically ice-covered for more than half the year. Snowmelt is the dominant hydrological event each year, flushing about 70% of the annual discharge from each lake between April and mid-July. The lakes do not thermally stratify during the period of open water. Data from these lakes included surface water temper-ature, sulphate, nitrate, calcium, silica, bicarbonate alkalinity and conductivity. 3. Coherence was estimated by Pearson's correlation coefficient between lake pairs for each of the different variables. Despite close geographical proximity, there was not a strong direct signal from climatic or atmospheric conditions across all lakes in the study. Individual lake characteristics overwhelmed regional responses. Temporal coherence was higher for lakes within each basin than between basins and was highest for nearest neighbours. 4. Among the Green Lakes, conductivity, alkalinity and temperature were temporally coherent, suggesting that these lakes were sensitive to climate fluctuations. Water tem-perature is indicative of air temperature, and conductivity and alkalinity concentrations are indicative of dilution from the amount of precipitation flushed through by snowmelt. 5. In Loch Vale, calcium, conductivity, nitrate, sulphate and alkalinity were temporally coherent, while silica and temperature were not. This suggests that external influences are attenuated by internal catchment and lake processes in Loch Vale lakes. Calcium and sulphate are primarily weathering products, but sulphate derives both from deposition and from mineral weathering. Different proportions of snowmelt versus groundwater in different years could influence summer lake concentrations. Nitrate is elevated in lake waters from atmospheric deposition, but the internal dynamics of nitrate and silica may be controlled by lake food webs. Temperature is attenuated by inconsistently different climates across altitude and glacial meltwaters. 6. It appears that, while the lakes in the two basins are topographically close, geologically and morphologically similar, and often connected by streams, only some attributes are temporally coherent. Catchment and in-lake processes influenced temporal patterns, especially for temperature, alkalinity and silica. Montane lakes with high altitudinal gradients may be particularly prone to local controls compared to systems where coherence is more obvious.
A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater
Numerous methods have been proposed to estimate the pre-nuclear-detonation 14 C content of dissolved inorganic carbon (DIC) recharged to groundwater that has been corrected/adjusted for geochemical processes in the absence of radioactive decay ( 14 C 0 ) - a quantity that is essential for estimation of radiocarbon age of DIC in groundwater. The models/approaches most commonly used are grouped as follows: (1) single-sample-based models, (2) a statistical approach based on the observed (curved) relationship between 14 C and δ 13 C data for the aquifer, and (3) the geochemical mass-balance approach that constructs adjustment models accounting for all the geochemical reactions known to occur along a groundwater flow path. This review discusses first the geochemical processes behind each of the single-sample-based models, followed by discussions of the statistical approach and the geochemical mass-balance approach. Finally, the applications, advantages and limitations of the three groups of models/approaches are discussed. The single-sample-based models constitute the prevailing use of 14 C data in hydrogeology and hydrological studies. This is in part because the models are applied to an individual water sample to estimate the 14 C age, therefore the measurement data are easily available. These models have been shown to provide realistic radiocarbon ages in many studies. However, they usually are limited to simple carbonate aquifers and selection of model may have significant effects on 14 C 0 often resulting in a wide range of estimates of 14 C ages. Of the single-sample-based models, four are recommended for the estimation of 14 C 0 of DIC in groundwater: Pearson's model, (Ingerson and Pearson, 1964; Pearson and White, 1967), Han & Plummer's model (Han and Plummer, 2013), the IAEA model (Gonfiantini, 1972; Salem et al., 1980), and Oeschger's model (Geyh, 2000). These four models include all processes considered in single-sample-based models, and can be used in different ranges of 13 C values. In contrast to the single-sample-based models, the extended Gonfiantini & Zuppi model (Gonfiantini and Zuppi, 2003; Han et al., 2014) is a statistical approach. This approach can be used to estimate 14 C ages when a curved relationship between the 14 C and 13 C values of the DIC data is observed. In addition to estimation of groundwater ages, the relationship between 14 C and δ 13 C data can be used to interpret hydrogeological characteristics of the aquifer, e.g. estimating apparent rates of geochemical reactions and revealing the complexity of the geochemical environment, and identify samples that are not affected by the same set of reactions/processes as the rest of the dataset. The investigated water samples may have a wide range of ages, and for waters with very low values of 14 C, the model based on statistics may give more reliable age estimates than those obtained from single-sample-based models. In the extended Gonfiantini & Zuppi model, a representative system-wide value of the initial 14 C content is derived from the 14 C and δ 13 C data of DIC and can differ from that used in single-sample-based models. Therefore, the extended Gonfiantini & Zuppi model usually avoids the effect of modern water components which might retain ‘bomb’ pulse signatures. The geochemical mass-balance approach constructs an adjustment model that accounts for all the geochemical reactions known to occur along an aquifer flow path (Plummer et al., 1983; Wigley et al., 1978; Plummer et al., 1994; Plummer and Glynn, 2013), and includes, in addition to DIC, dissolved organic carbon (DOC) and methane (CH 4 ). If sufficient chemical, mineralogical and isotopic data are available, the geochemical mass-balance method can yield the most accurate estimates of the adjusted radiocarbon age. The main limitation of this approach is that complete information is necessary on chemical, mineralogical and isotopic data and these data are often limited. Failure to recognize the limitations and underlying assumptions on which the various models and approaches are based can result in a wide range of estimates of 14 C 0 and limit the usefulness of radiocarbon as a dating tool for groundwater. In each of the three generalized approaches (single-sample-based models, statistical approach, and geochemical mass-balance approach), successful application depends on scrutiny of the isotopic ( 14 C and 13 C) and chemical data to conceptualize the reactions and processes that affect the 14 C content of DIC in aquifers. The recently developed graphical analysis method is shown to aid in determining which approach is most appropriate for the isotopic and chemical data from a groundwater system.
Observations of an extreme atmospheric river storm with a diverse sensor network
Observational networks enhance real‐time situational awareness for emergency and water resource management during extreme weather events. We present examples of how a diverse, multitiered observational network in California provided insights into hydrometeorological processes and impacts during a 3‐day atmospheric river storm centered on 14 February 2019. This network, which has been developed over the past two decades, aims to improve understanding and mitigation of effects from extreme storms influencing water resources and natural hazards. We combine atmospheric reanalysis output and additional observations to show how the network allows: (1) the validation of record cool season precipitable water observations over southern California; (2) the identification of phenomena that produce natural hazards and present difficulties for short‐term weather forecast models, such as extreme precipitation amounts and snow level variability; (3) the use of soil moisture data to improve hydrologic model forecast skill in northern California's Russian River basin; and (4) the combination of meteorological data with seismic observations to identify when a large avalanche occurred on Mount Shasta. This case study highlights the value of investments in diverse observational assets and the importance of continued support and synthesis of these networks to characterize climatological context and advance understanding of processes modulating extreme weather.
Machine-learning models to map pH and redox conditions in groundwater in a layered aquifer system, Northern Atlantic Coastal Plain, eastern USA
Study region The study was conducted in the Northern Atlantic Coastal Plain aquifer system, in the eastern USA. Study focus Groundwater pH and redox conditions are fundamental chemical characteristics controlling the distribution of many contaminants of concern for drinking water or the ecological health of receiving waters. In this study, pH and redox conditions were modeled and mapped in a complex, layered aquifer system. Machine-learning methods (boosted regression trees) were applied to data from 3000 to 5000 wells. Predicted pH and the probability of anoxic conditions, defined by three thresholds of dissolved oxygen (0.5, 1, and 2 mg/L), were mapped at the 1-km 2 scale for each of 10 regional aquifer layers. New Hydrological Insights for the Region Maps depict the extent of acidic groundwater and oxic conditions in the shallow, unconfined surficial aquifer and in unconfined, recharge-proximal areas of underlying aquifers, in contrast to alkaline and anoxic groundwater elsewhere. Geographic patterns and influential predictors–including elevation, overlying confining-units thickness, and simulated groundwater age and flux–are consistent with prior understanding of the processes controlling pH and redox in the aquifer system. The model-based maps support robust estimates of aquifer proportions, either areal or volumetric, likely to contain groundwater of a specified quality or be vulnerable to specific pH- or redox-sensitive contaminants. The machine-learning methods were an effective tool to map groundwater quality at the regional scale.
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