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Worldwide, tree or shrub dominated woodlands have encroached into herbaceous dominated grasslands. While very few studies have evaluated the impact of Eastern Redcedar (redcedar) encroachment on the water budget, none have analyzed the impact on water quality. In this study, we evaluated the impact of redcedar encroachment on the water budget in the Nebraska Sand Hills and how the decreased streamflow would increase nitrate and atrazine concentrations in the Platte River. We calibrated a Soil and Water Assessment Tool (SWAT model) for streamflow, recharge, and evapotranspiration. Using a moving window with a dilate morphological filter, encroachment scenarios of 11.9 %, 16.1 %, 28.0 %, 40.6 %, 57.5 %, 72.5 % and 100 % were developed and simulated by the calibrated model. At 11.9 % and 100 % encroachment, streamflow was reduced by 4.6 % and 45.5 %, respectively in the Upper Middle Loup River, a tributary to the Platte River. Percolation and deep aquifer recharge increased by 27 % and 26 % at 100 % encroachment. Streamflow in the Platte River, a major water source for Omaha and Lincoln, would decrease by 2.6 %, 5.5 % and 10.5 % for 28 %, 57.5 %, and 100 % encroachment of the Loup River watershed, respectively. This reduction in streamflow could increase nitrate and atrazine concentrations in the Platte River by 4 to 15 % and 4 to 30 %, respectively. While the density of redcedar is minimal, it is important to manage their encroachment to prevent reductions in streamflow and potential increases in pollutant concentrations.

Made available in DSpace on 2022-04-28T19:50:00Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-01-01 Changes in climate and water demand in densely populated regions increasingly affect hydrological systems, and, in turn, impact socioeconomic conditions. In this case study, we identify how the hydrogeological frameworks of two water resource management units, Tietê-Jacaré (TJ) and Piracicaba-Capivari-Jundiaí (PCJ) in Sao Paulo state (Brazil), control the baseflow processes and resilience in the face of streamflow fluctuations in response to anthropogenic activities and climate variation. The results reveal between 40% and 75% contributions of baseflow to total streamflow in basins overlying crystalline and sedimentary aquifers. The basins in PCJ which mostly overly crystalline aquifers, have shorter water residence times and greater dependence on surface water. Therefore, streamflow in the PCJ basins is vulnerable during the drought period and the management model affected the water resilience of the basins (transfer of water to Cantareira System). The TJ basins have greater streamflow contributions from aquifer discharge linked to the presence of important sedimentary aquifers, which improves resilience under changing rainfall patterns, these basins present a more stable situation of resilience. Ultimately, the two management units require different planning strategies with adaptive and dynamic actions to mitigate the social, economic, and environmental effects caused by the variability and reduction of water sources. Environmental Studies Center São Paulo State University (UNESP) Conservation and Survey Division School of Natural Resources University of Nebraska Lincoln Department of Biological Systems Engineering University of Nebraska-Lincoln Civil and Environmental Engineering Faculty Washington State University Faculty of Alta Paulista – FAP Instituto Dom Bosco de Ensino. R. Mandaguaris Agroenvironmental Engineering Terrestrial Research and Monitoring Center (CIMTE) Technological University of Uruguay (UTEC) South Central Regional Technological Institute (ITR-CS) Francisco Antonio Maciel s/n esq. Luis Morquio Environmental Studies Center São Paulo State University (UNESP)

Groundwater age-dating is an important tool for quantifying and managing water resources. Groundwater age is the elapsed time between recharge (at the land surface or water table) and the time when groundwater is sampled. If groundwater is sampled at the point of discharge from an aquifer, then the age represents the groundwater transit time. Groundwater that has recharged in recent decades is considered young groundwater. In many areas, the quality and quantity of young groundwater has been impacted by human activities and groundwater age-dating is useful for quantifying current and historical water and contaminant fluxes into and through aquifers. This review is focused on the tritium-helium (3H/3He) method, which is a robust and widely applied age-dating technique for young groundwater. We present the development of the 3H/3He method and practical considerations for sampling groundwater in shallow unconfined aquifers. Along the way, we highlight available resources: (1) educational software for building intuition around groundwater age-dating and selection of sampling sites and (2) software that can be used to calculate 3H/3He age from noble gas and 3H data. We also highlight strengths and potential uncertainties associated with the method. For example, while other age-dating techniques require a known historical record of tracer concentration in the atmosphere, the 3H/3He age-dating technique does not require such historical records. However, the 3H/3He method requires measurement of two tracers to produce a groundwater age estimate (“apparent age” or “tracer age”). Precise measurement of 3H and noble gases, plus careful analysis of noble gas data to calculate the tritiogenic 3He (i.e., the portion of 3He derived from decay of 3H in the aquifer) is required to calculate the groundwater apparent age. Sampling for noble gases is sometimes challenging and requires specialized sample containers and technique. We also introduce basic sampling methods in this review but highlight how practitioners should work closely with a noble gas laboratory to obtain the correct containers and assess field conditions and/or the overall feasibility of projects. Lastly, the review highlights recent applications of the 3H/3He method, including recharge rate estimation, characterization of contaminant input histories for aquifers, quantifying groundwater transit times by sampling at aquifer discharge points, and the use of isotope data to constrain and inform numerical and statistical models of groundwater and contaminant movement in the subsurface.

The Guarani Aquifer System (GAS) has been studied since the 1970s, a time frame that coincides with the advent of isotopic techniques in Brazil. The GAS isotope data from many studies are organized in different phases: (a) the advent of isotope techniques, (b) consolidation and new applications, (c) isotope assessments and hydrochemistry evolution, and (d) a roadmap to a new conceptual model. The reasons behind the phases, their methodological approaches, and impacts on the regional flow conceptual models are examined. Starting with local δ²H and δ¹⁸O assessments of values for water fingerprinting and estimates of recharge palaeoclimate scenarios, studies evolved to more integrated approaches based on multiple tracers. Stable isotope application techniques were consolidated during the 1980s, when new dating approaches dealing with radiogenic and heavy isotopes were introduced. Through the execution of an international transboundary project, the GAS was studied and extensively sampled for isotopes. These results have triggered wider application of isotope techniques, reflecting also world research trends. Presently, hydrochemical evolution models along flow lines from recharge to discharge areas, across large‐scale tectonic features within the entire sedimentary basin, are being combined with residence time estimates at GAS outcrop areas and deep confined units. In a complex system, it is normal that many, and even contradictory hypotheses are proposed, but isotope techniques provide a unique chance to test them. Stable isotope assessments are still needed near recharge areas, and they can be combined with groundwater classical dating procedures, complemented by newer techniques (³H‐³He, CFCs, and SF₆). Recent noble gas sampling and world pioneer analytical efforts focused on the confined units in the GAS will certainly led to new findings on the overall GAS circulation. The objective of this article is to discuss how isotope information can contribute to the evolution of conceptual groundwater flow models for regional continental aquifers, such as the GAS.

Nebraskan streams contribute excess nitrogen to the Mississippi/Atchafalaya River Basin and Gulf of Mexico, which results in major water-quality impairments. Reducing the amount of nitrogen (N) exported in these streams requires the use of best management practices (BMPs) within the landscape. However, proper BMP utilization has rarely been statistically connected to potential controls of N export within watersheds, particularly precipitation and soil characteristics. In this study, 19 watershed variables were evaluated in five categories (hydrological, physiographic, point sources, land use, and soil properties) to determine the characteristics that influenced variable nitrate nitrogen (NO3-N) concentrations in 17 Nebraska watersheds with known high NO3-N export rates. Each characteristic was derived from publicly-available datasets in an effort to develop a multiregional method. Of the 19 variables evaluated, 10 variables (developed, cropland, herbaceous, forest, excessively-drained soils, precipitation, base-flow index, slope, organic matter and point sources) were identified to statistically influence stream NO3-N concentrations. The 17 watersheds were divided into five subset groups using principal component analysis. Distributions of the 10 watershed variables were then used to determine the most applicable BMPs for NO3-N reductions for each stream subset: excessively drained with high baseflow index (Groups 1 and 2), dominantely row crop land usage with well-drained soils, higher precipitation, and an increased tendency for surface runoff concerns (Group 3), highly developed watersheds (Group 4), and single river dominated by wastewater treatment plant discharge (Group 5). Based on the most influential variables a variety of BMPs were recommended, including N fertilizer application management and accounting for N credit from mineralization and NO3-N in irrigation water (Groups 1 and 2), installation of riparian buffers and wetlands (Group 3), urban BMPs such as bioretention cells and permeable pavement (Group 4), and upgrades to the wastewater treatment plant (Group 5). This study provides an improved technique for facilitating watershed management by linking BMPs directly to the characteristics of each watershed to reduce current nitrate export.

We quantified per- and polyfluoroalkyl substance (PFAS) transport from groundwater to five tributaries of the Cape Fear River near a PFAS manufacturing facility in North Carolina (USA). Hydrologic and PFAS data were coupled to quantify PFAS fluxes from groundwater to the tributaries. Up to 29 PFAS were analyzed, including perfluoroalkyl acids and recently identified fluoroethers. Total quantified PFAS (ΣPFAS) in groundwater was 20-4773 ng/L (mean = 1863 ng/L); the range for stream water was 426-3617 ng/L (mean = 1717 ng/L). Eight PFAS constituted 98% of ΣPFAS; perfluoro-2-(perfluoromethoxy)propanoic acid (PMPA) and hexafluoropropylene oxide dimer acid (GenX) accounted for 61%. For PFAS discharge from groundwater to one tributary, values estimated from stream water measurements (18 ± 4 kg/yr) were similar to those from groundwater measurements in streambeds (22-25 ± 5 kg/yr). At baseflow, 32 ± 7 kg/yr of PFAS discharged from groundwater to the five tributaries, eventually reaching the Cape Fear River. Given the PFAS emission timeline at the site, groundwater data suggest the abundant fluoroethers moved through the subsurface to streams in ≪50 yr. Discharge of contaminated groundwater may lead to long-term contamination of surface water and impacts on downstream drinking water supplies. This work addresses a gap in the PFAS literature: quantifying PFAS mass transfer between groundwater and surface water using field data.

Time-lapse imagery of streams and rivers provide new qualitative insights into hydrologic conditions at stream gauges, especially when site visits are biased toward baseflow or fair-weather conditions. Imagery from fixed, ground-based cameras is also rich in quantitative information that can improve streamflow monitoring. For instance, time-lapse imagery may be valuable for filling data gaps when sensors fail and/or during lapses in funding for monitoring programs. In this study, we automated the analysis of time-lapse imagery from a single camera at a single location, then built and tested machine learning models using programmatically calculable scalar image features to fill data gaps in stream gauge records. Time-lapse images were taken with a fixed, ground-based camera that is part of a documentary watershed imaging project (https://plattebasintimelapse.com/). Features were extracted from 40,000+ daylight images taken at one-hour intervals from 2012 to 2019. The algorithms removed dawn and dusk images that were too dark for feature extraction. The image features were merged with United States Geological Survey (USGS) stage and discharge data (i.e., response variables) from the site based on image capture times and USGS timestamps. We then developed a workflow to identify a suitable feature set to build machine learning models with a randomly selected training set of 30 % of the images with the remaining 70 % for a test set. Predictions were generated from Multi-layer Perceptron (MLP), Random Forest Regression (RFR), and Support Vector Regression (SVR) models. A Kalman filter was applied to the predictions to remove noise. Error metrics were calculated, including Nash-Sutcliffe Efficiency (NSE), Prediction Bias (PBIAS), RMSE-Standard Deviation Ratio (RSR), and an alternative metric that accounted for seasonal runoff. After suitable features were identified, the dataset was divided into test sets of simulated data gaps for 2015, 2016, and 2017. The training sets for each gap were features from contiguous images and sensor readings before and after the gaps. NSE for the year-long gap predictions ranged from 0.63 to 0.90 for discharge and 0.47 to 0.90 for stage. The predictions for 2015 and 2017 displayed lower prediction errors than for 2016. The 2016 discharge was significantly higher than training data, which could explain the poorer performance. First and second half-year test sets were created for 2016 along with MLP models from before/after training sets for each of the gaps that held discharge measurements similar to those in the gaps. The half-year gap models' predictions improved NSE, PBIAS and RSR. The results show it is possible to extract features from images taken with the downstream facing camera to build machine learning models that produce accurate stage and discharge predictions. The methods employed should be transferrable to other sites with ground-based cameras.

In this study, we explored the use of statistical machine learning and long-term groundwater nitrate monitoring data to estimate vadose-zone and saturated-zone lag times in an irrigated alluvial agricultural setting. Unlike most previous statistical machine learning studies that sought to predict groundwater nitrate concentrations within aquifers, the focus of this study was to leverage available groundwater nitrate concentrations and other environmental variable data to determine mean vertical velocities (transport rates) of water and solutes in the vadose zone and saturated zone (3.50 m/year and 3.75 m/year, respectively). Although a saturated-zone velocity that is greater than a vadose-zone velocity would be counterintuitive in most aquifer settings, the statistical machine learning results are consistent with two contrasting primary recharge processes in this aquifer: (1) diffuse recharge from irrigation and precipitation across the landscape, and (2) focused recharge from leaking irrigation conveyance canals. The vadose-zone mean velocity yielded a mean recharge rate (0.46 m/year) consistent with previous estimates from groundwater age-dating in shallow wells (0.38 m/year). The saturated zone mean velocity yielded a recharge rate (1.31 m/year) that was more consistent with focused recharge from leaky irrigation canals, as indicated by previous results of groundwater age-dating in intermediate-depth wells (1.22 m/year). Collectively, the statistical machine-learning model results are consistent with previous observations of relatively high-water fluxes and short transit times for water and nitrate in the aquifer. Partial dependence plots from the model indicate a sharp threshold where high groundwater nitrate concentrations are mostly associated with total travel times of seven years or less, possibly reflecting some combination of recent management practices and a tendency for nitrate concentrations to be higher in diffuse infiltration recharge than in canal leakage water. Limitations to the machine learning approach include potential non-uniqueness when comparing model performance for different transport rate combinations and highlight the need to corroborate statistical model results with a robust conceptual model and complementary information such as groundwater age.

Aerated, slow-release oxidants are a relatively new technology for treating contaminated aquifers. A critical need for advancing this technology is developing a reliable method for predicting the radius of influence (ROI) around each drive point. In this work, we report a series of laboratory flow tank experiments and numerical modeling efforts designed to predict the release and spreading of permanganate from aerated oxidant candles (oxidant-wax composites). To mimic the design of the oxidant delivery system used in the field, a double screen was used in a series of flow tank experiments where the oxidant was placed inside the inner screen and air was bubbled upward in the gap between the screens. This airflow pattern creates an airlift pump that causes water and oxidant to be dispersed from the top of the outer screen and drawn in at the bottom. Using this design, we observed that permanganate spreading and ROI increased with aeration and decreased with advection. A coupled bubble flow and transport model was able to successfully reproduce observed results by mimicking the upward shape and spreading of permanganate under various aeration and advection rates.

Made available in DSpace on 2020-12-12T01:13:47Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-03-30 National Institute of Food and Agriculture The sustainability of groundwater resources for agricultural and domestic use is dependent on both the groundwater recharge rate and the groundwater quality. The main purpose of this study was to improve the understanding of the timing, or seasonality, of groundwater recharge through the use of stable isotopes. Based on 768 groundwater samples collected from aquifers underlying natural resources districts in Nebraska, the isotopic composition of groundwater (δ2H and δ18O) was compared with that of precipitation by (a) mapping the isotopic composition of groundwater samples and (b) mapping a seasonality index for groundwater. Results suggest that for the majority of the state, groundwater recharge has a nongrowing season signature (October–April). However, the isotopic composition of groundwater suggests that in some intensively irrigated areas, human intervention in the water cycle has shifted the recharge signature towards the growing season. In other areas, a different human intervention (diversion of Platte River water for irrigation) has likely produced an apparent but possibly misleading nongrowing season recharge signal because the Platte River water differs isotopically from local precipitation. These results highlight the need for local information even when interpreting isotopic data over larger regions. Understanding the seasonality of recharge can provide insight into the optimal times to apply fertilizer, specifically in highly conductive soils with high leaching potential. In areas with high groundwater nitrate concentrations, this information is valuable for protecting the groundwater from further degradation. Although previous studies have framed nongrowing season recharge within the context of future climate change, this study also illustrates the importance of understanding how historical human intervention in the water cycle has affected groundwater recharge seasonality and subsequent implications for groundwater recharge and quality. Conservation and Survey Division School of Natural Resources University of Nebraska Department of Biological Systems Engineering University of Nebraska Environmental Studies Center São Paulo State University (UNESP) CropMetrics Environmental Studies Center São Paulo State University (UNESP) National Institute of Food and Agriculture: Hatch project NEB-21-177

Most single-point methods of measuring seepage fluxes across the surface water-groundwater interface in lakes, streams, and estuaries (e.g., volumetric, head-based, and thermal) have one trait in common: they produce seepage rate values, averaged over substantial periods of time, thereby limiting resolution of the intra-day dynamics. Recently, Solomon et al. (Water Resources Research, 2019, in review) presented a new instrument and modification to a previously tested concept (Solder et al., Groundwater, 2016). This instrument has an open-bottom permeameter (OBP) design, which is commonly used for investigating hydraulic conductivity of the interface with falling or rising head tests, but historically not used for flux estimates. The novel dynamic seepage meter (DSM) evaluates the transient water level in the OBP-based instrument with submillimeter accuracy, exceeding the performance of traditional pressure transducers. The initial dynamics of the water level response over fractions of an hour holds the necessary information to infer the natural seepage rate in both gaining and losing conditions. The tests can be repeated frequently in an automatic regime. If a single test lasts long enough, hydraulic conductivity, in addition to the seepage rate can also be accurately determined. Here, a detailed hydrodynamic theory of the flow systems inside and outside the OBP is presented and the accuracy of measured water fluxes is investigated with emphasis on interpretation of the data with ambient noise. The results of this study will facilitate rapid, accurate, and massive data collection in diverse field conditions. (Research was supported by the NSF grant EAR 1744719.)

Groundwater recharge rate estimation is crucial to sustainable development of aquifers in intensely pumped regions, such as the Urucuia Aquifer System (UAS). A sedimentary aquifer in Western Bahia, Brazil, that underlies one of the major agricultural areas of the country where there has been major growth of irrigated areas. This study seeks to evaluate the recharge component of the water budget in the UAS area, based on three complementary techniques. The double-ring infiltrometer test was used to evaluate surface infiltration capacity, an important control on recharge. Water level data from wells (2011–2019 period, 19 wells) in the Brazilian Geological Survey's Integrated Groundwater Monitoring Network (RIMAS-CPRM) was used to estimate the aquifer recharge using the water table fluctuation (WTF) method. Additionally, this study used the Soil Water Assessment Tool (SWAT) model in two selected sub-basins to estimate deep recharge from the surface hydrological data. The results of the infiltrometer tests show a notable difference in the infiltration rates between the natural vegetation zones and cropped areas. The WTF and SWAT simulations results suggest similar ranges of recharge rate (an average of 24% of precipitation, in both methods). Results of the study indicate equivalence of these methods to estimate the recharge in sedimentary unconfined aquifers as UAS.

The spatial variability of groundwater levels is often inferred from sparsely located hydraulic head observations in wells. The spatial correlation structure derived from sparse observations is associated with uncertainties that spread to estimates at unsampled locations. In areas where surface water represents the nearby groundwater level, remote sensing techniques can estimate and increase the number of hydraulic head measurements. This research uses light detection and ranging (LIDAR) to estimate lake surface water level to characterize the groundwater level in the Nebraska Sand Hills (NSH), an area with few observation wells. The LIDAR derived lake groundwater level accuracy was within 40 cm mean square error (MSE) of the nearest observation wells. The lake groundwater level estimates were used to predict the groundwater level at unsampled locations using universal kriging (UK) and kriging with an external drift (KED). The results indicate unbiased estimates of groundwater level in the NSH. UK showed the influence of regional trends in groundwater level while KED revealed the local variation present in the groundwater level. A 10-fold cross-validation demonstrated KED with better mean squared error (ME) [−0.003, 0.007], root mean square error (RMSE) [2.39, 4.46], residual prediction deviation (RPD) [1.32, 0.71] and mean squared deviation ratio (MSDR) [1.01, 1.49] than UK. The research highlights that the lake groundwater level provides an accurate and cost-effective approach to measure and monitor the subtle changes in groundwater level in the NSH. This methodology can be applied to other locations where surface water bodies represent the water level of the unconfined aquifer and the results can aid in groundwater management and modeling.

The hydrologic function of riverbeds is greatly dependent upon the spatiotemporal distribution of hydraulic conductivity and grain size. Vertical hydraulic conductivity (K v) is highly variable in space and time, and controls the rate of stream–aquifer interaction. Links between sedimentary processes, deposits, and K v heterogeneity have not been well established from field studies. Unit bars are building blocks of fluvial deposits and are key to understanding controls on heterogeneity. This study links unit bar migration to K v and grain size variability in a sand-dominated, low-sinuosity stream in Nebraska (USA) during a single 10-day hydrologic event. An incipient bar formed parallel to the thalweg and was highly permeable and homogenous. During high flow, this bar was submerged under 10–20 cm of water and migrated ~ 100 m downstream and toward the channel margin, where it became markedly heterogeneous. Low-K v zones formed in the subsequent heterogeneous bar downstream of the original 15–40-cm-thick bar front and past abandoned bridge pilings. These low-K v zones correspond to a discontinuous 1-cm layer of fine sand and silt deposited in the bar trough. Findings show that K v heterogeneity relates chiefly to the deposition of suspended materials in low-velocity zones downstream of the bar and obstructions, and to their subsequent burial by migration of the bar during high flow. Deposition of the unit bar itself, although it emplaced the vast majority of the sediment volume, was secondary to bar-trough deposition as a control on the overall pattern of heterogeneity.

Streambeds are critical hydrological interfaces: their physical properties regulate the rate, timing, and location of fluxes between aquifers and streams. Streambed vertical hydraulic conductivity (Kv) is a key parameter in watershed models, so understanding its spatial variability and uncertainty is essential to accurately predicting how stresses and environmental signals propagate through the hydrologic system. Most distributed modeling studies use generalized Kv estimates from column experiments or grain-size distribution, but Kv may include a wide range of orders of magnitude for a given particle size group. Thus, precisely predicting Kv spatially has remained conceptual, experimental, and/or poorly constrained. This usually leads to increased uncertainty in modeling results. There is a need to shift focus from scaling up pore-scale column experiments to watershed dimensions by proposing a new kind of approach that can apply to a whole watershed while incorporating spatial variability of complex hydrological processes. Here we present a new approach, Multi-Stemmed Nested Funnel (MSNF), to develop pedo-transfer functions (PTFs) capable of simulating the effects of complex sediment routing on Kv variability across multiple stream orders in Frenchman Creek watershed, USA. We find that using the product of Kv and drainage area as a response variable reduces the fuzziness in selecting the “best” PTF. We propose that the PTF can be used in predicting the ranges of Kv values across multiple stream orders.

There is a need to evaluate high surface nitrate concentrations across agricultural watersheds, both spatially and temporally, to increase understanding of source and timing of nitrogen loads in streams and rivers. Bazile Creek is a high-nitrate stream originating in the agriculturally intensive Bazile Groundwater Management Area of Eastern Nebraska, USA. It is a gaining stream that receives groundwater with high nitrate concentrations originating from nonpoint sources. The objective of this study was to determine spatial and temporal variability of baseflow nitrate concentrations in Bazile Creek and its tributaries and to relate this variability to watershed characteristics. Surface-water nitrate samples were collected monthly from July 2018 through September 2019 from nine sites in the watershed and were analyzed for nitrate concentration. Average surface water nitrate-N concentrations within the watershed ranged from 2.7 to 15 mg L−1 and were significantly different between the sites (p

Novel groundwater sampling (age, flux, and nitrate) carried out beneath a streambed and in wells was used to estimate (1) the current rate of change of nitrate storage, dSNO3/dt, in a contaminated unconfined aquifer, and (2) future [ NO3−]FWM (the flow-weighted mean nitrate concentration in groundwater discharge) and fNO3 (the nitrate flux from aquifer to stream). Estimates of dSNO3/dt suggested that at the time of sampling (2013) the nitrate storage in the aquifer was decreasing at an annual rate (mean = −9 mmol/m2yr) equal to about one-tenth the rate of nitrate input by recharge. This is consistent with data showing a slow decrease in the [ NO3−] of groundwater recharge in recent years. Regarding future [ NO3−]FWM and fNO3, predictions based on well data show an immediate decrease that becomes more rapid after ∼5 years before leveling out in the early 2040s. Predictions based on streambed data generally show an increase in future [ NO3−]FWM and fNO3 until the late 2020s, followed by a decrease before leveling out in the 2040s. Differences show the potential value of using information directly from the groundwater—surface water interface to quantify the future impact of groundwater nitrate on surface water quality. The choice of denitrification kinetics was similarly important; compared to zero-order kinetics, a first-order rate law levels out estimates of future [ NO3−]FWM and fNO3 (lower peak, higher minimum) as legacy nitrate is flushed from the aquifer. Major fundamental questions about nonpoint-source aquifer contamination can be answered without a complex numerical model or long-term monitoring program.

Methane emissions from streams and rivers have recently been recognized as an important component of global greenhouse budgets. Stream methane is lost as evasion to the atmosphere or in-stream methane oxidation. Previous studies have quantified evasion and oxidation with point-scale measurements. In this study, dissolved gases (methane, krypton) were injected into a coastal plain stream in North Carolina to quantify stream CH4 losses at the watershed scale. Stream-reach modeling yielded gas transfer and oxidation rate constants of 3.2 ± 0.5 and 0.5 ± 1.5 d–1, respectively, indicating a ratio of about 6:1. The resulting evasion and oxidation rates of 2.9 mmol m–2 d–1 and 1,140 nmol L–1 d–1, respectively, lie within ranges of published values. Similarly, the gas transfer velocity (K600) of 2.1 m d–1 is consistent with other gas tracer studies. This study illustrates the utility of dissolved-gas tracers for evaluating stream methane fluxes. In contrast to point measurements, this approach provides a larger w...

We measured groundwater apparent age (τ) and seepage rate (v) in a sandy streambed using point-scale sampling and seepage blankets (a novel seepage meter). We found very similar MTT estimates from streambed point sampling in a 58 m reach (29 years) and a 2.5 km reach (31 years). The TTD for groundwater discharging to the stream was best fit by a gamma distribution model and was very similar for streambed point sampling in both reaches. Between adjacent point-scale and seepage blanket samples, water from the seepage blankets was generally younger, largely because blanket samples contained a fraction of “young” stream water. Correcting blanket data for the stream water fraction brought τ estimates for most blanket samples closer to those for adjacent point samples. The MTT estimates from corrected blanket data were in good agreement with those from sampling streambed points adjacent to the blankets. Collectively, agreement among age-dating tracers, general accord between tracer data and piston-flow model curves, and large groundwater age gradients in the streambed, suggested that the piston flow apparent ages were reasonable estimates of the groundwater transit times for most samples. Overall, our results from two field campaigns suggest that groundwater collected in the streambed can provide reasonable estimates of apparent age of groundwater discharge, and that MTT can be determined from different age-dating tracers and by sampling with different groundwater collection devices. Coupled streambed point measurements of groundwater age and groundwater seepage rate represent a novel, reproducible, and effective approach to estimating aquifer TTD and MTT.

We compared three stream-based sampling methods to study the fate of nitrate in groundwater in a coastal plain watershed: point measurements beneath the streambed, seepage blankets (novel seepage-meter design), and reach mass-balance. The methods gave similar mean groundwater seepage rates into the stream (0.3–0.6 m/d) during two 3–4 day field campaigns despite an order of magnitude difference in stream discharge between the campaigns. At low flow, estimates of flow-weighted mean nitrate concentrations in groundwater discharge ([ NO3−]FWM) and nitrate flux from groundwater to the stream decreased with increasing degree of channel influence and measurement scale, i.e., [ NO3−]FWM was 654, 561, and 451 µM for point, blanket, and reach mass-balance sampling, respectively. At high flow the trend was reversed, likely because reach mass-balance captured inputs from shallow transient high-nitrate flow paths while point and blanket measurements did not. Point sampling may be better suited to estimating aquifer discharge of nitrate, while reach mass-balance reflects full nitrate inputs into the channel (which at high flow may be more than aquifer discharge due to transient flow paths, and at low flow may be less than aquifer discharge due to channel-based nitrate removal). Modeling dissolved N2 from streambed samples suggested (1) about half of groundwater nitrate was denitrified prior to discharge from the aquifer, and (2) both extent of denitrification and initial nitrate concentration in groundwater (700–1300 µM) were related to land use, suggesting these forms of streambed sampling for groundwater can reveal watershed spatial relations relevant to nitrate contamination and fate in the aquifer.

We designed and evaluated a "tube seepage meter" for point measurements of vertical seepage rates (q), collecting groundwater samples, and estimating vertical hydraulic conductivity (K) in streambeds. Laboratory testing in artificial streambeds show that seepage rates from the tube seepage meter agreed well with expected values. Results of field testing of the tube seepage meter in a sandy-bottom stream with a mean seepage rate of about 0.5 m/day agreed well with Darcian estimates (vertical hydraulic conductivity times head gradient) when averaged over multiple measurements. The uncertainties in q and K were evaluated with a Monte Carlo method and are typically 20% and 60%, respectively, for field data, and depend on the magnitude of the hydraulic gradient and the uncertainty in head measurements. The primary advantages of the tube seepage meter are its small footprint, concurrent and colocated assessments of q and K, and that it can also be configured as a self-purging groundwater-sampling device.

The mean transit time (MTT) is a fundamental property of a groundwater flow system that is strongly related to the ratio of recharge rate to storage volume. However, obtaining samples for estimating the MTT using environmental tracers is problematic as flow-weighted samples over the full spectrum of transit times are needed. Samples collected from the base flow of a gaining stream in the North Carolina Coastal Plain (West Bear Creek) that were corrected for exchange with the atmosphere yielded environmental tracer concentrations (SF6 and CFC-11) very similar to flow-weighted values from nine or ten streambed piezometers that directly sampled groundwater during low streamflow. At higher streamflow on the falling limb of the hydrograph, stream tracer concentrations (after correction for gas exchange) were significantly higher than the flow-weighted mean from piezometers, consistent with dominance of the stream tracer signal by transient influx of surface water and/or younger subsurface water. The apparent MTT derived from SF6 in low flow stream water samples was 26 years, suggesting a groundwater recharge rate of about 210 mm/yr, that is consistent with vertical profiles obtained by sampling nested piezometers in the aquifer. When sampled under low flow conditions when streamflow consists of a high component of groundwater discharge, West Bear Creek appears to act as a flow-weighted integrator of transit times and, streamflow samples can provide fundamental information regarding groundwater recharge rate and MTT. Our study suggests that watershed-scale evaluation of some groundwater flow systems is possible without utilizing monitoring wells.

We propose a new method for groundwater recharge rate estimation in regions with stream-aquifer interactions, at a linear scale on the order of 10 km and more. The method is based on visual identification and quantification of classically recognized water table contour patterns. Simple quantitative analysis of these patterns can be done manually from measurements on a map, or from more complex GIS data extraction and curve fitting. Recharge rate is then estimated from the groundwater table contour parameters, streambed gradients, and aquifer transmissivity using an analytical model for groundwater flow between parallel perennial streams. Recharge estimates were obtained in three regions (areas of 1500, 2200, and 3300 km2 ) using available water table maps produced by different methods at different times in the area of High Plains Aquifer in Nebraska. One region is located in the largely undeveloped Nebraska Sand Hills area, while the other two regions are located at a transition zone from Sand Hills to loess-covered area and include areas where groundwater is used for irrigation. Obtained recharge rates are consistent with other independent estimates. The approach is useful and robust diagnostic tool for preliminary estimates of recharge rates, evaluation of the quality of groundwater table maps, identification of priority areas for further aquifer characterization and expansion of groundwater monitoring networks prior to using more detailed methods.

Groundwater discharge though streambeds is often focused toward discrete zones, indicating that preliminary reconnaissance may be useful for capturing the full spectrum of groundwater discharge rates using point-scale quantitative methods. However, many direct-contact reconnaissance techniques can be time-consuming, and remote sensing (e.g., thermal infrared) typically does not penetrate the water column to locate submerged seepages. In this study, we tested whether dozens of groundwater discharge measurements made at &ldquo, uninformed&rdquo, (i.e., selected without knowledge on high-resolution temperature variations at the streambed) point locations along a reach would yield significantly different Darcy-based groundwater discharge rates when compared with &ldquo, informed&rdquo, measurements, focused at streambed thermal anomalies that were identified a priori using fiber-optic distributed temperature sensing (FO-DTS). A non-parametric U-test showed a significant difference between median discharge rates for uninformed (0.05 m&middot, day&minus, 1, n = 30) and informed (0.17 m&middot, n = 20) measurement locations. Mean values followed a similar pattern (0.12 versus 0.27 m&middot, 1), and frequency distributions for uninformed and informed measurements were also significantly different based on a Kolmogorov&ndash, Smirnov test. Results suggest that even using a quick &ldquo, snapshot-in-time&rdquo, field analysis of FO-DTS data can be useful in streambeds with groundwater discharge rates &lt, 0.2 m&middot, 1, a lower threshold than proposed in a previous study. Collectively, study results highlight that FO-DTS is a powerful technique for identifying higher-discharge zones in streambeds, but the pros and cons of informed and uninformed sampling depend in part on groundwater/surface water exchange study goals. For example, studies focused on measuring representative groundwater and solute fluxes may be biased if high-discharge locations are preferentially sampled. However, identification of high-discharge locations may complement more randomized sampling plans and lead to improvements in interpolating streambed fluxes and upscaling point measurements to the stream reach scale.

Summary Recent technological advances have opened the possibility to use webcams and images as part of the environmental monitoring arsenal. The potential sources and magnitude of uncertainties inherent to an image-based water level measurement system are evaluated in an experimental design in the laboratory. Sources of error investigated include image resolution, lighting effects, perspective, lens distortion and water meniscus. Image resolution and meniscus were found to weigh the most in the overall uncertainty of this system. Image distortion, although largely taken into account by the software developed, may also significantly add to uncertainty. Results suggest that “flat” images with little distortion are preferable. After correction for the water meniscus, images captured with a camera (12 mm or 16 mm focal lengths) positioned 4–7 m from the water level edge have the potential to yield water level measurements within ±3 mm when using this technique.

Shallow aquifers are prone to nitrate contamination worldwide. In western Nebraska, high groundwater nitrate concentrations ([NO3&minus, ]) have resulted in the exploration of new groundwater and nitrogen management regulations in the North Platte Natural Resources District (NPNRD). A small region of NPNRD (&ldquo, Dutch Flats&rdquo, ) was the focus of intensive groundwater sampling by the United States Geological Survey from 1995 to 1999. Nearly two decades later, notable shifts have occurred in variables related to groundwater recharge and [NO3&minus, ], including irrigation methods. The objective of this study was to evaluate how changes in these variables, in part due to regulatory changes, have impacted nitrate-contaminated groundwater in the Dutch Flats area. Groundwater samples were collected to assess changes in: (1) recharge rates, (2) biogeochemical processes, and (3) [NO3&minus, ]. Groundwater age increased in 63% of wells and estimated recharge rates were lower for 88% of wells sampled (n = 8). However, mean age and recharge rate estimated in 2016 (19.3 years, R = 0.35 m/year) did not differ significantly from mean values determined in 1998 (15.6 years, R = 0.50 m/year). &delta, 15N-NO3&minus, (n = 14) and dissolved oxygen data indicate no major changes in biogeochemical processes. Available long-term data suggest a downward trend in normalized [NO3&minus, ] from 1998 to 2016, and lower [NO3&minus, ] was observed in 60% of wells sampled in both years (n = 87), but median values were not significantly different. Collectively, results suggest the groundwater system is responding to environmental variables to a degree that is detectable (e.g., trends in [NO3&minus, ]), although more time and/or substantial changes may be required before it is possible to detect significantly different mean recharge.