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USGS2015

Riverbed clogging associated with a California riverbank filtration system: An assessment of mechanisms and monitoring approaches

An experimental field study was performed to investigate riverbed clogging processes and associated monitoring approaches near a dam-controlled riverbank filtration facility in Northern California. Motivated by previous studies at the site that indicated riverbed clogging plays an important role in the performance of the riverbank filtration system, we investigated the spatiotemporal variability and nature of the clogging. In particular, we investigated whether the clogging was due to abiotic or biotic mechanisms. A secondary aspect of the study was the testing of different methods to monitor riverbed clogging and related processes, such as seepage. Monitoring was conducted using both point-based approaches and spatially extensive geophysical approaches, including: grain-size analysis, temperature sensing, electrical resistivity tomography, seepage meters, microbial analysis, and cryocoring, along two transects. The point monitoring measurements suggested a substantial increase in riverbed biomass (2 orders of magnitude) after the dam was raised compared to the small increase (∼2%) in fine-grained sediment. These changes were concomitant with decreased seepage. The decreased seepage eventually led to the development of an unsaturated zone beneath the riverbed, which further decreased infiltration capacity. Comparison of our time-lapse grain-size and biomass datasets suggested that biotic processes played a greater role in clogging than did abiotic processes. Cryocoring and autonomous temperature loggers were most useful for locally monitoring clogging agents, while electrical resistivity data were useful for interpreting the spatial extent of a pumping-induced unsaturated zone that developed beneath the riverbed after riverbed clogging was initiated. The improved understanding of spatiotemporally variable riverbed clogging and monitoring approaches is expected to be useful for optimizing the riverbank filtration system operations.

Journal of Hydrology↗

USGS2015

Groundwater recharge assessment at local and episodic scale in a soil mantled perched karst aquifer in southern Italy

Groundwater recharge assessment of karst aquifers, at various spatial and temporal scales, is a major scientific topic of current importance, since these aquifers play an essential role for both socio-economic development and fluvial ecosystems. In this study, groundwater recharge was estimated at local and episodic scales in a representative perched karst aquifer in a region of southern Italy with a Mediterranean climate. The research utilized measurements of precipitation, air temperature, soil water content, and water-table depth, obtained in 2008 at the Acqua della Madonna test area (Terminio Mount karst aquifer, Campania region). At this location the aquifer is overlain by ash-fall pyroclastic soils. The Episodic Master Recession (EMR) method, an improved version of the Water Table Fluctuation (WTF) method, was applied to estimate the amount of recharge generated episodically by individual rainfall events. The method also quantifies the amount of precipitation generating each recharge episode, thus permitting calculation of the Recharge to the Precipitation Ratio (RPR) on a storm-by-storm basis. Depending on the seasonally varying air temperature, evapotranspiration, and precipitation patterns, calculated values of RPR varied between 35% and 97% among the individual episodes. A multiple linear correlation of the RPR with both the average intensity of recharging rainfall events and the antecedent soil water content was calculated. Given the relatively easy measurability of precipitation and soil water content, such an empirical model would have great hydrogeological and practical utility. It would facilitate short-term forecasting of recharge in karst aquifers of the Mediterranean region and other aquifers with similar hydrogeological characteristics. By establishing relationships between the RPR and climate-dependent variables such as average storm intensity, it would facilitate prediction of climate-change effects on groundwater recharge. The EMR methodology could further be applied to other aquifers for evaluating the relationship of recharge to various hydrometeorological and hydrogeological processes.

Journal of Hydrology↗

USGS2015

A comparison of thermal infrared to fiber-optic distributed temperature sensing for evaluation of groundwater discharge to surface water

Groundwater has a predictable thermal signature that can be used to locate discrete zones of discharge to surface water. As climate warms, surface water with strong groundwater influence will provide habitat stability and refuge for thermally stressed aquatic species, and is therefore critical to locate and protect. Alternatively, these discrete seepage locations may serve as potential point sources of contaminants from polluted aquifers. This study compares two increasingly common heat tracing methods to locate discrete groundwater discharge: direct-contact measurements made with fiber-optic distributed temperature sensing (FO-DTS) and remote sensing measurements collected with thermal infrared (TIR) cameras. FO-DTS is used to make high spatial resolution (typically m) thermal measurements through time within the water column using temperature-sensitive cables. The spatialtemporal data can be analyzed with statistical measures to reveal zones of groundwater influence, however, the personnel requirements, time to install, and time to georeference the cables can be burdensome, and the control units need constant calibration. In contrast, TIR data collection, either from handheld, airborne, or satellite platforms, can quickly capture point-in-time evaluations of groundwater seepage zones across large scales. However the remote nature of TIR measurements means they can be adversely influenced by a number of environmental and physical factors, and the measurements are limited to the surface skin temperature of water features. We present case studies from a range of lentic to lotic aquatic systems to identify capabilities and limitations of both technologies and highlight situations in which one or the other might be a better instrument choice for locating groundwater discharge. FO-DTS performs well in all systems across seasons, but data collection was limited spatially by practical considerations of cable installation. TIR is found to consistently locate groundwater seepage zones above and along the streambank, but submerged seepage zones are only well identified in shallow systems (e.g. <0.5 m depth) with moderate flow. Winter data collection, when groundwater is relatively warm and buoyant, increases the water surface expression of discharge zones in shallow systems.

Massachusetts, Michigan, Montana, New York, Pennsy↗

USGS2015

A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA

We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R 2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R 2 and a version with R 2 within one standard error of the maximum (the 1SE model). The former yielded CV training R 2 values of 0.94–1.0. Cross-validation testing R 2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R 2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R 2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R 2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

California↗

USGS2015

Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain

Growing use of two-dimensional (2-D) hydraulic models has created a need for high resolution data to support flood volume estimates, floodplain specific engineering data, and accurate flood inundation scenarios. Elevation data are a critical input to these models that guide the flood-wave across the landscape allowing the computation of valuable engineering specific data that provides a better understanding of flooding impacts on structures, debris movement, bed scour, and direction. High resolution elevation data are becoming publicly available that can benefit the 2-D flood modeling community. Comparison of these newly available data with legacy data suggests that better modeling outcomes are achieved by using 3D Elevation Program (3DEP) lidar point data and the derived 1 m Digital Elevation Model (DEM) product relative to the legacy 3 m, 10 m, or 30 m products currently available in the U.S. Geological Survey (USGS) National Elevation Dataset. Within the low topographic relief of a coastal floodplain, the newer 3DEP data better resolved elevations within the forested and swampy areas achieving simulations that compared well with a historic flooding event. Results show that the 1 m DEM derived from 3DEP lidar source provides a more conservative estimate of specific energy, static pressure, and impact pressure for grid elements at maximum flow relative to the legacy DEM data. Better flood simulations are critically important in coastal floodplains where climate change driven storm frequency and sea level rise will contribute to more frequent flooding events.

North Carolina↗

USGS2016

Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites

Evapotranspiration (ET) is an important component of the water cycle – ET from the land surface returns approximately 60% of the global precipitation back to the atmosphere. ET also plays an important role in energy transport among the biosphere, atmosphere, and hydrosphere. Current regional to global and daily to annual ET estimation relies mainly on surface energy balance (SEB) ET models or statistical and empirical methods driven by remote sensing data and various climatological databases. These models have uncertainties due to inevitable input errors, poorly defined parameters, and inadequate model structures. The eddy covariance measurements on water, energy, and carbon fluxes at the AmeriFlux tower sites provide an opportunity to assess the ET modeling uncertainties. In this study, we focused on uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model for ET estimation at multiple AmeriFlux tower sites with diverse land cover characteristics and climatic conditions. The 8-day composite 1-km MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) was used as input land surface temperature for the SSEBop algorithms. The other input data were taken from the AmeriFlux database. Results of statistical analysis indicated that the SSEBop model performed well in estimating ET with an R2 of 0.86 between estimated ET and eddy covariance measurements at 42 AmeriFlux tower sites during 2001–2007. It was encouraging to see that the best performance was observed for croplands, where R2 was 0.92 with a root mean square error of 13 mm/month. The uncertainties or random errors from input variables and parameters of the SSEBop model led to monthly ET estimates with relative errors less than 20% across multiple flux tower sites distributed across different biomes. This uncertainty of the SSEBop model lies within the error range of other SEB models, suggesting systematic error or bias of the SSEBop model is within the normal range. This finding implies that the simplified parameterization of the SSEBop model did not significantly affect the accuracy of the ET estimate while increasing the ease of model setup for operational applications. The sensitivity analysis indicated that the SSEBop model is most sensitive to input variables, land surface temperature (LST) and reference ET ( ET o ); and parameters, differential temperature ( dT ), and maximum ET scalar ( K max ), particularly during the non-growing season and in dry areas. In summary, the uncertainty assessment verifies that the SSEBop model is a reliable and robust method for large-area ET estimation. The SSEBop model estimates can be further improved by reducing errors in two input variables ( ET o and LST) and two key parameters ( K max and dT ).

Journal of Hydrology↗

USGS2016

A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells

A partial exponential lumped parameter model (PEM) was derived to determine age distributions and nitrate trends in long-screened production wells. The PEM can simulate age distributions for wells screened over any finite interval of an aquifer that has an exponential distribution of age with depth. The PEM has 3 parameters – the ratio of saturated thickness to the top and bottom of the screen and mean age, but these can be reduced to 1 parameter (mean age) by using well construction information and estimates of the saturated thickness. The PEM was tested with data from 30 production wells in a heterogeneous alluvial fan aquifer in California, USA. Well construction data were used to guide parameterization of a PEM for each well and mean age was calibrated to measured environmental tracer data ( 3 H, 3 He, CFC-113, and 14 C). Results were compared to age distributions generated for individual wells using advective particle tracking models (PTMs). Age distributions from PTMs were more complex than PEM distributions, but PEMs provided better fits to tracer data, partly because the PTMs did not simulate 14 C accurately in wells that captured varying amounts of old groundwater recharged at lower rates prior to groundwater development and irrigation. Nitrate trends were simulated independently of the calibration process and the PEM provided good fits for at least 11 of 24 wells. This work shows that the PEM, and lumped parameter models (LPMs) in general, can often identify critical features of the age distributions in wells that are needed to explain observed tracer data and nonpoint source contaminant trends, even in systems where aquifer heterogeneity and water-use complicate distributions of age. While accurate PTMs are preferable for understanding and predicting aquifer-scale responses to water use and contaminant transport, LPMs can be sensitive to local conditions near individual wells that may be inaccurately represented or missing in an aquifer-scale flow model.

California↗

USGS2016

Hydrogeologic controls on groundwater discharge and nitrogen loads in a coastal watershed

Submarine groundwater discharge (SGD) is a small portion of the global water budget, but a potentially large contributor to coastal nutrient budgets due to high concentrations relative to stream discharge. A numerical groundwater flow model of the Inland Bays Watershed, Delaware, USA, was developed to identify the primary hydrogeologic factors that affect groundwater discharge rates and transit times to streams and bays. The distribution of groundwater discharge between streams and bays is sensitive to the depth of the water table below land surface. Higher recharge and reduced hydraulic conductivity raised the water table and increased discharge to streams relative to bays compared to the Reference case (in which 66% of recharge is discharged to streams). Increases to either factor decreased transit times for discharge to both streams and bays compared to the Reference case (in which mean transit times are 56.5 and 94.3 years, respectively), though sensitivity to recharge is greater. Groundwater-borne nitrogen loads were calculated from nitrogen concentrations measured in discharging fresh groundwater and modeled SGD rates. These loads combined with long SGD transit times suggest groundwater-borne nitrogen reductions and estuarine water quality improvements will lag decades behind implementation of efforts to manage nutrient sources. This work enhances understanding of the hydrogeologic controls on and uncertainties in absolute and relative rates and transit times of groundwater discharge to streams and bays in coastal watersheds.

Journal of Hydrology↗

USGS2016

Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O 2 reduction and denitrification (NO 3 − reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF 6 , CFCs, 3 H, He from 3 H (tritiogenic He), 14 C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO 3 − and dissolved gas data to estimate zero order and first order rates of O 2 reduction and denitrification. Results indicated that O 2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O 2 and NO 3 − reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O 2 reduction rates. Estimated historical NO 3 − trends were similar to historical measurements. Results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O 2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.

California↗

USGS2016

An evaluation of methods for estimating decadal stream loads

Effective management of water resources requires accurate information on the mass, or load of water-quality constituents transported from upstream watersheds to downstream receiving waters. Despite this need, no single method has been shown to consistently provide accurate load estimates among different water-quality constituents, sampling sites, and sampling regimes. We evaluate the accuracy of several load estimation methods across a broad range of sampling and environmental conditions. This analysis uses random sub-samples drawn from temporally-dense data sets of total nitrogen, total phosphorus, nitrate, and suspended-sediment concentration, and includes measurements of specific conductance which was used as a surrogate for dissolved solids concentration. Methods considered include linear interpolation and ratio estimators, regression-based methods historically employed by the U.S. Geological Survey, and newer flexible techniques including Weighted Regressions on Time, Season, and Discharge (WRTDS) and a generalized non-linear additive model. No single method is identified to have the greatest accuracy across all constituents, sites, and sampling scenarios. Most methods provide accurate estimates of specific conductance (used as a surrogate for total dissolved solids or specific major ions) and total nitrogen – lower accuracy is observed for the estimation of nitrate, total phosphorus and suspended sediment loads. Methods that allow for flexibility in the relation between concentration and flow conditions, specifically Beale’s ratio estimator and WRTDS, exhibit greater estimation accuracy and lower bias. Evaluation of methods across simulated sampling scenarios indicate that (1) high-flow sampling is necessary to produce accurate load estimates, (2) extrapolation of sample data through time or across more extreme flow conditions reduces load estimate accuracy, and (3) WRTDS and methods that use a Kalman filter or smoothing to correct for departures between individual modeled and observed values benefit most from more frequent water-quality sampling.

Journal of Hydrology↗

USGS2017

New insights into nitrate dynamics in a karst groundwater system gained from in situ high-frequency optical sensor measurements

Understanding nitrate dynamics in groundwater systems as a function of climatic conditions, especially during contrasting patterns of drought and wet cycles, is limited by a lack of temporal and spatial data. Nitrate sensors have the capability for making accurate, high-frequency measurements of nitrate in situ, but have not yet been evaluated for long-term use in groundwater wells. We measured in situ nitrate continuously in two groundwater monitoring wells —one rural and one urban—located in the recharge zone of a productive karst aquifer in central Texas in order to resolve changes that occur over both short-term (hourly to daily) and long-term (monthly to yearly) periods. Nitrate concentrations, measured as nitrate-nitrogen in milligrams per liter (mg/L), during drought conditions showed little or no temporal change as groundwater levels declined. During aquifer recharge, extremely rapid changes in concentration occurred at both wells as documented by hourly data. At both sites, nitrate concentrations were affected by recharging surface water as evidenced by nitrate concentrations in groundwater recharge (0.8–1.3 mg/L) that were similar to previously reported values for regional recharging streams. Groundwater nitrate concentrations responded differently at urban and rural sites during groundwater recharge. Concentrations at the rural well (approximately 1.0 mg/L) increased as a result of higher nitrate concentrations in groundwater recharge relative to ambient nitrate concentrations in groundwater, whereas concentrations at the urban well (approximately 2.7 mg/L) decreased as a result of the dilution of higher ambient nitrate concentrations relative to those in groundwater recharge. Notably, nitrate concentrations decreased to as low as 0.8 mg/L at the urban site during recharge but postrecharge concentrations exceeded 3.0 mg/L. A return to higher nitrate concentrations postrecharge indicates mobilization of a localized source of elevated nitrate within the urbanized area of the aquifer. Changes in specific conductance were observed at both sites during groundwater recharge, and a significant correlation between specific conductance and nitrate (correlation coefficient [R] = 0.455) was evident at the urban site where large (3-fold) changes in nitrate occurred. Nitrate concentrations and specific conductance measured during a depth profile indicated that the water column was generally homogeneous as expected for this karst environment, but changes were observed in the most productive zone of the aquifer that might indicate some heterogeneity within the complex network of flow paths. Resolving the timing and magnitude of changes and characterizing fine-scale vertical differences would not be possible using conventional sampling techniques. The patterns observed in situ provided new insight into the dynamic nature of nitrate in a karst groundwater system.

Texas↗

USGS2017

Trends in snowmelt-related streamflow timing in the conterminous United States

Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940–2014 and 1960–2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (<1600 m) basins in the West, predominantly located in the Northwest, had median earlier WSCVD by 6.8 days (1940–2014, 0.9 days/decade) and 3.4 days (1960–2014, 0.6 days/decade). Streamflow timing at high-elevation (⩾1600 m) basins in the West had median earlier WSCVD by 4.0 days (1940–2014, 0.5 days/decade) and 5.2 days (1960–2014, 0.9 days/decade). Trends toward earlier WSCVD in the Northwest were not statistically significant, differing from previous studies that observed many large and (or) significant trends in this region. Much of this difference is likely due to the sensitivity of trend tests to the time period being tested, as well as differences in the streamflow timing metrics used among the studies. Mean February–May air temperature was significantly correlated with WSCVD at 100 percent of the study gages (field significant, p < 0.0001), demonstrating the sensitivity of WSCVD to air temperature across snowmelt dominated basins in the U.S. WSCVD in high elevation basins in the West, however, was related to both air temperature and precipitation yielding earlier snowmelt-related streamflow timing under warmer and drier conditions.

Journal of Hydrology↗

USGS2017

Climate-driven variability in the occurrence of major floods across North America and Europe

Concern over the potential impact of anthropogenic climate change on flooding has led to a proliferation of studies examining past flood trends. Many studies have analysed annual-maximum flow trends but few have quantified changes in major (25–100 year return period) floods, i.e. those that have the greatest societal impacts. Existing major-flood studies used a limited number of very large catchments affected to varying degrees by alterations such as reservoirs and urbanisation. In the current study, trends in major-flood occurrence from 1961 to 2010 and from 1931 to 2010 were assessed using a very large dataset (>1200 gauges) of diverse catchments from North America and Europe; only minimally altered catchments were used, to focus on climate-driven changes rather than changes due to catchment alterations. Trend testing of major floods was based on counting the number of exceedances of a given flood threshold within a group of gauges. Evidence for significant trends varied between groups of gauges that were defined by catchment size, location, climate, flood threshold and period of record, indicating that generalizations about flood trends across large domains or a diversity of catchment types are ungrounded. Overall, the number of significant trends in major-flood occurrence across North America and Europe was approximately the number expected due to chance alone. Changes over time in the occurrence of major floods were dominated by multidecadal variability rather than by long-term trends. There were more than three times as many significant relationships between major-flood occurrence and the Atlantic Multidecadal Oscillation than significant long-term trends.

Journal of Hydrology↗

USGS2017

Groundwater-level trends in the U.S. glacial aquifer system, 1964-2013

The glacial aquifer system in the United States is a major source of water supply but previous work on historical groundwater trends across the system is lacking. Trends in annual minimum, mean, and maximum groundwater levels for 205 monitoring wells were analyzed across three regions of the system (East, Central, West Central) for four time periods: 1964-2013, 1974-2013, 1984-2013, and 1994-2013. Trends were computed separately for wells in the glacial aquifer system with low potential for human influence on groundwater levels and ones with high potential influence from activities such as groundwater pumping. Generally there were more wells with significantly increasing groundwater levels (levels closer to ground surface) than wells with significantly decreasing levels. The highest numbers of significant increases for all four time periods were with annual minimum and/or mean levels. There were many more wells with significant increases from 1964 to 2013 than from more recent periods, consistent with low precipitation in the 1960s. Overall there were low numbers of wells with significantly decreasing trends regardless of time period considered; the highest number of these were generally for annual minimum groundwater levels at wells with likely human influence. There were substantial differences in the number of wells with significant groundwater-level trends over time, depending on whether the historical time series are assumed to be independent, have short-term persistence, or have long-term persistence. Mean annual groundwater levels have significant lag-one-year autocorrelation at 26.0% of wells in the East region, 65.4% of wells in the Central region, and 100% of wells in the West Central region. Annual precipitation across the glacial aquifer system, on the other hand, has significant autocorrelation at only 5.5% of stations, about the percentage expected due to chance.

Journal of Hydrology↗

USGS2018

Climate variability and vadose zone controls on damping of transient recharge

Increasing demand on groundwater resources motivates understanding of the controls on recharge dynamics so model predictions under current and future climate may improve. Here we address questions about the nonlinear behavior of flux variability in the vadose zone that may explain previously reported teleconnections between global-scale climate variability and fluctuations in groundwater levels. We use hundreds of HYDRUS-1D simulations in a sensitivity analysis approach to evaluate the damping depth of transient recharge over a range of periodic boundary conditions and vadose zone geometries and hydraulic parameters that are representative of aquifer systems of the conterminous United States (U.S). Although the models were parameterized based on U.S. aquifers, findings from this study are applicable elsewhere that have mean recharge rates between 3.65 and 730 mm yr –1 . We find that mean infiltration flux, period of time varying infiltration, and hydraulic conductivity are statistically significant predictors of damping depth. The resulting framework explains why some periodic infiltration fluxes associated with climate variability dampen with depth in the vadose zone, resulting in steady-state recharge, while other periodic surface fluxes do not dampen with depth, resulting in transient recharge. We find that transient recharge in response to the climate variability patterns could be detected at the depths of water levels in most U.S. aquifers. Our findings indicate that the damping behavior of transient infiltration fluxes is linear across soil layers for a range of texture combinations. The implications are that relatively simple, homogeneous models of the vadose zone may provide reasonable estimates of the damping depth of climate-varying transient recharge in some complex, layered vadose zone profiles.

Journal of Hydrology↗

USGS2018

Drought-induced recharge promotes long-term storage of porewater salinity beneath a prairie wetland

Subsurface storage of sulfate salts allows closed-basin wetlands in the semiarid Prairie Pothole Region (PPR) of North America to maintain moderate surface water salinity (total dissolved solids [TDS] from 1 to 10 g L −1 ), which provides critical habitat for communities of aquatic biota. However, it is unclear how the salinity of wetland ponds will respond to a recent shift in mid-continental climate to wetter conditions. To understand better the mechanisms that control surface-subsurface salinity exchanges during regional dry-wet climate cycles, we made a detailed geoelectrical study of a closed-basin prairie wetland (P1 in the Cottonwood Lake Study Area, North Dakota) that is currently experiencing record wet conditions. We found saline lenses of sulfate-rich porewater (TDS > 10 g L −1 ) contained in fine-grained wetland sediments 2–4 m beneath the bathymetric low of the wetland and within the currently ponded area along the shoreline of a prior pond stand ( c . 1983). During the most recent drought (1988–1993), the wetland switched from a groundwater discharge to recharge function, allowing salts dissolved in surface runoff to move into wetland sediments beneath the bathymetric low of the basin. However, groundwater levels during this time did not decline to the elevation of the saline lenses, suggesting these features formed during more extended paleo-droughts and are stable in the subsurface on at least centennial timescales. We hypothesize a “drought-induced recharge” mechanism that allows wetland ponds to maintain moderate salinity under semiarid climate. Discharge of drought-derived saline groundwater has the potential to increase the salinity of wetland ponds during wet climate.

North Dakota↗

USGS2018

The suitability of using dissolved gases to determine groundwater discharge to high gradient streams

Determining groundwater discharge to streams using dissolved gases is known to be useful over a wide range of streamflow rates but the suitability of dissolved gas methods to determine discharge rates in high gradient mountain streams has not been sufficiently tested, even though headwater streams are critical as ecological habitats and water resources. The aim of this study is to test the suitability of using dissolved gases to determine groundwater discharge rates to high gradient streams by field experiments in a well-characterized, high gradient mountain stream and a literature review. At a reach scale (550 m) we combined stream and groundwater radon activity measurements with an in-stream SF 6 tracer test. By means of numerical modeling we determined gas exchange velocities and derived very low groundwater discharge rates (∼15% of streamflow). These groundwater discharge rates are below the uncertainty range of physical streamflow measurements and consistent with temperature, specific conductance and streamflow measured at multiple locations along the reach. At a watershed-scale (4 km), we measured CFC-12 and δ 18 O concentrations and determined gas exchange velocities and groundwater discharge rates with the same numerical model. The groundwater discharge rates along the 4 km stream reach were highly variable, but were consistent with the values derived in the detailed study reach. Additionally, we synthesized literature values of gas exchange velocities for different stream gradients which show an empirical relationship that will be valuable in planning future dissolved gas studies on streams with various gradients. In sum, we show that multiple dissolved gas tracers can be used to determine groundwater discharge to high gradient mountain streams from reach to watershed scales.

California↗

USGS2018

Managing the water-energy-food nexus: Opportunities in Central Asia

This article examines impacts of infrastructure development and climate variability on economic outcomes for the Amu Darya Basin in Central Asia. It aims to identify the most economically productive mix of expanded reservoir storage for economic benefit sharing to occur, in which economic welfare of all riparians is improved. Policies examined include four combinations of storage infrastructure for each of two climate futures. An empirical optimization model is developed and applied to identify opportunities for improving the welfare of Tajikistan, Uzbekistan, Afghanistan, and Turkmenistan. The analysis 1) characterizes politically constrained and economically optimized water-use patterns for these combinations of expanded reservoir storage capacity, 2) describes Pareto-Improving packages of expanded storage capacity that could raise economic welfare for all four riparians, and accounts for impacts for each of two climate scenarios. Results indicate that a combination of targeted water storage infrastructure and efficient water allocation could produce outcomes for which the discounted net present value of benefits are favorable for each riparian. Results identify a framework to provide economic motivation for all riparians to cooperate through development of water storage infrastructure. Our findings illustrate the principle that development of water infrastructure can expand the negotiation space by which all communities can gain economic benefits in the face of limited water supply. Still, despite our optimistic findings, patient and deliberate negotiation will be required to transform potential improvements into actual gains.

Journal of Hydrology↗