Spatial and temporal groundwater dynamics in extreme arid basins

To accurately obtain the spatial distribution characteristics of groundwater level in an extremely arid zone and its dynamic change patterns under the influence of human activities, based on the data of 55 groundwater observation wells in the middle and lower reaches of the Kriya River, spatial interpolation of regional groundwater level data were performed using the inverse distance weight, spline function, trend surface, and the ordinary kriging methods. The optimal interpolation method was selected by its accuracy to spatially interpolate the groundwater level data in the study area from 2019 to 2021. The results show that: (1) the ordinary kriging method has the highest interpolation accuracy (MAE = 7.1393, MRE = 0.0058, RMSE = 9.4314) and reflects the spatial and temporal variability and distribution characteristics of groundwater levels with great accuracy. (2)The relationship between surface water–groundwater recharge and discharge in different areas of the river channel in the desert section varies depending on geological structure, surface water seepage, and other elements. (3) Groundwater in the Taklamakan Desert has little effect on groundwater recharge in the Dariyabui Oasis, and changes in groundwater dynamics in the oasis are predominantly influenced by surface runoff. (4) Monthly changes in groundwater levels in the Yutian Oasis are continuous, with ‘V’ shaped fluctuations, a declining trend in the southern part, no significant change in the central part, and a slight increase in the northern part. These results contribute to the sustainable management of water resources in the Kriya River Basin, provide a basis for groundwater prediction, and offer a reference for studies of other, similar extreme desert area basins.     

Mapping groundwater quality in the Netherlands

Maps of 25 groundwater quality variables were obtained by estimating 4 km × 4 km block median concentrations. Estimates were presented as approximate 95% confidence intervals related to four concentration levels mostly obtained from critical levels for human consumption. These maps were based on measurements from 425 monitoring sites of national and provincial groundwater quality monitoring networks. The estimation procedure was based on a stratification by soil type and land use. Within each soil-land use category, measurements were interpolated. Spatial dependence between measurements and regional differences in mean level were taken into account. Stratification turned out to be essential: no or partial stratification (using either soil type or land use) results in essentially different maps. The effect of monitoring network density was studied by leaving out the 173 monitoring sites of the provincial monitoring networks. Important changes in resulting maps were assigned to loss of information on short-distance variation, as well as loss of location-specific information. For 12 variables, maps of changes in groundwater quality were made by spatial interpolation of short-term predictions calculated for each well screen from time series of yearly measurements over 5–7 years, using a simple regression model for variation over time and taking location-specific time-prediction uncertainties into account.

From a policy point of view, the resulting maps can be used either for quantifying diffuse groundwater contamination and location-specific background concentrations (in order to assist local contamination assessment) or for input and validation of policy supporting regional or national groundwater quality models. The maps can be considered as a translation of point information obtained from the monitoring networks into information on spatial units, the size of which is used in regional groundwater models. The maps enable location-specific network optimization. In general, the maps give little reason for reducing the monitoring network density (wide confidence intervals).     

Mapping groundwater quality variables using PCA and geostatistics: a case study of Bajo Andarax,southeastern Spain

Abstract

A case study is presented for the application of statistical and geostatistical methods to the problem of estimating groundwater quality variables. This methodology has been applied to the investigation of the detrital aquifer of the Bajo Andarax (Almería, Spain). The use of principal components analysis is proposed, as a first step, for identifying relevant types of groundwater and the processes that bring about a change in their quality. As a result of this application, three factors were obtained, which were used as three new variables (VI: sulphate influence; V2: thermal influence; and V3: marine influence). Analysis of their spatial distribution was performed through the calculation of experimental and theoretical variograms, which served as input for geostatistical modelling using ordinary block kriging. This analysis has allowed a probabilistic representation of the data to be obtained by mapping the three variables throughout the aquifer for each sampling point. In this way, one can evaluate the spatial and temporal variation of the principal physico-chemical processes associated with the three variables VI, V2 and V3 implicated in the groundwater quality of the detrital aquifer.     

Understanding fen hydrology across multiple scales

Fens, which are among the most biodiverse of wetland types in the USA, typically occur in glacial landscapes characterized by geo‐morphologic variability at multiple spatial scales. As a result, the hydrologic systems that sustain fens are complex and not well understood. Traditional approaches for characterizing such systems use simplifying assumptions that cannot adequately capture the impact of variability in geology and topography. In this study, a hierarchical, multi‐scale groundwater modelling approach coupled with a geologic model is used to understand the hydrology of a fen in Michigan. This approach uses high‐resolution data to simulate the multi‐scale topographic and hydrologic framework and lithologic data from more than 8500 boreholes in a statewide water well database to capture the complex geology. A hierarchy of dynamically linked models is developed that simulates groundwater flow at all scales of interest and to delineate the areas that contribute groundwater to the fen. The results show the fen receiving groundwater from multiple sources: an adjacent wetland, local recharge, a nearby lake and a regional groundwater mound. Water from the regional mound flows to an intermediate source before reaching the fen, forming a ‘cascading’ connection, while other sources provide water through ‘direct’ connections. The regional mound is also the source of water to other fens, streams and lakes in this area, thus creating a large, interconnected hydrologic system that sustains the entire ecosystem. In order to sustainably manage such systems, conservation efforts must include both site‐based protection and management, as well as regional protection and management of groundwater source areas. Copyright © 2016 John Wiley & Sons, Ltd.     

Temporal change of spatial heterogeneity and its effect on regional trend of annual precipitation heterogeneity indices

A statistical test on climate and hydrological series from different spatial resolution could obtain different regional trend due to spatial heterogeneity and its temporal variability. In this study, annual series of the precipitation heterogeneity indices of concentration index (CI) and the number of wet days (NW) along with annual total amount of precipitation were calculated based on at‐site daily precipitation series during 1962–2011 in the headwater basin of the Huaihe River, China. The regional trends of the indices were first detected based on at‐site series by using the aligned and intrablock methods, and field significance tests that consider spatial heterogeneity over sites. The detected trends were then compared with the trends of the regional index series derived from daily areal average precipitation (DAAP), which averages at‐site differences and thus neglects spatial heterogeneity. It was found that the at‐site‐based regional test shows increasing trends of CI and NW in the basin, which follows the test on individual sites that most of sites were characterized by increasing CI and NW. However, the DAAP‐derived regional series of CI and NW were tested to show a decreasing trend. The disparity of the regional trend test on at‐site‐based regional series and the DAAP‐derived regional series arises from a temporal change of the spatial heterogeneity, which was quantified by the generalized additive models for location, scale, and shape. This study highlights that compared with averaging indices, averaging at‐site daily precipitation could lead to an error in the regional trend inference on annual precipitation heterogeneity indices. More attention should be paid to temporal variability in spatial heterogeneity when data at large scales are used for regional trend detection on hydro‐meteorological events associated with intra‐annual heterogeneity.     

Applying a Regional Transport Modeling Framework to Manage Nitrate Contamination of Groundwater

Regional nitrate contamination in groundwater is a management challenge involving multisector benefits. There is always conflict between restricting anthropogenic activities to protect groundwater quality and prioritizing economic development, especially in productive agriculture dominated areas. To mitigate the nitrate contamination in groundwater, it is necessary to develop management alternatives that simultaneously support environmental protection and sustainable economic development. A regional transport modeling framework is applied to evaluate nitrate fate and transport in the Dagu Aquifer, a shallow sandy aquifer that supplies drinking water and irrigation water for a thriving agricultural economy in Shandong Province in east coastal China. The aquifer supports intensive high-value vegetable farms and nitrate contamination is extensive. Detailed land-use information and fertilizer use data were compiled and statistical approaches were employed to analyze nitrogen source loadings and the spatiotemporal distribution of nitrate in groundwater to support model construction and calibration. The evaluations reveal that the spatial distribution and temporal trends of nitrate contamination in the Dagu Aquifer are driven by intensive fertilization and vertical water exchange, the dominant flow pattern derived from intensive agricultural pumping and irrigation. The modeling framework is employed to assess the effectiveness of potentially applicable management alternatives. The predictive results provide quantitative comparisons for the trend and extent of groundwater quality mitigation under each scenario. Recommendations are made for measures that can both improve groundwater quality and sustain productive agricultural development.     

Quantifying climate internal variability using an hourly ensemble generator over South Korea

Identifying climate internal variability (CIV) generated by non-linear interactions and feedbacks among many components of the climate system is essential and challenging because of its irreducible and unpredictable characteristics. A range of studies have addressed this issue; however, these studies focused on the first order moments of few representative climate variables at relatively larger spatial and temporal scales. To investigate the magnitude and the spatial pattern of CIV relevant at finer spatial (point) and temporal (hourly) scales, CIV is assessed over a 30-year period in South Korea by analyzing 100-member ensemble generated using an hourly weather generator and a bootstrapping approach. Statistics addressing the first and second order moments, occurrences, and extremes are successfully verified at various temporal scales. The CIV is then estimated by the ‘detrended’ and ‘differenced’ methods for the four metrics proposed at different scales that signify rainfall volume, maxima, and occurrence. Consequently, the implications of this study are the following: (1) the estimation of CIV using bootstrapped ensembles often fails to represent the proper uncertainty range, resulting in high chances of underestimating extreme statistics, such as the maximum rainfall depth; (2) regardless of which of the two methods is used, no significant difference in the CIV estimation is observed; and (3) a temporal scale-dependency is observed for the proposed metrics used to identify the magnitude and the seasonal pattern of the CIV—the utility of an hourly time series and its associated extreme properties deserves significant attention. Ultimately, the spatial mapping and grouping of CIV will provide valuable information to identify which regions have high variability compared to climatological norms and thus are more vulnerable to extremes, and will serve as a guide for planning adaptation and mitigation measures against future extreme events.     

Temporal and spatial response of hyporheic zone geochemistry to a storm event

Although there has been recent focus on understanding spatial variability in hyporheic zone geochemistry across different morphological units under baseflow conditions, less attention has been paid to temporal responses of hyporheic zone geochemistry to non‐steady‐state conditions. We documented spatial and temporal variability of hyporheic zone geochemistry in response to a large‐scale storm event, Tropical Storm Irene (August 2011), across a pool–riffle–pool sequence along Chittenango Creek in Chittenango, NY, USA. We sampled stream water as well as pore water at 15 cm depth in the streambed at 14 locations across a 30 m reach. Sampling occurred seven times at daily intervals: once during baseflow conditions, once during the rising limb of the storm hydrograph, and five times during the receding limb. Principal component analysis was used to interpret temporal and spatial changes and dominant drivers in stream and pore water geochemistry (n = 111). Results show the majority of spatial variance in hyporheic geochemistry (62%) is driven by differential mixing of stream and ground water in the hyporheic zone. The second largest driver (17%) of hyporheic geochemistry was temporal dilution and enrichment of infiltrating stream water during the storm. Hyporheic sites minimally influenced by discharging groundwater (‘connected’ sites) showed temporal changes in water chemistry in response to the storm event. Connected sites within and upstream of the riffle reflected stream geochemistry throughout the storm, whereas downstream sites showed temporally lagged responses in some conservative and biogeochemically reactive solutes. This suggests temporal changes in hyporheic geochemistry at these locations reflect a combination of changes in infiltrating stream chemistry and hyporheic flowpath length and residence time. The portion of the study area strongly influenced by groundwater discharge increased in size throughout the storm, producing elevated Ca²⁺ and concentrations in the streambed, suggesting zones of localized groundwater inputs expand in response to storms. Copyright © 2013 John Wiley & Sons, Ltd.     

Water quality trends at an upland site in wales,UK, 1983–1993

Ten years of detailed upland stream and bulk deposition water quality data from Plynlimon, mid-Wales, are examined for trend. A robust statistical test (the seasonal Kendall test) is applied and data are presented graphically. Smoothing techniques are used to highlight the patterns of change which underlie high data scatter. The graphs show long-term cycles within the data which violate the assumptions of common statistical tests for trend. These cycles relate to fluctuations in the weather patterns at Plynlimon. Even though the seasonal Kendall test is significant for some determinands, the evidence from the graphs suggests that many of these ‘trends’ are unlikely to continue. For solutes in rainfall, there is no convincing long-term trend. There is a possible increase in ammonium concentrations, which may indicate an increasing atmospheric source generated by farming activities, but this will require a longer data series for confirmation. Several trace metal concentrations increased significantly part way through the study period, but later returned to the original levels. The bulk precipitation sea salt input has been uneven over the 10-year sampling period, with the highest inputs occurring during the wetter winters. For solutes in streamwaters, there are clear trends in dissolved organic carbon (DOC), iodine and bromide, which increase over time and may be attributed to an increase in organic decomposition in the catchment. Previous studies in Wales have shown similar behaviour for colour, which is related to DOC, but the corresponding changes for bromide and iodine are new. For most other streamwater determinands, any changes are masked by the effects of year to year variations in the quality and quantity of rainfall. For example, zinc and chromium variations parallel the corresponding rainfall quantity variations. The effect of rainfall quality variation is marked for marine-derived elements such as chloride. For sulphate, streamwater variations are inverted relative to chloride. This suggests that dry deposition may vary with weather conditions: high when the wind direction is from the land and low when weather systems are predominantly frontal and laden with sea salts. Alternatively, high sea salt rainfall may be affecting absorption/solubility reactions in the soils. There are four main conclusions. Firstly, there is no indication of changing acid deposition inputs or changing acidity within the runoff, despite a decline in UK sulphur dioxide emissions. Secondly, streamwater DOC has shown an increase over time, but there is no clear corresponding decrease in pH as might be expected from acidification theory. Thirdly, there are cyclical variations in bulk precipitation inputs and in streamwater quality, which mean that trends cannot be established even with 10 years of data. Long-term cycles are likely to exist in other environmental data and extreme care is required for the interpretation of trend, especially if data sets are short. This aspect strongly supports the continuation of long-term monitoring programmes over several decades. Finally, the graphical application strongly enhances data analysis and should be considered an essential component of trend investigation.     

Natural Buffering of Groundwater Contaminants Related to Development in Fractured Rock

In rural areas of New England groundwater from fractured crystalline and sedimentary bedrock is a critical water resource. Increasingly, studies have shown that development occurring in rural areas is resulting in the impairment of water quality in fractured rock aquifers. The objective of this study was to evaluate the spatial and temporal variations in groundwater quality associated with development and evaluate the extent to which common groundwater contaminants associated with rural development may be naturally buffered. The study entailed a compilation and synthesis of over 2500 reports on domestic water quality that spanned a 30 year period. Focus was placed on the spatial distribution and temporal variations in sodium, chloride, iron, manganese, nitrate, and nitrite. Results indicate that despite significant levels of development, the amount of contamination to the bedrock has been minimal. Of the constituents examined, only the chloride concentration exhibits a systematic increase over time, but the level of chloride remained relatively low. The flux of chloride to the bedrock from deicing appears minimal despite the significant amounts of road salt used in the study area. Sodium concentrations in the bedrock remained relatively constant and appear to be buffered by ion exchange with calcium as suggested by the increase in hardness with time. Iron and manganese were present at relatively low levels but did not show any systematic trends over time. Nitrate and nitrite concentrations were very low and found to be inversely correlated with manganese and iron concentrations. This suggests that the presence of iron and manganese contribute to denitrification. This study indicated that both geochemical and biogeochemical processes are active buffering mechanisms that help shield the bedrock from contaminants associated with development.     

Accounting for Temporal Variations in Large-Scale Retrospective Studies of Agricultural Chemicals in Ground Water

Ground water studies that require long data collection periods may be affected by temporal changes in ground water chemistry. Seasonal fluctuations in ground water chemistry are particularly apparent in shallow aquifers. Of specific interest is the inclusion of temporal variability in the design of statistical surveys of agricultural chemicals in well water. Statistical treatment of temporal variability involves selecting a probability sample from temporal units. The selection strategy may include repeating the same spatial units in each temporal stratum or choosing an independent sample of spatial units for each temporal stratum. The appropriate strategy depends on the specific study objectives. Failure to account for temporal variability may compromise the validity of study conclusions. An example of a large-scale retrospective survey designed to estimate temporal averages of water quality across all wells is presented.     

南四湖流域1980-2015年土地利用变化及其对流域生境质量的影响

生境质量在一定程度上决定了区域生物多样性维持能力的高低,评估区域生境质量对土地利用/覆被变化的响应,可以间接衡量区域生物多样性维持功能的时空变化,为生物多样性保护提供定量参考.本文以南四湖流域为例,运用InVEST-Habitat Quality模型模拟评价1980-2015年流域生境质量的时空变化,定量评估湖区退耕还湿还林和丘陵地区退耕还林2种政策情景对区域生境质量改善的效果.结果表明：35 a间流域耕地、林地和草地大量转化为建设用地,城市建设用地增长40.23%,湖泊面积减少35.56%,主要转化为渔业坑塘;南四湖流域整体生境质量处于较低水平,近35 a来快速发展的工农业生产和不断扩张的城市用地使得流域生境质量呈现降低趋势,当前平均生境质量为历年最低（0.20）.环境保护力度和人类活动剧烈程度的差异导致生境质量在空间上呈现出西部平原区（0.19） < 东部丘陵山区（0.44） < 南四湖湖区（0.81）的分布特征.近35 a来生境稀有度（即生境保存完整性指数）较高的区域主要是湖区主体和流域东部丘陵山区,但部分边缘湖区生境稀有度指数却极低,受人类活动干扰剧烈,主要原因在于沿湖渔业养殖和农业活动.定量评估湖区退耕还林还湿和流域丘陵旱地退耕还林2种政策情景对生境质量的改善效果,结果表明湖区退耕还湿还林能使湖区生境质量上升9.21%,而丘陵旱地退耕还林可使流域平均生境质量提高16.75%.     

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box‐plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously.     

Seasonal and spatial variability of water quality parameters in the Port of Genoa, Italy, from 2000 to 2007

This paper presents the results of the statistical analysis of a set of physico-chemical and biological water quality parameters, monthly collected from 2000 to 2007 in the Genoa Harbour area (Ligurian Sea). We applied multivariate methods, such as principal component analysis (PCA) and dynamic factor analysis (DFA) for investigating the spatial and temporal variability and for providing important background information on pollution problems in the region. PCA evidenced the role of the sewage and river discharges and of the exchanges with the open sea in determining the harbour water quality. DFA was used to estimate underlying common trends in the time series. The DFA results partly show a general improvement of water quality over the 8-years period. However, in other areas, we found inter-annual variations but no significant multi-annual trend. Furthermore, we included meteorological variables in our statistical analyses because of their potential influence on the water quality parameters. These natural forcings explain part of the variability in water quality parameters that are superimposed on the dominating anthropogenic pollution factors.     

Polynomial smoothing of quiet-time magnetic variations for an irregularly spaced array of sites

Both magnetospheric and solid Earth geophysicists often employ two-dimensional arrays of recording variometers to reconstruct the spatial distribution of transient magnetic field variations at the Earth's surface. These discrete data are typically interpolated over a dense grid and the results, for example, are contoured. Few studies, however, have explored the efficacy of employing various polynomial forms for interpolating the same data set, nor have they examined how regional polynomial forms relate to magnetic variation sources on a global scale. The present study addresses some of these concerns. We quantify the characteristics of various smoothed models (i.e., low-order polynomial trend surfaces) for the same data set from a subglobal network of magnetic variometers. Using a relatively quiet interval of undisturbed diurnal variation, we characterize the spatial distribution of the three individual magnetic vector components at a single instant of time—or for what we call a ‘time slice’. We then explore how our model functions are affected by the presence or absence of various site data, i.e., what is the ‘information content’ of a particular site in our array and how important is it to constraining the final smooth model function that we derive? Finally, we explore how such local model functions are affected by including data from outside the array by studying the relation between our local polynomial forms and the global source fields from which they derive.     

Groundwater Storage Changes: Present Status from GRACE Observations

Satellite gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) provide quantitative measurement of terrestrial water storage (TWS) changes with unprecedented accuracy. Combining GRACE-observed TWS changes and independent estimates of water change in soil and snow and surface reservoirs offers a means for estimating groundwater storage change. Since its launch in March 2002, GRACE time-variable gravity data have been successfully used to quantify long-term groundwater storage changes in different regions over the world, including northwest India, the High Plains Aquifer and the Central Valley in the USA, the North China Plain, Middle East, and southern Murray–Darling Basin in Australia, where groundwater storage has been significantly depleted in recent years (or decades). It is difficult to rely on in situ groundwater measurements for accurate quantification of large, regional-scale groundwater storage changes, especially at long timescales due to inadequate spatial and temporal coverage of in situ data and uncertainties in storage coefficients. The now nearly 13 years of GRACE gravity data provide a successful and unique complementary tool for monitoring and measuring groundwater changes on a global and regional basis. Despite the successful applications of GRACE in studying global groundwater storage change, there are still some major challenges limiting the application and interpretation of GRACE data. In this paper, we present an overview of GRACE applications in groundwater studies and discuss if and how the main challenges to using GRACE data can be addressed.     

Uncertainty in hydrograph separations based on geochemical mixing models

A detailed uncertainty analysis of three-component mixing models based on the Haute–Mentue watershed (Switzerland) is presented. Two types of uncertainty are distinguished: the ‘model uncertainty’, which is affected by model assumptions, and the ‘statistical uncertainty’, which is due to temporal and spatial variability of chemical tracer concentrations of components. The statistical uncertainty is studied using a Monte Carlo procedure. The model uncertainty is investigated by the comparison of four different mixing models all based on the same tracers but considering for each component alternative hypotheses about their concentration and their spatio-temporal variability. This analysis indicates that despite the uncertainty, the flow sources, which generate the stream flow are clearly identified at the catchments scale by the application of the mixing model. However, the precision and the coherence of hydrograph separations can be improved by taking into account any available information about the temporal and spatial variability of component chemical concentrations.     

Using a groundwater quality negotiation support system to change land-use management near a drinking-water abstraction in the Netherlands

A negotiation support system (NSS) was developed to solve groundwater conflicts that arose during land-use management. It was set up in cooperation with the stakeholders involved to provide information on the impact of land use, e.g., agriculture, nature (forested areas), recreation, and urban areas, on the quality of both infiltrating and abstracted groundwater. This NSS combined simulation programs that calculate (1) the concentrations of nitrate in shallow groundwater for each land-use area and (2) the transport of nitrate in the groundwater-saturated zone. The user interface of the NSS enabled scenario analyses. The NSS was validated at a drinking-water abstraction near Holten (the Netherlands) using a spatial planning process aimed at sustainable land-use and groundwater-resource management. Two land-use scenarios were considered: a base scenario reflecting the autonomous development and an adapted land-use scenario. The calculated results for shallow groundwater provided an explicit spatial overview of the impact of historical land use and N application on the quality of abstracted groundwater as well as insight into the impact of changes in land use and N application. Visualization of the conflicting interests of agriculture and the drinking-water abstraction helped all stakeholders accept the necessary changes in land use identified by the adapted land-use scenario of the NSS. These changes were included in the preferred land-use management option in the regional planning process, which has since been formalized. The NSS provided system insight, scoping analyses, and education, in addition to generating quantitative information on the impact of land-use functions on groundwater quality.     

Tritium in ground water of the georgia piedmont: Implications for recharge and flow paths

Environmental tritium was measured in 33 natural water samples representative of precipitation, stream runoff, and groundwater (derived principally from production wells) within the Georgia Piedmont Province. Major ion analyses were used to assist in the interpretation of the tritium results. Tritium concentrations were significantly greater within shallow groundwater derived from the regolith (28–34 TU) and stream runoff (25–30 TU) than within recent rainfall (4–17 TU). Based upon the decay-corrected tritium input function, this probably indicates that at least some of the shallow water is stored within the regolith for a period of approximately 25 years. A ‘post-bomb’ component of recharge was present in all groundwater derived from production wells in the study area. Groundwater sampled from the bedrock aquifers was commonly less tritiated than either stream runoff or shallow water stored in the regolith. the lower tritium concentrations May, have resulted from the mixing of ‘pre-bomb’ water stored within the fractures or the transitional zone directly above the bedrock and modern water stored in the shallow regolith. the preponderance of modern water provides evidence that groundwater flow paths are areally restricted within this setting, probably confined to local surface water drainage basins. the residence time of groundwater in the Piedmont is limited by the lack of deep, gravity-driven regional flow and the localized vertical flow induced by pumping. the results of this study indicate that relatively small tritium concentration variations (10-20 TU) May, have regional hydrological significance in the southeastern Piedmont Province and similar settings.     

Quantification of river water infiltration in shallow aquifers using acesulfame and anthropogenic gadolinium

This study has investigated the use of the artificial sweetener acesulfame and the magnetic resonance imaging contrast agent gadolinium as quantitative tracers for river water infiltration into shallow groundwater. The influence of a river on alluvial groundwater in a subalpine catchment in western Europe has been assessed using the ‘classical’ hydrochemical tracer chloride and the trace contaminants acesulfame and anthropogenic gadolinium. Mixing ratios for riverine bank filtrate with ambient groundwater and the uncertainties associated with the temporal and spatial tracer variability were calculated using acesulfame and gadolinium and compared with those obtained using chloride. The temporal variability of tracer concentrations in river water of gadolinium (standard deviation SD: 63%) and acesulfame (SD: 71%) both exceeded that of chloride (SD: 27%), and this was identified as the main source of uncertainty in the mixing analysis. Similar spatial distributions were detected in the groundwater for chloride and gadolinium, but not for acesulfame. Mixing analyses using acesulfame resulted in calculated mixing ratios that differed from those obtained using gadolinium and chloride by up to 83% and 92%, respectively. At the investigated site, which had oxic conditions and moderate temperatures, acesulfame was found to be a less reliable tracer than either gadolinium or chloride, probably because of natural attenuation and input from other sources. There was no statistically significant difference between the mixing ratios obtained using chloride or gadolinium, the mixing ratios obtained using gadolinium were 40–50% lower than those obtained using chloride. This is mainly due to a bias of the mean gadolinium concentration in river water towards higher values. In view of the uncertainties of the two tracers, neither could be preferred over the other for the quantification of bank filtrate in groundwater. At this specific site gadolinium was able to reliably identify river water infiltration and was a more precise tracer than chloride at low mixing ratios (<20%), because of the exclusive occurrence of gadolinium in river water and its high dynamic range. Copyright © 2015 John Wiley & Sons, Ltd.