National Groundwater Monitoring Network Research Articles

Seasonal Groundwater Level Dynamics in Unconfined Aquifers across the United States.

Groundwater hydrographs contain a rich set of information on the dynamics of aquifer systems and the processes and properties that influence them. While the importance of seasonal cycles in hydrologic and environmental state variables is widely recognized there has yet to be a comprehensive analysis of the seasonal dynamics of groundwater across the United States. Here we use time series of groundwater level measurements from 997 wells from the National Groundwater Monitoring Network to identify and describe groundwater seasonal cycles in unconfined aquifers across the United States. We use functional data analysis to obtain a functional form fit for each site and apply an unsupervised clustering algorithm to identify a set of five distinct seasonal cycles regimes. Each seasonal cycle regime has a distinctive shape and distinct timing of its annual minimum and maximum water level. There are clear spatial patterns in the occurrence of each seasonal cycle regime, with the relative occurrence of each regime strongly influenced by the geologic setting (aquifer system), climate, and topography. Our findings provide a comprehensive characterization of groundwater seasonal cycles across much of the United States and present both a methodology and results useful for assessing and understanding unconfined groundwater systems.

Groundwater level monitoring of Danish chalk and limestone aquifers to survey trends in quantitative status and groundwater resources

Abstract Chalk and limestone aquifers contribute one-third of the drinking water supply in Denmark, and one-sixth of that national groundwater resource is assessed as having a ‘Poor’ status in terms of the quantitative Water Framework Directive due to intensive abstraction. This paper describes the national groundwater level monitoring network with regard to the following three applications: (1) when used for the annual surveying and reporting of groundwater resources and impacts from climate and groundwater abstraction; (2) as part of real-time monitoring and modelling for daily and seasonal forecasting; and (3) for tracking long-term climate change impacts on groundwater levels. Groundwater level monitoring provides a particularly important indicator of abstraction pressure and sustainable balance compared with recharge. Many larger chalk and limestone groundwater bodies in Denmark are only monitored by local water companies and not represented in the national groundwater level network. This raises the concern that current national groundwater level monitoring does not fully support integrated modelling and assessment purposes for chalk and limestone groundwater bodies. This also implies that, for tracking long-term climate change and anthropogenic impacts on groundwater levels, the national groundwater monitoring network especially lacks long-term records with complete 30-year time-series for many intensively exploited large chalk and limestone aquifers.

Spatiotemporal dynamics of Escherichia coli presence and magnitude across a national groundwater monitoring network, Republic of Ireland, 2011–2020

Groundwater is a vital drinking water resource and its protection from microbiological contamination is paramount to safeguard public health. The Republic of Ireland (RoI) is characterised by the highest incidence of verocytotoxigenic Escherichia coli (VTEC) enteritis in the European Union (EU), linked to high reliance on unregulated groundwater sources (~16% of the population). Yet, the spatio-temporal factors influencing the frequency and magnitude of microbial contamination remain largely unknown, with past studies typically constrained to spatio-temporally ‘limited’ sampling campaigns. Accordingly, the current investigation sought to analyse an extensive spatially distributed time-series (2011−2020) of groundwater monitoring data in the RoI. The dataset, compiled by the Environmental Protection Agency (EPA), showed ‘high’ contamination rates, with 66.7% (88/132) of supplies testing positive for E. coli, and 29.5% (39/132) exceeding concentrations of 10MPN/100 ml (i.e. gross contamination) at least once during the 10-year monitoring period. Seasonal decomposition analyses indicate that E. coli detection rates peak during late autumn/early winter, coinciding with increases in annual rainfall, while gross contamination peaks in spring (May) and late-summer (August), likely reflecting seasonal shifts in agricultural practices. Mixed effects logistic regression modelling indicates that monitoring sources located in karst limestone are statistically associated with E. coli presence (OR = 2.76, p = 0.03) and gross contamination (OR = 2.54, p = 0.037) when compared to poorly productive aquifers (i.e., transmissivity below 10m2/d). Moreover, 5-day and 30-day antecedent rainfall increased the likelihood of E. coli contamination (OR = 1.027, p < 0.001 and OR = 1.005, p = 0.016, respectively), with the former also being associated with gross contamination (OR = 1.042, p < 0.001). As such, it is inferred that preferential flow and direct ingress of surface runoff are the most likely ingress mechanisms associated with E. coli groundwater supply contamination. The results presented are expected to inform policy change around groundwater source protection and provide insight for the development of groundwater monitoring programmes in geologically heterogeneous regions.

Analysis of the condition of karst springs included in the National Groundwater Monitoring Network

Approximately 20% of the monitored points in the National Groundwater Monitoring Network (NGMN) of Bulgaria are karst springs. The number of monitored karst springs is changing over time for various reasons and currently there are 33 springs monitored continuously and 53 on monthly basis. The monitoring points are distributed over 39 karst basins around the whole country. There are between 1 and 5 monitored springs per karst basin and no monitoring points in 23 karst basins. The present analysis includes the determination of some of the main statistical characteristics of karst springs and it is based on the monitoring data series. The obtained data allow us to make some conclusions of the nature of their water regime. Based on the analysis, some suggestions and recommendations are made with regard to improvements in the monitoring of karst springs in Bulgaria.

Physicochemical patterns observed in a groundwater well with CO2 stratification: Learnings from an automated monitoring from South Korean national groundwater monitoring network

Unusual episodic fluctuations of electrical conductivity (EC) were observed twice a year in a national groundwater monitoring network well in South Korea where EC was automatically monitored at a depth of 20 m below ground level (bgl). To address the causes of the observed EC fluctuations, this study examined the depth profile of wellbore water in the 70-meter-deep monitoring well screened between 50 and 70 m bgl and cased down to 50 m bgl. The results of well logging, borehole video recording, and hydrochemical analysis of wellbore water indicated that the CO2-rich groundwater entering through the screened zones below 50 m bgl was physicochemically stratified into three layers with distinct EC that were separated by two transition zones in the well: a bottom layer (70–43 m bgl) with an EC of ∼3900 μS/cm, intermediate layer (35–24 m bgl) of ∼1800 μS/cm, and top layer (16–3 m bgl) of ∼300 μS/cm. The first transition zone at depths of 43–35 m bgl was attributed to CO2 exsolution in the open system and the subsequent physicochemical changes of wellbore water, while the second transition zone at depths of 24–16 m bgl was formed by the precipitation of hydrous ferric oxides with consequent sorption of remaining ions due to a sudden change toward the oxidizing environment. The monitoring probe installed at a depth of 20 m bgl was found to be located within the upper transition zone, which caused EC peaks when the well was purged at a depth of 25 m bgl for well maintenance twice a year. This study shows that automated groundwater monitoring systems may misguide one about the groundwater quality if an unexpected physicochemical variation (such as stratification) occurs in a monitoring well. Therefore, the presence of interface zones caused by abrupt changes in EC must be carefully considered when an automated monitoring well is designed. The screened zone is a suitable location for installing an automated monitoring probe to measure the representative water quality (i.e., EC), in particular, in an aquifer that is under the influence of inputs of low-pH and high-TDS fluids (e.g., CO2-rich groundwater and acid mine drainage).

Predicting Changes in Spatiotemporal Groundwater Storage Through the Integration of Multi-Satellite Data and Deep Learning Models

Continuous monitoring and accurate spatiotemporal groundwater storage change predictions can help support sustainable development and efficient groundwater resources management. In this study, remote sensing-based data were used to develop two deep learning predictive models, long short term memory (LSTM), and convolutional neural network-LSTM (CNN-LSTM) models. The input variables were terrestrial water storage anomaly (TWSA) recorded by the Gravity Recovery and Climate Experiment (GRACE) satellites and the GRACE-Follow-On (GRACE-FO) mission, precipitation measured by the Tropical Rainfall Measuring Mission (TRMM) satellite, average temperature and soil moisture obtained from the Global Land Data Assimilation System (GLDAS), and normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI) acquired from the Landsat 5 and 8 satellites. A comparison of groundwater storage change predictions by the two deep learning predictive models with in situ measurements of the National Groundwater Monitoring Network (NGMN) in South Korea showed that the CNN-LSTM model was more accurate [root mean square error (RMSE) = 44.92 mm/month, correlation coefficient (r) = 0.70, index of agreement (IOA) = 0.81] than the LSTM model [RMSE = 47.44 mm/month, r = 0.62, and IOA = 0.77]. Furthermore, a comparison of the performance of the two models for three specific regions showed that the CNN-LSTM model captured spatiotemporal variations in groundwater storage better. Additionally, a comparison of cumulative change trends in groundwater storage with the NDVI, MNDWI, and TWSA data showed that changes in land cover and total water storage affect groundwater storage. These comparison results demonstrate that the use of parameters recorded by multiple satellites as training data for deep learning models can play an important role in the model’s performance.

National Ground‐Water Monitoring Network (DOI)

Federal Grants & ContractsVolume 44, Issue 22 p. 5-5 Grants Alerts National Ground-Water Monitoring Network (DOI) First published: 16 October 2020 https://doi.org/10.1002/fgc.31351 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume44, Issue2222 October 2020Pages 5-5 RelatedInformation

Presence of pharmaceutical compounds in groundwater with respect to land use in the vicinity of sampling sites

Abstract The present paper discusses the results of an analysis of the impact of land use on the distribution of pharmaceuticals in groundwater samples collected during a pilot study of the contents of pharmaceuticals and hormones in ground-water taken from the national groundwater monitoring network of the Polish Geological Institute - National Research Institute. Samples were collected during monitoring campaigns from 160 groundwater monitoring sites in various land use types in 2016 and 2017. Samples were analysed for a total of 34 active substances, including natural and synthetic oestrogen hormones, cardiovascular and respiratory medications, analgesics and anti-inflammatories, antidepressants, antimicrobial drugs and anti-epileptics. Our study confirmed the presence of pharmaceuticals in 53 per cent of ground-water samples taken. Data show variations in the distribution of pharmaceuticals depending on land use type, which can thus be employed in pressure analysis and identification of sources of pollution.

Occurrence of metal-rich acidic groundwaters around the Mekong Delta (Vietnam): A phenomenon linked to well installation

Acidic groundwaters enriched with heavy metals are frequently observed in the coastal plain aquifers. The acidic pHs are observed even in the deep confined aquifers in southern Vietnam. This study geochemically explores the causes of these acidic groundwaters by investigating 41 groundwater samples, 4 soil samples and a 54 m long sediment core and the long-term monitoring data (4189 observations) obtained from 178 wells of the National Groundwater Monitoring Network for the South of Vietnam (NGMNS). The groundwater data show elevated Fe, Mn, Al, Pb, and Zn concentrations as the pH becomes acidic and suggest pyrite oxidation be the major cause for the groundwater acidification. This is further confirmed by pyrite framboids observed in the sediment or soil samples taken from the sites where strongly acidic groundwaters were observed. Results of leaching experiments using sediment and soil samples indicate that high metal concentrations in the acidic pH are associated with the increased metal solubility and mineral dissolution kinetics. The acidification of deep groundwaters is revealed to be associated with well installation, indicating the importance of proper well-installation techniques to protect water quality of deep confined aquifers.

National Ground Water Monitoring Network Data Providers Meet to Discuss Network Status and Plans

Groundwater Monitoring & RemediationVolume 37, Issue 1 p. 15-16 Letter to the Editor National Ground Water Monitoring Network Data Providers Meet to Discuss Network Status and Plans by Lauren Schapker M.A., Lauren Schapker M.A.Search for more papers by this author by Lauren Schapker M.A., Lauren Schapker M.A.Search for more papers by this author First published: 12 February 2017 https://doi.org/10.1111/gwmr.12202Citations: 1Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article.Citing Literature Volume37, Issue1Winter 2017Pages 15-16 RelatedInformation

FROM FLOOD TO DROUGHT – CHANGES OF HYDROGEOLOGICAL SITUATION IN POLAND BETWEEN 2010–2015

Hydrogeological and hydrological situation is primarily conditioned by climate and natural features, however, land use and catchment management are also important. Both droughts and low groundwater levels, as well as floods and flooding have been occurring in Poland in the past and they will certainly be repeated in the future. Undertaking measures aimed at effective mitigation of effects of such extreme events is possible. Nevertheless, this requires reliable and verifiable hydrogeological forecasting. In order to meet these expectations, the Polish Hydrogeological Survey undertakes cyclic assessments of hydrogeological situation in Poland on a national scale and carries out projections of its changes. This paper presents results of an analysis of hydrogeological situation in Poland between 2010–2015, during which a transition from high groundwater levels in 2010 and 2011 (related to flood events in 2010) to low levels (related to the drought in 2015) were observed. To present the spatio-temporal changes of hydrogeological situation in years 2010–2015 the authors analyze extreme groundwater levels in the considered period based on data from the national groundwater monitoring network of the Polish Geological Institute - National Research Institute.

가우시안 프로세스 회귀분석을 이용한 지하수위 추세분석 및 장기예측 연구

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

Current Status of Groundwater Monitoring Networks in Korea

Korea has been operating groundwater monitoring systems since 1996 as the Groundwater Act enacted in 1994 enforces nationwide monitoring. Currently, there are six main groundwater monitoring networks operated by different government ministries with different purposes: National Groundwater Monitoring Network (NGMN), Groundwater Quality Monitoring Network (GQMN), Seawater Intrusion Monitoring Network (SIMN), Rural Groundwater Monitoring Network (RGMN), Subsidiary Groundwater Monitoring Network (SGMN), and Drinking Water Monitoring Network (DWMN). The Networks have a total of over 3500 monitoring wells and the majority of them are now equipped with automatic data loggers and remote terminal units. Most of the monitoring data are available to the public through internet websites. These Networks have provided scientific data for designing groundwater management plans and contributed to securing the groundwater resource particularly for recent prolonged drought seasons. Each Network, however, utilizes its own well-specifications, probes, and telecommunication protocols with minimal communication with other Networks, and thus duplicate installations of monitoring wells are not uncommon among different Networks. This mini-review introduces the current regulations and the Groundwater Monitoring Networks operated in Korea and provides some suggestions to improve the sustainability of the current groundwater monitoring system in Korea.

Characterization of the Karst water regime in the Danube catchment area (Bulgaria)

The purpose of study is to estimate the role of karst springs in the formation of the flow of the Bulgarian rivers that are right tributaries of the Danube River. The study area includes the region from the Danube River to the main ridge of the Balkan (Stara Planina), representing a major water divide that separates the Black Sea catchment area from the Aegean one. The eastern border represents the watershed between the Danube and the Black Sea hydrological zones. From a geological point of view, the northern part of the area is located on the Moesian platform and the southern part belongs to the Fore Balkan and Balkan areas where various types of rocks of different geologic age outcrop. In some of them, there are conditions for the formation of karst water. In the northern part of the area they form distinct aquifers that gradually sink to the north; this is so called "platform" type of karst. In the southern mountainous part there are numerous karst basins. The most significant of karst springs are included in the national groundwater monitoring network. The hydrographs of karst springs are analyzed in view of the specific features of karstification. To classify the studied springs with respect to their regime, several indicators are used. Furthermore, the role of karst waters in the river runoff of the Bulgarian tributaries of the Danube River is assessed.

Development and Implementation of a National Groundwater Monitoring Network

Development and Implementation of a National Groundwater Monitoring Network

굴포천 임시방수로 굴착구간 주변의 지하수 수위 변동 유형 분류

Characteristics of water-level changes in the Temporary Gulpocheon Discharge Channel were identified by observing and analyzing changes in the subterranean water level induced by hydrological stresses the underground aquifer. The subterranean water level refers to the level at which the pressure of subterranean water passing through the corresponding position has an equipotential value that is in equilibrium with the atmospheric pressure at that location. This water level is not fixed but changes in response to hydrological stress. It can be identified by repeatedly measuring the distance from the observation point to the surface of the subterranean water. The subterranean water-level change equation and the variance range of the hydrological curve of subterranean water over 24 hours at the Gimpo-Gimpo National Groundwater Monitoring Network (NGMN) were used as assessment factors. The variance characteristics of the subterranean water at the 18 monitoring system locations were classified into three impact, observational wish, and non-impact. The impact type accounted for 50% of the subterranean water of and accurately reflected the water-level changes due to hydrological stress, showing that distance is the major controlling factor. The observational wish type accounted for 27.8% of the subterranean water, and one of the two assessment factors did not meet the assessment factors. The nonimpact type accounted for 22.2% of the subterranean water. This type satisfied the two assessment factors and represents subterranean water-level changes response to precipitation.

Determination of natural backgrounds and thresholds of nitrate in South Korean groundwater using model-based statistical approaches

Increased nitrate loading of groundwater has emerged as a major environmental problem in many countries, including South Korea. This study aims to evaluate the nitrate levels of South Korean groundwater on a regional (national) scale and specifically to demonstrate the procedure to better estimate the natural background level (NBL) and threshold of nitrate as the basis of groundwater management. For this work, nitrate data of groundwater (n=8510) in two major hydrogeologic units (alluvium and bedrock) were collected from the National Groundwater Monitoring Network (NGMN) of South Korea. Four supplementary datasets (n=1074) were also used to test the rationality of estimated thresholds by comparing them with NGMN datasets. Compared with the data reported in many countries, the nitrate concentrations in NGMN groundwater in 2009 are high, with median values of 12.2 and 8.7mg/L, respectively, for alluvial groundwater and bedrock groundwater. The nitrate levels of South Korean groundwater seem to have been historically steady at these high levels between 1997 and 2009, suggesting widespread diffusive contamination since the 1980s. The NBLs and anthropogenic polluted levels (APLs) of nitrate on a regional (national) scale are statistically established by the model-based approach using a finite normal (Gaussian) two-component mixture model, because (1) the sample size (frequency) of the natural background group is much smaller than that of the polluted group, as a result of widespread nitrate contamination, and (2) nitrate concentrations are more or less affected by natural attenuation processes. Accordingly, thresholds of nitrate (as the concentration level indicating groundwater pollution) are selected as the lower limits (i.e., 10th percentile) of the polluted group, which are 3.0 and 5.5mg/L NO3−, respectively, for bedrock groundwater and alluvial groundwater. This study provides a practical guideline for national groundwater management, based on a heuristic procedure to statistically determine the NBLs and thresholds in the case of groundwater systems with pervasive contamination. Compared with the other classical methods to estimate NBLs, the model-based approach using a finite normal-mixture model can be more effective to reasonably separate the polluted samples from a regional (or national) dataset.

TFNM, ANN, ANFIS를 이용한 국가지하수관측망 지하수위 변동 예측 비교 연구

It is important to predict the groundwater level fluctuation for effective management of groundwater monitoring system and groundwater resources. In the present study, three different time series models for the prediction of groundwater level in response to rainfall were built, those are transfer function noise model (TFNM), artificial neural network (ANN), and adaptive neuro fuzzy interference system (ANFIS). The models were applied to time series data of Boen, Cheolsan, and Hongcheon stations in National Groundwater Monitoring Network. The result shows that the model performance of ANN and ANFIS was higher than that of TFNM for the present case study. As lead time increased, prediction accuracy decreased with underestimation of peak values. The performance of the three models at Boen station was worst especially for TFNM, where the correlation between rainfall and groundwater data was lowest and the groundwater extraction is expected on account of agricultural activities. The sensitivity analysis for the input structure showed that ANFIS was most sensitive to input data combinations. It is expected that the time series model approach and results of the present study are meaningful and useful for the effective management of monitoring stations and groundwater resources.

Hydrogeochemical interpretation of South Korean groundwater monitoring data using Self-Organizing Maps

The National Groundwater Monitoring Network (NGMN) of South Korea provides data since 1995 to monitor the water level and quality of groundwater on a national scale. Major ions such as Ca, Mg, Na, K, HCO3, Cl, SO4 and NO3 have been monitored since 2008 to assess groundwater quality. Hydrochemical data of bedrock groundwater samples collected from 299 monitoring stations in 2009 were examined using the Self-Organizing Map (SOM) approach. Based on hydrochemical characteristics, bedrock groundwater is clustered into two groups and six subgroups. Group I containing 70.2% of groundwater samples (and monitoring stations) is characterized by lower TDS values and NO3 concentrations than Group II, indicating that Group I waters are less affected by contamination. Subgroup I-1 (39.1%) represents Ca–HCO3-type groundwater with relatively low pH, TDS and concentrations of most ions compared with groundwater of Subgroups I-2-1 (26.1%) and I-2-2 (5.0%). Subgroup I-2-2 represents a moderately alkaline, F-rich, Na–HCO3-type groundwater. Group II records either anthropogenic or natural processes. Subgroup II-1 (16.1%) contains groundwater with low values of TDS, HCO3 and pH, and moderately high NO3 concentrations due to nitrification, while groundwater of Subgroups II-2-1 and II-2-2 is characteristically high in Ca and Mg. Subgroup II-2-1 is also very high in SO4 and HCO3 but very low in NO3, while Subgroup II-2-2 is substantially enriched in Cl and NO3. The hydrochemistry of groundwater of Subgroup II-2-1 likely results from dissolution of carbonates and gypsum in clastic sedimentary rocks and is affected by dissolution of pyrite and/or S-bearing fertilizers in crystalline rocks. The enrichment of NO3, Cl, Ca and Mg in groundwater of Subgroup II-2-2 is the result of substantial contamination from agrochemicals and manure. Thus, about 20.5% (Subgroups II-1 and II-2-2) of bedrock groundwater in South Korea records anthropogenic contamination. This study shows that the SOM approach can be successfully used to classify and characterize the groundwater in terms of hydrochemistry and quality on a regional scale.

Remediation of Contaminated Groundwater: Change of Paradigm for Sustainable Use

Groundwater development and use have been increasing in Korea causing frequent occurrences of related hazards such as groundwater level decline, land subsidence, and groundwater contamination. To tackle these groundwater problems, central and local governments have set-up and maintained many groundwater monitoring programs such as the National Groundwater Monitoring Network and the Groundwater Quality Monitoring Network, which collect very valuable data on the overall status of domestic groundwater to aid proper groundwater management. However, several problems mainly related to the remediation of contaminated groundwater remain unresolved. Recently, there have been some incidents related to the contamination of groundwater, and these have drawn the concern of the Korean people. Although groundwater contamination has been investigated in detail, actual groundwater remediation work has not yet been implemented. The remediation of the contaminated groundwater must begin immediately in order to sustain the eco-system service of clean groundwater and enhance the welfare of the Korean people.