Quaternary Groundwater in Latvia

Elektroniskā versija nesatur pielikumu

GROUNDWATER, SURFACE WATER AND LEACHATE MONITORING IN HOUSEHOLD WASTE LANDFILL „GETLINI”

The paper is about the largest landfill in Latvia Getlini. Waste from Riga city and surroundings are disposed here. The waste landfilling once was started in the old sand-gravel quarry, next to the Getlini bog, and no environment protection measures were taken. Currently total area of the Getlini landfill is 87 ha and 36 ha of it occupy the old dumpsite (waste hill). Contaminants from the waste with storm water leached to the over groundwater and under groundwater and contaminated it. In the paper contamination level and spreading of leachate, surface water and groundwater are described

Pleistocene age paleo-groundwater inferred from water-stable isotope values in the central part of the Baltic Artesian Basin

<p>A new data set of δ²H and δ¹⁸O in the groundwater from the central part of the Baltic Artesian Basin is presented. The hydrogeological section is subdivided into stagnation, slow exchange and active exchange zones. Na–Ca–Cl brine found at the deepest part – the stagnation zone – is characterized by δ¹⁸O values above −5 ‰ and δ²H values approaching −40 ‰ with respect to Vienna Standard Mean Ocean Water. The slow exchange zone where waters of mostly intermediate salinity reside is characterized by δ¹⁸O values around −11.7 ‰ and δ²H values around −85.3 ‰. Mean δ¹⁸O and δ²H values of the fresh groundwater in the active water exchange zone are −11.1 and −79.9 ‰, respectively. Characteristically, the groundwater in the active and slow exchange zone is isotopically more depleted compared with the precipitation values observed, and the depletion increases with depth down to the level where strongly enriched brines are encountered.</p

Risks of Antibiotic Resistance Dissemination by Leachates from Municipal Landfills of Different Ages

Landfill leachate is regarded as a significant point source of pollutants that may pose a hazard to the environment, particularly to surface and ground waters. Leachates are highly variable and heterogeneous. Our study was focused on the characterization of landfill leachates derived from young (YDS) and matured (MDS) dumpsites in terms of the abundance of micropollutants, antimicrobial resistance genes (ARG), and microbial community structure. The concentrations of poly- and perfluoroalkyl substances (PFASs) were found to be higher in MDS compared to YDS, i.e., 13.19 and 7.16 μg/L, respectively. Among pharmaceutical compounds, ibuprofen was detected at the highest concentrations, i.e., 12.54, 12.81, and 13.13 μg/L, in the leachates derived from MDS, YDS, and ponds. The distribution of bacteria, archaea, eukaryotes, and viruses in the three leachate samples was as follows: 85.15 ÷ 88.04%, 9.13 ÷ 12.29%, 2.20 ÷ 2.68%, and 0.12 ÷ 0.15%, respectively. In total, 31 distinct families of ARGs were identified, comprising a total of 80 ARGs. Incubation of P. putida MSCL650 in sterile leachate from the pond resulted in decreasing the minimum inhibitory concentrations for six antibiotics as compared to cells incubated in nutrient broth. Hydrological processes, i.e., runoff and infiltration, can increase the dissemination of ARGs

Rescue of groundwater level time series: How to visually identify and treat errors”

Groundwater level time series are of great value for a variety of groundwater studies, particularly for those dealing with the impacts of anthropogenic and climate change. Quality control of groundwater level observations is an essential step prior to any further application, e.g., trend analysis. Often the quality control of data is limited to the removal of outliers or elimination of entire time series from a dataset, while such approaches drastically reduce the spatial coverage of initially huge datasets. Frequently studies tend to present already qualitycontrolleddata, but neglect to demonstrate how the data were selected, judged, and modified. We present a data rescue approach developed for correcting the Latvian national groundwater level database, containing 1.68 million groundwater level observations since 1959, including 0.69 million manual measurements. A web-based R-Shiny interface was developed and used for visual identification and manual correction of erroneous measurements in groundwater level time series. All data manipulations were performed programmatically. Reproducibilityand traceability were ensured by deploying separate data tables for raw observations, data repair actions and the final dataset. As a result of applied actions, 34.3% of all automatic measurements were either deleted or corrected, while only 6.5% of manual measurements were edited. Commonly found errors ingroundwater level time series were grouped into: errors in measurement and data recording; technical problems at the observation site; local anthropogenic impact and other unclassified problems. The improvement from the rescue approach was assessed by comparing the Akaike information criterion derived from fitted ARMA and ARIMA models to both original and repaired time series. The results showed that models fitted using repaired time series were better than those fitted on the original time series for the same time series sections. The presented rescue approach and results can be of great value for all studies using groundwater level time series as an input.Original artticle excluded the Delft the affiliation (second) of Willem Jan Zaadnoordijk Corrigendum DOI 10.16/j.hydrol.2022.127563Water ResourcesCivil Engineering and Geoscience