Regionalisierte Darstellung der Nitratbelastung im Grundwasser Niedersachsens

Wriedt, Gunter; Vries, Dieter de; Eden, Tanja; Federolf, Christian

doi:10.1007/s00767-019-00415-0

Cited by 12 publications

(10 citation statements)

References 7 publications

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“…However, predictions are accompanied by rather high uncertainties, so that higher concentrations are at least within the confidence limits of the model. In the north-western part of Germany, high NO 3 concentrations occur in the Geest regions formed in the Middle Pleistocene, whereas in the lowlands the groundwater is almost nitrate-free, which is in line with Wriedt et al (2019). The redox conditions tend to be less anaerobic to intermediate in the Geest areas in contrast to the lowlands where strong anaerobic conditions prevail, which was also reported by Eschenbach et al (2018).…”

Section: Discussionsupporting

confidence: 81%

“…Tesoriero et al (2017) also showed a higher probability for high nitrate concentrations near the groundwater surface. Wriedt et al (2019) reported a decrease in nitrate concentrations with depth, but they concluded that a vertical gradation of depth horizons cannot adequately describe the hydrogeochemical zoning of the aquifers. Long screened sections can also lead to mixing of groundwater from the aerobic and anaerobic zone during sampling.…”

Section: Discussionmentioning

confidence: 99%

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Nation-wide estimation of groundwater redox conditions and nitrate concentrations through machine learning

Knoll

Bach

2020

Environ. Res. Lett.

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The protection of water resources and development of mitigation strategies require large-scale information on water pollution such as nitrate. Machine learning techniques like random forest (RF) have proven their worth for estimating groundwater quality based on spatial environmental predictors. We investigate the potential of RF and quantile random forest (QRF) to estimate redox conditions and nitrate concentration in groundwater (1 km × 1 km resolution) using the European Water Framework Directive groundwater monitoring network as well as spatial environmental information available throughout Germany. The RF model for nitrate achieves a good predictive performance with an R 2 of 0.52. Dominant predictors are the redox conditions in the groundwater body, hydrogeological units and the percentage of arable land. An uncertainty assessment using QRF shows rather large uncertainties with a mean prediction interval (MPI) of 53.0 mg l −1 . This study represents the first nation-wide data-driven assessment of the spatial distribution of groundwater nitrate concentrations for Germany.

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Section: Discussionsupporting

confidence: 81%

Section: Discussionmentioning

confidence: 99%

Nation-wide estimation of groundwater redox conditions and nitrate concentrations through machine learning

Knoll

Bach

2020

Environ. Res. Lett.

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“…While not as evident as for the screen lengths, the screen depth (below surface) showed a qualitatively inverse relationship with Mn concentration (Figure 6), demonstrating the greater susceptibility of shallow groundwater for elevated Mn concentrations, e.g., [39]. In another study [40] conducted in the in the same area to assess nitrate in surficial groundwater, the authors tried to address the problem of overlapping redox zones in monitoring wells by grouping the wells in classes according to the depth of the screens below the groundwater table. Regardless, they found only limited spatial correlation even amongst monitoring wells in close proximity.…”

Section: Discussionmentioning

confidence: 81%

Manganese (Mn) Concentrations and the Mn-Fe Relationship in Shallow Groundwater: Implications for Groundwater Monitoring

2020

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Manganese (Mn) concentrations in approximately 32,000 groundwater analyses from more than 4800 monitoring wells in northern Germany were evaluated. This region was considered well suited to study Mn in shallow groundwater in unconsolidated sediments. Spearman rank correlation was used to correlate between redox-sensitive parameters and the Mann–Kendall test for an evaluation of temporal trends. Manganese concentrations varied over two orders of magnitude and more than 40% of the wells had concentrations above 0.3 mg/L. Median Mn concentrations in the major hydrogeological units, the Geesten, tidal wetlands, and fluviatile lowlands were 0.12 mg/L, 0.46 mg/L, and 0.27 mg/L, respectively. Separating the data by land use, the median concentrations were 0.20 mg/L for arable land, 0.15 mg/L for forests, and 0.24 for grassland. Calculated background concentrations of Mn varied from <0.25 mg/L to 4.79 mg/L. A new parameter, ∆Mn-Fe, defined as the concentration difference between Mn and Fe in mg/L together with nitrate concentrations exceeding 50 mg/L was used to identify the fertilizer-borne input of nitrate. However, the factor controlling Mn occurrence seemingly was the depth of monitoring wells and the screen-length. Elevated concentrations of Mn and a high ∆Mn-Fe were generally found in shallow wells and wells with short screen-lengths.

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“…Those groundwater samples were collected mainly from wells in the Geesten hydrogeological unit. There, it can be assumed that the relatively high annual groundwater recharge of 200 mm to 400 mm (Elbracht et al ) caused fast seepage of nitrate surplus from agriculture (Wriedt et al ). Denitrification caused changes in the redox composition and subsequent acidification of groundwater, for example, by pyrite oxidation (Böhlke ).…”

Section: Resultsmentioning

confidence: 99%

“…The main land use in the present study area is farmland (46%), followed by woodland (22%), grassland (21%), and urban areas (7%) (BKG ). Most groundwater Cd concentrations that exceeded 0.5 µg/L were found in the western part of the Geesten (Figure ), which is characterized by intensive livestock farming and agriculture (LSKN ; Wriedt et al ). That observation seems to be closely related to the input of nitrate into groundwater, either by fertilizers or by effluent or manure application (Kubier and Pichler ).…”

Section: Methodsmentioning

confidence: 99%

Cadmium Background Levels in Groundwater in an Area Dominated by Agriculture

Kubier

Hamer

Pichler

2019

Integr Envir Assess & Manag

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Cadmium is a highly toxic trace metal, which can be of geogenic or anthropogenic origin, for example, minerals, phosphate fertilizers, and combustion emissions. Due to its low sorption affinity compared to other heavy metals, Cd is easily mobilized, potentially resulting in elevated Cd concentrations in groundwater. This study assessed background levels of Cd in groundwater related to hydrogeology and hydrogeochemical processes through evaluation of a large hydrogeochemical data set composed of groundwater analyses from 6300 wells in Northwestern Germany. Calculated Cd background levels in groundwater were between 0.01 µg/L in hydrogeological units with mainly reducing conditions and 0.98 µg/L in less reducing groundwater recharge areas. The results showed that groundwater Cd concentrations above 0.5 µg/L (the German threshold value) are not necessarily elevated but could be the regional or ambient background level, depending on the hydrogeological unit. What would be considered as ambient background levels, however, indicated the influence by continuous intensive land use as well as the local geology, which is dominated by glacial deposits. Cadmium concentrations in groundwater were mainly controlled by hydrogeochemical and hydrogeological parameters and not by the amount of anthropogenic Cd input, in particular through the use of phosphate fertilizers. Instead, analyses of the solid phase revealed that Cd release from the aquifer matrix due to changes in hydrogeochemical parameters was more likely. Aquifer sediments in Northwestern Germany can be enriched in Cd originating from multiple sources, which in turn can cause elevated Cd concentrations in groundwater. Integr Environ Assess Manag 2019;00:1–11. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)

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Regionalisierte Darstellung der Nitratbelastung im Grundwasser Niedersachsens

Cited by 12 publications

References 7 publications

Nation-wide estimation of groundwater redox conditions and nitrate concentrations through machine learning

Nation-wide estimation of groundwater redox conditions and nitrate concentrations through machine learning

Manganese (Mn) Concentrations and the Mn-Fe Relationship in Shallow Groundwater: Implications for Groundwater Monitoring

Cadmium Background Levels in Groundwater in an Area Dominated by Agriculture

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