Charakterisierung des Nitratabbauvermögens der Grundwasserleiter in Sachsen-Anhalt

Hannappel, Stephan; Kopp, C.; Bach, Thomas

doi:10.1007/s00767-018-0402-7

Cited by 13 publications

(22 citation statements)

References 12 publications

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“…Similar findings are described in Kunkel et al (2004) who conclude that aquifers with reduced nitrate degrading capacity occur in the North German Plain, while non-nitrate-degrading conditions prevail in aquifers of consolidated units. Hannappel et al (2018) also found that the denitrification potential in quaternary and tertiary unconsolidated rocks is clearly higher than in the consolidated units.…”

Section: Discussionmentioning

confidence: 78%

“…The uncertainties in this area are also high. In the consolidated units of central and southern Germany, fractured and karst aquifers are generally more vulnerable to contamination and predominantly indicate higher groundwater nitrate concentrations, which is also in line with a lower nitrate reduction potential due to aerobic to intermediate redox conditions (Hannappel et al 2018). In these consolidated regions, the high nitrate concentrations in the groundwater correspond to areas with high nitrogen surpluses caused by intensively agriculturally used depressions.…”

Section: Discussionmentioning

confidence: 81%

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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: Discussionmentioning

confidence: 78%

Section: Discussionmentioning

confidence: 81%

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

Knoll

Bach

2020

Environ. Res. Lett.

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Section: Weighted Regression On Time Discharge and Season (Wrtds) Amentioning

confidence: 99%

“…The software package "Exploration and Graphics for RivEr Trends" (EGRET) in the R environment by Hirsch and DeCicco (2019) was used to estimate daily concentrations of NO 3 -N utilizing "Weighted Regressions on Time, Discharge, and Season" (WRTDS). The WRTDS method allows the interpolation of an irregularly sampled concentration to a regular series at a daily timescale using a flexible statistical representation for every day of the discharge record and proved to provide robust estimates (Hirsch et al, 2010;van Meter and Basu, 2017). In brief, a regression model based on the predictors discharge and time (to represent long-term trend and seasonal component) is fitted for each day of the flow record with a flexible weighting of observations based on their time, seasonal and discharge "distance" (Hirsch et al, 2010).…”

Section: Weighted Regression On Time Discharge and Season (Wrtds) Amentioning

confidence: 99%

“…The mass of N being transported through the catchment storage can be referred to as hydrological legacy. Data-driven or simplified mechanistic approaches have often been used to derive stationary and seasonally variable travel time distributions (TTDs) using input and output signals of conservative tracers or isotopes (Jasechko et al, 2016;Heidbüchel et al, 2012) or chloride concentrations (Kirchner et al, 2000;Bennettin et al, 2015). Recently, van Meter and Basu (2017) estimated the solute TTs for N transport at several stations across a catchment located in Southern Ontario, Canada, showing decadal timelags between input and riverine exports.…”

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confidence: 99%

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Trajectories of nitrate input and output in three nested catchments along a land use gradient

Ehrhardt

Kumar

Fleckenstein

et al. 2019

Hydrol. Earth Syst. Sci.

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Increased anthropogenic inputs of nitrogen (N) to the biosphere during the last few decades have resulted in increased groundwater and surface water concentrations of N (primarily as nitrate), posing a global problem. Although measures have been implemented to reduce N inputs, they have not always led to decreasing riverine nitrate concentrations and loads. This limited response to the measures can either be caused by the accumulation of organic N in the soils (biogeochemical legacy) -or by long travel times (TTs) of inorganic N to the streams (hydrological legacy). Here, we compare atmospheric and agricultural N inputs with longterm observations of riverine nitrate concentrations and loads in a central German mesoscale catchment with three nested subcatchments of increasing agricultural land use. Based on a data-driven approach, we assess jointly the N budget and the effective TTs of N through the soil and groundwater compartments. In combination with long-term trajectories of the C-Q relationships, we evaluate the potential for and the characteristics of an N legacy.We show that in the 40-year-long observation period, the catchment (270 km 2 ) with 60 % agricultural area received an N input of 53 437 t, while it exported 6592 t, indicating an overall retention of 88 %. Removal of N by denitrification could not sufficiently explain this imbalance. Log-normal travel time distributions (TTDs) that link the N input history to the riverine export differed seasonally, with modes spanning 7-22 years and the mean TTs being systematically shorter during the high-flow season as compared to low-flow conditions. Systematic shifts in the C-Q relationships were noticed over time that could be attributed to strong changes in N inputs resulting from agricultural intensification before 1989, the break-down of East German agriculture after 1989 and the seasonal differences in TTs. A chemostatic export regime of nitrate was only found after several years of stabilized N inputs. The changes in C-Q relationships suggest a dominance of the hydrological N legacy over the biogeochemical N fixation in the soils, as we expected to observe a stronger and even increasing dampening of the riverine N concentrations after sustained high N inputs. Our analyses reveal an imbalance between N input and output, long timelags and a lack of significant denitrification in the catchment. All these suggest that catchment management needs to address both a longer-term reduction of N inputs and shorterterm mitigation of today's high N loads. The latter may be covered by interventions triggering denitrification, such as hedgerows around agricultural fields, riparian buffers zones or constructed wetlands. Further joint analyses of N budgets and TTs covering a higher variety of catchments will provide a deeper insight into N trajectories and their controlling parameters.

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Modeling Nitrate Export from a Mesoscale Catchment Using StorAge Selection Functions

Nguyen

Kumar

Lutz

et al. 2020

Preprint

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Human activities, especially agricultural practices, have altered the Earth's landscape. About 40% of the Earth's land surface has been converted to agricultural land (Foley, 2017). With a predicted increase in the global population until the middle of the 21st century, agricultural activities will be further intensified to meet the global food demand (The Royal Society, 2009;Godfray et al., 2010). This may have negative impacts on the ecosystem and human health. Nutrient pollution from agricultural sources has been identified as one of the major threats to aquatic ecosystems and via drinking water to human health in many areas worldwide (Alvarez-Cobelas et al., 2008;Vitousek et al., 2009). In recent years, there has been a call for a "sustainable intensification" (increasing agricultural productivity from the same agricultural land area while reducing its environmental impacts) of agricultural practices (The Royal Society, 2009; Godfray et al., 2010). To achieve such an objective, understanding the transport and fate of solutes from their entry into a catchment to the catchment outlet is necessary.The age of a water parcel, that is, the time passed since its entry into a catchment, provides valuable information for understanding flow and transport processes at the catchment scale (Benettin, Bailey, et al., 2015;Botter et al., 2011;Sprenger et al., 2019). This is because the age of a water parcel encapsulates information about its flow path characteristics, the time it has been in contact with catchment material, and the hydrological processes it has been subjected to (Asadollahi et al., 2020;McDonnell et al., 2010;Rodriguez et al., 2018). In recent years, the formulation of transport based on the age of water (transit time distributions, TTDs) has been emerging as a useful tool for understanding how catchments store, mix, and release water and solutes (

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Charakterisierung des Nitratabbauvermögens der Grundwasserleiter in Sachsen-Anhalt

Cited by 13 publications

References 12 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

Trajectories of nitrate input and output in three nested catchments along a land use gradient

Modeling Nitrate Export from a Mesoscale Catchment Using StorAge Selection Functions

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