Analysing agricultural plant protection product concentrations in groundwater in Germany: Nationwide database with site and compound insights.

Pesticides from agricultural practices are among the most pressing reasons why groundwater sources do not reach the good chemical status standards as required by the European Water Framework directive. Complementary to previous federal pesticide reports, we analysed groundwater-monitoring data from 13 German Länder assembled in a database consisting of 26.192 groundwater measuring sites sampled between 1973 and 2021 of in total 521 parent compounds and metabolites. This study focuses on agricultural plant protection products. The monitored substance spectrum and site density developed over time and differs between Länder. More than 95 % of all samples lie below the respective (multiple) limits of quantification (LOQ). We thus report the frequency of exceedance above concentration thresholds, which allows to compare measurements temporally and spatially. Pesticide detections were found in all aquifer types, land uses and well screen depths. Most detections of higher concentrations were found in agricultural areas, at shallow screen depth in porous aquifers. Karst aquifers showed also a higher percentage of samples in higher concentration classes. Metabolites with high mobility and persistence were found in higher concentration ranges. Herbicides and metabolites thereof dominate the top 20 of pesticides that most frequently exceed 0.1 µg L-1. The ranking for 2010-2019 includes both authorised and banned compounds and their occurrence is discussed in the context of their mobility, persistence and underlying monitoring density. Yearly exceedance frequencies above 0.05, 0.1 µg L-1 and higher thresholds of metazachlor and its esa-metabolite, and national sales data of the parent compound did not show a temporal correlation in subsequent years. This study stresses the need for the harmonisation of heterogeneous pesticide data. Further, a characterisation of the groundwater data used to analyse pesticide occurrence in selected concentration ranges for relevant site factors and compound properties and provides a pesticide ranking based on exceedance frequencies is provided.

Multiorder hydrologic Position for Europe - a Set of Features for Machine Learning and Analysis in Hydrology.

The presented dataset EU-MOHP v013.1.1 provides multiscale information on the hydrologic position (MOHP) of a geographic point within its respective river network and catchment as gridded maps. More precisely, it comprises the three measures "divide to stream distance" (DSD) as sum of the distances to the nearest stream and catchment divide, "lateral position" (LP) as a relative measure of the position between the nearest stream and divide and "stream distance" (SD) as the distance to the nearest stream. These three measures are calculated for nine hydrologic orders to reflect different spatial scales from local to continental. Its spatial extent covers major parts of the European Economic Area (EEA39) which also largely coincides with physiographical Europe. Although there are multiple potential use cases, this dataset serves predominantly as valuable static environmental descriptor or predictor variable for hydrogeological and hydrological modelling such as mapping or forecasting tasks using machine learning. The generation of this dataset uses free open source software only and therefore can be transferred to other regions or input datasets.

Deep learning shows declining groundwater levels in Germany until 2100 due to climate change.

In this study we investigate how climate change will directly influence the groundwater resources in Germany during the 21st century. We apply a machine learning groundwater level prediction approach based on convolutional neural networks to 118 sites well distributed over Germany to assess the groundwater level development under different RCP scenarios (2.6, 4.5, 8.5). We consider only direct meteorological inputs, while highly uncertain anthropogenic factors such as groundwater extractions are excluded. While less pronounced and fewer significant trends can be found under RCP2.6 and RCP4.5, we detect significantly declining trends of groundwater levels for most of the sites under RCP8.5, revealing a spatial pattern of stronger decreases, especially in the northern and eastern part of Germany, emphasizing already existing decreasing trends in these regions. We can further show an increased variability and longer periods of low groundwater levels during the annual cycle towards the end of the century.

Fiber Optic Measurements of Soil Moisture in a Waste Rock Pile.

The design and construction of a waste rock pile influences water infiltration and may promote the production of contaminated mine drainage. The objective of this project is to evaluate the use of an active fiber optic distributed temperature sensing (aFO-DTS) protocol to measure infiltration and soil moisture within a flow control layer capping an experimental waste rock pile. Five hundred meters of fiber optic cable were installed in a waste rock pile that is 70 m long, 10 m wide, and was covered with 0.60 m of fine compacted sand and 0.25 m of non-reactive crushed waste rock. Volumetric water content was assessed by heating the fiber optic cable with 15-min heat pulses at 15 W/m every 30 min. To test the aFO-DTS system 14 mm of recharge was applied to the top surface of the waste rock pile over 4 h, simulating a major rain event. The average volumetric water content in the FCL increased from 0.10 to 0.24 over the duration of the test. The volumetric water content measured with aFO-DTS in the FCL and waste rock was within ±0.06 and ±0.03, respectively, compared with values measured using 96 dielectric soil moisture probes over the same time period. Additional results illustrate how water can be confined within the FCL and monitored through an aFO-DTS protocol serving as a practical means to measure soil moisture at an industrial capacity.