This study evaluates the effectiveness of Wallonia's sustainable nitrogen management program against groundwater nitrate contamination, 20 years post-implementation. We analysed nitrate concentration time series from 36 locations, finding a modest overall improvement and variability across sites. Results reveal interrelated controlling factors, with land use and aquifer characteristics being key. Lack of improvement may be due to a time lag before the impact of regulatory measures is observable.

Causal inference methods (CIMs) aim at identifying causal links from temporal dependencies found in time-series data. Using both synthetic data and real-time series from a karst system, we study and discuss the potential of four CIMs to reveal hydrological connections between variables in hydrological systems. Despite the ever-present risk of spurious hydrological connections, our results highlight that the nonlinear and multivariate CIM has a substantially lower false-positive rate.

Cover cropping enhance many agricultural services, but few studies are available on the long term effect on hydraulic properties. Soil water content was monitored daily in a 10-year field experiment and hydraulic properties were determined based on inverse calibration. Cover crop increased of the soil micro- and macro-porosity. Then, the expected cover crop competition for water can be compensated by an improvement of the water retention in the intermediate layers of the soil profile.

Few studies are available allowing to evaluate the impact of cover cropping on the long term change of soil hydrologic functions, so we assessed the changes during a 10-year field experiment. This study shows that the expected cover crop competition for water with the main crop can be compensated by an improvement of the water retention in the intermediate layers of the soil profile, enhancing the hydrologic functions of agricultural soils in regions which often are constrained by water stress.

In this paper, we present a meta-analysis of nitrate contamination in groundwater at the pan-African scale. A nitrate data set is constructed based on publications in the web of sciences, and combined with high-resolution generic spatial environmental attributes. A statistical model explains 65 % of the variation of nitrate contamination in groundwater in terms of generic spatial attributes. Nitrate contamination of groundwater at the pan-African scale is mainly affected by population density.