Mitigating glyphosate levels in surface waters: Long-term assessment in an agricultural catchment in Belgium.

The increasing concern over pesticide pollution in water bodies underscores the need for effective mitigation strategies to support the transition towards sustainable agriculture. This study assesses the effectiveness of landscape mitigation strategies, specifically vegetative buffer strips, in reducing glyphosate loads at the catchment scale under realistic conditions. Conducted over six years (2014-2019) in a small agricultural region in Belgium, our research involved the analysis of 732 water samples from two monitoring stations, differentiated by baseflow and event-driven sampling, and before (baseline) and after the implementation of mitigation measures. The results indicated a decline in both the number and intensity of point source losses over the years. Additionally, there was a general decrease in load intensity; however, the confluence of varying weather conditions (notably dry years during the mitigation period) and management practices (the introduction of buffer strips) posed challenges for a statistically robust evaluation of each contributing factor. A reduction of loads was measured when comparing mitigation with baseline, although this reduction is not statistically significant. Glyphosate loads during rainfall events correlated with a rainfall index and runoff ratio. Overall, focusing the mitigation strategy on runoff and erosion was a valid approach. Nevertheless, challenges remain, as evidenced by the continuous presence of glyphosate in baseflow conditions, highlighting the complex dynamics of pesticide transport. The study concludes that while progress has been made towards reducing pesticide pollution, the complexity of interacting factors necessitates further research. Future directions should focus on enhancing farmer engagement in mitigation programs and developing experiments with more intense data collection that help to assess underlying dynamics of pesticide pollution and the impact of mitigation strategies in more detail, contributing towards the goal of reducing pesticide pollution in water bodies.

A multi-actor, participatory approach to identify policy and technical barriers to better farming practices that protect our drinking water sources.

Despite an improvement of water quality across Europe there are many pollution hotspots for both nitrates and PPPs, mainly due to agricultural activities. The BMPs and MMs to reduce pollution from agriculture are well known, and there are policy instruments in place to ensure drinking water standards, but the current approach has not been efficient enough. Within the H2020 Water Protect project the premise was that there is a need for a multi-actor, participatory approach to tackle the issue from a new angle, and to assess why the uptake of known BMPs and MMs was not better among farmers. Seven "Action Labs" were selected that represent major physical, socio-economical, cultural and farming settings across Europe. A methodology of multi-actor engagement was chosen but with different approaches due to the local context. Initially the level of farmers' awareness about water quality issues was matched to the observed uptake rates of BMPs and MMs. In a second survey barriers hindering the uptake of measures were identified. The first survey revealed a low general awareness on the potential pollution to drinking water sources. Despite this, between 24% to 88% of the surveyed farmers per Action Lab were already voluntarily adopting one quarter of the selected BMPs and MMs. The second survey demonstrated the need to address organisational, legislative, sociological and technical barriers. The lack of coordination between different institutional bodies promoting measures and the financial incentives needed to invest and operate these often-costly measures need to be considered. The multi-actor, participatory approach with its improved awareness and collaboration made it possible to identify the crucial factors for improvement - to build a social acceptance among all actors and communicate the issues and solutions from the start.

A spatial approach to identify priority areas for pesticide pollution mitigation.

Identifying priority areas is an essential step in developing management strategies to reduce pesticide loads in surface water. A spatially explicit model-based approach was developed to detect priority areas for diffuse pesticide pollution at catchment scale. The method uses available datasets and considers different pesticide pathways in the environment post-application. The approach was applied in a catchment area in SE Flanders (Belgium) as a case study. Calculated risk areas were obtained using detailed landscape data and combining pesticide emissions and hydrological connectivity. The risk areas obtained were further compared with an alternative observation-based method, developed specifically for this study site that includes long-term field observations and local expert knowledge. Both methods equally classified 50% of the areas. The impact of crop rotation on the calculated risk was analysed. High-risk areas were identified and added to a cumulative map over all five years to evaluate temporal variations. The model-based approach was used for the initial identification of risk areas at the study site. The tool helps to prioritise zones and detect particular fields to target landscape mitigation measures to reduce diffuse pesticide pollution reaching surface water bodies.

Model-based Scenario Analysis of the Impact of Remediation Measures on Metal Leaching from Soils Contaminated by Historic Smelter Emissions.

A spatially distributed model for leaching of Cd from the unsaturated zone was developed for the Belgian-Dutch transnational Kempen region. The model uses as input land-use maps, atmospheric deposition data, and soil data and is part of a larger regional model that simulates transport of Cd in soil, groundwater, and surface water. A new method for deriving deposition from multiple sites was validated using soil data in different wind directions. Leaching was calculated for the period 1890 to 2010 using a reconstruction of metal loads in the region. The model was able to reproduce spatial patterns of concentrations in soil and groundwater and predicted the concentration in shallow groundwater adequately well for the purpose of evaluating management options. For 42% of the data points, measurements and calculations were within the same concentration class. The model was used for forecasting under a reference scenario, an autonomous development scenario including climate change, and a scenario with implementation of remediation measures. The impact of autonomous development (under the most extreme scenario of climatic change) amounted to an increase of 10% in cumulative Cd flux after 100 yr as compared with the reference scenario. The impact of remediation measures was mainly local and is less pronounced (i.e., only 3% change in cumulative flux at the regional scale). The integrated model served as a tool to assist in developing management strategies and prioritization of remediation of the wide-spread heavy metal contamination in the region.

The addition of organic carbon and nitrate affects reactive transport of heavy metals in sandy aquifers.

Organic carbon introduction in the soil to initiate remedial measures, nitrate infiltration due to agricultural practices or sulphate intrusion owing to industrial usage can influence the redox conditions and pH, thus affecting the mobility of heavy metals in soil and groundwater. This study reports the fate of Zn and Cd in sandy aquifers under a variety of plausible in-situ redox conditions that were induced by introduction of carbon and various electron acceptors in column experiments. Up to 100% Zn and Cd removal (from the liquid phase) was observed in all the four columns, however the mechanisms were different. Metal removal in column K1 (containing sulphate), was attributed to biological sulphate reduction and subsequent metal precipitation (as sulphides). In the presence of both nitrate and sulphate (K2), the former dominated the process, precipitating the heavy metals as hydroxides and/or carbonates. In the presence of sulphate, nitrate and supplemental iron (Fe(OH)(3)) (K3), metal removal was also due to precipitation as hydroxides and/or carbonates. In abiotic column, K4, (with supplemental iron (Fe(OH)(3)), but no nitrate), cation exchange with soil led to metal removal. The results obtained were modeled using the reactive transport model PHREEQC-2 to elucidate governing processes and to evaluate scenarios of organic carbon, sulphate and nitrate inputs.