Comparison of measured and predicted herbicide concentrations in surface water catchments in Belgium.

In the process of approval of active substances and authorization in the European Union and at the member state level, it must be shown by the applicant that an unacceptable risk for nontarget organisms in the aquatic environment by the active substance can be excluded. To achieve this aim, standardized models, scenarios, and agreed pesticide input parameters have to be used to calculate the exposure as defined by the FOrum for the Co-ordination of pesticide fate models and their Use (FOCUS). During a period of daily surface water sampling lasting 3.5 years, a survey was conducted among farmers in the highly vulnerable catchment of Grote Kemmelbeek in Belgium to collect agronomic data on crops, application dates, and application rates of 12 applied herbicides and one metabolite. Daily surface water concentrations for the same herbicides were measured over 2.5 years for a second, much larger but less vulnerable, catchment of Kleine Aa (KAa). A comparison of realistic worst-case predicted environmental concentrations in surface water (PECsw) according to FOCUS with measured concentrations shows that, in the GKb catchment, the PECsw was never exceeded for six substances, was exceeded on only 1-2 days for five substances, and was exceeded on 9-27 days for two substances. For the KAa catchment, the PECsw was only exceeded on two days for one compound and never for the other 12 compounds. These numbers correspond to a level of protection of the FOCUS PECsw between 100% and 97% and are much higher than the regulatory protection goal of 90%. These two case studies demonstrate the protectiveness of the FOCUS surface water approach. Integr Environ Assess Manag 2024;00:1-16. © 2024 Bayer AG. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Runoff mitigation on agricultural fields via micro-dams - Literature review and derivation of runoff curve number reductions.

Water runoff and soil erosion by water from agricultural fields lead to a loss of water available for plant growth, loss of topsoil and transport of plant protection products (PPPs), hence constituting contaminant pathways to adjacent surface water. Several mitigation measures are used, including small earthen dams or depressions, referred to as micro-dams. This practice has been applied worldwide since the 1930s. In the regulatory exposure assessment for the registration of PPPs, runoff curve numbers (CNs) are used in the PRZM model to quantify runoff and the effect of mitigation measures. An overview of the pertinent literature is presented to enlarge the knowledge base to give robust recommendations for the inclusion of the practice in the regulatory exposure assessment of PPPs. Literature on micro-dams was collected here in a review of the reported results from field trials in terms of runoff, erosion, and PPP transport mitigation. Selected data were further evaluated to derive runoff CNs. From 21 studies with 252 individual setups and trials, we derived a geometric mean reduction of runoff of 62% (42%-90%); results for maize and potatoes only were 62% (53%-73%) and 81% (71%-93%), respectively. Erosion was reduced by 73% (60%-90%; maize: 75% [63%-88%]; potatoes 89% [83%-97%]). From 19 studies with 246 individual setups and trials, the geometric mean of the CN reduction is 11% (4%-25%; maize: 7% [3%-17%], potatoes: 14% [6%-36%]). For PPP transport (5 studies; 10 different PPP), a geometric mean reduction of 67% (48%-94%) was derived (maize: 56% [38%-81%; 3 studies; 10 PPP]; potatoes: 91% [1 study; 4 PPP]). The application of micro-dams provides considerable reductions and can therefore be factored into the environmental exposure assessment by using percent reductions of runoff, erosion, and PPP transport or lowering the runoff CN in numerical modelling.

Analysis and management of herbicidal mixtures in a high-intensity agricultural landscape in Belgium.

Water bodies located in anthropogenically influenced environments, such as agricultural landscapes, may be exposed to different chemicals simultaneously or sequentially. Yet, current environmental risk assessments focus on single active substances for unintended mixtures. For 3.5 years, the present study monitored the mixture of herbicides, within an intensively managed agricultural catchment, accompanied by a stewardship program. Twelve herbicides and one metabolite were monitored on a daily to sub-daily basis, generating a unique, high temporal resolution data set, enabling an assessment of cumulative exposure in a worst-case scenario. Analyses focused on the number of events at which the herbicide mixture concentration exceeded the regulatory accepted concentration for algae and macrophytes, based on concentration addition, and the potential factors influencing the frequency of these events are considered. A low number of individual herbicides drove the toxicity and only two of these overlapped for the two organism groups, algae and macrophytes. The observed exceedance events coincided with seasonal influences, and low rainfall during the 2011 season correlated with a highly reduced number of these events. The major influence was found to be the implementation of the stewardship program, which directed farmers to use more advanced farming techniques, avoid spillages, and other point sources. The number of exceedance events was reduced by more than half for algae (9% of the daily mean samples in 2010 and 4% in 2013) and by approximately 10 times for macrophytes (36% in 2010 to 3% in 2013). This high-resolution monitoring data set illustrates how knowledge of the influencing factors can help reduce unintended exposure to chemicals and achieve real-world improvements. Overall, a single-substance assessment is protective of mixture effects. Where mixture effects do play a role, local measures to manage point sources are more effective than changes to the desk-based environmental risk assessments that focus on diffuse sources. Integr Environ Assess Manag 2023;19:1297-1306. © 2022 Cambridge Environmental Assessments RSK ADAS Ltd and Bayer AG. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Dynamic prediction of effective runoff sediment particle size for improved assessment of erosion mitigation efficiency with vegetative filter strips.

The most widely implemented mitigation measure to reduce transfer of surface runoff pesticides and other pollutants to surface water bodies are vegetative filter strips (VFS). The most commonly used dynamic model for quantifying the reduction by VFS of surface runoff, eroded sediment, pesticides and other pollutants is VFSMOD, which simulates reduction of total inflow (∆Q) and of incoming eroded sediment load (∆E) mechanistically during the rainfall-runoff event. These variables are subsequently used to calculate the reduction of pesticide load by the VFS (∆P). Since errors in ∆Q and ∆E propagate into ∆P, for strongly-sorbing compounds an accurate prediction of ∆E is crucial for a reliable prediction of ∆P. The most important incoming sediment characteristic for ∆E is the median particle diameter (d50). Current d50 estimation methods are simplistic, yielding fixed d50 based on soil properties and ignoring specific event characteristics and dynamics. We derive an improved dynamic d50 parameterization equation for use in regulatory VFS scenarios based on an extensive dataset of 93 d50 values and 17 candidate explanatory variables compiled from heterogeneous data sources and methods. The dataset was analysed first using machine learning techniques (Random Forest, Gradient Boosting) and Global Sensitivity Analysis (GSA) as a dimension reduction technique and to identify potential interactions between explanatory variables. Using the knowledge gained, a parsimonious multiple regression equation with 6 predictors was developed and thoroughly tested. Since three of the predictors are event-specific (eroded sediment yield, rainfall intensity and peak runoff rate), predicted d50 vary dynamically across event magnitudes and intensities. Incorporation of the improved d50 parameterization equation in higher-tier pesticide assessment tools with VFSMOD provides more realistic quantitative mitigation in regulatory US-EPA and EU FOCUS pesticide risk assessment frameworks. The equation is also readily applicable to other erosion management problems.

Evaluation of SEAWAVE-QEX in a high agricultural intensity catchment in Belgium.

Pesticide surface water monitoring data have rarely been used as the only quantitative measure of exposure because the available monitoring data for most pesticides has not been considered robust enough for direct use in pesticide exposure assessments due to infrequent sampling. The cost of daily sample collection and analysis prohibits frequent sampling for most monitoring programs. In this context, a common question raised in assessments is how likely peak concentrations (i.e., annual maxima) may be missed if sampling intervals are longer than daily. The US Geological Survey developed the statistical model "seasonal wave with streamflow adjustment and extended capability" (SEAWAVE-QEX) to address the need to estimate infrequently occurring pesticide concentrations, such as annual maximum daily concentrations, for sites with nondaily monitoring data. This study compares the results of two postprocessing methods and evaluates the capability of SEAWAVE-QEX to estimate annual maximum concentrations of three commonly used herbicides and one metabolite in a catchment in Belgium. The study concludes that the appropriateness of using SEAWAVE-QEX to estimate annual maximum concentrations depends on pesticide characteristics and use and that the model can be particularly sensitive to nonflow correlated exposure events (e.g., point source contributions or drift). Integr Environ Assess Manag 2023;19:513-526. © 2022 Stone Environmental and Bayer AG Crop Science Division. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Field leaching study - Inverse estimation of degradation and sorption parameters for a mobile soil metabolite and its pesticide parent.

Pesticide concentration measurements from field studies under real-world conditions can improve the derivation of more representative modelling input parameters for the exposure assessment of agrochemicals in the authorization process of plant protection products. The pertinent guidance documents foresee the application of inverse modelling approaches in combination with environmental fate and transport models to estimate e.g., soil dissipation rates that are solely based on microbial degradation and are not lumped with contributions from other dissipation processes such as leaching, plant uptake, volatilization and photodegradation. Field leaching studies can be used to estimate both degradation and sorption of chemicals in the soil matrix. In this study, inverse modelling of environmental fate parameters is presented based on solute concentrations from a field leaching study sampling pore water from five different depths down to 1.5 m. The leaching model PEARL and the universal optimization tool PEST were coupled, and sorption and degradation of the fungicide fluopicolide and its soil metabolite BAM (2,6-dichlorobenzamide) were quantified. Soil degradation half-lives were not different from results obtained in regular field degradation studies sampling residues in the total soil matrix (236 d vs. 158 d for fluopicolide and 53 d vs. 45 d for BAM); whereas a sorption increase with time (time-dependent sorption) was observed for the parent compound. This work aims at pointing out the feasibility to include field leaching studies with measurements at different soil depths in regulatory exposure assessment, since a statistically significant derivation of degradation and sorption parameters is presented, along with low uncertainties in the estimated parameter values of ±10%.

Modeling effectiveness of two runoff mitigation measures in the Netherlands.

Rainfall that exceeds the soil's maximum infiltration rate is prone to runoff, and the excess rainfall will flow toward open water systems. Nutrients, pesticides or other contaminants may be transported along with this overland flow, thus contaminating surface waters. There are various measures that can be implemented to prevent or reduce runoff, which involve either improving the soil's infiltration capacity or temporarily storing more water at the field scale. The aim of this study was to determine the effectiveness of two mitigation measures, i.e., micro-dams and edge-of-field trenches, in reducing the total number of runoff events and the runoff volume for specific rainfall events. For this purpose, numerical simulations were performed with a deterministic soil-water-atmosphere-plant model for reference situations and for situations involving either of the two mitigation measures. The mitigation measures are implemented as a change in the ponding threshold height above which the model predicts runoff. For this purpose, we considered several soil / groundwater level / crop / intrinsic field soil surface storage situations that are common in the Netherlands. For ridge-furrow cropping systems, micro-dams are more effective than edge-of-field trenches. Depending on the soil type (excluding sand), the minimum effectiveness is 70% and may be >90% in specific situations. For the edge-of-field trench, the reduction in runoff events was mostly in the 24-35% range, while the effectiveness for the runoff volume for a rainfall event that typically occurs once per year was in the 13-48% range (excluding sand). Due to the relatively high hydraulic conductivity at saturation for the sandy soils, runoff was simulated in only a few cases for these soils. The effectiveness was evidently dependent on intrinsic field soil surface storage and soil types, varied slightly between crop types and was very similar across the groundwater level classes considered.

Runoff mitigation via micro-dams and conservation tillage-Numerical modeling of runoff and erosion from maize field trials.

Runoff and erosion are the most important transport pathways of water, sediment, and associated pesticides from sloped agricultural fields. This results in the loss of fertile topsoil material, nutrients, irrigation water, and plant protection products (PPP) into adjacent surface water bodies. In the European and US risk assessment for the registration of PPP, runoff and erosion are numerically calculated with the simulation Pesticide Root Zone Model (PRZM) using the US Department of Agriculture (USDA) runoff curve number (CN) concept for the water movement and the MUSS equation to quantify the sediment transfer. This work presents an evaluation of maize field trials conducted in three seasons that considered micro-dams (i.e., small earthen dams between the rows; also known as "furrow diking," "furrow damming," etc.) and/or conservation tillage (via subsoiling) as mitigation measures to investigate the effects on the reduction in runoff and erosion. Measured quantitative reductions and event-wise calculated CN are presented. Furthermore, the trials were simulated using the PRZM over the complete vegetation period and runoff CN as well as parameter values of the MUSS erosion equation (a relative adaptation of the C-factor) were inversely estimated. Compared with the control plots (i.e., conventional tillage), micro-dams or conservation tillage reduced runoff by 24%-71% or 69%-89%, and erosion by 54%-81% or 91%-98%. Based on these data, a robust case can be made to lower CN or parameters in the MUSS equation for surface water exposure scenarios to consider the effects on predicted environmental concentrations (PECs) and estimated environmental concentrations (EECs). Mean resulting CN reductions by micro-dams or conservation tillage were ascertained to be 6% (±2.5%) or 12% (±3.0%), the C-factor was reduced by a factor of 0.1 (±0.15) or 0.48 (±0.19). Example calculations show reductions in the ranges of 11%-100% for PECs and 30%-98% for EECs. Integr Environ Assess Manag 2022;18:1348-1363. © 2021 Bayer AG Crop Science. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Recalibration and cross-validation of pesticide trapping equations for vegetative filter strips (VFS) using additional experimental data.

Vegetative filter strips (VFS) are widely used for mitigating pesticide inputs into surface waters via surface runoff and erosion. To simulate the effectiveness of VFS the model VFSMOD is frequently used. While VFSMOD simulates infiltration and sedimentation mechanistically, the reduction of pesticide load in surface runoff by the VFS is calculated with the empirical Sabbagh equation. This multiple regression equation has not been widely accepted by regulatory authorities, because its reliability has not been sufficiently demonstrated yet. A major drawback is the small number of calibration data points (n = 47). To corroborate and improve the predictive capability of the Sabbagh equation, additional experimental VFS data were compiled from the available literature. The enlarged dataset (n = 244) was used to recalibrate the Sabbagh equation, the recently proposed Chen equation and a set of "reduced" Sabbagh equations with fewer independent variables, with ordinary least squares (OLS) regression and to test an alternative, regression-free mass balance approach. The Sabbagh equation fitted the dataset slightly better than the Chen equation (coefficient of determination R2 = 0.82 vs. 0.79). The purely predictive mass balance approach performed slightly worse (Nash-Sutcliffe Efficiency NSE = 0.74), but significantly better than the Sabbagh and Chen equations with their old coefficients. In a k-fold cross validation analysis to assess the predictive capability of the various regression equations, both the full Sabbagh and the reduced Sabbagh equations with two or more variables outperformed the Chen equation. Finally, a maximum-likelihood-based calibration and uncertainty analysis were conducted for the Sabbagh equation using the DREAM_ZS algorithm and two different likelihood functions. The DREAM simulations corroborated the parameter values obtained with OLS regression. The study confirmed the suitability of the Sabbagh equation for regulatory modelling of pesticide trapping in VFS. However, the regression-free mass balance approach turned out to be a viable alternative.

Evaluation of a novel test design to determine uptake of chemicals by plant roots.

A new hydroponic study design to determine uptake of chemicals by plant roots was tested by (i) investigating uptake of [14C]-1,2,4-triazole by wheat plants in a ring test with ten laboratory organizations and (ii) studying uptake of ten other radiolabelled chemicals by potato, tomato or wheat plants in two laboratories. Replicate data from the ring test were used to calculate plant uptake factor (PUF) values (uptake into roots and shoots) and transpiration stream concentration factor (TSCF) values (uptake into shoots). Average PUF for 1,2,4-triazole was 0.73 (n=39, 95% confidence interval (CI): 0.64, 0.82) and the corresponding TSCF value was 1.03 (n=49, 95% CI: 0.76, 1.3). Boxplots and subsequent classification tree analysis of PUF and TSCF values showed that potential outlier values were >1.38 and were observed for PUF replicates with low biomass increase (ratio of final to initial biomass ≤1.739) and small initial biomass (≤1.55g) and for TSCF replicates with an increase in biomass of <0.67g over a period of eight days. Considering only valid replicate data, average values of PUF and TSCF were 0.65 (n=33, 95% CI: 0.57, 0.73) and 0.64 (n=39, 95% CI: 0.58, 0.70). The additional experiments with ten chemicals and three plant species showed that uptake was low for polar substances of high molecular weight (≥394g/mol) and that TSCF values increased with log Kow values of the tested chemicals ranging from -1.54 to 1.88 (polynomial equation with R2=0.64). A cluster analysis for three of the compounds that were tested on wheat and tomato indicated that the plant uptake was mainly determined by the substance. Overall, the findings show that the hydroponic study design allows for reliable quantification of plant uptake over a range of compound/crop combinations.