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.

Risk mitigation measures for pesticide runoff: How effective are they?

BACKGROUND: One of the most important sources of pesticide pollution of surface waters is runoff and erosion from agricultural fields after rainfall. This study analyses the efficacy of different risk mitigation measures to reduce pesticide runoff and erosion inputs into surface waters from arable land excluding rice fields. RESULTS: Three groups of risk mitigation measures were quantitatively analyzed: vegetative filter strips, micro-dams in row crops and soil conservation measures. Their effectiveness was evaluated based on a meta-analysis of available experimental data using statistical methods such as classification and regression trees, and exploratory data analysis. Results confirmed the effectiveness of vegetative filter strips and micro-dams. Contrary to common assumption, the width of vegetative filter strips alone is not sufficient to predict their effectiveness. The effectiveness of soil conservation measures (especially mulch-tillage) varied widely. This was in part due to the heterogeneity of the available experimental data, probably resulting from the inconsistent implementation and the inadequate definitions of these measures. CONCLUSION: Both vegetative filter strips and micro-dams are effective and suitable, and can therefore be recommended for quantitative assessment of environmental pesticide exposure in surface waters. However, the processes of infiltration and sedimentation in vegetative filter strips should be simulated with a mechanistic model like Vegetative Filter Strip Modeling System, VFSMOD. The reduction effect of micro-dams can be modelled by reducing the runoff curve number, e.g., in the pesticide root zone model, PRZM. Soil conservation measures are in principle promising, but further well-documented data are needed to determine under which conditions they are effective. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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.

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%.

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.

Fate of the antibiotic sulfadiazine in natural soils: Experimental and numerical investigations.

Based on small-scale laboratory and field-scale lysimeter experiments, the sorption and biodegradation of sulfonamide sulfadiazine (SDZ) were investigated in unsaturated sandy and silty-clay soils. Sorption and biodegradation were low in the laboratory, while the highest leaching rates were observed when SDZ was mixed with manure. The leaching rate decreased when SDZ was mixed with pure water, and was smallest with the highest SDZ concentrations. In the laboratory, three transformation products (TPs) developed after an initial lag phase. However, the amount of TPs was different for different mixing-scenarios. The TP 2-aminopyrimidine was not observed in the laboratory, but was the most prevalent TP at the field scale. Sorption was within the same range at the laboratory and field scales. However, distinctive differences occurred with respect to biodegradation, which was higher in the field lysimeters than at the laboratory scale. While the silty-clay soil favored sorption of SDZ, the sandy, and thus highly permeable, soil was characterized by short half-lives and thus a quick biodegradation of SDZ. For 2-aminopyrimidine, half-lives of only a few days were observed. Increased field-scale biodegradation in the sandy soil resulted from a higher water and air permeability that enhanced oxygen transport and limited oxygen depletion. Furthermore, low pH was more important than the organic matter and clay content for increasing the biodegradation of SDZ. A numerical analysis of breakthrough curves of bromide, SDZ, and its TPs showed that preferential flow pathways strongly affected the solute transport within shallow parts of the soil profile at the field scale. However, this effect was reduced in deeper parts of the soil profile. Due to high field-scale biodegradation in several layers of both soils, neither SDZ nor 2-aminopyrimidine was detected in the discharge of the lysimeter at a depth of 1m. Synthetic 50 year long simulations, which considered the application of manure with SDZ for general agricultural practices in Germany and humid climate conditions, showed that the concentration of SDZ decreased below 0.1 µg/L in both soils below the depth of 50 cm.

Dynamics of transformation of the veterinary antibiotic sulfadiazine in two soils.

Veterinary antibiotics administered to livestock can be unintentionally released into the environment, for example by the application of manure to soils. The fate of such antibiotics in soils is mostly determined by sorption and degradation processes, including transformation. There is a need to further examine the combined transformation and sorption behavior of these emerging pollutants in soils. Long-term batch sorption experiments with the (14)C-radiolabeled antibiotic sulfadiazine enabled us to simultaneously trace the sorption and transformation dynamics of sulfadiazine. The parent compound and the transformation products were analyzed in the liquid phase and in the extracts from the solid phase after a sequential extraction. We found that of up to six transformation products were formed during degradation and that these products exhibited quite different dynamics in the two soils. Transformation products were formed rapidly and were extractable from the solid phase. We observed identical sets of the transformation products in both phases. The input concentration influenced the course of transformation of the parent substance. We present a detailed analysis including a mathematical description and derive regulatory kinetic endpoints for predicting environmental concentrations.

Long-term sorption and sequestration dynamics of the antibiotic sulfadiazine: a batch study.

Understanding the long-term sequestration of veterinary antibiotics into soil fractions with different bioavailability is important in terms of assessing their eco-toxicological impact. We performed 60-d batch sorption experiments with radiolabeled sulfadiazine (SDZ) using samples from two agricultural soils. Sequential extraction with CaCl/MeOH (easily accessible fraction), microwave (residual fraction, RES), and combustion (nonextractable residues, NER) was used to quantify the sequestration dynamics of the C-derived SDZ-equivalent concentration. Multiple harsh extractions allowed us to mathematically extrapolate to the amount of SDZ equivalents that can be potentially extracted, resulting in halving the NER fraction after 60 d. A modified two-stage model with irreversible sorption combined with global parameter optimization was able to display the sequestration dynamics. We demonstrated this with sterilized samples in which no transformation of the parent compound was observed. This also showed that transformation was primarily biologically driven. These modeling results verified the procedure, which was then applied to nontreated samples from both soils to estimate effective parameter values for SDZ-derived equivalents. Observed initial sorption, to which up to 20% of the kinetic sorption sites attributed, was included in the model. Both the RES and NER fractions reached a sorption plateau, with NER occupying about 30% of the kinetic fraction (RES+NER) for all soils. The sorption and sequestration of SDZ were soil-specific and dominated by kinetics. Sequestration in the RES fraction was much slower (characteristic time: 60 d) than the redistribution in the NER fraction (characteristic time: <6 d). The work presented here contributes to the prediction of the dynamics of (bio-)availability.