Parameter importance and uncertainty in predicting runoff pesticide reduction with filter strips

A conceptual framework for landscape-based environmental risk assessment (ERA) of pesticides

While pesticide use is subject to strict regulatory oversight worldwide, it remains a main concern for environmental protection, including biodiversity conservation. This is partly due to the current regulatory approach that relies on separate assessments for each single pesticide, crop use, and non-target organism group at local scales. Such assessments tend to overlook the combined effects of overall pesticide usage at larger spatial scales. Integrative landscape-based approaches are emerging, enabling the consideration of agricultural management, the environmental characteristics, and the combined effects of pesticides applied in a same or in different crops within an area. These developments offer the opportunity to deliver informative risk predictions relevant for different decision contexts including their connection to larger spatial scales and to combine environmental risks of pesticides, with those from other environmental stressors. We discuss the needs, challenges, opportunities and available tools for implementing landscape-based approaches for prospective and retrospective pesticide Environmental Risk Assessments (ERA). A set of "building blocks" that emerged from the discussions have been integrated into a conceptual framework. The framework includes elements to facilitate its implementation, in particular: flexibility to address the needs of relevant users and stakeholders; means to address the inherent complexity of environmental systems; connections to make use of and integrate data derived from monitoring programs; and options for validation and approaches to facilitate future use in a regulatory context. The conceptual model can be applied to existing ERA methodologies, facilitating its comparability, and highlighting interoperability drivers at landscape level. The benefits of landscape-based pesticide ERA extend beyond regulation. Linking and validating risk predictions with relevant environmental impacts under a solid science-based approach will support the setting of protection goals and the formulation of sustainable agricultural strategies. Moreover, landscape ERA offers a communication tool on realistic pesticide impacts in a multistressors environment for stakeholders and citizens.

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.

Effectiveness of side-inlet vegetated filter strips at trapping pesticides from agricultural runoff

Agriculture can be a contributor of pollutants, including pesticides and excess sediment, to aquatic environments. However, side-inlet vegetated filter strips (VFSs), which are planted around the upstream side of culverts draining agricultural fields, may provide reductions in pesticide and sediment losses from agricultural fields, and have the additional benefit of removing less land from production than traditional VFS. In this study, reductions of runoff, the soluble pesticide acetochlor, and total suspended solids were estimated using a paired watershed field study and coupled PRZM/VFSMOD modeling for two treatment watersheds with source to buffer area ratios (SBAR) of 80:1 (SI-A) and 481:1 (SI-B). Based on the paired watershed ANCOVA analysis, runoff and acetochlor load reductions were significant following the implementation of a VFS at SIA but not SI-B, indicating the potential for side-inlet VFS to reduce runoff and acetochlor load from a watershed with an area ratio of 80:1 but not a higher ratio of 481:1. VFSMOD simulations were consistent with the results of the paired watershed monitoring study, where simulated reductions of runoff, acetochlor loads, and TSS loads were substantially lower for SI-B than SI-A. VFSMOD simulations of SI-B with the SBAR ratio observed at SI-A (80:1) also show that VFSMOD can be used to capture variability in effectiveness of VFS based on multiple factors including SBAR. While this study focused on the effectiveness of side-inlet VFSs at the field scale, broader adoption of properly sized side-inlet VFSs could improve surface water quality at the watershed or larger scales. Additionally, modeling at the watershed scale could aid in locating, sizing, and assessing the impacts of side-inlet VFSs at this larger scale.

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.

Influence of Vegetation Filter Strip on Slope Runoff, Sediment Yield and Nutrient Loss

It is an important branch of erosion research to control soil erosion on eroded gullies and slopes by using vegetation filter strip. Several simulated rainfall experiments were carried out in soil tanks filled with loess sandy loam taken from a typical eroded gully area with less vegetation coverage in Yanghe hilly basin in Xuanhua District, Zhangjiakou City, Hebei Province. The soil and water conservation effects of two different vegetation setting modes were compared under the same vegetation strip width and different rainfall intensities and slopes. During the rainfall process, the changes of runoff and sediment yield and nutrient loss were not stable, but the same erosion index had similar variation trends under different combinations of rainfall intensity, slope and vegetation coverage. Multiple regression results showed that runoff and sediment production in eroded gully can be effectively reduced through vegetation filter strips, which are jointly affected by rainfall intensity and slope. There was no significant difference in the amount of runoff and sediment yield between the two vegetation setting modes. Rainfall intensity and slope gradient showed different strengths of impact on nutrient loss. Through cluster analysis, the results showed that the impacts of rainfall intensity, slope gradient and vegetation setting modes on soil and water loss on slope can be equal or offset. In general, setting vegetation filter strips can offset the effects of rainfall intensity and slope, but vegetation regulation of erosion was not obvious under extreme rainfall and steep slope conditions. What’s more, rainfall intensity had a dominant effect on erosion. The results in this research may provide reference for practical application of vegetation filter strips on eroded slopes.

Sobol Global Sensitivity Analysis of a Coupled Surface/Subsurface Water Flow and Reactive Solute Transfer Model on a Real Hillslope

The migration and fate of pesticides in natural environments is highly complex. At the hillslope scale, the quantification of contaminant fluxes and concentrations requires a physically based model. This class of model has recently been extended to include coupling between the surface and the subsurface domains for both the water flow and solute transport regimes. Due to their novelty, the relative importance of and interactions between the main model parameters has not yet been fully investigated. In this study, a global Sobol sensitivity analysis is performed on a vineyard hillslope for a one hour intensive rain event with the CATHY (CATchment HYdrology) integrated surface/subsurface model. The event-based simulation involves runoff generation, infiltration, surface and subsurface solute transfers, and shallow groundwater flow. The results highlight the importance of the saturated hydraulic conductivity K s and the retention curve shape parameter n and they reveal a strong role for parameter interactions associated with the exchange processes represented in the model. The mass conservation errors generated by the model are lower than 1% in 99.7% of the simulations. Boostrapping analysis of sampling methods and errors associated with the Sobol indices highlights the relevance of choosing a large sampling size (at least N = 1000) and raises issues associated with rare but extreme output results.

Comparison of empirical and mechanistic equations for vegetative filter strip pesticide mitigation in long-term environmental exposure assessments

Recent advances in mechanistic modeling of vegetated filter strips (VFS) have made it possible to incorporate VFS mitigation into environmental exposure assessments (EEAs). However, outside of fixed efficiency approaches, there are no widely adopted and standardized procedures for incorporating VFS quantitative mitigation into long-term, higher-tier EEAs. A source of hesitation involves the use of empirical equations for predicting pesticide trapping by the VFS. A recent study evaluated existing empirical equations and a mechanistic mass-balance approach using the most extensive field database available of VFS pesticide efficiency from single-event storms. That study concluded that an updated empirical equation (Sabbagh equation) and a mechanistic mass-balance approach performed reasonably well. The objective of this research was to study the effect of upscaling the VFS trapping equations from single events into long-term EEAs. The U.S. EPA Pesticide in Water Calculator (PWC) model linked with the Vegetative Filter Strip MODeling system (VFSMOD) long-term EEA modeling framework (30 yr) was updated to incorporate the alternative trapping equations and tested VFS mitigation results under contrasting agroecological settings with varying erosion/sediment transport conditions. Differences in both acute and chronic 90th percentile estimated environmental exposure concentrations (EECs) were relatively small when comparing predictions using the four pesticide trapping equations. A global sensitivity analysis (GSA) also indicated that selection of a specific trapping equation for predicting EECs was less important than other important input factors such as the VFS length and pesticide properties. However, in terms of the percent reductions in EECs, the choice of pesticide trapping equation was as important as the VFS length. This research builds upon the conclusion of previous single-event studies that the mechanistic mass-balance and refit Sabbagh empirical equation were both valid for EEAs. The mass balance approach represents a reasonable option for regulatory agencies that prefer mechanistic approaches.

Soil and Crop Management Practices to Minimize the Impact of Waterlogging on Crop Productivity

Waterlogging remains a significant constraint to cereal production across the globe in areas with high rainfall and/or poor drainage. Improving tolerance of plants to waterlogging is the most economical way of tackling the problem. However, under severe waterlogging combined agronomic, engineering and genetic solutions will be more effective. A wide range of agronomic and engineering solutions are currently being used by grain growers to reduce losses from waterlogging. In this scoping study, we reviewed the effects of waterlogging on plant growth, and advantages and disadvantages of various agronomic and engineering solutions which are used to mitigate waterlogging damage. Further research should be focused on: cost/benefit analyses of different drainage strategies; understanding the mechanisms of nutrient loss during waterlogging and quantifying the benefits of nutrient application; increasing soil profile de-watering through soil improvement and agronomic strategies; revealing specificity of the interaction between different management practices and environment as well as among management practices; and more importantly, combined genetic, agronomic and engineering strategies for varying environments.

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.

Effect of vegetative filter strip pesticide residue degradation assumptions for environmental exposure assessments

Understanding and simulating the fate and transport of pesticides from a field to adjacent receiving water bodies is critical for estimating long-term environmental exposure concentrations (EECs) in regulatory higher-tier environmental exposure assessments (EEA). The potential of field mitigation practices like vegetative filter strips (VFS) to reduce pesticide pollution is receiving increasing attention. Previous research has proposed a modeling framework that links the US Environmental Protection Agency's (US-EPA) PRZM/EXAMS higher-tier EEA with a process-based VFS model (VFSMOD). This framework was updated to consider degradation and carryover of pesticide residue trapped in the VFS. However, there is disagreement on pesticide degradation assumptions among different regional EEA regulations (i.e. US or European Union), and in particular on how temperature and soil moisture dynamics may affect EECs. This research updated the VFS modeling framework to consider four degradation assumptions and determine if VFS residues and/or EECs differed with each assumption. Two model pesticides (mobile-labile and immobile-persistent) were evaluated for three distinct agroecological scenarios (continental row-crop agriculture, wet maritime agriculture, and dry Mediterranean intensive horticulture) with receiving water bodies and VFS lengths from 0 to 9m. The degradation assumption was important in long-term assessments to predict VFS pesticide residues (statistically different at p<0.01). However, due to the relatively small contribution of residues on the total pesticide mass moving through the VFS, degradation assumptions had a negligible impact on EECs. This indicates that, while important differences exist between EU or US EEAs, the choice of pesticide degradation assumption is not a main source of these differences.

Dynamics of runoff and sediment trapping performance of vegetative filter strips: Run-on experiments and modeling

Vegetative filter strips (VFSs) are a labor-saving and cost-effective agricultural best management practice to trap water runoff and sediment from the source areas. They also provide forage and/or fuel and are therefore potentially profitable for land owners. VFSs are however a dynamic system: the runoff delivery ratio (RDR) and sediment delivery ratio (SDR) vary with growth stage and vegetation types. The impacts of vegetation characteristics as well as soil physical properties modified by vegetation growth, on the RDR and SDR of VFS were evaluated by a flume experiment. Two plant species (cocksfoot (Dactylis glomerata L.) and white clover (Trifolium repens L.)) were tested at three stages in the growing season of 2016 (May, July, and August). The measured RDR and SDR were compared with the simulated results from Vegetative Filter Strip Modeling System (VFSMOD). In the early stages of the growing season, the cocksfoot formed a dense network of stems with high strip Manning's roughness faster than white clover. The runoff and sediment trapping effects of the white clover VFS were greater than that of cocksfoot VFS in all the three stages (lower RDR and SDR). This is likely attributed to strongly tillering, creeping stem posture and high infiltration capacity of the white clover VFS. VFSMOD simulated the RDR and SDR reliably except under low vegetation coverage conditions (white clover in May). The results suggested that (1) both soil physical properties and vegetation characteristics should be considered for the species-specific, temporally variable performance of VFS; and (2) when using VFSMOD inform the VFS design, modelers should take the dynamics of vegetation, mainly through vertical saturated hydraulic conductivity, stem spacing and strip Manning's roughness into account, and select parameters that reflect the actual field conditions.

Evaluating the impacts of agricultural land management practices on water resources: A probabilistic hydrologic modeling approach

Evaluating the effectiveness of agricultural land management practices in minimizing environmental impacts using models is challenged by the presence of inherent uncertainties during the model development stage. One issue faced during the model development stage is the uncertainty involved in model parameterization. Using a single optimized set of parameters (one snapshot) to represent baseline conditions of the system limits the applicability and robustness of the model to properly represent future or alternative scenarios. The objective of this study was to develop a framework that facilitates model parameter selection while evaluating uncertainty to assess the impacts of land management practices at the watershed scale. The model framework was applied to the Lake Creek watershed located in southwestern Oklahoma, USA. A two-step probabilistic approach was implemented to parameterize the Agricultural Policy/Environmental eXtender (APEX) model using global uncertainty and sensitivity analysis to estimate the full spectrum of total monthly water yield (WYLD) and total monthly Nitrogen loads (N) in the watershed under different land management practices. Twenty-seven models were found to represent the baseline scenario in which uncertainty of up to 29% and 400% in WYLD and N, respectively, is plausible. Changing the land cover to pasture manifested the highest decrease in N to up to 30% for a full pasture coverage while changing to full winter wheat cover can increase the N up to 11%. The methodology developed in this study was able to quantify the full spectrum of system responses, the uncertainty associated with them, and the most important parameters that drive their variability. Results from this study can be used to develop strategic decisions on the risks and tradeoffs associated with different management alternatives that aim to increase productivity while also minimizing their environmental impacts.

An integrated vegetated ditch system reduces chlorpyrifos loading in agricultural runoff

Agricultural runoff containing toxic concentrations of the organophosphate pesticide chlorpyrifos has led to impaired water body listings and total maximum daily load restrictions in California's central coast watersheds. Chlorpyrifos use is now tightly regulated by the Central Coast Regional Water Quality Control Board. This study evaluated treatments designed to reduce chlorpyrifos in agricultural runoff. Initial trials evaluated the efficacy of 3 different drainage ditch installations individually: compost filters, granulated activated carbon (GAC) filters, and native grasses in a vegetated ditch. Treatments were compared to bare ditch controls, and experiments were conducted with simulated runoff spiked with chlorpyrifos at a 1.9 L/s flow rate. Chlorpyrifos concentrations and toxicity to Ceriodaphnia dubia were measured at the input and output of the system. Input concentrations of chlorpyrifos ranged from 858 ng/L to 2840 ng/L. Carbon filters and vegetation provided the greatest load reduction of chlorpyrifos (99% and 90%, respectively). Toxicity was completely removed in only one of the carbon filter trials. A second set of trials evaluated an integrated approach combining all 3 treatments. Three trials were conducted each at 3.2 L/s and 6.3 L/s flow rates at input concentrations ranging from 282 ng/L to 973 ng/L. Chlorpyrifos loadings were reduced by an average of 98% at the low flow rate and 94% at the high flow rate. Final chlorpyrifos concentrations ranged from nondetect (<50 ng/L) to 82 ng/L. Toxicity to C. dubia was eliminated in 3 of 6 integrated trials. Modeling of the ditch and its components informed design alterations that are intended to eventually remove up to 100% of pesticides and sediment. Future work includes investigating the adsorption capacity of GAC, costs associated with GAC disposal, and real-world field trials to further reduce model uncertainties and confirm design optimization. Trials with more water-soluble pesticides such as neonicotinoids are also recommended. Integr Environ Assess Manag 2017;13:423-430. © 2016 SETAC.

Defining context-specific scenarios to design vegetated buffer zones that limit pesticide transfer via surface runoff

When used in addition to environmentally friendly cultural practices, buffer zones can limit the water transfer of pollutants, in particular pesticides, towards water resources. The choice of the buffer zones' type and positioning, considering water pathways and flow components, is crucial. When this choice has been performed, buffer zones dimensions must still be optimized, according to the environment characteristics, which strongly influence their effectiveness. This article presents a method and its associated tools, including VFSMOD model, which aim at optimizing vegetative buffer zones (VFS) sizes, by simulating their transfer mitigation effectiveness. A first application of this methodology is illustrated on a small agricultural watershed in Brittany. A second application, based on the simulation of a large number of scenarios, leads to the elaboration of nomograms. They allow optimizing VFS size in a simpler way from the user's point of view.

Predicting pesticide removal efficacy of vegetated filter strips: A meta-regression analysis

Vegetated Filter Strips (VFS's) are widely used for alleviating agricultural pesticide loadings to surface water bodies. However, effective tools are lacking to quantify the performance of VFS's in reducing off-site pesticide transport. In this study, we applied meta-regression to develop a model for predicting VFS pesticide retention efficiency based on hydrologic responses of VFS's, incoming pollutant characteristics and the interaction within and between these two factor groups (R(2)=0.83). In cross-validation analysis, our model (Q(2)=0.81) outperformed the existing pesticide retention module of VFSMOD (Q(2)=0.72) by explicitly accounting for interaction effect and the categorical effect of pesticide adsorption properties. Based on the 181 data points studied, infiltration had a leading, positive influence on pesticide retention, followed by sedimentation and interaction between the two. Interaction between infiltration and pesticide adsorption properties was also prominent, as the influence of infiltration was significantly lower for strongly adsorbed pesticides. In addition, the clay content of incoming sediment was negatively associated with pesticide retention. Our model is not only valuable in predicting VFS performance, but also provides a quantitative characterization of the interacting VFS processes, thereby facilitating a deeper understanding of the underlying mechanisms.

Colloid filtration in surface dense vegetation: experimental results and theoretical predictions

Understanding colloid and colloid-facilitated contaminant transport in overland flow through dense vegetation is important to protect water quality in the environment, especially for water bodies receiving agricultural and urban runoff. In previous studies, a single-stem efficiency theory for rigid and clean stem systems was developed to predict colloid filtration by plant stems of vegetation in laminar overland flow. Hence, in order to improve the accuracy of the single-stem efficiency theory to real dense vegetation system, we incorporated the effect of natural organic matter (NOM) on the filtration of colloids by stems. Laboratory dense vegetation flow chamber experiments and model simulations were used to determine the kinetic deposition (filtration) rate of colloids under various conditions. The results show that, in addition to flow hydrodynamics and solution chemistry, steric repulsion afforded by NOM layer on the plants stem surface also plays a significant role in controlling colloid deposition on vegetation in overland flow. For the first time, a refined single-stem efficiency theory with considerations of the NOM effect is developed that describes the experimental data with good accuracy. This theory can be used to not only help construct and refine mathematical models of colloid transport in real vegetation systems in overland flow, but also inform the development of theories of colloid deposition on NOM-coated surfaces in natural, engineered, and biomedical systems.

Three-dimensional lake water quality modeling: sensitivity and uncertainty analyses

Two sensitivity and uncertainty analysis methods are applied to a three-dimensional coupled hydrodynamic-ecological model (ELCOM-CAEDYM) of a morphologically complex lake. The primary goals of the analyses are to increase confidence in the model predictions, identify influential model parameters, quantify the uncertainty of model prediction, and explore the spatial and temporal variabilities of model predictions. The influence of model parameters on four model-predicted variables (model output) and the contributions of each of the model-predicted variables to the total variations in model output are presented. The contributions of predicted water temperature, dissolved oxygen, total phosphorus, and algal biomass contributed 3, 13, 26, and 58% of total model output variance, respectively. The fraction of variance resulting from model parameter uncertainty was calculated by two methods and used for evaluation and ranking of the most influential model parameters. Nine out of the top 10 parameters identified by each method agreed, but their ranks were different. Spatial and temporal changes of model uncertainty were investigated and visualized. Model uncertainty appeared to be concentrated around specific water depths and dates that corresponded to significant storm events. The results suggest that spatial and temporal variations in the predicted water quality variables are sensitive to the hydrodynamics of physical perturbations such as those caused by stream inflows generated by storm events. The sensitivity and uncertainty analyses identified the mineralization of dissolved organic carbon, sediment phosphorus release rate, algal metabolic loss rate, internal phosphorus concentration, and phosphorus uptake rate as the most influential model parameters.

Distinct influence of filter strips on acute and chronic pesticide aquatic environmental exposure assessments across U.S. EPA scenarios

Vegetative filter strips (VFS) are proposed for protection of receiving water bodies and aquatic organisms from pesticides in runoff, but there is debate regarding the efficiency and filter size requirements. This debate is largely due to the belief that no quantitative methodology exists for predicting runoff buffer efficiency when conducting acute and/or chronic environmental exposure assessments. Previous research has proposed a modeling approach that links the U.S. Environmental Protection Agency's (EPA's) PRZM/EXAMS with a well-tested process-based model for VFS (VFSMOD). In this research, we apply the modeling framework to determine (1) the most important input factors for quantifying mass reductions of pesticides by VFS in aquatic exposure assessments relative to three distinct U.S. EPA scenarios encompassing a wide range of conditions; (2) the expected range in percent reductions in acute and chronic estimated environmental concentrations (EECs); and (3) the differential influence of VFS when conducting acute versus chronic exposure assessments. This research utilized three, 30-yr U.S. EPA scenarios: Illinois corn, California tomato, and Oregon wheat. A global sensitivity analysis (GSA) method identified the most important input factors based on discrete uniform probability distributions for five input factors: VFS length (VL), organic-carbon sorption coefficient (K(oc)), half-lives in both water and soil phases, and application timing. For percent reductions in acute and chronic EECs, VL and application timing were consistently the most important input factors independent of EPA scenario. The potential ranges in acute and chronic EECs varied as a function of EPA scenario and application timing. Reductions in acute EECs were typically less than percent reductions in chronic EECs because acute exposure was driven primarily by large individual rainfall and runon events. Importantly, generic specification of VFS design characteristics equal across scenarios should be avoided. The revised pesticide assessment modeling framework offers the ability to elucidate the complex and non-linear relationships that can inform targeted VFS design specifications.

Effect of vegetative filter strips on herbicide runoff under various types of rainfall

Narrow vegetative filter strips proved to effectively reduce herbicide runoff from cultivated fields mainly due to the ability of vegetation to delay surface runoff, promote infiltration and adsorb herbicides. A field trial was conducted from 2007 to 2009 in north-east Italy in order to evaluate the effectiveness of various types of vegetative filter strips to reduce spring-summer runoff of the herbicides mesotrione, metolachlor and terbuthylazine, widely used in maize, and to evaluate the effect of the rainfall characteristics on the runoff volume and concentration. Results show that without vegetative filter strip the herbicide load that reaches the surface water is about 5-6 g ha(-1)year(-1) for metolachlor and terbuthylazine (i.e. 0.5-0.9% of the applied rate), confirming that runoff from flat fields as in the Po Valley can have a minor effect on the water quality, and that most of the risk is posed by a few, or even just one extreme rainfall event with a return period of about 25-27 years, causing runoff with a maximum concentration of 64-77 μg L(-1). Mesotrione instead showed rapid soil disappearance and was observed at a concentration of 1.0-3.8 μg L(-1) only after one extreme (artificial) rainfall. Vegetative filter strips of any type are generally effective and can reduce herbicide runoff by 80-88%. Their effectiveness is steady even under severe rainfall conditions, and this supports their implementation in an environmental regulatory scheme at a catchment or regional scale.

Escherichia coli load reduction from runoff by vegetative filter strips: a laboratory-scale study

Vegetative filter strips (VFS) are commonly used best management practices for removing contaminants from runoff. Additional research is warranted to determine their efficiency and the most appropriate metrics for predicting fecal bacteria reductions. The objective of this research was to determine VFS effectiveness in removing from runoff relative to inflow rate, infiltration capacity, and flow concentration. This research also investigated the presence of in runoff from clean water runon after diluted manure runon events. A laboratory-scale VFS soil box (200 cm long, 100 cm wide, 7.5% slope) was packed with a sandy loam soil. Ten constant-flow VFS experiments were conducted with and without vegetation (8-10 cm ryegrass [ L.]) at low (20-40 cm s), medium (40-60 cm s), and high (85-120 cm s) flow rates and for a full (100 cm) or concentrated (40 cm) VFS flow width to simulate a channelizing flow condition. Two runon events were investigated for each experimental condition: (i) diluted liquid swine manure runon and (ii) clean water runon 48 h afterward. was used as an indicator of fecal contamination and was quantified by the most probable number (MPN) technique. No concentration reductions were observed based on peak outflow concentrations, and only small concentration reductions were observed based on outflow event mean concentrations. The mass reductions ranged from 22 to 71% and were strongly correlated to infiltration or runoff reduction ( = 0.88), which was dependent on the degree of flow concentration. Little to no effect of sedimentation on transport was observed, hypothesized to be due to minimum attachment to sediment particles because the bacteria originated from manure sources. Therefore, the design of VFS for bacteria removal should be based on the infiltration capacity in the VFS and should prevent concentrated flow, which limits total infiltration. The event mean concentrations in clean water runon experiments were between 10 and 100 MPN per 100 mL; therefore, under these conditions, VFS served as a source of residual from previous runon events.

Modeling effectiveness of agricultural BMPs to reduce sediment load and organophosphate pesticides in surface runoff

Quantifying effectiveness of agricultural BMPs at the watershed scale is a challenging issue, requiring robust algorithms to simulate not only the agricultural production system but also pollutant transport and fate. This research addresses the challenge to simulate performances of BMPs in reducing organophosphates (OPs) runoff at the watershed scale. The SWAT model is calibrated and validated following a sensitivity analysis combining Latin Hypercube sampling and One-factor-At-a-Time simulation. The calibrated model is then applied in the Orestimba Creek Watershed to simulate BMPs including buffer strips, sediment ponds, vegetated ditches, use reduction, and their combinations. BMP simulation suggested that sediment ponds trap 54-85% of sediment from field runoff, but less than 10% of dissolved diazinon and chlorpyrifos. Use reduction can reduce pesticide load in a close-to-linear fashion. Effectiveness of vegetated ditches and buffers depends on their physical dimension and vegetation cover. Combining individual BMPs provides enhanced mitigation effects. The combination of vegetated ditches, buffer strips and use reduction decreases diazinon and chlorpyrifos load by over 94%. This study has suggested that the SWAT model reasonably predicts BMP effectiveness at the watershed scale. Results will assist decision making in implementing BMPs to reduce pesticide loads in surface runoff.