Application of the theory of planned behavior with agent-based modeling for sustainable management of vegetative filter strips

<p>An innovative socio-hydrological modeling framework for the development of environmental policies tailored to farmers' attitudes and economic interests is proposed with the inclusion of optimal environmental criteria. It focuses on modeling the complex relation of farmers, the environment, and the agricultural practices recommended by policy developers. An on-site survey of farmers is used to develop a behavior model based on a modified Theory of Planned Behavior (TPB). An agent-based model (ABM) is coupled with an agro-hydrological model for vegetative filter strips (VFS) to create dynamics of the social and environmental system.</p><p>The farmers from the Larqui river basin, Chile took part in the survey to understand their standpoint on the use of VFS to reduce soil loss in their agricultural fields and protect water bodies. The farmers were categorized into perceptive, proactive, bounded rational and interactive agents based on their answers to the survey. This categorization along with decision rules, and utility functions of agricultural activities including the VFS implementation and management are used to develop an ABM. Partial least square structural equation modeling (PLS-SEM) is used to analyze the modified TPB of farmers. Behavioral morality, behavioral willingness, knowledge of farmers showed a significant effect on modeling the intention and behavior of farmers to have VFS in their land. Subjective norm was the only construct that was not significant. The results of the ABM validate with the survey of the farmers. It shows that the decision on the width of VFS is not solely dependent on the utility generated and the reduction in soil losses but also on the behavior of farmers. This behavioral socio-hydrological modeling framework is capable of supporting policy-makers in developing tailored environmental policies that might improve the acceptance of sustainable agricultural practices by farmers.</p>

Implementation of shallow water table effects on pesticide runoff mitigation efficiency by vegetative filter strips within SWAN-VFSMOD

<p>Quantitative mitigation of pesticides entering surface water using vegetative filter strips (VFS) is currently available within the regulatory SWAN tool for EU FOCUS STEP 4 simulations. For the VFSMOD model option, field estimates of surface runoff, sediment and pesticide loads simulated with the model PRZM are routed through the VFS where VFSMOD estimates the reductions of total inflow (dQ), eroded sediment (dE) and pesticide (dP) loads before the remaining runoff enters the waterbody. The reduced runoff is handed over to the TOXSWA aquatic model to calculate predicted environmental concentrations in surface water (PECsw). Brown et al. (2012) proposed VFSMOD parametrization rules including the selection of VFS soils and other characteristics for use in the FOCUS R1 to R4 (Rx) SWAN scenarios. The rules apply to free-draining soils, described in VFSMOD by the Green-Ampt model extended for unsteady rainfall. However, in some EU regions, the presence of a seasonal shallow water table (sWT) is common. In these cases, the VFS efficiency can be limited, depending on water table depth (WTD) and soil type. VFSMOD incorporates a sWT mechanistic infiltration component that has proven successful to predict sWT effects in VFS experiments. This component requires soil hydraulic characteristics, described by e.g. the Mualem-van Genuchten (MvG) equations.</p><p>The main objective of this study is to identify Rx representative VFS soils to study the effects of sWT on pesticide mitigation for a combination of illustrative storms and pesticides, as well as on PECsw from long-term SWAN simulations.</p><p>The selection and testing of the Rx VFS soils seeks to reflect a 90<sup>th</sup>-percentile worst case in space of dP. The multicriteria adopted in the soil selection evaluate not only dP, but also the percentile of important soil parameters for noWT (K<sub>s</sub>, S<sub>av</sub>) and sWT infiltration conditions (fillable pore volume f<sub>pv</sub>). The framework consisted of 4 steps: (a) soil spatial soil database analysis for VFS Rx mitigation scenarios; (b) selection of VFS candidate soils; (c) analysis of effects of sWT and sorption on dP for individual storm events; (d) Effect of sWT on long-term STEP 4 SWAN VFS mitigation simulations. For (a), representative soil profiles and area coverage for each of the EU Rx were obtained by combining the latest EU JRC soil profile databases SPADE2 and SPADE14. Each multilayer soil was aggregated into single-layer depth-weighted profiles, and MvG parameters were estimated using HYPRES pedotransfer functions (PTF). Water table depths (WTD) were set at equilibrium with TOXSWA median surface water level, and S<sub>av</sub> and f<sub>pv</sub> were calculated by numerical integration from MvG characteristics. For (b), 10644 VFSMOD simulations were run for all combinations of soils, T=1 and 10 yr storms, high/low Koc pesticides, and sWT/noWT conditions. Candidate Rx VFS soils were selected for the most conservative case (low Koc=100 Kg/L pesticide, T=10 yr storm) and noWT to achieve the target spatial 90<sup>th</sup> percentile worst case of pesticide load reduction by the VFS. </p><p>The implementation of the new sWT VFS mitigation component provides a more realistic description of pesticide reduction in accordance with STEP 4 EU FOCUS objectives.</p>

An improved method for the parameterization of sediment trapping in VFSMOD

<p>The most widely implemented mitigation measure to reduce transfer of pesticides to surface water bodies via surface runoff are vegetative filter strips (VFS). To reliably model the reduction of surface runoff, eroded sediment and pesticide load by VFS an event-based model is needed. The most commonly used model for this purpose is VFSMOD. VFSMOD simulates reduction of total inflow (∆Q) and reduction of incoming eroded sediment load (∆E) mechanistically. These variables are subsequently used to calculate the reduction of pesticide load (∆P). While ∆P can be relatively well predicted from ∆Q, ∆E and some other variables, errors in ∆Q and ∆E will propagate to ∆P. Hence, for strongly sorbing compounds, an accurate prediction of ∆E is crucial. The most important parameter characterizing the incoming sediment in VFSMOD is the median particle diameter d50. The objective of this study was to derive a generic d50 parameterization methodology for sediment trapping in VFSMOD that can be readily used for regulatory VFS scenarios.</p><p>Four studies with 16 hydrological events were selected for modelling. A first set of VFSMOD simulations, following the SWAN-VFSMOD sediment parameterization with d50 = 20 µm yielded a general overestimation of ∆E. Consequently, a maximum-likelihood-based calibration and uncertainty analysis with the DREAM-ZS algorithm was performed for the 16 events. The resulting d50 values were all in the low range (1.3-5.4 µm) and did not allow to establish a robust relationship to predict a wider range of d50 from the available explanatory variables. To increase the sample size and the range of d50 values, the comprehensive Kinston dataset for a loamy sand in North Carolina was calibrated with DREAM-ZS. Calibration was performed separately for each hydrological event. Further data points with measured particle size distributions in run-on were assimilated from the literature. The extended test data set of d50 values and explanatory variables was analysed using an extended multiple linear regression (MLR) approach and Classification and Regression Trees (CART).</p><p>A good calibration of event totals and outflow hydrographs could be achieved for most events and VFS treatments of the Kinston site. The calibrated d50 values yielded a wider range (2-16 µm) than the initial 16 events.</p><p>The improved d50 parameterization method derived with MLR/CART will be adopted in the next version of SWAN-VFSMOD to provide more realistic quantitative mitigation within FOCUS STEP4.</p>

Fate of pesticide residues in vegetative filter strips in long-term exposure assessments: VFSMOD development and analysis

<p>Inclusion of quantitative mitigation of pesticides in regulatory environmental risk assessment (ERA) using common agricultural field conservation practices is a critical need recently identified by experts in North America and EU [1]. Currently, mitigation by vegetative filter strips (VFS) is available by coupling the event-based model VFSMOD in continuous simulations within current long-term higher-tier surface water ERA frameworks (EU FOCUS SWAN, US EPA PWC, PRMA Canada, California CDPR PREM, etc.). In this case, the field management and pesticide-laden surface runoff at the edge of the field is calculated by the model PRZM and VFSMOD routes it from the edge of field through a VFS of desired characteristics to estimate potential load reductions before entering the aquatic environment, simulated by the receiving water body model (FOCUS TOXSWA, EPA VVWM). While under proper settings VFS could effectively reduce pesticide concentrations in surface water below thresholds of concern- what happens to the residues trapped in the VFS? The current ERA VFS framework uses a highly risk-conservative assumption, whereby the pesticide trapped in the VFS undergoes degradation between storm events and the surface residue (soil mixing layer and adsorbed to trapped sediment) is remobilized in full and added to the incoming pesticide load in the next event in the series. While risk conservative, this initial approach is not consistent with the nonuniform pesticide redistribution and extraction with depth used in the model PRZM within current ERA, and it has also been found too conservative for highly sorbed compounds with high specific toxicity like pyrethroids and others. The objective of this study is to develop a complete VFSMOD component to quantify the fate of VFS pesticide residues between runoff events for use in long-term ERA simulations. This includes realistic assumptions of the fate of the residues, including non-linear pesticide redistribution in the soil, mass balance of the VFS soil mixing layer and sediment trapped, degradation between runoff events, and partial remobilization and carryover of the remaining residue to the next event. Initial sensitivity and limited testing with existing field data are discussed.</p>

Metamodeling methods that incorporate qualitative variables for improved design of vegetative filter strips.

<p>Significant amounts of pollutant are measured in surface water, their presence due in part to the use of pesticides in agriculture. One solution to limit pesticide transfer by surface runoff is to implement vegetative filter strips (VFS) along rivers. The sizing of these strips is a major issue, with influencing factors that include local conditions (climate, soil, etc.). The BUVARD modeling toolkit was developed to design VFSs throughout France according to these properties. This toolkit includes the numerical model VFSMOD, which quantifies dynamic effects of VFS site-specific pesticide mitigation efficiency. In this study, a metamodeling (or model dimension reduction) approach is proposed to ease the use of BUVARD and to help users design VFSs that are adapted to specific contexts. Different reduced models, or surrogates, are compared: GAM, Polynomial Chaos Expansions, Kriging, and Mixed-kriging. Mixed-kriging is a kriging method that was implemented with a covariance kernel for a mixture of qualitative and quantitative inputs. Kriging and PCE are built by couple of modalities and Mixed-kriging  and GAM are built considering mixed quantitative and qualitative variables. The metamodel is a simple way to provide a relevant first guess to help design the pollution reduction device. In addition, the surrogate model is a relevant tool to visualize the impact that lack of knowledge of some parameters of filter efficiency can have when performing risk analysis and management.</p>

Effectiveness of Vegetative Filter Strips for Mitigation in Higher-Tier Pesticide Exposure Assessments: Mechanistic Analysis with VFSMOD

<p>Pesticides high-tier, long-term environmental risk assessments (ERA) are based on the combination of complicated mechanistic models to evaluate regulatory compliance. The modeling framework often involves large sets of input factors (model parameters, initial and boundary conditions, and other model structure options). How can we identify the relative importance of human, chemical, physical and biological drivers on the assessment results? Is there a case for “the right answers for the right reasons”? For the case of pesticide mitigation practices like vegetative filter strips (VFS) for runoff mitigation, what are the important factors controlling or limiting their efficiency under different field settings? We evaluate the combination of the current ERA frameworks (US EPA PWC and EU FOCUS SWAN) in combination with VFSMOD, an established and commonly used numerical model for the analysis of runoff, sediment, and pesticide transport in VFS. We present a systematic study of the importance of different field conditions that have been proposed in the past as limiting the efficiency of VFS in realistic settings: flow concentration (channelization) through the filter, timing of pesticide application compared to other drivers, assumptions about the degradation and remobilization of pesticide trapped in the filter between runoff events, seasonal presence of a shallow water table near the receiving water body. We identify instances in which the importance commonly assigned to these factors is not supported by the mechanistic analysis, where other factors different than those proposed largely control the results of the assessments.</p>