Simulating pesticide leaching and runoff in rice paddies with the RICEWQ-VADOFT model

There is a current need to simulate leaching and runoff of pesticide from rice (Oryza sativa L.) paddies for assessing environmental impacts on a valuable agricultural system. The objective of this study was to develop a model for determining predicted environmental concentration (PEC) in soil, runoff, and ground water through the linkage of two models, rice water quality model (RICEWQ) and vadose zone transport model (VADOFT), to simulate pesticide fate and transport within a rice paddy and underlying soil profile. Model performance was evaluated with a field data set obtained from a 2-yr field experiment in 1997 and 1998 in northern Italy. The predictions of amount of pesticide running off from the paddy field and accumulating in the paddy sediment were in agreement with measured values. Leaching into the vadose zone accounted for approximately 19% of the applied dose, but only a small amount of chemical (<0.1%) was predicted to reach ground water at a 5-m depth due to sorption and transformation in the soil. The permeability of the soil and the water management practices in the paddy field were shown to have a strong influence on pesticide fate. These factors need to be well characterized in the field if model predictions are to be successful. The combined model developed in this work is an effective tool for exposure assessments for soil, surface water, and ground water, in the particular conditions of rice cultivation.     

Propagation of uncertainties in soil and pesticide properties to pesticide leaching

In the new Dutch decision tree for the evaluation of pesticide leaching to groundwater, spatially distributed soil data are used by the GeoPEARL model to calculate the 90th percentile of the spatial cumulative distribution function of the leaching concentration in the area of potential usage (SP90). Until now it was not known to what extent uncertainties in soil and pesticide properties propagate to spatially aggregated parameters like the SP90. A study was performed to quantify the uncertainties in soil and pesticide properties and to analyze their contribution to the uncertainty in SP90. First, uncertainties in the soil and pesticide properties were quantified. Next, a regular grid sample of points covering the whole of the agricultural area in the Netherlands was randomly selected. At the grid nodes, realizations from the probability distributions of the uncertain inputs were generated and used as input to a Monte Carlo uncertainty propagation analysis. The analysis showed that the uncertainty concerning the SP90 is 10 times smaller than the uncertainty about the leaching concentration at individual point locations. The parameters that contribute most to the uncertainty about the SP90 are, however, the same as the parameters that contribute most to uncertainty about the leaching concentration at individual point locations (e.g., the transformation half-life in soil and the coefficient of sorption on organic matter). Taking uncertainties in soil and pesticide properties into account further leads to a systematic increase of the predicted SP90. The important implication for pesticide regulation is that the leaching concentration is systematically underestimated when these uncertainties are ignored.     

Turfgrass thatch effects on pesticide leaching: a laboratory and modeling study

Process-based models are frequently used to assess the water quality impacts of turfgrass management emanating from proposed or existing golf courses. Thatch complicates the prediction of pesticide transport because surface-applied pesticides must pass through an organic-rich layer before entering the soil. This study was conducted to (i) compare the use of a linear equilibrium model (LEM) and two-site nonequilibrium (2SNE) model to predict pesticide transport through soil and thatch + soil columns, and (ii) evaluate thatch effects on pesticide transport through soil columns with a volume-averaging approach. Pesticide breakthrough curves were obtained for soil and thatch + soil columns from a 1 cm h(-1) flux applied one day after applying triclopyr (3,5,6-trichloro-2-pyridinyloxyacetic acid) and carbaryl (1-napthyl-methyl carbamate). Pesticide and bromide transport parameters indicated that nonequilibrium processes were affecting pesticide transport. Columns containing zoysiagrass (Zoysia japonica Steud.) thatch had lower triclopyr and carbaryl leaching losses than did soil-only columns, although total reductions attributable to thatch did not exceed 15% of the applied pesticide. When laboratory-based retardation factors were used, the 2SNE model explained 88 to 93% of the variability for triclopyr and 70 to 94% of the variability for carbaryl. Laboratory-based retardation factors performed well in a 2SNE model to predict the peak concentration and tailing behavior of triclopyr and carbaryl with a volume-averaging approach. These results suggest that separate representation of the thatch layer in process-based models is not a prerequisite to obtain reasonable estimates of pesticide transport under steady state flow conditions.     

Variations in pesticide leaching related to land use, pesticide properties, and unsaturated zone thickness

Pesticide leaching through variably thick soils beneath agricultural fields in Morgan Creek, Maryland was simulated for water years 1995 to 2004 using LEACHM (Leaching Estimation and Chemistry Model). Fifteen individual models were constructed to simulate five depths and three crop rotations with associated pesticide applications. Unsaturated zone thickness averaged 4.7 m but reached a maximum of 18.7 m. Average annual recharge to ground water decreased from 15.9 to 11.1 cm as the unsaturated zone increased in thickness from 1 to 10 m. These point estimates of recharge are at the lower end of previously published values, which used methods that integrate over larger areas capturing focused recharge in the numerous detention ponds in the watershed. The total amount of applied and leached masses for five parent pesticide compounds and seven metabolites were estimated for the 32-km2 Morgan Creek watershed by associating each hectare to the closest one-dimensional model analog of model depth and crop rotation scenario as determined from land-use surveys. LEACHM parameters were set such that branched, serial, first-order decay of pesticides and metabolites was realistically simulated. Leaching is predicted to be greatest for shallow soils and for persistent compounds with low sorptivity. Based on simulation results, percent parent compounds leached within the watershed can be described by a regression model of the form e(-depth) (a ln t1/2-b ln K OC) where t1/2 is the degradation half-life in aerobic soils, K OC is the organic carbon normalized sorption coefficient, and a and b are fitted coefficients (R2 = 0.86, p value = 7 x 10(-9)).     

Impact of sampling techniques on measured stormwater quality data for small streams

Science-based sampling methodologies are needed to enhance water quality characterization for setting appropriate water quality standards, developing Total Maximum Daily Loads, and managing nonpoint source pollution. Storm event sampling, which is vital for adequate assessment of water quality in small (wadeable) streams, is typically conducted by manual grab or integrated sampling or with an automated sampler. Although it is typically assumed that samples from a single point adequately represent mean cross-sectional concentrations, especially for dissolved constituents, this assumption of well-mixed conditions has received limited evaluation. Similarly, the impact of temporal (within-storm) concentration variability is rarely considered. Therefore, this study evaluated differences in stormwater quality measured in small streams with several common sampling techniques, which in essence evaluated within-channel and within-storm concentration variability. Constituent concentrations from manual grab samples and from integrated samples were compared for 31 events, then concentrations were also compared for seven events with automated sample collection. Comparison of sampling techniques indicated varying degrees of concentration variability within channel cross sections for both dissolved and particulate constituents, which is contrary to common assumptions of substantial variability in particulate concentrations and of minimal variability in dissolved concentrations. Results also indicated the potential for substantial within-storm (temporal) concentration variability for both dissolved and particulate constituents. Thus, failing to account for potential cross-sectional and temporal concentration variability in stormwater monitoring projects can introduce additional uncertainty in measured water quality data.     

Modeling macropore flow effects on pesticide leaching: inverse parameter estimation using microlysimeters

Macropore flow is a key factor determining pesticide fate, but models accounting for this process need parameters that cannot be easily measured. This study was conducted to investigate the use of inverse techniques to estimate parameters controlling macropore flow and pesticide fate in the dual-permeability model MACRO. Undisturbed columns were sampled at three landscape positions (hilltop, slope, hollow) with contrasting texture and organic carbon content. Transient leaching experiments were performed for an anionic tracer and the herbicide MCPA (4-chloro-2methylphenoxy acetic acid) during a 4-mo period, first under natural rainfall, and then under controlled irrigation in the laboratory. The tracer breakthrough for the liner-textured soil from the hilltop showed strong evidence of macropore flow, resulting in a rapid leaching of MCPA, while leaching was minimal from the organic-rich hollow soil, since macropore flow was weaker and adsorption stronger. The MACRO model was linked to the inverse modeling program SUFI (Sequential Uncertainty Fitting) to enable calibration of nine key model parameters. Based on calculated model efficiencies, MACRO-SUFI gave generally good predictions of water movement and tracer and pesticide transport, although some errors were attributed to difficulties in simulating the effects of soil moisture on degradation and the timing of water outflows. Even after calibration, significant uncertainties remained for some key parameters controlling macropore flow. Nevertheless, the parameter estimates were significantly different between landscape positions and could also be related to basic soil properties. The posterior uncertainty ranges could probably be reduced with a more exhaustive sampling of the parameter space and improved experimental designs.     

Effects of soil data resolution on SWAT model stream flow and water quality predictions

The prediction accuracy of agricultural nonpoint source pollution models such as Soil and Water Assessment Tool (SWAT) depends on how well model input spatial parameters describe the characteristics of the watershed. The objective of this study was to assess the effects of different soil data resolutions on stream flow, sediment and nutrient predictions when used as input for SWAT. SWAT model predictions were compared for the two US Department of Agriculture soil databases with different resolution, namely the State Soil Geographic database (STATSGO) and the Soil Survey Geographic database (SSURGO). Same number of sub-basins was used in the watershed delineation. However, the number of HRUs generated when STATSGO and SSURGO soil data were used is 261 and 1301, respectively. SSURGO, with the highest spatial resolution, has 51 unique soil types in the watershed distributed in 1301 HRUs, while STATSGO has only three distributed in 261 HRUS. As a result of low resolution STATSGO assigns a single classification to areas that may have different soil types if SSURGO were used. SSURGO included Hydrologic Response Units (HRUs) with soil types that were generalized to one soil group in STATSGO. The difference in the number and size of HRUs also has an effect on sediment yield parameters (slope and slope length). Thus, as a result of the discrepancies in soil type and size of HRUs stream flow predicted was higher when SSURGO was used compared to STATSGO. SSURGO predicted less stream loading than STATSGO in terms of sediment and sediment-attached nutrients components, and vice versa for dissolved nutrients. When compared to mean daily measured flow, STATSGO performed better relative to SSURGO before calibration. SSURGO provided better results after calibration as evaluated by R(2) value (0.74 compared to 0.61 for STATSGO) and the Nash-Sutcliffe coefficient of Efficiency (NSE) values (0.70 and 0.61 for SSURGO and STATSGO, respectively) although both are in the same satisfactory range. Modelers need to weigh the benefits before selecting the type of data resolution they are going to use depending on the watershed size and level of accuracy required because more effort is required to prepare and calibrate the model when a fine resolution soil data is used.     

Mapping ground water vulnerability to pesticide leaching with a process-based metamodel of EuroPEARL

To support EU policy, indicators of pesticide leaching at the European level are required. For this reason, a metamodel of the spatially distributed European pesticide leaching model EuroPEARL was developed. EuroPEARL considers transient flow and solute transport and assumes Freundlich adsorption, first-order degradation and passive plant uptake of pesticides. Physical parameters are depth dependent while (bio)-chemical parameters are depth, temperature, and moisture dependent. The metamodel is based on an analytical expression that describes the mass fraction of pesticide leached. The metamodel ignores vertical parameter variations and assumes steady flow. The calibration dataset was generated with EuroPEARL and consisted of approximately 60,000 simulations done for 56 pesticides with different half-lives and partitioning coefficients. The target variable was the 80th percentile of the annual average leaching concentration at 1-m depth from a time series of 20 yr. The metamodel explains over 90% of the variation of the original model with only four independent spatial attributes. These parameters are available in European soil and climate databases, so that the calibrated metamodel could be applied to generate maps of the predicted leaching concentration in the European Union. Maps generated with the metamodel showed a good similarity with the maps obtained with EuroPEARL, which was confirmed by means of quantitative performance indicators.     

Nitrate leaching and turf quality in established 'Floratam' St. Augustinegrass and 'Empire' zoysiagrass

The objectives of this research were to evaluate nitrate N (NO3-N) leaching and turf response to nitrogen rate (NR) and irrigation regime (IR) in 'Floratam' St. Augustinegrass ( [Walt.] Kuntze.) and 'Empire' zoysiagrass ( Steud). The research was conducted in Citra, FL, from 2005 through 2007. Nitrogen (N) was applied at annual rates of 32, 64, 128, and 196 kg ha?1 in 2005, and at 49, 196, 343, or 490 kg ha?1 in 2006 and 2007. Irrigation treatments consisted of 1.3 cm applied twice weekly or 2.6 cm applied once weekly. In general, NO?-N leaching was greater from zoysiagrass. In 2007, annual NO?-N leached varied due to the interaction of NR, IR, and grass. There was little association between NR and increased NO?-N leaching in St. Augustinegrass in any year. While St. Augustinegrass had no differences in NO?-N leached within NR due to IR, there were some differences in NO?-N leached from zoysiagrass at some N levels, with greater NO?-N leached from the more frequent irrigation regime. Turf quality (TQ) was generally above an acceptable level in St. Augustinegrass at all but the lowest NRs and at all NRs in zoysiagrass with the exception of the spring fertilizer cycle (SFC) in 2007, when high NR treatments resulted in disease. Maintenance of a healthy turfgrass cover is an important strategy for reducing potential nutrient movement from fertilizer application. The current recommended rates for St. Augustinegrass provide good turf cover and health, and result in minimal NO?-N leaching. Zoysiagrass N rates may need to be revised downward to reduce disease, improve turf cover, and reduce NO?-N leaching.     

Integration of long-term fish kill data with ambient water quality monitoring data and application to water quality management

Almost half (354) of all fish kills (805) in South Carolina, USA, between 1978 and 1988 occurred in the coastal zone. These kills were analyzed for causative, spatial, and temporal associations as a distinct data set and as one integrated with ambient water quality monitoring data. Estuarine kills as a result of natural causes accounted for 42.8% followed by man-induced (35.1%) and undetermined causes (22.1%). Although general pesticide usage was responsible for 53.9% of man-induced kills, weed control activities around resorts and municipal areas accounted for slightly more kills (20.9%) than did agricultural (19.8%) or vector control (13.2%) uses. A dramatic decline in agricultural-related kills has been observed since 1986 as the integrated pest management approach was adopted by many farmers. When taken with the few kills (12.0%) resulting from wastewaters, this suggests that these two land-use activities have been successfully managed via existing programs (IPM and NPDES, respectively) to minimize their contributions to estuarine fish kills. Ambient trend monitoring data demonstrated no coastal-wide dispersion of pesticide pollution. These data confirmed the nature of fish kills to be site-specific, near-field events most closely associated with the contiguous land-use practices and intensities. Typically, fish kill data are considered as event-specific data limited to the bounds of that event only. Our analysis has shown, however, that a long-term data set, when integrated with ambient water quality data, can assist in regulatory and resource management decisions for both short- and long-term planning and protection applications.     

Application of land-use data and screening tests for evaluating pesticide runoff toxicity in surface waters

Survey information on pesticide usage in New Zealand during 1985–1989 is summarized by regions and principal applications. Two screening tests, one based on a simple water-balance method and the other based on a semiempirical runoff formula, have been used to identify 18 pesticides with application rates that may yield runoff concentrations that are harmful to aquatic fauna. These are predominantly associated either with intensive applications in horticulture or extensive applications to cereal crops and pasture. The purpose of the screening tests was to calculate typical edge-of-field concentrations in runoff and, by comparing them with known aquatic toxicity values, determine which compounds are applied at rates that may yield toxic runoff. While it may be possible to extend these methods to calculate typical surface water concentrations, further studies will be needed to evaluate pesticide persistence and assimilation in stream channels.     

Assessing and communicating data quality in policy-relevant research

The quality of scientific information in policy-relevant fields of research is difficult to assess, and quality control in these important areas is correspondingly difficult to maintain. Frequently there are insufficient high-quality measurements for the presentation of the statistical uncertainty in the numerical estimates that are crucial to policy decisions. We propose and develop a grading system for numerical estimates that can deal with the full range of data quality—from statistically valid estimates to informed guesses. By analyzing the underlying quality of numerical estimates, summarized as spread and grade, we are able to provide simple rules whereby input data can be coded for quality, and these codings carried through arithmetical calculations for assessing the quality of model results. For this we use the NUSAP (numeral, unit, spread, assessment, pedigree) notational system. It allows the more quantitative and the more qualitative aspects of data uncertainty to be managed separately. By way of example, we apply the system to an ecosystem valuation study that used several different models and data of widely varying quality to arrive at a single estimate of the economic value of wetlands. The NUSAP approach illustrates the major sources of uncertainty in this study and can guide new research aimed at the improvement of the quality of outputs and the efficiency of the procedures.     

Assessment of the predictive quality of simple indicator approaches for nitrate leaching from agricultural fields

Diffuse N losses from agriculture are a major cause of excessive nitrate concentrations in surface and groundwaters. Leaching through the soil is the main pathway of nitrate loss. For environmental management, an anticipatory assessment and monitoring of nitrate leaching risk by indicator (index) approaches is increasingly being used. Although complex Nitrogen Loss Indicator (NLI) approaches may provide more information, relatively simple NLIs may have advantages in many practical situations, for instance, when data availability is restricted.In this study, we tested four simple NLIs to assess their predictive properties: 1. N balance (Nbal); 2. Exchange frequency of soil solution (EF); 3. Potential nitrate concentration in leachate (PNCL); 4. A composite NLI (balance exchange frequency product, BEP). Field data of nitrate leaching from two sites in northeast Germany along with published data from several sites in Germany, Scotland and the USA were utilized.Nbal proved to be a relatively poor indicator of Nloss for the time frame of one year, whereas its prediction accuracy improved for longterm-averaged data. Correlation between calculated EF and experimental data was high for single-year data, whereas it was lower for longterm-averaged data. PNCL gave no significant correlations with measured data and high deviations. The results for BEP were intermediate between those for Nbal and EF.The results suggest that the use of EF is appropriate for assessing N leaching loss for single-year data and specific sites with comparable N input and management practices, whereas for longterm-averaged data, Nbal is better suited. BEP is an appropriate NLI both for single year and longterm data which accounts for source and transport factors and thus is more flexible than source-based Nbal and transport-based EF. However, such simplified NLIs have limitations: 1. The N cycle is not covered completely; 2. Processes in the vadose zone and the aquifer are neglected, 3. Assessment of management factors is restricted.     

Estimating nitrate leaching with a transfer function model incorporating net mineralization and uptake of nitrogen

Because of the complex interaction of chemical and biological processes of nitrogen (N) in soils, it is difficult to estimate the leaching of nitrate with various N transformations in porous media. In this study, a transfer function model was developed to simulate the outflow concentration of nitrate in soils during the growth of winter wheat (Triticum aestivum L.), taking into account the main N transformations using source and sink terms. The source and sink terms were treated as inputs to the solute transport volume and incorporated into the transfer function model to characterize their effects on nitrate concentration in the outflow. A field experiment was conducted in three nonweighing lysimeters for 181 d. Nitrate concentrations were measured along the 2-m soil profile of each lysimeter at different times. Comparison between the experimental data and simulated results with the transfer function showed that the model provided reasonable prediction of the nitrate leaching process as well as the total amount leached. Results also indicated that considering the N transformations in the transfer function significantly increased the estimation accuracy. The relative errors of total amount leached were < 7% with the N transformations included, but up to 17% without including the transformation processes.     

The use of regression equations for quality control in a pesticide physical property database

Quality control is a crucial aspect of database management, particularly for physicochemical parameters that are widely used in modeling environmental fate processes. Complete rechecking of original studies to verify environmental fate parameters is time consuming and difficult. This paper evaluates an alternative, more efficient approach to identifying database errors. The approach focuses verification efforts on a targeted subset of entries by making use of the relationship between water solubility (S) and soil organic carbon partition coefficient (K _oc ). Two regression equations, one selected from the literature and one calculated from entries in the database, were used to evaluate the reasonableness of (S, K _oc ) pairs among control compared to the targeted outlier group from a total of 59 pesticides. Our hypothesis was that (S, K _oc ) pairs that lay far from the regression line were more likely to be in error than those that fit the regression. Database values were checked against original studies. Identified errors in the database included coding mistakes, miscalculations, and incorrect chemical identification codes. The error rate in outlier (S, K _oc ) pairs was about twice that of pairs that conformed to the regression equation; however, the error rate differential was probably not large enough to justify the use of this quality control method. Through our close scrutiny of database entries we were able to identify administrative practices that led to mistakes in the data base. Resolution of these problems will significantly decrease the number of future mistakes.     

Impact of informal regulation of pollution on water quality in rivers in India

In this paper an attempt is made to assess the impact of informal regulation of water pollution on water quality in Indian rivers. For this purpose, an econometric analysis of determinants of water quality in Indian rivers is carried out using water quality (water class) data for 106 monitoring points on 10 important rivers for five years, 1995-1999. To explain variations in water quality, an Ordered Probit model is estimated, in which poll percentage in parliamentary elections, a proxy for the intensity of informal regulation, is taken as one of the main explanatory variables. Rainfall, industrialization, irrigation intensity and fertilizer use are some of the other explanatory variables used in the model to control for the influence of these factors. As expected, river water quality is found to be positively related with rainfall, and negatively related with industrialization, irrigation intensity and fertilizer use. A significant positive relationship is found between poll percentage and water quality, and also between the rate of increase in literacy level in a district and the water quality in rivers flowing through the district. These results point to a significant favorable effect of informal regulation of pollution on water quality in rivers in India.     

Multivariate analysis and visualization of soil quality data for no-till systems

To evidence the multidimensionality of the soil quality concept, we propose the use of data visualization as a tool for exploratory data analyses, model building, and diagnostics. Our objective was to establish the best edaphic indicators for assessing soil quality in four no-till systems with regard to functioning as a medium for crop production and nutrient cycling across two Illinois locations. The compared situations were no-till corn-soybean rotations including either winter fallowing (C/S) or cover crops of rye (Secale cereale; C-R/S-R), hairy vetch (Vicia villosa; C-R/S-V), or their mixture (C-R/S-VR). The dataset included the variables bulk density (BD), penetration resistance (PR), water aggregate stability (WAS), soil reaction (pH), and the contents of soil organic matter (SOM), total nitrogen (TN), soil nitrates (NO(3)-N), and available phosphorus (P). Interactive data visualization along with canonical discriminant analysis (CDA) allowed us to show that WAS, BD, and the contents of P, TN, and SOM have the greatest potential as soil quality indicators in no-till systems in Illinois. It was more difficult to discriminate among WCC rotations than to separate these from C/S, considerably inflating the error rate associated with CDA. We predict that observations of no-till C/S will be classified correctly 51% of the time, while observations of no-till WCC rotations will be classified correctly 74% of the time. High error rates in CDA underscore the complexity of no-till systems and the need in this area for more long-term studies with larger datasets to increase accuracy to acceptable levels.     

Influence of water treatment residuals on phosphorus solubility and leaching

Laboratory and greenhouse studies compared the ability of water treatment residuals (WTRs) to alter P solubility and leaching in Immokalee sandy soil (sandy, siliceous, hyperthermic Arenic Alaquod) amended with biosolids and triple superphosphate (TSP). Aluminum sulfate (Al-WTR) and ferric sulfate (Fe-WTR) coagulation residuals, a lime softening residual (Ca-WTR) produced during hardness removal, and pure hematite were examined. In equilibration studies, the ability to reduce soluble P followed the order Al-WTR > Ca-WTR = Fe-WTR > hematite. Differences in the P-fixing capacity of the sesquioxide-dominated materials (Al-WTR, Fe-WTR, hematite) were attributed to their varying reactive Fe- and Al-hydrous oxide contents as measured by oxalate extraction. Leachate P was monitored from greenhouse columns where bahiagrass (Paspalum notatum Flugge) was grown on Immokalee soil amended with biosolids or TSP at an equivalent rate of 224 kg P ha(-1) and WTRs at 2.5% (56 Mg ha(-1)). In the absence of WTRs, 21% of TSP and 11% of Largo cake biosolids total phosphorus (PT) leached over 4 mo. With co-applied WTRs, losses from TSP columns were reduced to 3.5% (Fe-WTR), 2.5% (Ca-WTR), and <1% (Al-WTR) of applied P. For the Largo biosolids treatments all WTRs retarded downward P flux such that leachate P was not statistically different than for control (soil only) columns. The phosphorus saturation index (PSI = [Pox]/ [Al(ox) + Fe(ox)], where Pox, Al, and Fe(ox) are oxalate-extractable P, Al, and Fe, respectively) based on a simple oxalate extraction of the WTR and biosolids is potentially useful for determining WTR application rates for controlled reduction of P in drainage when biosolids are applied to low P-sorbing soils.