Vernal pools are ephemeral wetlands that provide critical habitat to many listed species. Pesticide fate in vernal pools is poorly understood because of uncertainties in the amount of pesticide entering these ecosystems and their bioavailability throughout cycles of wet and dry periods. The Pesticide Water Calculator (PWC), a model used for the regulation of pesticides in the US, was used to predict surface water and sediment pore water pesticide concentrations in vernal pool habitats. The PWC model (version 1.59) was implemented with deterministic and probabilistic approaches and parameterized for three agricultural vernal pool watersheds located in the San Joaquin River basin in the Central Valley of California. Exposure concentrations for chlorpyrifos, diazinon and malathion were simulated. The deterministic approach used default values and professional judgment to calculate point values of estimated concentrations. In the probabilistic approach, Monte Carlo (MC) simulations were conducted across the full input parameter space with a sensitivity analysis that quantified the parameter contribution to model prediction uncertainty. Partial correlation coefficients were used as the primary sensitivity metric for analyzing model outputs. Conditioned daily sensitivity analysis indicates curve number (CN) and the universal soil loss equation (USLE) parameters as the most important environmental parameters. Therefore, exposure estimation can be improved efficiently by focusing parameterization efforts on these driving processes, and agricultural pesticide inputs in these critical habitats can be reduced by best management practices focused on runoff and sediment reductions.

This chapter reviews the concepts and tools used by U.S. Environmental Protection Agency (USEPA) to model pesticides in surface water. Surface water assessments are performed with the Pesticide in Water Calculator (PWC), which simulates a field and an adjacent water body and then processes the resulting surface water concentrations in a manner appropriate for use in ecological and human health assessments. The PWC offers consistency in pesticide risk assessments by simplifying rote tasks, but this ease may result in complacency and misunderstandings of the underlying assumptions and mechanisms. This chapter is aimed at clarifying some of the misunderstandings by giving an overview of the most important aspects of the USEPA surface water model for estimating pesticide concentrations.

The uptake of soil-applied pesticide by runoff was evaluated at the field scale (0.06-3.6 ha) by examining data from previous field studies and using two popular chemical-uptake models: a uniform mixing cell, in which runoff mixes uniformly to a set depth, and a non-uniform uptake model, where chemical uptake decreases exponentially with soil depth. Both uptake models were implemented through the field-scale Pesticide Root Zone Model (PRZM5), which includes an update for adjusting runoff uptake parameters. For the nonuniform model, we conceptualized runoff as a distribution of subsurface flow, which assisted in revealing that a large amount (81%) of runoff must bypass soil interaction to adequately simulate the field data, with the remaining runoff acting over about a 3-cm depth. Similarly, the mixing cell required a large amount (84%) of runoff bypass for proper simulation, with the remaining portion acting over a 0.75-cm depth. Published by Elsevier Ltd.

Daily weather is compiled for pesticide exposure modeling from 1961 to 2014 at 0.25 x 0.25 degrees latitude/longitude resolution for the United States using two National Oceanic and Atmospheric Administration (NOAA) products: National Center for Environmental Prediction Reanalysis and NOAA Climate Prediction Center Unified Rain Gauge Analysis. The compiled weather includes precipitation, temperature, wind speed, solar radiation, and reference evapotranspiration. Reference evapotranspiration is calculated using the Hargreaves-Samani method. Prior to this update, US pesticide exposure models relied upon the Solar and Meteorological Surface Observation Network dataset, which provides the same variables but only from 1961 to 1990 for 237 US weather stations. More extensive (1961-2014), spatially-resolved weather allows for more robust estimates of time-averaged pesticide concentrations for assessing acute and chronic exposure to pesticides. Continued expansion of the weather dataset is planned as the latest data is released. Processed weather for pesticide exposure modeling will be publicly available from the US EPA. Published by Elsevier Ltd.

The pesticides in flooded applications model (PFAM) is a regulatory model for government agencies and others interested in estimating water concentrations of pesticides used in flooded agriculture applications such as rice paddies and cranberries bogs. PFAM was designed around the specific parameters that are typically available for a pesticide risk assessment, thereby simplifying the model and allowing the user to concentrate on only the most relevant model inputs. The model considers the fate properties of pesticides and allows for the specifications of typical flooded agriculture management practices such as scheduled water releases and refills. It also allows for natural water-level fluctuations resulting from precipitation and evapotranspiration. Model quality assurance requirements for regulatory models aimed at protecting the public are that the models err on the high side of measured data and at the same time should not cause undue burden to stakeholders by being overly conservative. For the studies herein, PFAM did tend to err on the high side of the data yet provided more realistic estimates than the currently used methods, which thereby reduced stakeholder burden. As is also important for a regulatory model, PFAM is nonproprietary and freely available.