Developing safe and sustainable uses are
Critical for the environment and human health
Our modelers are experts in higher-tiered modeling such as mitigation and Best Management Practice (BMP) evaluations, probabilistic exposure assessment, including point and non-point source modeling. Waterborne is experienced with performing degradation kinetics following the FOCUS guidelines for laboratory, field, and water sediment studies using Modelmaker and Excel®, the software recommended by the Workgroup. We also have expertise in using newer software such as KinGUI (developed by Bayer CropScience) and CAKE (sponsored by Syngenta) for degradation kinetics.
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Our Higher-Tiered Work
By having a thorough understanding of cause, effect, and probability of occurrence we can design and evaluate structural and procedural management plans for mitigation of potential adverse effects of agrochemicals on the environment. Simulation modeling (i.e., “what-if” scenarios) are often used to compare alternate mitigation measures, individually and in combination, so that the costs, benefits, and effectiveness can be evaluated prior to their implementation in the environment. Examples of mitigation modeling is Vegetative filter strips (VFS) and vegetative ditch modeling. The vegetative filter strip is a BMP that reduces runoff of agrochemicals from fields into nearby waterways (e.g., streams). We, at Waterborne, have developed models such as PRZM-BUFF to simulate the removal of agrochemicals flowing through a vegetative filter strip and have compared it with other VFS models (APEX, REMM, SWAT, and VFSMOD) to assess predictive capabilities. Further, we have worked extensively with VFSMOD and developed a program to interact between PRZM and VVWM or EXAMS. The use of vegetated agricultural drainage ditches (VADD) has been proposed as a potentially economical and environmentally efficient management practice to mitigate the effects of pesticides in runoff.
Probabilistic exposure assessments incorporate spatial and temporal characterization of exposure duration, frequency, and magnitude. At Waterborne, our modelers have performed many studies using spatial approaches to examine the natural variability in the agricultural landscape and to create distributions of potential exposure in the agricultural landscape for exposure assessments. Using this information, we can then generate probabilistic inputs for pesticide aquatic exposure modeling which in-turn is useful in reducing uncertainty of some aspects of exposure assessment aiding the regulatory decision-making process.