Dept. of Environmental & Molecular Toxicology, 1007 Ag & Life Sciences, Oregon State Univ., Corvallis, OR 97331-7301, United States.
Dept. of Environmental & Molecular Toxicology, 1007 Ag & Life Sciences, Oregon State Univ., Corvallis, OR 97331-7301, United States.
Sci Total Environ. 2022 May 1;819:152955. doi: 10.1016/j.scitotenv.2022.152955. Epub 2022 Jan 8.
In the U.S. Pacific Northwest and California contaminants entering surface water may harm Endangered Species Act (ESA) listed salmonid species and consequently there is ongoing concern regarding agricultural practices and resulting pesticide surface water loading may adversely impact salmonid species, their food web, and habitat. Characterizing pesticide exposure in surface water at the watershed scale and beyond is challenging due to uncertainty regarding pesticide use practices and sparse monitoring data. We report here a 2-year continuous deployment of passive sampling devices (PSDs) for monitoring of pesticides in surface water at the outflow of the Zollner Creek watershed located within the Willamette Basin, Oregon, USA. This watershed is predominately agricultural and within the geographic range of two ESA listed Pacific salmonid species. Grab and passive sampling monitoring data were used to evaluate the performance of a probabilistic application of the Soil and Water Assessment Tool (SWAT), a physically based process model which integrates institutional and local knowledge and expertise to investigate the relationship between land use practices and pesticide surface water loading at the watershed scale. SWAT estimated pesticide surface water concentrations for the pesticides chlorpyrifos and trifluralin followed temporal trend in PSD monitoring results and the 5th to 95th percentile range of estimated pesticide concentrations based on the probabilistic assessment encompassed 65-76% of the observed PSD concentrations. Evaluation of model estimates for metolachlor in surface water was challenged by insufficient publicly available grab sample monitoring data. A process to estimate pesticide surface water concentrations on biologically relevant time scales and comparison to screening level aquatic life benchmarks is presented. Additionally, model estimates were used to characterize the variance in surface water concentrations in this small hydrologically responsive watershed to determine grab sampling frequency adequate for model evaluation.
在美国太平洋西北地区和加利福尼亚州，进入地表水的污染物可能会危害《濒危物种法》（ESA）中列出的鲑鱼物种，因此人们一直关注农业实践以及由此产生的农药地表水负荷可能对鲑鱼物种、其食物网和栖息地产生不利影响。由于对农药使用实践的不确定性和监测数据稀疏，在流域尺度及以上尺度上对地表水的农药暴露进行特征描述具有挑战性。我们在这里报告了一项为期 2 年的连续部署被动采样设备（PSD）的研究，用于监测位于美国俄勒冈州威拉米特流域的佐勒尔克里克流域出口处地表水的农药。该流域主要是农业区，位于两种 ESA 列出的太平洋鲑鱼物种的地理范围内。Grab 和被动采样监测数据用于评估土壤和水评估工具（SWAT）的概率应用的性能，SWAT 是一种基于物理的过程模型，它整合了制度和地方知识和专业知识，以调查土地利用实践与流域尺度上农药地表水负荷之间的关系。SWAT 估计了氯吡硫磷和氟乐灵这两种农药的地表水浓度，这些浓度与 PSD 监测结果的时间趋势一致，基于概率评估的估计农药浓度的第 5 到第 95 百分位数范围涵盖了 65-76%的观察到的 PSD 浓度。对地表水中甲草胺模型估计值的评估受到公开获得的 Grab 样本监测数据不足的挑战。提出了一种在生物相关时间尺度上估计农药地表水浓度并与筛选水平水生生物基准进行比较的方法。此外，还使用模型估计值来描述这个小水文响应流域中地表水浓度的变化，以确定用于模型评估的适当的 Grab 采样频率。
