School of Environment, State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China.
School of Environment, State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China.
Water Res. 2017 Oct 1;122:377-386. doi: 10.1016/j.watres.2017.06.023. Epub 2017 Jun 8.
Pesticide loadings to watersheds increase during agricultural development and may vary in accordance with different crop types and seasons. High pesticide loadings can potentially result in polluted stream water. The objective of this study was to determine the pesticide loadings and concentrations of three typical pesticides (atrazine, oxadiazon, and isoprothiolane) in river water from a middle-high latitude agricultural watershed in northern China. During this study, we evaluated the watershed pesticide loss patterns for two crop types over three decades. For this purpose, we integrated data from field investigations, laboratory experiments, and modeling simulations involving a distributed hydrological solute transport model (Soil and Water Assessment Tool, SWAT). SWAT was employed to compare the temporal-spatial fate and behaviors of atrazine, oxadiazon, and isoprothiolane from 1990 to 2014 in a watershed area amounting to 141.5 km. The results showed that the three pesticides could be detected at different locations throughout the watershed, and isoprothiolane was detected at the maximum value of 1.082 μg/L in surface runoff of paddy land. The temporal trend for the yearly loading of atrazine decreased slightly over time, but the trends for oxadiazon and isoprothiolane increased markedly over an 18-year analysis period. In regard to the pesticide concentrations in water, atrazine was associated with the largest value of nearly 1.4 μg/L. July and August were the found to be prime periods for pesticide loss from paddy land, and the biggest monthly loss of atrazine from dryland appeared in June. Under similar usage conditions, isoprothiolane loading from paddy fields ranked as the largest one among the three types of pesticides and reached up to 17 g/ha. Limited monitoring data were useful for validating the model, which yielded valuable temporal-spatial data on the fate of pesticides in this watershed. With the expansion of paddy rice cultivation, risks for pesticide contamination of water bodies will increase. The results of this study should be valuable for future exposure and risk assessments aimed at protecting the environment and human health.
在农业发展过程中，流域的农药负荷量会增加，且可能因不同的作物类型和季节而有所变化。高浓度的农药负荷可能导致受污染的地表水。本研究的目的是确定中国北方中高纬度农业流域河水中三种典型农药（莠去津、恶草酮和异噻菌胺）的农药负荷量和浓度。在这项研究中，我们评估了三十年来两种作物类型的流域农药损失模式。为此，我们整合了实地调查、实验室实验和模型模拟的数据，其中涉及分布式水文溶质输运模型（土壤和水评估工具，SWAT）。SWAT 被用于比较 1990 年至 2014 年流域面积 141.5 平方公里内莠去津、恶草酮和异噻菌胺的时空分布和行为。结果表明，这三种农药可以在流域的不同位置被检测到，并且在稻田地表径流中检测到异噻菌胺的最大浓度为 1.082μg/L。莠去津的年负荷量随时间略有下降，但恶草酮和异噻菌胺的趋势在 18 年的分析期间明显增加。就水中的农药浓度而言，莠去津与近 1.4μg/L 的最大浓度相关。7 月和 8 月被发现是稻田农药流失的主要时期，旱地中莠去津的最大月流失量出现在 6 月。在类似的使用条件下，来自稻田的异噻菌胺负荷量在三种类型的农药中最大，达到 17g/ha。有限的监测数据可用于验证模型，该模型提供了有关该流域农药命运的有价值的时空数据。随着稻田种植面积的扩大，水体农药污染的风险将会增加。本研究的结果对于未来旨在保护环境和人类健康的暴露和风险评估具有重要意义。
