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Pesticide Exposure Assessment in Rice Paddies in Europe

机译:欧洲稻田中农药暴露评估

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The increasing cost of monitoring and field studies have made mathematical modeling an indispensable part of pesticide registration process. Although, a uniform approach for proper model use has now been established in Europe this could not be used in rice due to the unique flooding conditions applied in rice cropping. Currently, in most cases predicted environmental concentrations (PECs)of pesticides applied in rice are calculated with a Tier 1 spreadsheet which was developed by the Med-Rice group. Recently, the SWAGW model was developed as a Tier 2 modeling tool, which is based on the Tier 1 spreadsheet but incorporates certain improvements including a more realistic partitioning of pesticide between water and soil. However, the use of more sophisticated models is essential in cases where refined modeling or application of mitigation strategies have to be applied. The RICEWQ model is the only validated model at present which can adequately predict the environmental fate of pesticides in rice paddies and provide PECs for GW and immediately adjacent SW systems. This model has been used in Europe for a realistic estimation of pesticide exposure at paddy-field scale. Rice is commonly cultivated in Europe in large river basins such as the Axios river basin in Greece or the National Park of Donana in Spain. Artificial and natural SW bodies are present in most of the rice- cultivated basins in Europe constituting a unique ecosystem. Therefore, it is relevant to consider pesticide risk assessment for rice at basin-scale level. The combined use of RICEWQ with the SW model RIVWQ allows a realistic estimation of PECs in SW bodies receiving water from treated paddies. This modeling tool has been already used for calculating exposure in rice-cultivated basins within the frame of basin-scale scenarios or in conjunction with spatial GIS data of specific rice cultivated zones.
机译:监测和实地研究成本的增加使数学建模成为农药注册过程中必不可少的部分。尽管现在在欧洲已经建立了统一的模型使用方法,但是由于水稻种植中存在独特的洪水条件,因此无法在水稻中使用。当前,在大多数情况下,使用Med-Rice小组开发的Tier 1电子表格来计算水稻中农药的预测环境浓度(PECs)。最近,SWAGW模型被开发为Tier 2建模工具,该工具基于Tier 1电子表格,但结合了某些改进,包括在水和土壤之间更实际地分配农药。但是,在必须应用精细的建模或应用缓解策略的情况下,使用更复杂的模型至关重要。 RICEWQ模型是目前唯一经过验证的模型,可以充分预测稻田中农药的环境命运,并为GW和紧邻的SW系统提供PEC。在欧洲,该模型已用于在稻田规模上实际估算农药暴露量。稻米通常在欧洲的大型流域种植,例如希腊的Axios流域或西班牙的多纳纳国家公园。在欧洲大多数稻谷栽培盆地中都存在人工和天然西南SW体,构成了独特的生态系统。因此,有必要在流域范围内考虑水稻的农药风险评估。 RICEWQ与SW模型RIVWQ的组合使用可以对从处理过的稻田中接收水的SW体中的PEC进行实际估算。该建模工具已被用于在盆地规模情景的框架内或结合特定水稻种植区的空间GIS数据来计算水稻种植区的暴露量。

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