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Landscape risk analysis for pesticides applied to rice paddies.

机译:稻田用农药的景观风险分析。

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The use of geographical information system (GIS) datasets in combination with mathematical modelling has been proven a powerful tool for modelling refinement at higher tier assessment in all crop situations. This study constitutes the first attempt to predict pesticide exposure in surface-water and groundwater systems of a rice watershed using a combination of GIS and modelling. A rice-cultivated watershed in the region of Lombardy, province of Pavia, Italy was selected. The community of Tromello is bypassed by the river Terdoppio, which along with drainage canals and streams creates a rice watershed of 467 ha, comprising 201 paddies. The watershed was conceptualized using a combination of the rice water quality (RICEWQ 1.6.4v) and river water quality (RIVWQ 2.02) models. Spatial GIS data (land use, soil properties and hydrology), on-site scouting and personal interviews with the farmers were used for modelling parameterization. Application of RICEWQ in each of the paddies provided groundwater predicted environmental concentrations for the herbicides propanil and molinate. Groundwater predicted concentrations did not exceed 0.1 micro g/L in any of the propanil-treated paddies, unlike molinate, whose predicted concentrations exceeded 0.1 micro g/L in 7 of the 31 molinate-treated paddies. Pesticide mass and water releases from paddies were used as inputs for canals, streams and the river, and the fate of propanil and molinate was simulated with RIVWQ. Comparison of the predicted concentrations of molinate and propanil for the year 1999 at the most downstream point of the simulated segment of the river Terdoppio, with measured values obtained from approximately the same point of the river showed a relatively good agreement. These results indicate that the combination of GIS with validated models can be a useful option for higher tier exposure assessment and modelling refinement in rice-paddy areas..
机译:事实证明,将地理信息系统(GIS)数据集与数学建模结合使用,是在所有作物情况下进行更高层评估时,对精细化进行建模的强大工具。这项研究是结合GIS和建模方法预测水稻流域地表水和地下水系统中农药暴露的首次尝试。选择了意大利帕维亚省伦巴第地区的水稻种植分水岭。特罗梅洛(Tromello)社区被特尔多皮奥(Terdoppio)河绕过,河与排水渠和溪流共同构成了一个467公顷的水稻分水岭,包括201个稻田。分水岭的概念是结合稻米水质(RICEWQ 1.6.4v)和河流水质(RIVWQ 2.02)模型来进行的。使用空间GIS数据(土地使用,土壤特性和水文学),现场调查以及与农民的个人访谈来对参数化进行建模。在每个稻田中使用RICEWQ可以为地下水预测除草剂丙烷和mo酸盐的环境浓度。与丙酸盐相比,在任何经丙烷处理的稻田中,地下水的预测浓度均不超过0.1 micro g / L,而在31种经lin酸盐处理的稻田中,预测浓度均未超过0.1 micro g / L。稻田中农药的释放量和水的释放量被用作运河,溪流和河流的输入,并使用RIVWQ模拟了丙烷和mo酸盐的去向。比较了在Terdoppio河模拟段最下游点1999年的预测烟酸和丙酸浓度,并从与该河大致相同的点获得的测量值显示出相对较好的一致性。这些结果表明,将GIS与经过验证的模型相结合对于稻田地区更高的暴露评估和模型细化可能是一个有用的选择。

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