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A modelling framework to simulate river flow and pesticide loss via preferential flow at the catchment scale

机译:一种模拟河流流量和集水区流量的河流流量和农药损失的建模框架

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摘要

A modelling framework with field-scale models including the preferential flow model MACRO was developed to simulate transport of six contrasting herbicides in a 650 km2 catchment in eastern England. The catchment scale model SPIDER was also used for comparison. The catchment system was successfully simulated as the sum of multiple field-scale processes with little impact of in-stream processes on simulations. Preferential flow was predicted to be the main driver of pesticide transport in the catchment. A satisfactory simulation of the flow was achieved (Nash-Sutcliffe model efficiencies of 0.56 and 0.34 for MACRO and SPIDER, respectively) but differences between pesticide simulations were observed due to uncertainties in pesticide properties and application details. Uncertainty analyses were carried out to assess input parameters reported as sensitive including pesticide sorption, degradation and application dates; their impact on simulations was chemical-specific. The simulation of pesticide concentrations in the river during low flow periods was very sensitive to uncertainty from rain gauge measurements and the estimation of evapotranspiration.
机译:建立了包括优先流量模型MACRO在内的现场规模模型的建模框架,以模拟英格兰东部650 km2集水区中六种对比除草剂的运输。集水规模模型SPIDER也用于比较。集水系统已成功地模拟为多个现场规模过程的总和,而流内过程对模拟的影响很小。预测优先流是该流域农药运输的主要驱动力。实现了令人满意的流动模拟(MACRO和SPIDER的Nash-Sutcliffe模型效率分别为0.56和0.34),但是由于农药特性和应用细节的不确定性,观察到农药模拟之间存在差异。进行了不确定性分析,以评估被报告为敏感的输入参数,包括农药吸收,降解和施用日期;它们对模拟的影响是特定于化学的。在低流量时期,河流中农药浓度的模拟对雨量计测量和蒸散估算的不确定性非常敏感。

著录项

  • 作者

    M.L. Villamizar; C.D. Brown;

  • 作者单位
  • 年度 2017
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
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