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首页> 外文期刊>Hydrology and Earth System Sciences >Functional test of pedotransfer functions to predict water flow and solute transport with the dual-permeability model MACRO
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Functional test of pedotransfer functions to predict water flow and solute transport with the dual-permeability model MACRO

机译:利用双渗透模型MACRO对传水功能进行功能测试以预测水流量和溶质运移

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摘要

Estimating pesticide leaching risks at the regional scale requires the ability to completely parameterise a pesticide fate model using only survey data, such as soil and land-use maps. Such parameterisations usually rely on a set of lookup tables and (pedo)transfer functions, relating elementary soil and site properties to model parameters. The aim of this paper is to describe and test a complete set of parameter estimation algorithms developed for the pesticide fate model MACRO, which accounts for preferential flow in soil macropores. We used tracer monitoring data from 16 lysimeter studies, carried out in three European countries, to evaluate the ability of MACRO and this "blind parameterisation" scheme to reproduce measured solute leaching at the base of each lysimeter. We focused on the prediction of early tracer breakthrough due to preferential flow, because this is critical for pesticide leaching. We then calibrated a selected number of parameters in order to assess to what extent the prediction of water and solute leaching could be improved. Our results show that water flow was generally reasonably well predicted (median model efficiency, ME, of 0.42). Although the general pattern of solute leaching was reproduced well by the model, the overall model efficiency was low (median ME Combining double low line -0.26) due to errors in the timing and magnitude of some peaks. Preferential solute leaching at early pore volumes was also systematically underestimated. Nonetheless, the ranking of soils according to solute loads at early pore volumes was reasonably well estimated (concordance correlation coefficient, CCC, between 0.54 and 0.72). Moreover, we also found that ignoring macropore flow leads to a significant deterioration in the ability of the model to reproduce the observed leaching pattern, and especially the early breakthrough in some soils. Finally, the calibration procedure showed that improving the estimation of solute transport parameters is probably more important than the estimation of water flow parameters. Overall, the results are encouraging for the use of this modelling set-up to estimate pesticide leaching risks at the regional-scale, especially where the objective is to identify vulnerable soils and "source" areas of contamination.
机译:在区域范围内估算农药浸出风险要求仅使用调查数据(例如土壤和土地利用图)完全设定农药命运模型参数的能力。此类参数化通常依赖于一组查找表和(pedo)传递函数,将基本的土壤和场地特性与模型参数相关联。本文的目的是描述和测试针对农药归宿模型MACRO开发的一套完整的参数估计算法,该算法考虑了土壤大孔中的优先流动。我们使用了在三个欧洲国家进行的16台溶渗仪研究中的示踪剂监测数据,以评估MACRO的能力和这种“盲参数化”方案在每个溶渗仪底部重现测得的溶质浸出的能力。我们专注于由于优先流动而导致的示踪剂早期突破的预测,因为这对于农药浸出至关重要。然后,我们校准了选定数量的参数,以评估水和溶质浸出的预测可以提高到什么程度。我们的结果表明,通常可以合理预测水流(模型效率中位数ME为0.42)。尽管该模型很好地再现了溶质浸出的一般模式,但由于某些峰的时间和幅度存在误差,因此总体模型效率较低(中位ME结合双低线-0.26)。早期孔体积中的优先溶质淋洗也被系统地低估了。尽管如此,根据早期孔隙体积的溶质负荷对土壤的等级进行了合理的估计(一致性相关系数CCC在0.54至0.72之间)。此外,我们还发现忽略大孔流动会导致模型重现所观察到的浸出模式的能力显着下降,尤其是在某些土壤中的早期突破。最后,校准程序表明,改善溶质运移参数的估计可能比水流参数的估计更重要。总体而言,使用该模型设置来估算区域范围内农药淋失风险的结果令人鼓舞,尤其是在目标是确定脆弱土壤和“污染源”污染区域的情况下。

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