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首页> 外文期刊>Hydrology and Earth System Sciences >Analysis of the spatial variation in the parameters of the SWAT model with application in Flanders, Northern Belgium
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Analysis of the spatial variation in the parameters of the SWAT model with application in Flanders, Northern Belgium

机译:SWAT模型参数的空间变化分析及其在比利时北部佛兰德的应用

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Operational applications of a hydrological model often require the prediction of stream flow in (future) time periods without stream flow observations or in ungauged catchments. Data for a case-specific optimisation of model parameters are not available for such applications, so parameters have to be derived from other catchments or time periods. It has been demonstrated that for applications of the SWAT in Northern Belgium, temporal transfers of the parameters have less influence than spatial transfers on the performance of the model. This study examines the spatial variation in parameter optima in more detail. The aim was to delineate zones wherein model parameters can be transferred without a significant loss of model performance. SWAT was calibrated for 25 catchments that are part of eight larger sub-basins of the Scheldt river basin. Two approaches are discussed for grouping these units in zones with a uniform set of parameters: a single parameter approach considering each parameter separately and a parameter set approach evaluating the parameterisation as a whole. For every catchment, the SWAT model was run with the local parameter optima, with the average parameter values for the entire study region (Flanders), with the zones delineated with the single parameter approach and with the zones obtained by the parameter set approach. Comparison of the model performances of these four parameterisation strategies indicates that both the single parameter and the parameter set zones lead to stream flow predictions that are more accurate than if the entire study region were treated as one single zone. Oil the other hand, the use of zonal average parameter values results in a considerably worse model fit compared to local parameter optima. Clustering of parameter sets gives a more accurate result than the single parameter approach and is, therefore, the preferred technique for use in the parameterisation of ungauged sub-catchments as part of the simulation of a large river basin.
机译:在水文模型的实际应用中,通常需要在(未来)时间段内对水流进行预测,而无需进行水流观测或未受污染的集水区。对于此类应用程序,无法使用针对案例特定的模型参数优化的数据,因此必须从其他集水区或时段中获取参数。已经证明,对于SWAT在比利时北部的应用而言,参数的时间转移对模型性能的影响小于空间转移。这项研究更详细地研究了参数最优的空间变化。目的是描绘可以在不显着降低模型性能的情况下传递模型参数的区域。 SWAT已针对25个集水区进行了校准,这些集水区是Scheldt流域八个较大子流域的一部分。讨论了两种使用统一的参数集将这些单元按区域分组的方法:一种单独考虑每个参数的单参数方法,以及一个整体评估参数化的参数集方法。对于每个集水区,都使用局部参数最优值运行SWAT模型,并使用整个研究区域(佛兰德斯)的平均参数值,用单参数方法描绘区域,并通过参数集方法获得区域。这四种参数化策略的模型性能比较表明,与将整个研究区域都视为一个区域相比,单个参数区域和参数集区域都可以产生更精确的流量预测。另一方面,与局部参数优化相比,使用区域平均参数值会导致模型拟合显着变差。参数集的聚类比单参数方法提供了更准确的结果,因此,作为大型流域模拟的一部分,是用于未固结子汇水区参数化的首选技术。

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