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Improvement of Hydrological Simulations by Applying Daily Precipitation Interpolation Schemes in Meso-Scale Catchments

机译:在中尺度流域应用每日降水插值方案改进水文模拟

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Ground-based precipitation data are still the dominant input type for hydrological models. Spatial variability in precipitation can be represented by spatially interpolating gauge data using various techniques. In this study, the effect of daily precipitation interpolation methods on discharge simulations using the semi-distributed SWAT (Soil and Water Assessment Tool) model over a 30-year period is examined. The study was carried out in 11 meso-scale (119–3935 km2) sub-catchments lying in the Sulejów reservoir catchment in central Poland. Four methods were tested: the default SWAT method (Def) based on the Nearest Neighbour technique, Thiessen Polygons (TP), Inverse Distance Weighted (IDW) and Ordinary Kriging (OK). =The evaluation of methods was performed using a semi-automated calibration program SUFI-2 (Sequential Uncertainty Fitting Procedure Version 2) with two objective functions: Nash-Sutcliffe Efficiency (NSE) and the adjusted R2 coefficient (bR2). The results show that: (1) the most complex OK method outperformed other methods in terms of NSE; and (2) OK, IDW, and TP outperformed Def in terms of bR2. The median difference in daily/monthly NSE between OK and Def/TP/IDW calculated across all catchments ranged between 0.05 and 0.15, while the median difference between TP/IDW/OK and Def ranged between 0.05 and 0.07. The differences between pairs of interpolation methods were, however, spatially variable and a part of this variability was attributed to catchment properties: catchments characterised by low station density and low coefficient of variation of daily flows experienced more pronounced improvement resulting from using interpolation methods. Methods providing higher precipitation estimates often resulted in a better model performance. The implication from this study is that appropriate consideration of spatial precipitation variability (often neglected by model users) that can be achieved using relatively simple interpolation methods can significantly improve the reliability of model simulations.
机译:地面降水数据仍然是水文模型的主要输入类型。降水的空间变异性可以通过使用各种技术对测量数据进行空间插值来表示。在这项研究中,研究了日降水量插值方法对使用半分布式SWAT(土壤和水评估工具)模型的30年期间排放模拟的影响。该研究是在波兰中部苏莱霍水库集水区的11个中尺度(119-3935 km 2 )子集水区进行的。测试了四种方法:基于最近邻技术的默认SWAT方法(Def),蒂森多边形(TP),反距离加权(IDW)和普通克里金法(OK)。 =方法的评估是使用半自动校准程序SUFI-2(顺序不确定度拟合程序版本2)进行的,该程序具有两个目标函数:Nash-Sutcliffe效率(NSE)和调整后的R 2 系数(bR 2 )。结果表明:(1)最复杂的OK方法在NSE方面优于其他方法; (2)在bR 2 方面,OK,IDW和TP优于Def。在所有流域计算得出的OK和Def / TP / IDW之间的每日/每月NSE中位数差异在0.05到0.15之间,而TP / IDW / OK和Def之间的中位数差异在0.05到0.07之间。但是,插值方法对之间的差异在空间上是可变的,并且这种可变性的一部分归因于流域属性:以低水位密度和低日流量变化系数为特征的流域由于使用插值方法而获得了更为明显的改善。提供更高降水量估计值的方法通常会导致更好的模型性能。该研究的含义是,使用相对简单的插值方法可以适当考虑空间降水变化(通常被模型用户忽略),可以显着提高模型模拟的可靠性。

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