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Estimating catchment-scale groundwater dynamics from recession analysis – enhanced constraining of hydrological models

机译:通过衰退分析估算集水区规模的地下水动力学–加强水文模型约束

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摘要

In this study, we propose a new formulation of subsurface water storage dynamics for use in rainfall–runoff models. Under the assumption of a strong relationship between storage and runoff, the temporal distribution of catchment-scale storage is considered to have the same shape as the distribution of observed recessions (measured as the difference between the log of runoff values). The mean subsurface storage is estimated as the storage at steady state, where moisture input equals the mean annual runoff. An important contribution of the new formulation is that its parameters are derived directly from observed recession data and the mean annual runoff. The parameters are hence estimated prior to model calibration against runoff. The new storage routine is implemented in the parameter parsimonious distance distribution dynamics?(DDD) model and has been tested for 73?catchments in Norway of varying size, mean elevation and landscape type. Runoff simulations for the 73?catchments from two model structures (DDD with calibrated subsurface storage and DDD with the new estimated subsurface storage) were compared. Little loss in precision of runoff simulations was found using the new estimated storage routine. For the 73?catchments, an average of the Nash–Sutcliffe efficiency criterion of?0.73 was obtained using the new estimated storage routine compared with?0.75 using calibrated storage routine. The average Kling–Gupta efficiency criterion was?0.80 and?0.81 for the new and old storage routine, respectively. Runoff recessions are more realistically modelled using the new approach since the root mean square error between the mean of observed and simulated recession characteristics was reduced by almost 50?% using the new storage routine. The parameters of the proposed storage routine are found to be significantly correlated to catchment characteristics, which is potentially useful for predictions in ungauged basins.
机译:在这项研究中,我们提出了一种用于降雨和径流模型的地下储水动力学新公式。在蓄水量与径流量之间存在很强关系的假设下,流域规模蓄水的时间分布被认为与观测到的衰退的分布具有相同的形状(以径流量对数值之间的差异衡量)。平均地下蓄水量估计为稳态下的蓄水量,其中水分输入等于年平均径流量。新配方的重要贡献在于其参数直接来自观察到的衰退数据和年平均径流量。因此,在针对径流进行模型校准之前,需要估算参数。新的存储程序是在参数简约距离分布动力学模型(DDD)中实现的,并且已在挪威的73个集水区进行了测试,集水区的大小,平均海拔和景观类型都不同。比较了两个模型结构(带有校准的地下存储的DDD和带有新估算的地下存储的DDD)中73个汇水面积的径流模拟。使用新的估算存储程序,径流模拟精度几乎没有损失。对于73个集水区,使用新的估计存储程序获得的纳什萨克利夫效率标准的平均值为0.73,而使用校准存储程序则为0.75。对于新存储例程和旧存储例程,平均Kling-Gupta效率标准分别为0.80和0.81。使用新方法可以更实际地模拟径流衰退,因为使用新的存储程序可以将观测到的衰退特征与模拟衰退特征的均方根误差降低近50%。发现拟议的存储程序的参数与流域特征显着相关,这对于未流域的预测可能很有用。

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