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Assessing the impact of hydrodynamics on large-scale flood wave propagation – a case study for the Amazon Basin

机译:评估流体动力学对大规模洪水波传播的影响-亚马逊盆地的案例研究

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Large-scale flood events often show spatial correlation in neighbouring basins, and thus can affect adjacent basins simultaneously, as well as result in superposition of different flood peaks. Such flood events therefore need to be addressed with large-scale modelling approaches to capture these processes. Many approaches currently in place are based on either a hydrologic or a hydrodynamic model. However, the resulting lack of interaction between hydrology and hydrodynamics, for instance, by implementing groundwater infiltration on inundated floodplains, can hamper modelled inundation and discharge results where such interactions are important. In this study, the global hydrologic model PCR-GLOBWB at 30?arcmin spatial resolution was one-directionally and spatially coupled with the hydrodynamic model Delft 3D Flexible Mesh?(FM) for the Amazon River basin at a grid-by-grid basis and at a daily time step. The use of a flexible unstructured mesh allows for fine-scale representation of channels and floodplains, while preserving a coarser spatial resolution for less flood-prone areas, thus not unnecessarily increasing computational costs. In addition, we assessed the difference between a 1-D channel/2-D floodplain and a 2-D schematization in Delft 3D?FM. Validating modelled discharge results shows that coupling PCR-GLOBWB to a hydrodynamic routing scheme generally increases model performance compared to using a hydrodynamic or hydrologic model only for all validation parameters applied. Closer examination shows that the 1-D/2-D schematization outperforms 2-D for ir/isup2/sup and root mean square error (RMSE) whilst having a lower Kling–Gupta efficiency?(KGE). We also found that spatial coupling has the significant advantage of a better representation of inundation at smaller streams throughout the model domain. A validation of simulated inundation extent revealed that only those set-ups incorporating 1-D channels are capable of representing inundations for reaches below the spatial resolution of the 2-D mesh. Implementing 1-D channels is therefore particularly of advantage for large-scale inundation models, as they are often built upon remotely sensed surface elevation data which often enclose a strong vertical bias, hampering downstream connectivity. Since only a one-directional coupling approach was tested, and therefore important feedback processes are not incorporated, simulated discharge and inundation extent for both coupled set-ups is generally overpredicted. Hence, it will be the subsequent step to extend it to a two-directional coupling scheme to obtain a closed feedback loop between hydrologic and hydrodynamic processes. The current findings demonstrating the potential of one-directionally and spatially coupled models to obtain improved discharge estimates form an important step towards a large-scale inundation model with a full dynamic coupling between hydrology and hydrodynamics.
机译:大型洪水事件通常在邻近流域表现出空间相关性,因此可以同时影响邻近盆地,并导致不同洪峰的叠加。因此,需要使用大型建模方法来解决此类洪水事件,以捕获这些过程。当前采用的许多方法都基于水文模型或水动力模型。但是,由此导致的水文与水动力学之间缺乏相互作用,例如,通过在淹没的洪泛平原上进行地下水入渗,可能会妨碍模型化的淹没和排放结果,而这些相互作用很重要。在这项研究中,在30 arcmin空间分辨率下的全球水文模型PCR-GLOBWB与亚马逊河流域的水动力学模型Delft 3D Flexible Mesh?(FM)在一个网格和一个网格的基础上进行了单向和空间耦合,在每天的时间步。灵活的非结构化网格的使用允许对通道和洪泛区进行精细的表示,同时为较不易发生洪灾的区域保留较粗的空间分辨率,因此不会不必要地增加计算成本。另外,我们评估了代尔夫特3D?FM中一维通道/ 2维洪泛区和二维示意图之间的差异。验证建模的排放结果表明,与仅针对所应用的所有验证参数使用流体动力学或水文模型相比,将PCR-GLOBWB耦合至流体力学路由方案通常可提高模型性能。仔细检查发现,对于 r 2 和均方根误差(RMSE),1-D / 2-D模式化的性能优于2-D,而Kling– Gupta效率较低?(KGE)。我们还发现,空间耦合具有显着的优势,即可以更好地表示整个模型域中较小流上的淹没。对模拟淹没程度的验证表明,只有那些结合了1-D通道的设置才能代表低于2-D网格空间分辨率的范围的淹没。因此,实现一维通道对于大规模淹没模型尤其有利,因为它们通常建立在遥感表面高程数据的基础上,而遥感数据通常会封闭强烈的垂直偏差,从而阻碍了下游连通性。由于仅测试了一种单向耦合方法,因此未合并重要的反馈过程,因此通常会高估两种耦合设置的模拟放电和淹没程度。因此,将其扩展到双向耦合方案以在水文过程和水动力过程之间获得闭合反馈回路将是后续步骤。当前的发现证明了单向和空间耦合模型获得改进的流量估算的潜力,这是迈向大规模淹没模型的重要一步,该模型具有在水文学和水动力学之间进行完全动态耦合的功能。

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