Evaluating the impact of model complexity on flood wave propagation and inundation extent with a hydrologic–hydrodynamic model coupling framework
Evaluating the impact of model complexity on flood wave propagation and inundation extent with a hydrologic–hydrodynamic model coupling framework
复制标题
利用水文-水动力模型耦合框架评估模型复杂性对洪水波传播和淹没程度的影响
DOI：
10.5194/nhess-19-1723-2019
复制
发表时间：
2019
影响因子：
4.6
通讯作者：
H. Winsemius
中科院分区：
文献类型：
--
作者：
Jannis M. Hoch;D. Eilander;Hiroaki Ikeuchi;F. Baart;H. Winsemius
抽象的。河流洪水事件是对人们和
基础设施。通常，洪水风险是由水文或河流驱动的。
路线选择和泛滥平原流过程。因为它们通常被模拟为
不同的模型，耦合这些模型可能是增加
不同物理驱动因素的综合模拟洪水估计。为了促进不同模型的耦合和跨洪水风险过程的集成，我们在这里介绍了GLOFRIM 2.0，这是一个全球适用的集成水文-水动力模拟框架。然后，我们测试了这样一个假设，即智能模型耦合可以推进亚马逊和恒河盆地的洪水建模。通过GLOFRIM，我们将全球水文模型PCRGLOBWB与水动力模型CAMA-FLOOD和LISFLOOD-FP进行了耦合。结果表明，用CAMA-FLOAD局部惯性方程代替水文模型的运动波近似，极大地提高了峰值流量模拟的精度，表现为纳什-萨克利夫效率系数(NSE)从约0.48提高到约0.71。LISFLOOD-FP获得的洪水图改进了观测洪水范围的表示(临界成功指数C=0.46)，而缩小了的PCR-GLOBWB和CAMA-Flood产品(分别为C=0.30和C=0.25)。结果证实，模型耦合确实是走向更综合的洪水模拟的一种可行的方法。然而，结果也表明，耦合模式的精度仍然在很大程度上取决于模式的强迫。因此，必须进一步努力改进模拟径流的规模和时间。此外，洪水风险，特别是在三角洲地区，是由沿海过程驱动的。因此，GLOFRIM的下一步发展必须是更全面地表示三角洲地区的洪水过程，例如通过纳入潮汐和潮汐模型，从而为适当的洪水风险管理实践提供更可靠的物理估计。
Abstract. Fluvial flood events are a major threat to people and
infrastructure. Typically, flood hazard is driven by hydrologic or river
routing and floodplain flow processes. Since they are often simulated by
different models, coupling these models may be a viable way to increase the
integration of different physical drivers of simulated inundation estimates. To facilitate coupling different models and integrating across flood hazard processes, we here present GLOFRIM 2.0, a globally applicable framework for integrated hydrologic–hydrodynamic modelling. We then tested the hypothesis that smart model coupling can advance inundation modelling in the Amazon and Ganges basins. By means of GLOFRIM, we coupled the global hydrologic model PCR-GLOBWB with the hydrodynamic models CaMa-Flood and LISFLOOD-FP. Results show that replacing the kinematic wave approximation of the hydrologic model with the local inertia equation of CaMa-Flood greatly enhances accuracy of peak discharge simulations as expressed by an increase in the Nash–Sutcliffe efficiency (NSE) from 0.48 to 0.71. Flood maps obtained with LISFLOOD-FP improved representation of observed flood extent (critical success index C=0.46), compared to downscaled products of PCR-GLOBWB and CaMa-Flood (C=0.30 and C=0.25, respectively). Results confirm that model coupling can indeed be a viable way forward towards more integrated flood simulations. However, results also suggest that the accuracy of coupled models still largely depends on the model forcing. Hence, further efforts must be undertaken to improve the magnitude and timing of simulated runoff. In addition, flood risk is, particularly in delta areas, driven by coastal processes. A more holistic representation of flood processes in delta areas, for example by incorporating a tide and surge model, must therefore be a next development step of GLOFRIM, making even more physically robust estimates possible for adequate flood risk management practices.
影响因子：
56.9
作者：
Tessler, Z. D.;Voeroesmarty, C. J.;Foufoula-Georgiou, E.
通讯作者：
Foufoula-Georgiou, E.