A new method, with application, for analysis of the impacts on flood risk of widely distributed enhanced hillslope storage
A new method, with application, for analysis of the impacts on flood risk of widely distributed enhanced hillslope storage
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广泛分布的强化山坡蓄水对洪水风险影响分析的新方法及应用
DOI：
10.5194/hess-22-2589-2018
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发表时间：
2018
影响因子：
6.3
通讯作者：
R. Lamb
中科院分区：
文献类型：
--
作者：
Peter Metcalfe;K. Beven;B. Hankin;R. Lamb
抽象的。增强的山坡储存用于“自然”洪水管理，
为了保持陆地风暴径流，并减少快速之间的连接，
表面流动路径和通道。例子包括挖掘的池塘，
加深或筑堤的堆积区，以及冲沟和短暂的河道
用木制障碍物或碎片坝阻挡。大型分布式网络的这种措施的性能很差
明白广泛的计划可能会保留大量的
但有迹象表明，它们的大部分效力可以
这归因于子流域洪水波的去水化。
因此，不适当的措施可能会增加，而不是减少，
洪水风险全分布式水动力学模型已应用于
有限的研究，但引入了显著的计算复杂性。的
较长的运行时间也限制了这些模型在不确定性方面的应用
对许多潜在构型和风暴的估计或评估
可能影响洪水波的时间和幅度的序列。在这里，一个简化的陆路流量路由模块和半分布式
增强山坡蓄水的代表性。将其应用于
英国坎布里亚郡一个大型农村集水区的源头，
提出了一个广泛的存储功能网络，作为洪水缓解措施
战略这些模型是在蒙特卡罗框架内根据数据运行的
持续两个月的极端洪水事件，
下游地区的损失。可接受的实现和可能性
使用GLUE不确定性估计框架确定权重。
行为实现与修改后的集水模型进行了比较
加上山坡上的仓库。三种不同的排水率
参数应用于整个山坡存储网络。研究表明，包括广泛分布的山坡方案，
可以在这种降低的复杂性内有效地对存储进行建模
框架.它显示了存储特征排水率的重要性
同时通过一系列事件进行操作。我们将讨论
陆上水流的简化表示----路由和表示，
存储，以及如何使用实验证据来改善这一点。我们
提出了一些方法，可以更有战略性地对功能进行分组，
改善这些方案的性能。
Abstract. Enhanced hillslope storage is utilised in “natural” flood management in
order to retain overland storm run-off and to reduce connectivity between fast
surface flow pathways and the channel. Examples include excavated ponds,
deepened or bunded accumulation areas, and gullies and ephemeral channels
blocked with wooden barriers or debris dams. The performance of large, distributed networks of such measures is poorly
understood. Extensive schemes can potentially retain large quantities of
run-off, but there are indications that much of their effectiveness can be
attributed to desynchronisation of sub-catchment flood waves.
Inappropriately sited measures may therefore increase, rather than mitigate,
flood risk. Fully distributed hydrodynamic models have been applied in
limited studies but introduce significant computational complexity. The
longer run times of such models also restrict their use for uncertainty
estimation or evaluation of the many potential configurations and storm
sequences that may influence the timings and magnitudes of flood waves. Here a simplified overland flow-routing module and semi-distributed
representation of enhanced hillslope storage is developed. It is applied to
the headwaters of a large rural catchment in Cumbria, UK, where the use of
an extensive network of storage features is proposed as a flood mitigation
strategy. The models were run within a Monte Carlo framework against data
for a 2-month period of extreme flood events that caused significant
damage in areas downstream. Acceptable realisations and likelihood
weightings were identified using the GLUE uncertainty estimation framework.
Behavioural realisations were rerun against the catchment model modified
with the addition of the hillslope storage. Three different drainage rate
parameters were applied across the network of hillslope storage. The study demonstrates that schemes comprising widely distributed hillslope
storage can be modelled effectively within such a reduced complexity
framework. It shows the importance of drainage rates from storage features
while operating through a sequence of events. We discuss limitations in the
simplified representation of overland flow-routing and representation and
storage, and how this could be improved using experimental evidence. We
suggest ways in which features could be grouped more strategically and thus
improve the performance of such schemes.