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\begin{document}

\title{Filling the Evidence Gap: Physical and Mathematical Modelling of Leaky
Barriers as Flood Risk Reduction Measures}



\author[1]{Caspar J M Hewett}%
\author[1]{Shannon Leakey}%
\author[1]{Vassilis Glenis}%
\author[1]{Paul Quinn}%
\affil[1]{Newcastle University}%


\vspace{-1em}



  
  \date{May 20, 2024}


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\begin{abstract}
In recent years there has been growing interest in Nature-Based
Solutions (NBS) as a way of reducing flood risk. The premise is that
large numbers of small-scale features distributed across the landscape
can provide the same level of protection as large-scale traditional
flood defences. The in-channel Leaky Barrier (LB) is an example NBS
feature that has been widely implemented. LBs cause flow to back up and
temporarily move onto flood plains during high rainfall. However, there
is considerable resistance to their use at the scales required to impact
significantly on flood risk due to a lack of quantitative data on their
effectiveness. Notably, their hydraulics is poorly understood. This
motivated the research reported here. Physical modelling of simple LBs
was performed in a flume to improve understanding of fundamental
behaviour and provide data for mathematical models. The features consist
of one or more horizontal sheets spanning the channel with a gap
underneath allowing water to pass unimpeded in low flows. For
intermediate depths the feature acts as a sluice gate, while for high
depths water passes under, over and, in the case of more than one sheet,
through the feature. Experiments were carried out in steady-state and
flood-wave conditions. A finite volume model of the flume and features
was developed using a 1D Godunov-type scheme. Riemann solvers are used
to find mass and momentum fluxes between cells. The LB is treated as an
internal boundary condition using a combined weir and sluice gate
equation. Good agreement with experimental results was obtained for
steady-state configurations. Validation is limited for the flood-wave
experiments, but general behaviour was captured by the numerical model
for these cases. This approach could fill a key evidence gap by
answering questions about the optimal leakiness of LBs, the limits to
their usefulness, and how combining them may or may not cause
synchronisation problems when the effect of multiple features is
aggregated.%
\end{abstract}%



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