Bell, V.A.
ORCID: https://orcid.org/0000-0002-0792-5650; Kay, A.L.
ORCID: https://orcid.org/0000-0002-5526-1756; Jones, R.G.; Moore, R.J.; Reynard, N.S.
ORCID: https://orcid.org/0000-0002-5185-3869.
2009
Use of soil data in a grid-based hydrological model to estimate spatial variation in changing flood risk across the UK.
Journal of Hydrology, 377 (3-4).
335-350.
10.1016/j.jhydrol.2009.08.031
Abstract
A grid-based flow routing and runoff-production model, configured to employ as input either observed or
Regional Climate Model (RCM) estimates of precipitation and potential evaporation (PE), has previously
been used to assess how climate change may impact river flows across the UK. The slope-based Gridto-
Grid (G2G) model adequately simulated observed river flows under current climate conditions for high
relief catchments, but was less successful when applied to lower-relief and/or groundwater-dominated
areas. The model has now been enhanced to employ a soil dataset to configure the probability-distributed
store controlling soil-moisture and runoff generation within each grid-cell. A comparison is made of the
ability of both models to simulate gauged river flows across a range of British catchments using observations
of rainfall and PE as input. Superior performance from the enhanced G2G formulation incorporating
the soil dataset is demonstrated.
Following the model assessment, the observed precipitation and PE data used as input to both hydrological
models were replaced by RCM estimates on a 25 km grid for a Current (1961–1990) and a Future
(2071–2100) time-slice. Flood frequency curves derived from the flow simulations for the two time-slices
are used to estimate, for the first time, maps of changes in flood magnitude for all river points on a 1 km
grid across the UK. A high degree of spatial variability is seen in the estimated change in river flows,
reflecting both projected climate change and the influences of landscape and climate variability. These
maps also highlight large differences between the climate impact projections arising from the two models.
The improved structure and performance of the soil-based G2G model adds confidence to its projections
of flow changes being realistic consequences of the climate change scenario applied. A resampling
method is used to identify regions where these projections may be considered robust. However, with the
climate change scenario used representing only one plausible evolution of the future climate, no clear
message can be drawn here about projected river flow changes.
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