A GIS water balance approach to support surface water flood risk management.

Concern has arisen as to whether the lack of appropriate consideration to surface
water in urban spatial planning is reducing our capacity to manage surface water flood
risk. Appropriate tools are required that allow spatial planners to explore opportunities
and solutions for surface water flooding at large spatial scales. An urban surface water
balance model has been developed that screens large urban areas to identify flooded
areas and which allows solutions to be explored. The model hypothesis is that key
hydrological characteristics; storage volume and location, flow paths and surface water
generation capture the key processes responsible for surface water flooding. The
model uses a LiDAR DEM (Light Detection and Ranging Digital Elevation Model) as the
basis for determining surface water accumulation in a catchment and has been
developed so that it requires minimal inputs and computational resources.
The urban surface water balance approach is applied to Keighley in West Yorkshire
where several instances of surface water flooding have been reported. Data for
validating surface water flood risk models is sparse because such flooding events are of
short duration, very localized and distributed across the catchment. This research used
a postal questionnaire, followed up with site visits to collect data on surface water
flooding locations in Keighley. The validation exercise confirmed that the major
processes responsible for flooding are largely well represented in the model for
situations where interaction with the urban sewer network is well represented by the
assumptions made in the model. A qualitative analysis based on field visits revealed
that the degree of interaction with the sewer network varies spatially, and as the
importance of the interaction of the sewer system increases, the accuracy of the
model results are lowered. It also highlighted that local detail not present in the DEM,
the presence of urban drainage assets and the performance of the sewer system,
which are not be represented in the model, can determine the accuracy of model
results.
Model results were used as a basis to develop solutions to surface water flooding. A
least cost path methodology was developed to identify managed flood routes as a solution. These were translated into model inputs in the form a modified DEM. It was
shown that the simple and fast representation of flood routes and surface storage is of
considerable benefit for scenario analysis.