Geoscience Reference
In-Depth Information
Figure 3.7
Estimates of uncertainty in the extent of inundation of the 100-year return period flood for the town
of Carlisle, Cumbria, UK, superimposed on a satellite image of the area using GoogleMaps facilities; the inset
shows the exceedance probabilities for depth of inundation at the marked point (after Leedal et al., 2010).
3.12 Key Points from Chapter 3
•
The data available for rainfall-runoff modelling are generally point data and may not be error free,
even though they must often be treated as error free in applications.
•
Data should be checked for consistency before being used in a rainfall-runoff modelling study. Some
simple checks can be used to identify periods of unusual behaviour that can be checked more carefully
or eliminated from the analysis.
•
Methods for directly measuring evapotranspiration rates are not yet used routinely. A number of
different methods for estimating potential and actual evapotranspiration demand different levels of
data availability.
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Spatial data, such as radar rainfalls and satellite images at different wavelengths, are increasingly
becoming available through remote sensing, including active and passive microwave sensors used in
the estimation of surface soil moistures. In general, such data require some interpretative model to
provide hydrologically useful information. This interpretative model may be a source of error in this
information.
•
Geographical information systems are increasingly being used to store catchment data and interact with
distributed hydrological models in setting up model runs and displaying the results. The information
stored in a GIS (e.g. soil type and vegetation type) may also require an interpretative model before
being useful in hydrological modelling.
•
Digital elevation data, in either raster or vector form, can be the basis of distributed modelling of
both model inputs and rainfall-runoff processes. The latter may require the derivation of hillslope and
channel flow pathways from the digital elevation data. Different methods of analysis and different
resolutions of data will give different apparent flow pathways.
•
Environmental and artificial tracer data might provide valuable information to help in evaluating
whether rainfall-runoff models are getting the right results for the right reasons (see also Chapter 11).
•
There are developing software standards for interfacing different model components and data sets,
such as those provided by OpenMI, INTAMAP and the CUAHSI Hydrologic Information System. In
the future, there will be increasing use of cloud computing facilities in accessing data, running models
and visualising results.
