Geoscience Reference
In-Depth Information
time. Where rating curves have been carefully constructed and flows remain in channel,
then discharge can be estimated to an accuracy of perhaps 5-10 % (Fekete et al.
2012
).
However, where flow is out of bank, such that small increases in water height lead to large
increases in discharge, where fewer observations are available to constrain the shape of the
rating curve, or where flow is so high that the rating curve needs to be extrapolated, then
errors may increase significantly. For example, Di Baldassarre and Montanari (
2009
)
conducted a quantitative assessment of the effect of rating curve uncertainty on river
discharge estimation for a reach of the River Po in Italy and found errors in the range
6.2-42.8 % at the 95 % significance level, with an average of 25.6 %. In an extensive
previous study, Pelletier (
1987
) reviewed 140 publications that quantified uncertainty in
river discharge and found errors in the range 8-20 %. Ground gauging stations typically
record data at intervals between 15 min and 1 day and are located between tens and
hundreds of kilometres apart, depending on the flashiness of the flow regime and the
purpose for which the network is being used. Ground observations of inundation extent can
be made, although the possible coverage is very limited and typically remote sensing
platforms offer a much better solution for this variable. No global ground-based topog-
raphy and channel bathymetry data sets currently exist, and this situation appears unlikely
to change in the future.
Global coverage is clearly much easier to attain using remote sensing platforms;
however, this may come at the expense of accuracy, and the orbit and instrument char-
acteristics of existing systems may provide only a partial view of river, floodplain and
wetland surface water dynamics. Indeed, satellite systems may often miss flood events
entirely due to their particular orbital period/revisit times. This is largely because the
satellite data used by surface water scientists come from either generic systems (e.g., the
optical Landsat sensors) or more bespoke systems designed for applications in different
geophysical fields such as oceanography, glaciology or geodesy. These systems are less
than ideal for observing surface water floods, but can, if carefully employed, yield
important insights at certain scales. Below, we discuss the available systems for measuring
floodplain topography, water elevation, inundation extent and water storage. No current or
planned future satellite system is capable of measuring either river bathymetry or discharge
directly.
2.1 Remote Measurements of Floodplain Topography
For local-, regional- and national-scale studies, a number of high accuracy and fine spatial
resolution systems are available for collecting remotely sensed terrain data. These include
aerial stereo-photogrammetry (Baltsavias
1999
; Lane
2000
; Westaway et al.
2003
), air-
borne laser altimetry or LiDAR (Krabill et al.
1984
; Gomes-Pereira and Wicherson
1999
)
and airborne synthetic aperture radar (SAR) interferometry (Hodgson et al.
2003
). LiDAR
instruments in particular are now capable of generating data at sub-metre spatial resolution
with vertical accuracy of *5 cm root mean square error (RMSE) over wide areas and are
ideal for flood modelling. For example, over 70 % of England and Wales is now mapped
using LiDAR. Such data are capable of capturing the complexity of floodplain microto-
pography and have vertical errors much lower than typical flood wave amplitudes.
Globally, however, comparable data do not exist, and the terrain data available to surface
water scientists are of much lower resolution and accuracy. A number of near-global
terrain models are available, but amongst the most useful for surface water scientists are
the measurements from the NASA Shuttle Radar Topography Mission (SRTM, Farr et al.
2007
). SRTM was captured using an interferometric synthetic aperture radar flown on
