RESULTS
The training and validation of the CNN for surface pattern
classification achieved high accuracies (Figure 3), both for the
two-class and the three-class classification. Training losses were
similar to validation losses, suggesting a reasonable model fit. There
was no evidence of overfitting, as validation loss continued to decline
with epoch. The change in training loss tended to decline with each
successive epoch, but was still gently declining by epoch 15 for the
three-class surface classification system, suggesting slight
underfitting of the model. However, the CNN performed well when
predicting on new datasets, whether based on two classes (Sections 3.1)
or three classes (Section 3.2).
Hydromorphological unit
classification
Overall, the HMU classification system predicted HMUs that were
consistent with those that had been identified manually.
Alta. The Alta stretch, showing a sequence of alternating slow
flowing, mild-smooth HMUs and fast flowing, mild-turbulentHMUs (Figure 4; upper panel), was classified into a similar sequence by
the automated HMU classification system (Figure 4; middle panel). The
gentle gradient of the watercourse (<4%) meant thatsteep-smooth HMUs (associated with runs) were absent. Only one
cell was classified as being a steep-turbulent HMU, where the
surface gradient locally exceeded 4%: its small size suggests that it
is not a functionally “realistic” classification of flow conditions.
The automated classification showed a finer level of detail than the
manual classification, reflecting the surface patterns identified by the
CNN (Figure 4; lower panel). For example, standing waves extended around
the outer bank of a meander into an area that had been manually
classified into a mild-smooth HMU.
Nidelva. The automated HMU classification for the Nidelva
stretch alternated between mainly mild-smooth and mild- orsteep-turbulent HMUs (Figure 5). Steep-smooth HMUs were
rare and found as isolated cells. The HMUs with more turbulent flows
were found in the mid-part of the imaged stretch, where higher gradients
occurred (Supplementary figure 1). The spatial configuration of
mesohabitat classes largely concurred with those identified by Borsányi
(2006) (Supplementary figure 1). HMU classifications depended on flow
conditions, and the middle parts of the imaged stretch showed an
increase in the prevalence of turbulent HMUs at high discharge (see
inlet panels in Figure 5).
Orkla. Automated HMU classification of the Orkla stretch was
consistent with the manual classification in the mid- to downstream part
but diverged from the manual classification in the upstream part (Figure
6). The middle part, mainly downstream of an island, consisted of a
smooth water surface in a mild channel gradient (mainly classified as
the mild-smooth HMU); the surface became more turbulent further
downstream (mainly classified as the mild-turbulent HMU). The
upstream part of the Orkla stretch consisted of smooth surfaces,
separated by short regions of white water associated with rapids or
cascades. While the automated HMU classification system was successful
in classifying the mild-turbulent and steep-turbulent areas
successfully, it did not, however, always correctly identify areas free
from standing waves. For example, some areas were misclassified asmild-turbulent HMUs due to the two-class CNN assigning then astanding wave classification, when manual examination of the
imagery showed the presence of air bubbles/foam rather than standing
waves. These misclassifications typically occurred in mild gradient
areas, downstream of rapids or cascades where there was white water at
the surface from the downstream advective diffusion of air bubbles/foam.
Refined surface pattern
classification
The Refined surface pattern classification system (three classes:smooth or rippled , standing waves and diffusing
foam ) classified surface patterns in the Orkla stretch that were
consistent with visual inspection of the imagery (Figure 7). In
particular, it identified the presence of advective diffusion of air
bubbles/foam, immediately downstream of rapids and mainly in pool
mesohabitats. Here, white water was present on the surface but was not
in the form of standing waves generated by interaction between the flow
and the riverbed immediately beneath the white water. Smooth or
rippled surface patterns were more prevalent at the downstream side of
pools, where surface foam had disappeared due to diffusion.