5.2.2 Misleading Transient Signals
Spatial patterns in erosion rate are commonly used to inform tectonic
models and to infer rock uplift rates in mountain landscapes (e.g.,
Adams et al., 2020; Godard et al., 2014; Kober et al., 2015; Morell et
al., 2015; Safran et al., 2005; Scherler et al., 2014). However, we have
shown that changes in rainfall patterns can drive long-lived and complex
spatial patterns of erosion that differ from expectations for uniform
changes in rainfall and thus may not be readily recognized and
interpreted. We have also shown that that ongoing transient adjustment
may not be obviously expressed in landscape morphology (especially for
catchment-mean metrics) under some circumstances. If these caveats are
not considered, subtly expressed transient spatial variations in erosion
rate may be mistaken as representing quasi-steady state spatial
variations in uplift rate (i.e., E = U ). At once this
would give a false impression both about the spatial pattern of uplift
and the importance of past climate changes on a landscape’s evolution,
with direct implications for understanding connections among climate,
surface processes, and tectonics. Determining whether there are
circumstances in which spatial patterns of erosion and topography
produced by changes in rainfall patterns that can be misleading enough
to confound interpretations about factors controlling landscape
evolution is critically important.
During the early transient adjustment in Case 3 (transition to a
bottom-heavy rainfall pattern) there is a clear example of how such
confusion may occur (Figure 10). Recall, in this case, early transient
adjustment produces a concave-up knickpoint along the trunk profile but
as it migrates upstream the shape evolves. This creates a broad
adjustment zone. Over the first ~500 kyr, quasi-steady
state adjustment proceeds ~60% upstream along the
trunk, but the broad adjustment zone means most tributaries along this
length experience a protracted signal of base-level changes related to
trunk adjustment. Because these tributaries all also experience a net
increase in rainfall, knickpoints associated with local adjustment of
the trunk river (Stage 2) tend to relax as they work upstream making
them more diffuse. This protracted competition between local rainfall
and spatio-temporally variable rates of base-level fall, generally
results in diffuse concave to broad convexo-concave adjustment zones in
tributaries (e.g., Figure 8a; Movie S5). Broad adjustment zones,
particularly concave-up adjustment zones, are inherently subtle and this
can inhibit their recognition. This problem may be further compounded by
the influence of sediment flux in natural settings (Brocard & van der
Beek, 2006; Whipple & Tucker, 2002). Indeed, even in our idealized
model (i.e., no sediment influence), along-stream variations in trunk
and tributary local ksn variation is diffuse
(Figure 10c). Based on a lack of significant knickpoints that might
indicate transient adjustment and the several-fold spatial variation in
erosion rate, one might reasonably interpret relationships depicted in
Figure 10a reflect a quasi-steady-state landscape adjusted to a spatial
gradient in uplift rate. In the absence of known surface breaking
structures that might accommodate this gradient in uplift, blind
structures may be inferred, with potential implications for tectonic
models. The apparent viability of this interpretation is supported by
the SPM if rock uplift rate is assumed to match the observed pattern of
catchment averaged erosion rates in tributaries (steady-state
conditions) as illustrated in Figure 10b. Figure 10b shows that the
predicted steady-state upstream-averaged ksnpattern along the trunk river and mean ksn values
exhibited by the tributary network is essentially identical to the
transient pattern in Figure 10a. Moreover, even in detail, there are
only subtle differences in the along-stream pattern of localksn between the two scenarios (Figure 10c). Thus,
in this instance, ksn patterns and erosion rates
that actually record a complex transient response to a change in
rainfall pattern could reasonably be mistaken for a steady state
landscape adjusted to a spatial gradient in uplift.
Although subtle variations in ksn values might
give a misleading impression that a landscape is in quasi-steady-state,
the spatial pattern of ksn-q unambiguously
suggests along-stream variations in erosion rate exist along both the
trunk river and tributaries. ksn-q also exhibits
a coherent pattern of downstream adjustment that could readily be
interpreted as a transient signal sweeping upstream through the
catchment that, significantly, is inconsistent with a steady state
landscape adjusted to the spatial gradient in uplift shown in Figure 10b
(Figure 10c). This example shows the potential usefulness ofksn-q , both as a diagnostic tool for detecting
ongoing transient adjustment to changes in rainfall patterns whereksn may be misleading and for resolving the
relative influences of tectonics and climate.
Finally, we emphasize that our intention is not to suggest all, or any
specific examples, where spatial patterns of rock uplift are inferred
from erosion rates and channel steepness patterns are incorrect. Rather,
our intention here is to highlight the extent to which confusion may be
possible under the right circumstances, and how explicitly accounting
for rainfall patterns can be a step toward addressing these challenges.