6. Summary and Conclusions
In this study, we use a simple form of the SPM to explore how spatial
rainfall gradients influence both river profiles and expectations about
how fluvial landscapes should respond to changes in climate. Notably,
because changes in climate in mountain settings involve changes in
orographic precipitation patterns, advancing understanding about how
changes in climate influence the rivers and topography of mountain
landscapes requires a more nuanced, spatially variable, treatment of
climate at the catchment scale beyond broadly characterized changes in
mean climate. We show that spatially varying rainfall conditions
experienced by rivers occupying different landscape positions,
specifically trunk and tributary rivers, result in fundamentally
different expressions of a given rainfall pattern, and that they respond
to changes in rainfall pattern in fundamentally different ways. Further,
we show how complex transient responses may arise, and that even modest
variations in rainfall patterns can significantly affect spatial
patterns of erosion and topographic adjustments that directly contrast
with expectations for uniform changes in rainfall. In particular,
changes in rainfall pattern characteristically result in multi-stage
responses with adjustment zones that can be both spatially extensive and
subtly expressed, thus difficult to recognize. Interestingly, these
finding suggest more broadly that catchments of different sizes, shapes,
and locations set within regional orographic precipitation patterns may
have unique, and substantially variable, rainfall histories and
responses to changes in climate. These complications raise important
questions about how best to interpret spatial variations in erosion
rates and their relationship with topography. Finally, we discuss how
catchment-scale variations in rainfall generally complicate
relationships between conventional topographic metrics (e.g., meanksn ) and erosion rates, even at steady state, and
implications for empirical tests of the SPM in natural landscapes. More
precise metrics like ksn-q that leverage
ever-increasing resolution of rainfall datasets to better account for
the spatial distribution of rainfall – specifically its effect on
discharge and runoff – may be a significant step toward overcoming
these challenges and may prove vital for future studies seeking to
quantify interactions between climate, tectonics, and erosion in
mountain landscapes.