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.