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. In this study, we develop a watershed zonation approachfor characterizing watershed organization and functions in a tractablemanner by integrating multiple spatial data layers. We hypothesize that (1) a hillslope is an appropriate unit for capturing the watershed-scaleheterogeneity of key bedrock-through-canopy properties and for quantifying the co-variability of these properties representing coupled ecohydrologicaland biogeochemical interactions, (2) remote sensing data layers and clustering methods can be used to identify watershed hillslope zones havingthe unique distributions of these properties relative to neighboring parcels, and (3) property suites associated with the identified zones can beused to understand zone-based functions, such as response to early snowmeltor drought and solute exports to the river. We demonstrate this concept using unsupervised clustering methods that synthesize airborne remotesensing data (lidar, hyperspectral, and electromagnetic surveys) along with satellite and streamflow data collected in the East River Watershed, CrestedButte, Colorado, USA. Results show that (1) we can define the scale ofhillslopes at which the hillslope-averaged metrics can capture the majorityof the overall variability in key properties (such as elevation, netpotential annual radiation, and peak snow-water equivalent – SWE), (2) elevation and aspect are independent controls on plant and snow signatures, (3) near-surface bedrock electrical resistivity (top 20 m) and geological structures aresignificantly correlated with surface topography and plan speciesdistribution, and (4) K-means, hierarchical clustering, and Gaussian mixtureclustering methods generate similar zonation patterns across the watershed.Using independently collected data, we show that the identified zonesprovide information about zone-based watershed functions, includingforesummer drought sensitivity and river nitrogen exports. The approach isexpected to be applicable to other sites and generally useful for guidingthe selection of hillslope-experiment locations and informing modelparameterization.

Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions