Hierarchical Clustering for Paired Watershed Experiments: Case Study in Southeastern Arizona, U.S.A.

Abstract

Watershed studies are often onerous due to a lack of data available to portray baseline conditions with which to compare results of monitoring environmental effects. A paired-watershed approach is often adopted to simulate baseline conditions in an adjacent watershed that can be comparable but assumes there is a quantifiable relationship between the control and treated watersheds. Finding suitably matched pairs that can most accurately depict similar responses is challenging and attributes are rarely quantified. In southeastern Arizona, United States, researchers are investigating the effectiveness of watershed restoration techniques employed by land managers. We selected Smith Canyon to develop a rigorous and quantitatively defensible paired-watershed experimental design. The Smith Canyon watershed consists of 91 structurally similar sub-basins that have a defined basin-like structure and flow channel, allowing for consideration as replicate units. We developed a statistical approach to group sub-basins based on similar structural, biophysical, and hydrologic traits. Our geospatial database consisted of 35 environmental variables, which we reduced to 12 through a correlation analysis. We identified three primary collections of paired sub-basins within the larger watershed. These clusters are being used to inform studies actively being employed in the watershed. Overall, we propose a hierarchical clustering protocol for justification of watershed pairing experiments.