Topographic and depth-to-bedrock controls on non-perennial headwater streamflow

Abstract

Non-perennial headwater streams dominate river networks in terms of total flowing length and contribute substantially to downstream water conditions. The flowing extent of these streams varies over space and time, driven by several interacting controls that are themselves difficult to predict. Two of these major controls are topography and subsurface characteristics. The goal of this dissertation was to understand how topography and the distribution of subsurface storage, represented by depth-to-bedrock (DTB), interact to control patterns of non-perennial streamflow at the Hubbard Brook Experimental Forest in the White Mountains of New Hampshire. To do this, I conducted a field campaign to collect flowing-state observations for three non-perennial streams using a network of distributed flow presence and absence sensors. I paired these observations with a characterization of the depth-to-bedrock across one study watershed, combining passive seismic sensing with direct observations from ground surveys and soil pits. These datasets were integrated with a suite of topographic analyses and modeling methods, to examine how topography and depth-to-bedrock interact to explain wetting and drying patterns and flow persistence of a stream network. This dissertation had three research objectives: 1) to determine the order of wetting and drying in non-perennial stream networks during events, and if it can reveal catchment subsurface structure 2) to test whether characterization of depth-to-bedrock throughout a watershed explains flow persistence in a stream network, and 3) evaluating whether a process-based model with additional subsurface information can reproduce observed surface flow dynamics in space and time. Across these methods, both topography and subsurface properties explain processes that drive temporary flow in non-perennial streams. Non-perennial headwater streams do not activate in a fixed order of wetting and drying from event to event. There is no strong relationship between depth-to-bedrock and flow persistence, either locally or across hillslopes that drain to channel reaches. The process-based model was the most transferable approach, producing accurate predictions of discharge at the watershed outlet, but it could not resolve the finer-scale patterns of wetting and drying throughout the network. Explaining the controls of wetting and drying in non-perennial streams remains challenging, but this work validates past findings that topography-based frameworks are easy to implement and effective, and shows that, at least in these headwater networks, site-specific knowledge and thorough characterization of the subsurface does not improve the ability to predict these small, complex systems.