Logjam Characteristics as Drivers of Transient Storage in
Headwater Streams
A. Marshall1, X. Zhang2, A.H.
Sawyer2, E. Wohl1, and K.
Singha3
1Department of Geosciences, Colorado State University,
Fort Collins, CO, USA
2School of Earth Sciences, The Ohio State University,
Columbus, OH, USA
3Colorado School of Mines, Hydrologic Science and
Engineering Program, Golden, CO, USA
Corresponding author: Anna Marshall
(amarsh01@colostate.edu)
Key Points:
- Transient storage is maximal when there are many jams (large
longitudinal distribution density) with low permeability (tightly
packed jam).
- Solute breakthrough in the flume is more sensitive to surface flow
paths than subsurface flow
paths, suggesting much of the observed transient storage occurs in
backwater zones behind jams.
- Configurations with greater transient storage also have the greatest
rates of hyporheic exchange and longest residence times in the
subsurface.
Abstract
Logjams in a stream create backwater conditions and locally force water
to flow through the streambed, creating zones of transient storage
within the surface and subsurface of a stream. We investigate the
relative importance of logjam distribution density, logjam permeability,
and discharge on transient storage in a simplified experimental channel.
We use physical flume experiments in which we inject a salt tracer,
monitor fluid conductivity breakthrough curves in surface water, and use
breakthrough-curve skew to characterize transient storage. We then
develop numerical models in HydroGeoSphere to reveal flow paths through
the subsurface (or hyporheic zone) that contribute to some of the
longest transient-storage timescales. In both the flume and numerical
model, we observe an increase in backwater and hyporheic exchange at
logjams. Observed complexities in transient storage behavior may depend
largely on surface water flow in the backwater zone. As expected,
multiple successive logjams provide more pervasive hyporheic exchange by
distributing the head drop at each jam, leading to distributed but
shallow flow paths. Decreasing the permeability of a logjam or
increasing the discharge both facilitate more surface water storage and
elevate the surface water level upstream of a logjam, thus increasing
hyporheic exchange. Multiple logjams with low permeability result in the
greatest magnitude of transient storage, suggesting that this
configuration maximizes solute retention in backwater zones, while
hyporheic exchange rates also increase. Understanding how logjam
characteristics affect solute transport through both the channel and
hyporheic zone has important management implications for rivers in
forested, or historically forested, environments.
1 Introduction
Spatial heterogeneity in flow paths within a river corridor drives
stream solute exchange between mobile areas of the channel and
relatively immobile transient storage zones. Transient storage can be
generally segregated into surface transient storage—where water flows
slowly through recirculation zones and stagnant areas of low
velocity—and subsurface transient storage (controlled in part by
hyporheic exchange—where stream water flows through the subsurface and
returns to the channel). Transient storage has numerous benefits to
river corridor ecosystem services and processes including i) increased
biogeochemical cycling (Fischer et al., 2005; Battin et al., 2008;
Tonina & Buffington, 2009; Harvey & Gooseff, 2015; Marttila et al.,
2018); ii) nutrient and pollutant processing (Harvey & Wagnert, 2000;
Hall et al., 2002; Ensign & Doyle, 2005; Stewart et al., 2011); iii)
increased habitat diversity and thermal refugia (Mulholland et al.,
2004; Hester & Gooseff, 2010); and iv) flow attenuation (Herzog et al.,
2018). Transient storage can be increased by morphologic and geologic
features that create spatial heterogeneity in water velocity and drive
alternate patterns of downwelling and upwelling along the bed. Examples
of such features include bedforms and other variations in channel
cross-sectional geometry (Bencala, 1983; Harvey & Bencala, 1993;
Kasahara & Wondzell, 2003; Ensign & Doyle, 2005; Gooseff et al.,
2007), logjams (Hester & Doyle, 2008; Sawyer et al., 2011; Marttila et
al., 2018; Ader et al., 2021), and variations in alluvial thickness and
grain-size distribution (Harvey et al., 1996). Here, we focus on the
effects of logjams as an important morphologic element that creates both
surface transient storage in the channel (for example, backwater zones)
and subsurface transient storage in porous media (for example, hyporheic
exchange).
Logjams directly enhance transient storage in a number of ways. Logjams
obstruct flow and increase hydraulic resistance within the channel, thus
creating hydraulic head gradients that drive hyporheic exchange. Logjams
directly influence surface transient storage by creating low-velocity
zones within the channel (Gippel, 1995); enhancing the formation of
backwater pools (Richmond & Fausch, 1995; Kaufmann & Faustini, 2012;
Beckman & Wohl, 2014; Livers & Wohl, 2016); creating scour pools that
enhance residual pool volume (Fausch & Northcote, 1992; Ensign &
Doyle, 2005; Mao et al., 2008); and creating marginal eddies (Zhang et
al., 2019).
Logjams also indirectly affect surface and subsurface transient storage
by increasing the erosion and deposition of sediment (Wohl & Scott,
2017). Logjams locally enhance entrainment of bed material and erosion
of the channel bed and banks (Buffington et al., 2002). Studies of the
effects of logjams on floodplain-sediment dynamics emphasize how the
obstructions created by logjams can result in changes in bedforms via
overbank flows and vertical accretion or bank erosion, channel avulsion,
and formation of secondary channels (e.g., Sear et al., 2010; Wohl &
Scott, 2017). Logjams commonly create high spatial variability in
average bed grain size and alluvial thickness upstream and downstream of
a jam (Massong & Montgomery, 2000). Advective pumping, induced by
streamflow over a spatially heterogeneous and permeable bed, leads to a
distribution of pore-water flow paths in the streambed (Wörman et al.,
2002), which in turn enhances the magnitude of subsurface transient
storage via hyporheic exchange (Lautz et al., 2006; Hester & Doyle,
2008; Fanelli & Lautz, 2008; Sawyer et al., 2011; Sawyer & Cardenas,
2012).
As might be expected, previous work indicates that greater roughness
(e.g., Harvey et al., 2003) and spatial heterogeneity within a channel
(e.g., Gooseff et al., 2007) equate to greater potential for transient
storage. A growing body of research describes wood as a driver of
channel spatial heterogeneity (e.g., Buffington & Montgomery, 1999;
Collins et al., 2012; Faustini & Jones, 2003) and as a driver of
transient storage (e.g., Mutz et al., 2007; Sawyer et al., 2011; Sawyer
& Cardenas, 2012; Kaufmann & Faustini, 2012; Doughty et al. 2020; Ader
et al., 2021; Wilhelmsen et al., 2021). Recent work used bulk electrical
conductivity (Doughty et al., 2020) and fluid electrical conductivity
(Ader et al., 2021) to examine surface and subsurface transient storage
in a small stream with and without the presence of logjams and found
that the direct presence of wood increases transient storage and does so
at a greater magnitude than other geomorphic variables, such as bedform
dimensions. Wilhelmsen et al. (2021) combined flume experiments with a
numerical model to analyze the effects of jam complexity, in combination
with channel planform complexity, on the hyporheic flow regime of small
streams. Their numerical simulations suggest that logjams decrease the
turnover length that stream water travels before interacting with the
hyporheic zone by an order of magnitude and that the broadest range of
hyporheic residence times arise where logjams and multiple channel
threads co-occur. While these field and modeling studies have shaped our
understanding of transient storage around logjams and channel
morphologies of varying complexities, an opportunity exists to test the
effects of logjam characteristics on transient storage patterns. No
study, to our knowledge, has used empirical data to comparatively
examine transient storage in a stream as the number of logjams increases
(e.g., distribution density) nor have any addressed how the structure of
jams (e.g., permeability) influences transient storage.
These characteristics of logjams are important to understand because in
natural settings, jams vary in size, shape, and permeability depending
on the abundance and composition of large wood and coarse particulate
organic matter (see terminology in Table 1). Quantifying logjam
characteristics in the field has proved challenging (Manners et al.
2007, Livers et al., 2020) and physical and numerical modeling
approaches are commonly used to further constrain field variables.
Recent work explores the influence of jam sorting and organizational
structure on logjam permeability (Spreitzer et al., 2019) and resulting
hydraulic impacts (Schalko et al., 2018; Ismail et al, 2020; Follett et
al., 2021). A small number of physical modeling studies have relied on
natural wood to study hydraulics and geomorphology (e.g., Beebe 2000;
Mutz et al., 2007; Schalko 2020; Schalko & Weitbrecht, 2021; Spreitzer
et al., 2021), but none have used natural wood to examine logjam
accumulation characteristics (Friedrich et al., 2022). Knowledge of how
logjam characteristics influence hydrologic function is pertinent to
river management as wood is increasingly used to restore a more natural
hydrologic function to rivers (Roni et al., 2014; Grabowski et al.,
2019). Limited understanding of how logjam characteristics relate to
specific hydrologic effects constrains our ability to maximize functions
of constructed logjams to promote ecosystem services provided by
transient storage.
Here, we address some of the gaps in understanding the relationship
between logjam characteristics and transient storage at varying
discharges and logjam configurations. Our study objective is to assess
the relative response of transient storage to binary changes in logjam
permeability (high versus low), logjam distribution density (single
versus multiple jams along a given length of channel), and discharge
(high versus low). We achieve this objective through a two-part
approach. We use flume experiments, specifically focusing on measuring
salt breakthrough curves in the channel, to address faster timescales of
transient storage. Because breakthrough curves measured in surface water
often fail to capture some of the longer residence times in the
hyporheic zone (Harvey et al., 1996) and do not reveal spatial
information about flow paths, we also numerically simulated coupled
surface-subsurface flow in flume experiments to resolve longer flow
paths through the subsurface. We treated the jams themselves as an
extension of the porous medium with adjustable permeability. We test
four hypotheses: H1) increasing logjam longitudinal distribution density
enhances transient storage; H2) increasing the permeability of a single
logjam enhances transient storage; H3) a single low-permeability logjam
creates a comparable increase in transient storage to multiple
high-permeability logjams; and H4) transient storage increases at higher
discharge for all scenarios.
Table 1. Wood terminology definitions.