1.1 Quantifying Hydrologic Connectivity in River-Floodplain
Systems
The physical template that determines potential connective pathways in
river-floodplain systems is known as structural connectivity (Bracken &
Croke, 2007). In river-floodplain systems, analyses of digital elevation
models and/or habitat features is common for identifying surficial
structural connections, while identification of physical subsurface
structural connections is more limited given subsurface heterogeneity
and often requires broad simplifications of underlying complexity (K. L.
Jones et al., 2008; Thoms et al., 2005; A. S. Ward et al., 2012).
Functional hydrologic connectivity refers to the degree that material
and/or energy is transferred within the landscape. For functional
hydrologic connectivity (hereafter connectivity) to be achieved, flow
must overcome resistance, impedances, and losses along structurally
connected pathways (Ali et al., 2018). Thus, connectivity within
river-floodplain systems may only occur under specific hydrologic
conditions driven by internal (e.g., antecedent moisture conditions and
geomorphic structure) and external (e.g., river flow state, local
precipitation) factors (Fritz et al., 2018).
Assessing functional connectivity requires an approach that can quantify
the degree to which material and energy moves among landscape components
(Bracken et al., 2013; Turnbull et al., 2008). One common approach is to
use hydrodynamic models and topographic data to predict connectivity
dynamics (Chen et al., 2020; Stone et al., 2017). However, developing
accurate models can be challenging because both the models and the
underlying topographic datasets often miss do not capture the small
scale geomorphic features and processes that are critical drivers of
lateral connectivity (e.g., log jam development and failure) (Addy &
Wilkinson, 2019). Therefore, field methods that capture spatiotemporal
patterns in functional connectivity are also valuable. Common field
methods to measure functional connectivity between rivers and their
floodplains include hydrologic measurements (e.g., soil moisture, water
levels, streamflow), geochemical and isotopic end-member mixing analyses
and conservative tracer experiments (Cabezas et al., 2011; C. N. Jones
et al., 2014; Rinderer et al., 2018).
The field methods listed above tend to provide information about
different aspects of connectivity and are often only applicable at
specific spatial or temporal scales, hindering between-study comparisons
and the direct translation of connectivity assessments to policy and
management decisions (Wohl et al., 2019). Additionally, connectivity is
often considered as a categorical or binary attribute (i.e., connected
or isolated) where connectivity is achieved when river stage is above a
specific threshold or when physio-chemical states are similar between
two landscape components with a known structural connection. However,
fluvial networks such as river-floodplain systems also experience
gradients in hydrologic conditions, suggesting continuous metrics of
connectivity may more accurately describe system level properties
(Garbin et al., 2019).