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).