Method
Our investigation was structured by process class (Anderson and
McDonnell, 2005), for example “evapotranspiration”, “overland flow”,
or “groundwater flow”. McMillan (2020) provided a list of papers
describing processes in experimental watersheds. We searched literature
on perceptual models, including recent discussions of perceptual model
use and scope (Beven and Chappell, 2021; Wagener et al., 2021),
perceptual models of well-known watersheds such as Panola (Aulenbach et
al., 2021), Maimai (McGlynn et al., 2002) and the Attert Basin (Wrede et
al., 2015), and perceptual models of specific processes such as
infiltration (Beven, 2004). Many papers do not explicitly refer to
perceptual models but equivalently describe runoff generation processes.
We surveyed these papers with particular attention to studies from a
wide range of climate and landscape types. These included arid (Ries et
al., 2017), humid (Dunne and Black, 1970; Hewlett and Hibbert, 1967),
cold region (Peters et al., 1995; Pomeroy et al., 1999; Quinton and
Marsh, 1999; Rango, 1993), forested (Bonell, 1993; Jones, 2000), and
karst watersheds (Hartmann et al., 2013).
From each paper, we extracted all names or short phrases describing
runoff generation processes. Where available, we referred to previous
process classifications such as the typology of groundwater–surface
water interaction by Dahl et al. (2007), and processes in earth system
models (Clark et al., 2015; Fan et al., 2019). We noted alternative
names for each process, although it was sometimes difficult to ascertain
minor differences in meaning between terms; see further comment in the
Discussion section below.
To integrate the new taxonomy with previous classification systems, we
specified a functional class for each process. Bracken et al. (2013)
divided hydrological function into structural knowledge - to do
with stores - and process-based knowledge - to do with fluxes.
Wagener’s classification (2007) adds partitioning andrelease. We added a class Complex process for emergent
behaviors, and subcategories of each class were added as needed (Table
1).
The process taxonomy was collated into spreadsheet format that tracked
the hierarchical structure by assigning a ‘parent’ to each process name
(see Supplemental Information). The spreadsheet was processed inR using the collapsibleTree package to create an
interactive tree diagram (Khan et al., 2018). Processes were shown as
nodes that expand and collapse, and were coloured by functional class.
Tool tips displayed alternative names and the identifier.