2.4 CREST-iMAP model
Hydrologic modeling is so far a common approach to deliver timely flood
information for the sake of scalability and efficiency (Gourley et al.,
2017). Yet, conventional hydrologic models bear large uncertainties in
such developed regions, which is mainly due to 1) simplified
representation of terrain (Dullo et al., 2021) and 2) one-dimensional
routing that raises issues in flat regions (Flamig, Vergara, & Gourley,
2020; Getirana & Paiva, 2013; Li et al., 2021b). On the other hand,
hydraulic models do not excel in representing hydrologic processes. In
light of these issues, the newly developed Coupled Routing and Excess
STorage inundation MApping and Prediction (CREST-iMAP) model is used to
investigate the importance of the re-infiltration scheme in flood
inundation models. The CREST-iMAP integrates CREST V2.1 for the
hydrologic part that simulates vertical water distribution by land
surface and ANUGA V2.1 for the hydraulic routing that distributes
spatial water over terrain by solving 2D shallow water equation. Its
performance has been evaluated in this region against the non-coupled
hydrologic models and other popular coupled models – WRF-Hydro+HAND and
LISFLOOD FP (Chen et al., 2021; Li et al., 2021b). However, the previous
version of CREST-iMAP V1.0 does not include the re-infiltration scheme,
meaning that surface running water is not allowed to re-enter the soil.
Here, we release the CREST-iMAP V1.1, an upgrade version, which
considers two-way coupling via exchanging surface water between the
hydraulic and hydrologic module and re-infiltration. Two different
schemes are illustrated schematically in Figure 2, where the left panel
represents the re-infiltration scheme, and the right does not. The
CREST-iMAP V 1.0 and V1.1 are openly accessible from
https://github.com/chrimerss/CREST-iMAP.
[INSERT FIGURE 2 HERE]
CREST-iMAP inherits the previous version of the CREST model, which
simulates saturation excess runoff as the primary runoff generation
process (Wang et al., 2011; Xue et al., 2013; Flamig, Vergara, &
Gourley, 2020). The schematic model structure is depicted in Figure 2.
The study area is discretized in variable triangular meshes which allow
higher density in river channels to resolve high-resolution river flow.
Each modeling unit receives excess rainfall (rainfall minus evaporation)
from forcing data. Then surface water is divided into overland flow and
soil water according to the impervious area ratio through linear
weighting. Overland flow is generated once soil water exceeds its
holding capacity; otherwise, soil water is separated into the remaining
amount and interflow based on the Variable Infiltration Curve (VIC)
concept. The VIC model is a widely recognized infiltration model that
has been applied in several classic hydrologic models (Liang,
Lettenmaier, Wood, & Burges, 1994; Zhao, 1995). Overland flow, combined
with the impervious area and saturation excess flow, is eventually fed
into the 2D shallow water equation solver – the Finite Volume Scheme.
It solves water depth and momentum distributed at each grid cell and
propagates across boundaries. The outputs of the model include water
depth, velocity, discharge, and soil moisture at a desired time step. In
the current setting, re-infiltration, termed as water moves from
subsurface to surface, is not considered because surface flow is the
dominant process in major flood events (Freeze, 1974). The flexibility
of the unstructured mesh in CREST-iMAP allows dense meshes in regions
that reflect high terrain variability (e.g., river channel) and sparse
meshes in other regions (e.g., flood plain). This study simulates the
extreme flood events at 10-m resolution using the embedded unstructured
mesh generator.
There are five hydrologic parameters and one hydraulic parameter for the
CREST-iMAP, which are listed in Table 2 along with parameter ranges. It
is noteworthy that all these parameters are spatially distributed to
account for the spatial heterogeneity of land cover and soil types. The
mean soil saturated hydraulic conductivity, Ksat from 0 to 20 mm/d ,
indicates the soil infiltration capability. Higher Ksat values imply
higher infiltration rates if soils are not saturated while reaching
plateau for the saturated soils. The mean soil water capacity, WM from
10.4 to 365.4 mm, measures the total water content the soil can hold
with lower value representing the impermeable soils. The exponent of the
Variable Infiltration Curve (VIC), B, determines soil water partitioned
to saturation excess runoff or interflow, with a higher B value
corresponding to higher infiltration rates. KE is the ratio of the
potential evapotranspiration to actual evapotranspiration, similar to
the concept of pan coefficient. These soil-related a-priori parameters
can be approximated from a look-up table at an individual grid cell
basis (Chow, Maidment, & Mays, 1988). There are also CONUS-wide
optimized parameter sets that are configured for operational flood
monitoring systems (Flamig, Vergara, & Gourley, 2020). The impervious
area ratio, IM from 0% to 100%, is obtained directly from the NLCD
dataset; the manning’s n coefficient is derived from the LULC via a
look-up table. Both parameters determine water conveyance capacity,
meaning that higher values relate to faster and larger flood peaks. The
hydrologic parameters are configured at their optima based on previous
study, but for the hydraulic parameter – manning coefficient, we
manually adjusted it in a preceding event to ensure generating timely
and accurate possible flood peaks.
[INSERT TABLE 2 HERE]