1. INTRODUCTION
Flooding, as a natural hazard, has been increasingly threatening human
lives and economies (Gourley et al., 2017; Hirabayashi et al., 2013; Li
et al., 2021a). In the United States, most billion-dollar natural
hazards are tied to either local or regional flooding, making it the
major cost to human society. Unfortunately, under a warming climate with
anthropogenic pressure, flood crises are likely to continue expanding,
as the flood frequency accelerates and flood magnitude rises (Bates et
al., 2021; Hirabayashi et al., 2013; Tabari, 2020; Triet et al., 2020;
Swain et al., 2020; Viero et al., 2019;). To combat flood risks,
researchers have been developing hydrologic/hydraulic models to deliver
accurate and timely flood information for local communities and
decision-makers (Gourley et al., 2017). In the United States, two
pronounced flood forecasting systems – the National Water Model (NWM)
and FLASH – are capable of both simulating real-time floods and
forecasting floods in a short range (Cohen, Praskievicz, & Maidment,
2018; Gourley et al., 2017; Viterbo et al., 2020; Yussouf et al., 2020).
These large-scale flood monitoring systems, although claimed to offer
inundation maps and predictions, weaken their hydrodynamic simulation
due to computational requirements. For instance, the NWM adopts the
Height Above Nearest Drainage (HAND) method to produce flood inundation
maps along the river channels by mapping discharge to stage via rating
curves (Johnson, Munasinghe, Eyelade, & Cohen, 2019). This conceptual
method, however, overlooks the physics of floodwater propagation because
of no flow dynamics being represented (Wing et al., 2017). Moreover, it
cannot simulate the pluvial flood, which is a local effect caused by
intense rainfall rates and does not normally occur along river channels
(Bates et al., 2021). More recently, some emerging hydrodynamic models
have been successfully deployed and evaluated at continental or global
scales (Bates et al., 2021; Grimaldi et al., 2019; Sampson et al., 2015;
Wing et al., 2017; Yamazaki, Kanae, Kim, & Oki, 2011). These models
simplify the full Shallow Water Equation (SWE) to speed up the flood
simulation. Nevertheless, they normally do not represent the hydrologic
process well, especially for the infiltration process, which is proven
to be critical in flood simulations (Li et al., 2021b; Ni et al., 2020).
As such, a coupled physically-based hydrologic & hydraulic (H&H) model
appears to be a better choice, which takes the complementary advantages
for accurate flood modeling (Dullo et al., 2021; Felder, Zischg, &
Weingartner, 2017; Kim et al., 2012; Nguyen et al., 2016; Pontes et al.,
2017; Sebastian et al., 2021). Readers are referred to Teng et al.
(2017) and Grimaldi et al. (2019) for a detailed review of coupled
models. Most of such models, however, adopt one-way and weak coupling,
meaning that there is no interplay between the hydrologic component and
hydraulic component (Bravo, Allasia, Paz, & Collischonn, 2013). They
normally produce surface runoff outputs first to drive the hydraulic
model. The recent development of the Coupled Routing and Excess STorage
inundation MApping and Prediction (CREST-iMAP) version 1.0 also falls
into this category, although it is online coupled (Chen et al., 2021; Li
et al., 2021b).
Two-way coupling for the H&H models has not hitherto been
well-recognized. The accumulated surface water (hydraulic feature),
along with excess surface runoff during a flood event in principle would
alter infiltration rates, whereby both the flood magnitudes and timings
could differ. Therefore, we activate the surface water infiltration
along its way to downslope, which is called run-on infiltration or
re-infiltration in short (Smith & Hebbert, 1979; Nahar, Govindaraju,
Corradini, & Morbidelli, 2004; Zhang, Lin, Gao, & Fang, 2020). Nahar
et al. (2004) defined this re-infiltration as the infiltration of
surface water that, as it moves downslope, encounters areas where
moisture deficit has not yet been satisfied. It is often ignored in
rainfall-runoff studies, while it can be significant when the random
nature of infiltration properties is taken into account (Corradini,
Morbidelli, & Melone, 1998; Nahar et al., 2004). Smith and Hebbert
(1979) simulated the run-on process with varying saturated hydraulic
conductivity and rainfall rates, and they reported that the effect of
the run-on process is to decrease the ponding time dramatically.
Corradini et al. (2002) compared models with and without
re-infiltration, and they suggested that re-infiltration greatly reduces
surface flow and alters both rising and recession limbs of the
hydrograph. Nahar et al. (2004) emphasized the influence of
re-infiltration in hillslope hydrograph using the Green-Ampt model with
a 1D kinematic wave surface routing. A recent study by Zhang et al.
(2020) takes it one step further, in which they applied the community
model WRF-Hydro (Weather Research Forecasting model-Hydrological
modeling system) to explore the influence of rainfall rates, topography,
soil types on the re-infiltration process. However, none of these
studies have considered the implication of re-infiltration to
hydrodynamic studies, where the overland flow is driven by the 2D
Shallow Water Equation (SWE) instead of 1D routing. To do so, we can
obtain a more realistic view of how re-infiltration plays a role in
flood simulations.
During extreme flood events, the infiltration process is often
disregarded because the infiltration rates are relatively low compared
to excess rainfall rates. Yet, some studies claim that the infiltration
process is critical to determine flood wave propagation, such as arrival
and dissipation, especially in flat plain or regions with highly
permeable soil media (Corradini et al., 2002; Mahapartra, et al., 2020;
Nahar et al., 2004; Li et al., 2021b; Woolhiser, Smith, & Giraldez,
1996). A hydrodynamic model without infiltration is likely to
overestimate flood depth (Kim et al., 2012; Li et al., 2021b; Ni et al.,
2020). Nevertheless, it still remains unclear, or at least not as clear
as infiltration, whether re-infiltration is essential for H&H models in
extreme flood events. In other words, whether it is worth encapsulating
such a scheme in modern flood simulation frameworks. To our knowledge,
few studies have attempted to answer this question under the context of
extreme flood events. Moreover, further questions can arise as to what
the determining factors are during such a process and how it interacts
with both flood magnitude and dynamics. In light of these
questions, the objectives of this study are to explore 1) the
effectiveness and importance of the re-infiltration scheme to an H&H
model, 2) the contributing factors to the differences between with and
without re-infiltration, and 3) whether and to what extent the
re-infiltration process can help improve flood inundation mapping and
prediction of extreme events. We first test its effectiveness and
importance on a 100-year design extreme rainfall event during a
sensitivity test and then apply it to a real case study – Hurricane
Harvey – to validate the efficacy. It is anticipated to provide
insightful information for model developers and researchers to
understand the importance of the re-infiltration process to flood
modeling. In this study, we also release our latest development of
CREST-iMAP V1.1, which features a two-way coupling and re-infiltration
scheme on top of the previous version (Chen et al., 2021; Li et al.,
2021b).
The rest of this paper is structured as follows. Section 2 introduces
the study area and necessary datasets for the model setup, followed by
experimental designs. Section 3 presents the results from the
sensitivity test and the Hurricane Harvey event. Section 4 discusses
limitations of this study as well as recommendations for input data and
future model development. At last, Section 4 concludes the main findings
of this study.