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\begin{document}

\title{Influence of Forcing Conditions on Total Water Level Prediction and
Spatiotemporal Patterns in Delaware Bay, USA}



\author[1]{David Fernando Muñoz Pauta}%
\author[2]{Dongxiao Yin}%
\author[1]{Jiannan Tian}%
\author[3]{Roham Bakhtyar}%
\author[4]{Kyle Mandli}%
\author[5]{celso ferreira}%
\affil[1]{University of Alabama}%
\affil[2]{Louisiana State University}%
\affil[3]{U.S. Army Corps of Engineers}%
\affil[4]{Columbia University in the City of New York}%
\affil[5]{George Mason University}%


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  \date{June 14, 2024}


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\begin{abstract}
Accurate forecasts of total water level (i.e., a combination of tides,
surge, wave and freshwater components) is imperative for stakeholders
and federal agencies to adopt strategies for potential flooding hazards
in a timely-manner. In that regard, the National Water Center in
partnership with several federal agencies have been providing forecast
services to the United States since 2017. However, the complex
interaction of dynamical forcing conditions among other factors (e.g.,
anthropogenic activities, land cover change, etc.) reduce the National
Water Model's (NWM) ability to provide accurate Total Water Level (TWL)
prediction in Coastal Transition Zones (CTZs). In this study, we use an
existing inland to coastal model coupling framework (i.e., NWM, HWRF,
Delft3D-FM and ADCIRC) to analyze the influence of dynamical forcing
conditions (e.g., local wind, surge and river discharge) on TWL
prediction in Delaware Bay, USA. In addition, we quantify the
contribution of each component in TWL for Hurricanes Isabel and Sandy
based on a systematic set of scenarios generated in Delft3D-FM. It is
revealed that in both hurricanes, storm surge-induced water level is the
main contributor to TWL followed by astronomical tides. River discharge
induced-water level is rather small compared to the other components.
Analyses of spatial variation of TWL as well as temporal variation of
error in prediction suggest that wind forcing plays a key role in TWL
prediction followed by river discharge. Moreover, our results suggest
that the wind module of Delft3D-FM greatly improves the model
performance at TWL peak when compared to the other forcing.%
\end{abstract}%



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