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\begin{document}

\title{Improving WRF-Hydro Runoff Predictions of Heavy Floods Through Higher
Spatio-Temporal Sea Surface Temperature Products}



\author[1]{Berina Kilicarslan}%
\author[1]{ismail yucel}%
\author[1]{Heves Pilatin}%
\author[1]{Eren Duzenli}%
\author[2]{Mustafa Yılmaz}%
\affil[1]{Middle East Technical University}%
\affil[2]{Orta Dogu Teknik Universitesi}%


\vspace{-1em}



  
  \date{March 13, 2025}


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\begin{abstract}
In this study, the impact of spatio-temporal accuracy of four different
sea surface temperature (SST) datasets on the accuracy of the Weather
Research and Forecasting (WRF)-Hydro system to simulate hydrological
response during two catastrophic flood events over Eastern Black Sea
(EBS) and Mediterranean (MED) regions of Turkey is investigated. Three
time-varying and high spatial resolution external SST products (GHRSST,
Medspiration, and NCEP-SST) and one coarse-resolution and invariable SST
product (ERA5- and GFS-SST for EBS and MED regions, respectively)
already embedded in the initial and boundary condition dataset of WRF
model are used in deriving near-surface weather variables through WRF.
After the proper event-based calibration performed to the WRF-Hydro
using hourly and daily streamflow data of small catchments in both
regions, uncoupled model simulations for independent SST events are
conducted to assess the impact of SST-triggered precipitation on
simulated extreme runoff. Some localized and temporal differences in the
occurrence of the flood events with respect to observations depending on
the SST representation are noticeable. SST products represented with
higher temporal and spatial correlation revealed significant improvement
in flood hydrographs for both regions. The higher spatial and temporal
correlations of GHRSST dataset show RMSE reduction up to 20\% and
increase in correlation from 0.3 to 0.8 with respect to the invariable
SST (ERA5) in simulated runoffs over the EBS region. The error reduction
with GHRSST reached 35\% after the calibration of hydrological model
parameters compared to not calibrated model. The use of both GHRSST and
Medspiration SST data characterized with high spatiotemporal correlation
resulted in runoff simulations exactly matching the observed runoff peak
of 300 m3/s by reducing the overestimation seen in not calibrated runs
over the MED region.%
\end{abstract}%



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