# A Systematic Review: To Increase Transportation Infrastructure Resilience to Flooding Events
## 3 Results  
As aforementioned in the Materials and Methods section, a final 133 studies were investigated to review the studies conducted to increase transportation infrastructure resilience to flood events. Tables 2-7 present these 133 studies including the title, year of publication, authors, country of study area conducted, and the journal published within for each category. All studies are listed in a publication year order. In case a study did not apply to a specific area, the country of study area was presented as N/A. Table 2 represents the 17 studies within research category A, regarding flood risk correlated to transportation infrastructure [26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42]. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Study** & **Study Title:** & **Year** & **Authors:** & **Country of** **Study Area:** & **Journal:** \\
**Number:** & & & & & & \\ \hline \multirow{3}{*}{1} & Flood analysis and hydraulic competence of & & & & & \\  & drainage structures along Addis Abaq light & 2021 & [PERSON], [PERSON], et al. & Ethiopia & _Journal of Environmental Science_ \\  & rail transit [26] & 2021 & [PERSON], et al. & Bangladesh & _Geoscience Frontiers_ \\ \hline \multirow{3}{*}{2} & Flood risk assessment using the CV-TOPSIS & & & & & \\  & method for the Belt and Road Initiative: an & 2020 & [PERSON], et al. & Asia & _Ecosystem Health and_ _Sustainability_ \\  & empirical study of Southeast Asia [28] & & & & \\ \hline \multirow{3}{*}{4} & Assessing flood probability for & & & & \\  & transportation infrastructure based on & & & & \\  & catchment characteristics, sediment & 2019 & [PERSON], et al. & Sweden & _Science of The Total Environment_ \\  & connectivity and remotely sensed soil & & & & \\  & moisture [29] & & & & \\ \hline \multirow{3}{*}{5} & A Method for Urban Flood Risk Assessment & & & & \\  & and Zoning Considering Road & 2019 & [PERSON], et al. & China & _Sustainability_ \\  & Environments and Terrain [30] & & & & \\ \hline \multirow{3}{*}{6} & Changes concerning commute traffic & & & & \\  & distribution on a road network following the & 2019 & Borowska-Stefanska, & Poland & _Transportation Research Part D:_ \\  & occurrence of a natural disaster—The & 2019 & [PERSON], et al. & Transport and Environment_ \\  & example of a flood in the Mazovian & & & & \\  & Voivodeship (Eastern Poland) [31] & & & & \\ \hline \multirow{3}{*}{7} & Analysis of Flood Vulnerability and Transit & & & & \\  & Availability with a Changing Climate in & 2019 & [PERSON], et al. & USA & _Transportation Research Record:_ \\  & Harris County, Texas [32] & & & & \\ \hline \multirow{3}{*}{8} & Flood risk analysis for flood control and & & & & \\  & sediment transportation in sandy regions: A & 2018 & [PERSON], et al. & China & _Journal of Hydrology_ \\ \cline{1-1}  & case study in the Loess Plateau, China [33] & & & & \\ \hline \end{tabular}
\end{table} 
Table 2: 17 Studies of category A. Within category A, which is the flood risk analysis studies, hydrological and/or hydrodynamic modeling were often utilized to analyze flood depths. Geospatial tools were then used to display these depths which translated to flood risks. [PERSON], et al. (2014) used a hydrological model (HEC-HMS) to determine how land use and land cover change affected a sub-catchment and influenced the flood risk [43; 44]. [PERSON], et al. (2021) conducted hydrological analysis using HEC-HMS along several roadways in Addis Ababa City, Ethiopia. Geospatial tools then helped to display the physical aspects of elevation data [26; 44]. [PERSON], [PERSON], et al. (2018) developed a location intelligence system, extended from the Pluvial Risk Flood Assessment Tool. It included spatial and temporal pluvial flood analysis, elevation, and hydrologic analyses. This was used to find runoff depths and distribution of flood risks in Wroclaw, Poland [34]. [PERSON], [PERSON], et al. (2011) investigated flood risk in Jutland, Denmark with the 1-D hydrodynamic model, [PERSON] [41; 45].