## 4 Results  
### AHP-GIS Flood Risk Mapping  
To address the first research question, the relative weights of six hydrometeorological factors associated with flood risk were estimated. The calculated CR value in this evaluation was approximately 0.0930 (<0.1, which is acceptable). According to the results in Table 2, runoff, land use, and maximum daily rainfall have the highest weight scores, indicating that these are the most common causes of floods in Ayutthaya Province. Slope exhibits the lowest AHP weight. All six hydrometeorological factors (Figure 2) and the proposed weights of each were used to generate a flood risk map by applying the overlay technique. As depicted in Figure 3a-e, the analysis reveals that approximately 2489.26 km\({}^{2}\) of Ayutthaya Province is at risk of flooding, of which approximately 17, 36, and 44% of areas can be categorized as very high (Figure 3b), high (Figure 3c), moderate (Figure 3d), and low-risk areas (Figure 3e), respectively. Geographically, Phranakhon Si Ayutthaya (PNSA), Uthai, Bang Pa-in, and Wang Noi exhibit the highest flood risk when considering both high- and very high-risk areas. Interestingly, almost the entire PNSA region (99%), where most of the population resides, is considered to be at a high risk of flooding. The results of the current analysis are somewhat consistent with the report on the flood situation by the Ayutthaya Disaster Prevention and Mitigation Office (2019) [44], with PNSA, Bang Pa-in, Sena, and Bang Ban being identified as flood hazard areas in Ayutthaya Province. In this study, Sena presents the highest proportion of areas under moderate flood risk (78%), whereas Bang Ban demonstrates a combination of risk flood areas, with 12% being very high, 55% high, 32% moderate, and 1% low risk.  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Flood Incident** & **Policies/Strategies** & **References** \\
**Management Response Type** & \(\bullet\) & Flood risk mapping to define vulnerable areas & [42] \\ Pre-flood preparedness measures & \(\bullet\) & Flood forecasting and warning information & [42] \\ Forecasting and warning & \(\bullet\) & Insurance and financial support & [42] \\ Flood lesson plan & \(\bullet\) & Flood training & [42] \\ Equitable provision of essential services & \(\bullet\) & Provision of safe drinking water & [43] \\ Flood preparation action & \(\bullet\) & Medical preparedness to minimize health impacts & [43] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Survey questions associated with flood incident management strategies and action preparedness.  
Figure 2: Six thematic-layer factors of GIS flood risk maps.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline \multicolumn{1}{c}{**Factors**} & \multicolumn{1}{c}{**Sources of Data**} & \multicolumn{1}{c}{**Weighting**} & \multicolumn{1}{c}{**Rank**} \\ \hline Run-off (m\({}^{3}\)/s) & Average annual run-off during 1989–2020, Royal Irrigation Department, & 0.305 & 1 \\  & Thailand & & \\ \hline Land use & Land Development Department & 0.274 & 2 \\ \hline Daily maximum rainfall (mm/d) & Annual maximum daily rainfall during 1989–2020, Thai Meteorological & 0.211 & 3 \\  & Department & & \\ \hline Road density (km/km\({}^{2}\)) & Department of Environmental Quality Promotion, Thailand Institute for Scientific and Technological Research (TISTR) & 0.106 & 4 \\ \hline Past flood events (years) & All previous floods during 2005–2019, Geo-Informatics and Space Technology Development Agency, TISTR & 0.074 & 5 \\ \hline Slope (\%) & Topographic maps at the scale 1:50,000 and Royal Thai Survey Department, & 0.029 & 6 \\  & Office of Natural Resources and Environmental Policy and Planning & & \\ \hline \multicolumn{4}{c}{CR = 0.0930.} \\ \end{tabular}
\end{table}
Table 2: Spatial data and weighted ranking of all factors influencing flood risk in Ayuthaya Province, Thailand.  
Figure 3: Flood risk maps of Ayuthaya based on (**a**) AHP-GIS and satellite images and areas under (**b**) very high, (**c**) high, (**d**) moderate, and (**e**) low risk.