## 3 Results and Analysis
### Quantitative Impact of Urbanization on Compound Floods  
#### 3.2.1 Land Subsidence  
When evaluating flood risks in future climate change scenarios, it is essential to consider land subsidence issues [68]. Land subsidence can result from groundwater extraction, natural consolidation of alluvial soil, building loads, and tectonic subsidence [69]. For example, Jakarta is primarily affected by groundwater extraction and has been plagued by floods. The land subsidence rate in some areas can reach up to 20-28 cm per year, and the cumulative subsidence in Tokyo has reached nearly 5 m (Figure 3) [70]. By 2025, land subsidence in Manila is expected to increase the relative SLR by 0.4 m [71]. Similarly, Ho Chi Minh City (HCMC) is sinking rapidly, with 65% of its area now lying 1.5 m below average sea level, making it one of the most vulnerable cities to SLR-induced flooding [72].  
To develop strategies to address land subsidence and reduce flood losses, it is first necessary to assess the extent of increased flood risk caused by land subsidence. [PERSON] et al. (2016) [73] applied the Delft3D model to analyze the impact of extreme high tide, SLR, and land subsidence on Jakarta, Indonesia. Their results indicated that the flood-prone area would expand by 110.5 km\({}^{2}\) by 2050, with 88% of this increase attributed to land subsidence. [PERSON] et al. (2018) [38] used the MIKE 21 model to compare the individual and combined effects of SLR, land subsidence, and water depth changes on Shanghai's coastal  
Figure 3: Cumulative maximum land subsidence in major cities in the Asia-Pacific Region [70].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference** & **Study Area** & **Output** & **Dimensions** & **Numerical Model** \\ \hline [PERSON] et al. [65] & Gurugram City, India & Total runoff volume and total flood volume & 1D & SWMM \\ [PERSON] et al. [66] & Brisbane, Australia & Water level, discharge, and velocity & 2D & MIKE \\ [PERSON] et al. [67] & Ho Chi Minh City, Vietnam & Flood depth and flood & 2D & TELEMAC-2D \\ [PERSON] et al. [40] & New York City, USA & Flood inundated areas & 2D & LISFLOOD-FP \\ [PERSON] et al. [63] & Gin, Sri Lanka & Discharge, inundated extents, and water depths & 1D + 2D & MIKE 11 + MIKE21 \\ [PERSON] et al. [64] & Guangzhou, China & Flooding flow, inundation area, and inundation depth & 1D + 2D & LISFLOOD-FP + SWMM \\ \hline \hline \end{tabular}
\end{table}
Table 3: 1D, 2D, and combined 1D + 2D numerical models for extreme rainfall under climate change.  
areas for 2030 and 2050, finding that by 2050, land subsidence would be the dominant factor influencing coastal flood changes. Similarly, [PERSON] et al. (2021) [74] investigated extreme water levels in Semarang, Indonesia, using a grid-based inundation model (LISFLOOD-FP) to simulate flood inundation under scenarios of land subsidence and SLR in 2050. Their simulation revealed that land subsidence might be the leading reason that coastal flooding is getting worse. The scenario with SLR projection and subsidence interpolated based on the local measurements in the research area by 2050 showed the highest flood volume with an increase of 1,483,251 m\({}^{3}\) and a flood area increased by up to 1.5 km\({}^{2}\) (6.8% increase).