2.1 Hydraulic model

One-dimensional (1D) hydraulic models have been widely used in the simulation of urban drainage systems. First, 1D is appropriate for simulating the physical phenomena of flow in urban drainage systems when the cross-sectional size is much smaller than the length of the system's pipeline (Akan & Houghtalen, 2003). This is because the variation of the vertical flow has little effect on the flow in the sewers. In addition, 1-D in-pipe flow models tend to be “relatively easy to set up, calibrate, and interpret” (Seyoum et al., 2012) than most two-dimensional (2D) and three-dimensional (3D) models for simulating. Establishing 2D and 3D simulation models is a complex procedure, requiring a resource-intensive time for setting. Finally, developing 1D flow simulation software is often seen as more convenient than 2D or 3D models. Therefore, simulation according to 1D flow models such as MOUSE or SWMM is widely applied in calculating and designing drainage systems and urban flooding.

However, some disadvantages exist in urban drainage simulation utilizing 1D modeling. The most important thing about the 1D model is the difficulties in simulating physical interaction between water flowing in the drainage and flow on the surface (Seyoum et al., 2012). In addition, 1D models are more likely to ignore essential impact factors when simulating flows in flooded areas, such as bilateral or lateral diffusion and changes in the soil surface during simulation (Kuiry et al., 2010; Seyoum et al., 2012). Thus, coupling a 1D model to simulate a stream in a sewage system and a 2D flow for surface runoff is a possible solution to identify our flood hazard zones in the interested areas. This application is confirmed in many studies and is widely accepted (Leandro et al., 2016). However, for the scope of this study, 1D models are suitable because they only simulate the impact of flow rate changes in urban stormwater and highlight the difference in the locations prone to flooding.

Among the types of models, the Stormwater Management Model (SWMM) is one of the widely used models to simulate urban drainage problems in academic and engineering communities (Akan & Houghtalen, 2003). SWMM presents competence in dealing with a wide range of technical and management problems in consulting and research. For example, the model is used to assess the impacts of climate (Huong & Pathirana, 2013; Niazi et al., 2017), evaluate the influence of quasi-natural measures in urban flow management (Qin et al., 2013; Tobio et al., 2015) or assess the quality of water generated by rain in urban areas (Akan & Houghtalen, 2003). In addition, SWMM allowing users to evaluate freely from the internet tends to support research institutes and individual users. Moreover, individual users can quickly and easily master the model to support their work.

Therefore, this study will employ hydrology and hydraulic processes in drainage systems using SWMM. Key stormwater characteristics, including notes and pipelines, will be simulated for each catchment in the area. In addition, other considerations, such as the basin's penetration, slope, and shape, should also be described reflectively to improve simulation accuracy and reduce the uncertainty of results. The model parameters follow suggestions from national standards and experiences in related processes. Figure 1 represents the process of assessing the impact of urbanization and climate change for Tamki urban area.

2.2 Research area

The city of Tamky is the research area for this study. The city has had severe flooding recently, which caused extensive damage to people's lives and socioeconomic production activities. Total estimated damage due to floods in December 2018, October 2020, and October 2021 (Figure 2), caused VND 150 billion, VND 49.5 billion and VND 17.1 billion, respectively. In addition, the city is one of the impacted areas in the central region of Vietnam, and the city urbanization process has recently occurred. As a provincial city, Tam Ky's urbanization process took place rapidly from a town (Type III urban area) in 2006 to a provincial city (Type II city) in 2016 and planned to urban Type I city standard by 2030. According to statistics and satellite images, from 2016 up to now, the inner city of Tam Ky city and its vicinity have been invested in developing vast technical infrastructure, such as traffic routes and bridges, embankment, industrial park, new urban areas along the river with relatively high construction density.

Due to climate change, Tamky is becoming more vulnerable to urban flooding. Flow from the stormwater management system in the city directly discharges to three main rivers, Ban Thach, Tam Ky, and Truong Giang, before reaching East Sea through Cua Lo and An Hoa estuaries, which are predicted to rise due to climate change. Therefore, stormwater flow may be obstructed, reducing discharge capacity throughout the system. In addition, the extreme precipitation in Tamky can increase by over 10% by the end of the century.

In detail, a model for a drainage system in the An Ha Residential area was established to represent the whole of the city (Figure 3). The area has most characteristics of the urbanization process of Tam Ky. Many floodplain areas mostly changed into residential areas with entire infrastructure, some areas are on the process to entirely becoming urban areas and planned to be converted into urban areas. According to these characteristic, the research area are divided into four subareas (Figure 3 and Table 1) for investigating and assessment potential influences of altering urban surface and precipitation in urban flooding. In the context of climate change, the Urban Area is at risk of severe flooding when it has to cope with a significant increase in extreme rainfall. The region is divided

2.3 Climate change scenario

2.4 Climate change scenarios

Due to climate change in the central region, extreme rainfall may increase considerably. The change statements examined in the IPCC (2013) report predict that rainfall in central the region is projected to increase by 1%–7% by 2050 compared with average historical data from 1986 to 2005 in the RCP4.5 average emissions scenario. Precipitation may increase by 5% by the end of the 21st century (2%–10%). The observations for the Vietnam region also indicate an increase in the number of rainy days in a year and an increase in extreme rainfall for the rest of the century.

In addition, regional climate models developed for the climate change scenarios of Vietnam have shown detailed projections of annual precipitation and rainy season changes for future climate in the interested research area (Table 2). In the RCP 8.5 scenarios, the rainfall at Tam Ky station in 2048–2065 could rise by 11.8% over the winter of 1984–2005 (Raghavan et al., 2017). Meanwhile, following the average GHG emission scenario, RCP 4.5 is expected to be higher than the forecast RCP 8.5. During the rainy season (winter), precipitation would increase by 12.6% in 2050 and 54% in 2010 compared with the historical baseline.

2.5 Urbanization scenario

Climate change scenarios will combine with the urbanization scenarios, which are built based on the planning of Tam Ky over the period. In addition, images and interpretations from satellite aerial images help determine the period as well as the degree of urbanization of the area (Figure 4). Each scenario is represented in the mathematical model through land cover and topographic change parameters. The urbanization process in Tam Ky has taken place firmly since 2013. Therefore, the city's condition in 2011 is selected to demonstrate before the urbanizing scenario, while 2021 and 2030 account for partly and wholly urbanized, respectively.

2.6 Design rain

In recent years, the An Ha urban area has suffered severe urban floodings, such as in 2013, 2018, and 2021. These events have significantly affected people's lives and socioeconomic populations. The selection of rain to simulate will affect the assessment results of urban drainage capacity and show the interaction process of the basin for different rainfall patterns. This study uses rainfall in 2018 and 2021 to simulate the scenarios (Figure 5). Both rainfall events have a concentrated shower period from 50 to 60 h with approximately the same intensity. The most significant difference is when the two peaks of the rain appear. While in 2018, the two peaks are further apart than in 2021, and the latter is higher than the former. Meanwhile, the rain in 2021 has a higher peak of the previous rain than the latter's peak. The analysis and evaluation of two rainfalls will identify the rain patterns and the process of their influence on the basin.

Both rainfall events have a concentrated shower period from 50 to 60 h with approximately the same intensity. The most significant difference is when the two peaks of the rain appear. While in 2018, the two peaks are further apart than in 2021, and the latter is higher than the former. Meanwhile, the rain in 2021 has a higher peak of the previous rain than the latter's peak. The analysis and evaluation of two rainfalls will identify the rain patterns and the process of their influence on the basin.

2.7 Calibrate the model

A temporary station is established, measuring water depth to calibrate the simulation model's parameter (Figure 6). This activity will cover limitation in water level monitoring in urban drainage systems in the research area. Therefore, the simulation and observation of water depth at the monitoring maintenance hole for an event happened from 19 to 23 h on October 8, 2022. With R2 and NSE indexes of 0.816 and 0.76, respectively, the simulation result has shown a strong correlation to the observation of water depth (Figure 7). It can lead to the conclusion that the set-up model is suitable for simulating alternative scenarios.

3.1 Results based on urbanization processes

The simulation results show the influence of urbanization on flow formation in the study area. They are shown by the flood peak appearing later than the urbanization scenarios. In the early stages of runoff formation, when the ground is not saturated with water, the simulation results show that a large amount of discharge has decreased due to allowing precipitation to infiltrate the soil. However, the efficiency of impermeable aquifers decreases rapidly when the soil is saturated with water, and a small amount of runoff is also reduced but not significantly compared to the period before the soil saturation.

Figure 8 shows the effectiveness of permeable surfaces in reducing total flow generated from subcatchments by representing the interaction between simulated catchments in distinctive urbanization rates and flow through flow per area unit. Subcatchments with low urbanization rates fluctuate less than highly dense urban areas, even in high precipitation intensities. Unit flow generated from a unit of area is more significant in Zone 1 and Zone 3, which have higher urbanization rates than the others, with the highest value reaching 0.25 m³/ha. At the same time, the amount for Zone 4 is around 0.15 m³/ha. The consequence results from abstracting a large amount of outflow and latency in flow concentration in pervious land covers. In contrast, it confirms the increased risk of inundation in areas with high urbanization in the research area. In 90 min of time-lapse, the flow produced from catchments in Zone 4 is higher than the other due to latency caused by slow flow rate concentration in flow generation.

Areas that are not firmly urbanized can reduce the risk of flooding compared with urbanized areas when there are short-term high-intensity rains. When the rains last beyond the soil saturation point, the difference is not significant. However, when embedded in the entire system, reducing the amount of concentrated water simultaneously significantly affects the flow concentration. The peak formation period also shows urbanization's influence on the flow formation process in urban areas. Consequences of urbanization. In an area with a high degree of urbanization, the time when flood peaks and flows appear.

3.1.1 The influence of rain patterns

With two different rain patterns, the influence of rain patterns on the process of flow formation in the basin, primarily when urbanization occurs. Figure 9 shows the total amount of recharge seepage losses in subbasins with different percentages of impermeable soil. The graph shows that the less urbanized subbasins will have a large amount of rainwater infiltrating the ground, reducing the rate of runoff concentrated into the system. This ratio decreases as the amount of urbanization increases. The graph also shows that the amount of water infiltrating into the ground according to the pattern of the rain in 2018 is more unfavorable than in 2021, when the amount of infiltration loss is more extensive.

The variation between the amount of water recharged into groundwater between two distinctive rainfall decreases rapidly in areas with urbanization rates over 70%. This phenomenon may refer to effectiveness reduction in flow abstraction that may not depend on rainfall characteristics in highly urbanized areas. Another argument explains the reduction is the exchange of runoff between impervious and pervious areas in the catchment. In a high urbanization rate subcatchment, infiltration areas are more likely to receive potentially enhanced flowrate (Figure 10) from the over and easily reach saturated easy point compared to the low impervious area and lead to a reduction in the effectiveness recharge generated flow.