Abstract
Ca River is one of the largest rivers in Vietnam. The river provides water, electricity, and navigation for millions of people living along the banks. Besides these great benefits, the river also poses many potential risks for people. In the case of flooding, this river can cause terrible damage, especially in the case of dike breach. Therefore, this article, by combining a field survey and mathematical simulation, has been conducted to present the results of the dike breach for the La Giang dike of Ca river, in Ha Tinh province, Vietnam. Via the field survey, potential dike breach locations were specifically identified, which helps minimize the number of calculation scenarios. The mathematical model was calibrated and validated with large floods in the area. The results from the mathematical model show that the model is consistent with the observation data, with the Nash index at good to very good levels. Based on the data, a series of simulations was performed to assess the dike breach consequences. In each case, the study provided details on the inundation area, the number of affected residents and the length of flooded road for each inundation level by administrative unit. Based on the calculated results, the degree and scope of consequence varied depending on the locations of the dike breach. The results of the study are the foundation for the building of a local database of flood and storm control. This is very useful information for the decision-makers to establish different response plans for different emergency cases.
HIGHLIGHTS
The study conducted a survey to identify the dike break potential locations, which reduces the scenarios.
The study established a model to simulate hydraulic regimes with high reliability.
The results show that breach time development plays an important role.
The study provides detailed quantitative dike breach results, which is important information for the development of a disaster prevention plan for the study area.
INTRODUCTION
Floods are a common type of natural disaster in the world. Damage caused by floods is huge (The Central Steering Committee for Disaster Prevention and Control 2018, 2019, 2020, 2021). One of the current solutions to minimize the impact of floods is the construction of flood-resistant dikes. This measure is remarkably effective, but it increases the risk to people in the protected area. In case the dike breaks, the damage to the residents in the protected area will be beyond imagination (Apel et al. 2009). Although the consequences of a dike breach are massive, the risk of occurrence is very high and Vietnam is not an exception. Most dikes in major rivers in Vietnam have been built for a long time. In spite of regular supervision and repair, the deterioration of the dikes is inevitable. According to Ministry of Agriculture and Rural Development of Vietnam (2023), there are currently 288 key locations on the main dikes. Most of these locations are often under the influence of flow or are built on weak geological foundations. This leads to phenomena such as erosion, and subsidence, causing damage to the dike. It is urgent to have solutions to reduce the damage caused by floods, especially in the context of the increasingly obvious impacts of climate change.
The solution to this problem often lies in dike protection. More specifically, flood control solutions in general and dike protection solutions in particular are often classified into two categories: structural solutions and non-structural solutions. Each type of solution has its own advantages and disadvantages. Structural solutions are often effective immediately but normally have high cost. Moreover, under increasingly severe disaster conditions, to completely control natural disasters by using structural solutions is often not feasible. In contrast, non-structural solutions such as natural disaster warnings, development of emergency response plans, and raising awareness for the community are often adaptive. A great advantage of such solutions is that they are suitable for countries with limited economic conditions like Vietnam. Among these proposed solutions, developing emergency response plans is an effective solution that has been applied in many parts of the world. In order to develop an effective response plan that meets the actual needs of the local area, detailed information about the impacts and affected subjects is essential. As a result, assessing the consequences of floods, especially in the case of a dike breach, is an urgent need of the locals.
Flood has been studied extensively in Vietnam, and the Ca River is not an exception (Tran et al. 2014; Nguyen et al. 2020). However, studies of flood as a result of dike breaches are still limited. In fact, research on dike breaches is a challenge. First, a dike breach has a very complex mechanism. According to ASCE (2011) in the case of a dike breach, the water level outside the river will remain or decrease very little. Even when the outside and inside water levels are equal, the size of the breach continues to increase. Even when the outside and inside water levels are equal, the size of the breach continues to increase. Besides, the different locations of the breach in the dike will also cause different consequences (Bomers 2021). However, this was not mentioned in many previous studies when the breach location was often assumed to be at a specific location (Zolghadr et al. 2011; Viero et al. 2013). Therefore, the study of different consequences resulting from different breach locations on a dike is extremely vital, it provides important information for flood prevention and mitigation. However, it is not feasible to study all possibilities along a long dike. A more practical approach is required, which is a huge gap in research.
Approaches to dike breach are commonly divided into three categories, namely parametric models, mathematical models, and experimental and mathematical integrated models. In parametric models, studies are often simplified by calculating breach parameters using empirical formulas. For example, Nagy (2006) determined the breach length based on 2,200 records of the Carpathian basin. The research results presented a correlation equation between the length of the breach and the height of the dike. Meanwhile, Danka & Zhang (2015b) built a multivariate correlation equation to determine three parameters, namely the maximum discharge through the breach, breach length, and breach depth. The main advantage of empirical formulas is their simplicity, but the results of the formulas only give the maximum values and do not determine the flow process through the breach. The second approach is mathematical models, which build the development process of the breach via time or the rate of soil erosion. These statistics are defined as the input for mathematical models. In this approach, the physical processes are not modeled. Instead, the water flow through the breach is calculated using simple fluid dynamics equations, such as flow through the weir and orifice. They do not improve the accuracy compared to the parametric model approach, but the breach flow hydrograph can be determined. Some case studies following this approach can be mentioned (Huthoff et al. 2015; Tadesse & Fröhle 2020; Bomers 2021), which provide promising results. The third approach is to combine both mathematical and experimental models (Schmocker & Hager 2009; Tadesse et al. 2017; Liu et al. 2019). The main advantage of this approach is the increased accuracy. The breach development process in this approach takes several factors into account, such as erosion, sediment transport, and slope stability. Besides, the calculated results from the mathematical model are verified with physical experiments. However, studies in this approach often take a lot of time, and effort, and are not flexible in the calculation cases. Which approach to choose depends on the type of analysis, data conditions, and simulation scale. In the case of a large-scale river basin, the approach using mathematical models is proved to be most appropriate. It can be flexible to design many scenarios to meet the requirements of disaster prevention.
This paper will present the results of the study on floods caused by the breach in the research area. In this study, the field survey method was conducted in combination with mathematical models to simulate floods for a series of dike breach scenarios at different locations. The results of the study aim to find the most feasible dike breach scenarios in the La Giang dike. Based on the simulation results, the study has made quantitative assessments of the number of people as well as detailed statistics on the flooded area by different land users. The results of the study will help the authorities have a basis to build response scenarios in emergency cases.
METHODS
The study started by conducting a field survey along the La Giang dike. During the survey, the study collected information on the current status of the dike as well as high-risk locations. The information includes the erosion status of the dike, elevation along the dike, as well as information on the geology of the dike. These are all very important information to determine the high-risk locations of dike breaches. In addition, the study collected information from local officials who directly manage the dike, which increases the reliability of identifying potential locations of dike breaches.
At the same time as the survey, the study also collected data for the hydraulic simulation. In this study, 96 river cross-sections for the Ca River system were collected. This is the most important data to present the channel's current condition. The floodplain topography data were created from a topography map 1/10,000 scale which was published by the Ministry of Natural Resources and Environment. Hydrometeorological data from all stations, which are in the national monitoring system, in the system (Figure 1) were collected and studied. These data were not only used to calculate the boundary for the hydraulic model but also used for model calibration and verification. All data collected in the study have clear origins, ensuring the reliability of the model establishment.





The calculated and observed water levels in the flood event 2019: (a) Nam Dan; (b) Linh Cam; and (c) Cho Trang.
The calculated and observed water levels in the flood event 2019: (a) Nam Dan; (b) Linh Cam; and (c) Cho Trang.
The calculated and observed water levels in the flood event 2020: (a) Nam Dan; (b) Linh Cam; and (c) Cho Trang.
The calculated and observed water levels in the flood event 2020: (a) Nam Dan; (b) Linh Cam; and (c) Cho Trang.
Based on the calibrated and verified model, the study simulated flood scenarios. In fact, the existing dike can withstand the dike breach with the design frequency P = 0.6%. In order to test this hypothesis, the flood scenario of frequency P = 0.6% was simulated. This is considered as the based scenario to compare with other dike breach scenarios. Then, dike breach scenarios were simulated for each identified location. In this study, the authors also evaluated the impact of the breach development time on the maximum discharge through the breach and the inundation area caused by the dike breach. The assessment aimed to minimize the uncertainty of unwarranted factors such as the breach development time.
Based on the results of hydraulic calculations, inundation maps corresponding to the scenarios were built corresponding to each scenario. Using spatial analysis techniques in GIS, the inundation area as well as the number of affected households in each scenario were also determined. The study had detailed information for each flood level and each administrative unit. This will be important information for authorities in implementing rescue operations as well as in building evacuation plans in emergency conditions. Also, this is a premise for building a large database for further research such as artificial intelligence applications.
RESULTS AND DISCUSSION
Dike breach scenarios
Based on the identified locations, the study simulated a series of scenarios. The first scenario simulated a design flood of La Giang dike. This was a based scenario. Subsequent dike breach scenarios are compared with based scenarios to independently assess the consequences of a dike breach. For each dike breach location, the breach development time was changed from 1 to 24 h, respectively, to evaluate the sensitivity. 24 h is also the time to maintain a high flood level in the design flood.
In Table 1, the data on the dike size were determined from the actual measurement data in the area where the dike was located. The parameters m and t were determined based on the current condition of the dikes. For each condition of the specific dike, the parameter of breach form f was also determined via the field survey. With the assumption that the breach did not develop through the foundation of the dike, the study presents that if the calculated breach depth is greater than the dike height, the depth will be considered equal to the dike height. The calculation results of breach parameters are summarized in Table 1.
The dike breach parameter
Location . | h (m) . | w (m) . | m . | t . | f . | Breach length (m) . | Breach depth (m) . | Breach development time (h) . |
---|---|---|---|---|---|---|---|---|
Tung Anh | 7.0 | 35.5 | 0.42 | 0 | 0.81 | 111 | 7.0 | 1–24 |
Duc Dien | 6.6 | 37.5 | 0.42 | 0 | 1.21 | 149 | 6.6 | 1–24 |
Nga Song | 6.8 | 38.0 | 0.42 | 0 | 0.74 | 146 | 6.8 | 1–24 |
Location . | h (m) . | w (m) . | m . | t . | f . | Breach length (m) . | Breach depth (m) . | Breach development time (h) . |
---|---|---|---|---|---|---|---|---|
Tung Anh | 7.0 | 35.5 | 0.42 | 0 | 0.81 | 111 | 7.0 | 1–24 |
Duc Dien | 6.6 | 37.5 | 0.42 | 0 | 1.21 | 149 | 6.6 | 1–24 |
Nga Song | 6.8 | 38.0 | 0.42 | 0 | 0.74 | 146 | 6.8 | 1–24 |
Sensitivity breach development time analysis



Sensitivity breach development time analysis: (a) discharge and (b) inundation area.
Sensitivity breach development time analysis: (a) discharge and (b) inundation area.
Inundation mapping and consequence assessment
The inundation area in the base scenario
Province . | District . | Inundation area (ha) . | |||||||
---|---|---|---|---|---|---|---|---|---|
< 0.5m . | 0.5–1 m . | 1–1.5 m . | 1.5–2 m . | 2–2.5 m . | 2.5–3 m . | > 3 m . | Sum(ha) . | ||
Ha Tinh | Duc Tho | 323 | 343 | 397 | 543 | 801 | 867 | 3,520 | 6,793 |
Hong Linh | 8 | 6 | 5 | 4 | 5 | 6 | 182 | 216 | |
Huong Son | 802 | 1,000 | 1,022 | 1,105 | 1,229 | 1,047 | 1,741 | 7,946 | |
Nghi Loc | 31 | 23 | 35 | 36 | 22 | 5 | 152 | ||
Nghi Xuan | 96 | 108 | 159 | 97 | 101 | 137 | 1,208 | 1,906 | |
Vu Quang | 278 | 288 | 287 | 245 | 241 | 191 | 375 | 1,905 | |
Nghe An | Hung Nguyen | 43 | 43 | 45 | 55 | 146 | 382 | 1,590 | 2,304 |
Nam Dan | 230 | 296 | 441 | 698 | 906 | 973 | 3,094 | 6,638 | |
Thanh Chuong | 26 | 22 | 18 | 17 | 20 | 23 | 206 | 332 | |
Vinh | 65 | 43 | 39 | 41 | 46 | 35 | 292 | 561 | |
Sum (ha) | 1,901 | 2,172 | 2,446 | 2,841 | 3,518 | 3,667 | 12,209 | 28,754 |
Province . | District . | Inundation area (ha) . | |||||||
---|---|---|---|---|---|---|---|---|---|
< 0.5m . | 0.5–1 m . | 1–1.5 m . | 1.5–2 m . | 2–2.5 m . | 2.5–3 m . | > 3 m . | Sum(ha) . | ||
Ha Tinh | Duc Tho | 323 | 343 | 397 | 543 | 801 | 867 | 3,520 | 6,793 |
Hong Linh | 8 | 6 | 5 | 4 | 5 | 6 | 182 | 216 | |
Huong Son | 802 | 1,000 | 1,022 | 1,105 | 1,229 | 1,047 | 1,741 | 7,946 | |
Nghi Loc | 31 | 23 | 35 | 36 | 22 | 5 | 152 | ||
Nghi Xuan | 96 | 108 | 159 | 97 | 101 | 137 | 1,208 | 1,906 | |
Vu Quang | 278 | 288 | 287 | 245 | 241 | 191 | 375 | 1,905 | |
Nghe An | Hung Nguyen | 43 | 43 | 45 | 55 | 146 | 382 | 1,590 | 2,304 |
Nam Dan | 230 | 296 | 441 | 698 | 906 | 973 | 3,094 | 6,638 | |
Thanh Chuong | 26 | 22 | 18 | 17 | 20 | 23 | 206 | 332 | |
Vinh | 65 | 43 | 39 | 41 | 46 | 35 | 292 | 561 | |
Sum (ha) | 1,901 | 2,172 | 2,446 | 2,841 | 3,518 | 3,667 | 12,209 | 28,754 |
The inundation area, number of affected households, and length of flooded road by dike breach
Breach location . | District . | Inundation depth . | |||||||
---|---|---|---|---|---|---|---|---|---|
< 0.5 m . | 0.5–1 m . | 1–1.5 m . | 1.5–2 m . | 2–2.5 m . | 2.5–3 m . | > 3 m . | Total . | ||
Inundation area (ha) | |||||||||
Tung Anh | Can Loc | 302 | 361 | 140 | 5 | 0 | 0 | 0 | 807 |
Duc Tho | 1,716 | 2,434 | 777 | 83 | 6 | 3 | 1 | 5,019 | |
Hong Linh | 627 | 863 | 378 | 47 | 3 | 2 | 1 | 1,921 | |
Huu Dien | Can Loc | 561 | 794 | 643 | 718 | 340 | 20 | 0 | 3,077 |
Duc Tho | 446 | 1,021 | 1,703 | 2,219 | 987 | 47 | 4 | 6,427 | |
Hong Linh | 171 | 275 | 566 | 933 | 520 | 161 | 7 | 2,634 | |
Nga Song | Can Loc | 503 | 718 | 746 | 693 | 548 | 120 | 3 | 3,330 |
Duc Tho | 294 | 758 | 1,298 | 2,072 | 1,822 | 313 | 4 | 6,561 | |
Hong Linh | 145 | 193 | 412 | 759 | 794 | 344 | 34 | 2,681 | |
Number of affected households | |||||||||
Tung Anh | Can Loc | 554 | 374 | 15 | 0 | 0 | 0 | 0 | 943 |
Duc Tho | 4,790 | 3,124 | 636 | 94 | 11 | 1 | 0 | 8,656 | |
Hong Linh | 991 | 1,086 | 168 | 4 | 19 | 0 | 0 | 2,268 | |
Huu Dien | Can Loc | 1,137 | 1,019 | 945 | 962 | 251 | 0 | 0 | 4,314 |
Duc Tho | 1,772 | 3,464 | 4,872 | 3,256 | 648 | 2 | 1 | 14,015 | |
Hong Linh | 460 | 746 | 1,237 | 1,184 | 428 | 35 | 1 | 4,091 | |
Nga Song | Can Loc | 925 | 1,175 | 1,152 | 1,018 | 434 | 7 | 0 | 4,711 |
Duc Tho | 985 | 2,917 | 4,175 | 4,148 | 2,225 | 32 | 2 | 14,484 | |
Hong Linh | 526 | 300 | 1,245 | 1,130 | 981 | 79 | 4 | 4,265 | |
Flooded road (km) | |||||||||
Tung Anh | Can Loc | 25.15 | 28.34 | 9.96 | 0.05 | 0 | 0 | 0 | 63.51 |
Duc Tho | 113.14 | 133.03 | 32.96 | 7.98 | 4.57 | 1.60 | 0.15 | 293.43 | |
Hong Linh | 58.87 | 75.23 | 29.11 | 2.94 | 1.65 | 0.55 | 0.17 | 168.52 | |
Huu Dien | Can Loc | 31.36 | 37.00 | 37.50 | 40.95 | 19.10 | 1.17 | 0.00 | 167.08 |
Duc Tho | 30.15 | 65.72 | 114.95 | 126.61 | 49.73 | 5.69 | 1.76 | 394.62 | |
Hong Linh | 17.55 | 25.71 | 56.85 | 82.27 | 41.57 | 12.07 | 1.16 | 237.18 | |
Nga Song | Can Loc | 29.18 | 37.09 | 38.31 | 40.71 | 27.85 | 7.30 | 0.02 | 180.45 |
Duc Tho | 17.66 | 53.45 | 86.83 | 124.17 | 101.17 | 16.15 | 2.10 | 401.53 | |
Hong Linh | 18.29 | 16.75 | 42.50 | 68.79 | 67.02 | 27.41 | 3.09 | 243.85 |
Breach location . | District . | Inundation depth . | |||||||
---|---|---|---|---|---|---|---|---|---|
< 0.5 m . | 0.5–1 m . | 1–1.5 m . | 1.5–2 m . | 2–2.5 m . | 2.5–3 m . | > 3 m . | Total . | ||
Inundation area (ha) | |||||||||
Tung Anh | Can Loc | 302 | 361 | 140 | 5 | 0 | 0 | 0 | 807 |
Duc Tho | 1,716 | 2,434 | 777 | 83 | 6 | 3 | 1 | 5,019 | |
Hong Linh | 627 | 863 | 378 | 47 | 3 | 2 | 1 | 1,921 | |
Huu Dien | Can Loc | 561 | 794 | 643 | 718 | 340 | 20 | 0 | 3,077 |
Duc Tho | 446 | 1,021 | 1,703 | 2,219 | 987 | 47 | 4 | 6,427 | |
Hong Linh | 171 | 275 | 566 | 933 | 520 | 161 | 7 | 2,634 | |
Nga Song | Can Loc | 503 | 718 | 746 | 693 | 548 | 120 | 3 | 3,330 |
Duc Tho | 294 | 758 | 1,298 | 2,072 | 1,822 | 313 | 4 | 6,561 | |
Hong Linh | 145 | 193 | 412 | 759 | 794 | 344 | 34 | 2,681 | |
Number of affected households | |||||||||
Tung Anh | Can Loc | 554 | 374 | 15 | 0 | 0 | 0 | 0 | 943 |
Duc Tho | 4,790 | 3,124 | 636 | 94 | 11 | 1 | 0 | 8,656 | |
Hong Linh | 991 | 1,086 | 168 | 4 | 19 | 0 | 0 | 2,268 | |
Huu Dien | Can Loc | 1,137 | 1,019 | 945 | 962 | 251 | 0 | 0 | 4,314 |
Duc Tho | 1,772 | 3,464 | 4,872 | 3,256 | 648 | 2 | 1 | 14,015 | |
Hong Linh | 460 | 746 | 1,237 | 1,184 | 428 | 35 | 1 | 4,091 | |
Nga Song | Can Loc | 925 | 1,175 | 1,152 | 1,018 | 434 | 7 | 0 | 4,711 |
Duc Tho | 985 | 2,917 | 4,175 | 4,148 | 2,225 | 32 | 2 | 14,484 | |
Hong Linh | 526 | 300 | 1,245 | 1,130 | 981 | 79 | 4 | 4,265 | |
Flooded road (km) | |||||||||
Tung Anh | Can Loc | 25.15 | 28.34 | 9.96 | 0.05 | 0 | 0 | 0 | 63.51 |
Duc Tho | 113.14 | 133.03 | 32.96 | 7.98 | 4.57 | 1.60 | 0.15 | 293.43 | |
Hong Linh | 58.87 | 75.23 | 29.11 | 2.94 | 1.65 | 0.55 | 0.17 | 168.52 | |
Huu Dien | Can Loc | 31.36 | 37.00 | 37.50 | 40.95 | 19.10 | 1.17 | 0.00 | 167.08 |
Duc Tho | 30.15 | 65.72 | 114.95 | 126.61 | 49.73 | 5.69 | 1.76 | 394.62 | |
Hong Linh | 17.55 | 25.71 | 56.85 | 82.27 | 41.57 | 12.07 | 1.16 | 237.18 | |
Nga Song | Can Loc | 29.18 | 37.09 | 38.31 | 40.71 | 27.85 | 7.30 | 0.02 | 180.45 |
Duc Tho | 17.66 | 53.45 | 86.83 | 124.17 | 101.17 | 16.15 | 2.10 | 401.53 | |
Hong Linh | 18.29 | 16.75 | 42.50 | 68.79 | 67.02 | 27.41 | 3.09 | 243.85 |
Most of the people affected in the case of dike breach in Tung Anh were at low flood levels. The number of households which got flooded below 0.5 m deep was nearly 6,335, accounting for 53.4% of the affected households. This number increased to 92,000 households if the figure getting flooded under 1 m is counted. The number of people who had to relocate to high areas is fewer than 1,000 households. Therefore, in this case, the plan will focus more on supporting people to respond on the spot. In the case of the Huu Dien and Nga Song dike breach, the total number of affected households increased dramatically, with 22.4 thousand households and 23.5 thousand households, respectively. Furthermore, the number of households which got flooded over 1 m has also increased significantly. The number of households was 13.8 thousand households when the dike broke at Huu Dien, and 16.6 thousand households when the dike broke at Nga Song. This shows that the impacted scope as well as the impact on people when the dike breaks depends greatly on the location of the dike breach. In these cases, the response plan needs to pay more attention to evacuation. As the number of people to evacuate increases, the scope of response plans also increases greatly. Pressure on evacuation locations, food supplies, electricity and water also increases. Therefore, detailed information from the study will be an important input to develop an effective response plan.
Besides assessing the inundation area and the number of affected households, the study also assessed the degree of flooding on the roads. This information is not only the basis for assessing the extent of damage but also, more importantly, provides visual information about which sections of the road can be deeply flooded, limiting mobility in the case of a flood. This is also extremely useful information for decision-makers as well as local people.
Although the approach has shown clear advantages in terms of reducing the number of computational scenarios and providing detailed information to build emergency response scenarios, a number of limitations should be mentioned. First, the breach parameters are identified based on empirical formulas which can have uncertain variables. In the future, sensitivity analyses of these variables should be performed to assess their impacts on the flood consequence assessment. In addition, although the survey has found the most critical locations, the risk of dike breach can occur at any location on the dike for many reasons. Therefore, raising awareness of the local community as well as proactively responding to emergency situations should be implemented to minimize the damages. In this study, the authors only studied houses and roads. Other subjects such as crop area, and facilities have not been mentioned in the study. This is also the limitation of the study. With the same approach, such factors can completely be considered in the next studies.
CONCLUSIONS
The paper investigated the possible impact of dike breach scenarios for the La Giang dike. Based on the survey results, Tung Anh, Duc Dien, and Nga Song were determined as three high-risk dike breach locations. This has reduced the number of scenarios that need to be considered. The Mike Flood model was used to simulate the flow dynamic regime on the Ca River. The model was calibrated and validated with observer data at three hydrological stations. The results were very good with the Nash index up to 0.89. In this study, empirical formulas were used to calculate the breach parameters at three selected locations, including the length and depth of the breach in each location. The importance of breach development time, maximum discharge through the breach, and inundation area was analyzed via sensitivity analysis. The results show that breach time plays an important role, in influencing the above-mentioned factors. Through the GIS, the inundation area, the number of affected people, and the length of flooded roads are also statistically studied. All of the above elements are significantly different between the calculated cases. It means that we need a different response plan for each case. The results of the study also provide detailed statistics by administrative units and visual maps. This is useful information for the authorities and local people to help them have specific plans to face natural disasters. It is also very important information for the development of response plans as well as the establishment of a database for disaster prevention.
ACKNOWLEDGEMENTS
This research is supported by Thuyloi University.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.