Research Article
Print
Research Article
Flood hazard assessment in the Danube Delta using 2D hydraulic modeling
expand article infoNicu Ciobotaru§, Anca Crăciun§, Romulus-Dumitru Costache§
‡ National Institute of Hydrology and Water Management, Bucharest, Romania
§ ”Danube Delta” National Institute for Research and Development, Tulcea, Romania
Open Access

Abstract

The study analyzes flood risk in the Danube Delta, a fragile ecosystem at the intersection of natural processes and anthropogenic interventions, increasingly exposed to the effects of climate change. Using 2D hydraulic modeling with HEC-RAS software, the research assessed the extension of floodplains for 10, 100 and 1000-year return periods, based on hydrological data collected between 1971 and 2005. The results obtained demonstrate a significant increase in the areas affected by floods, especially in scenarios with a low probability of occurrence, thus highlighting the increased vulnerability of the region to extreme phenomena. Analysis of water depth in flooded areas indicates that regions with intermediate depths (0.2–0.5 m) are most affected by 100-year flood events, while rare events (1000 years) extend the impact to larger areas and greater depths (0.5–1 m). This evolution confirms the trend of increasing risks in the context of climate change and the increase in the frequency of extreme hydrological phenomena. The hazard maps generated are an essential tool for flood risk management, supporting informed decision-making to protect local communities and the delta’s biodiversity. Among the solutions proposed to reduce the impact of floods are the ecological reconstruction of wetlands, the implementation of effective climate change adaptation policies and the improvement of water management strategies. The study also highlights the need to integrate additional factors, such as the influence of the Black Sea level, in future simulation models, for better risk anticipation and optimization of protection measures.

Key words

2D hydraulic modeling, Danube Delta, flood risk, hazard maps, HEC-RAS, risk management

Introduction

Deltas are dynamic low-lying areas formed at the mouths of large rivers flowing into the receiving seas (Liu et al. 2024). They account for about 1% of the Earth’s land area globally and are home to more than 7% of the world’s population. These coastal areas are dominated by intensive agricultural activities favored by the presence of water and fertile soils (Chen et al. 2021) and are frequently heavily anthropized areas. The deltaic regions are characterized by frequent floods, some of them even showing a seasonality of the phenomenon, so in the context of increased anthropization they show increased flooding (Leduc et al. 2017). Since 2000, about 85% of the coastal deltas have been affected by severe flooding caused by changes in precipitation patterns due to global climate change and environmental change. These floods have temporarily affected a total area of about 260,000 km2 of coastal zones. Research has shown that about 50% of coastal deltaic areas are vulnerable to flooding caused by rising sea levels (Edmonds et al. 2020). This vulnerability has increased in recent years, as projected values for sea level rise in the 21st century and are above the inundability threshold of many deltaic areas (Youssef et al. 2024).

Flood risk assessment for coastal deltaic areas is based on the analysis of the floodplain area and the water depth in the floodplain (Nandam and Patel 2025). These parameters are used in the European Commission’s recommendations for flood hazard and flood risk maps (Velegrakis et al. 2024). The European Commission’s recommendations also include 3 possible scenarios for flood risk analysis (Arvidsson and Johansson 2024), including: i) low or extreme probability floods associated with a return period of once every 1000 years (0.1%); ii) medium probability floods associated with a return period of 100 years (1%); and iii) high probability floods that are associated with a return period of 10 years (10%). At the same time, in the context of global climate change, which leads to a high frequency of extreme meteorological and hydrological events, it is important for flood risk management in deltaic areas to also conduct flood hazard studies for flows associated with the impacts caused by different climate projections.

In the 20th and 21st centuries, the effects of human activity on climatic parameters have led to significant changes in ocean current patterns, marine processes and continental stream flows, accelerating the energy balance in the terrestrial atmosphere (Wang et al. 2024). Thus, the structural and functional parameters of coastal deltaic areas are directly and indirectly affected by the climatic changes of the last century. One of the largest coastal delta ecosystems in Europe is the Danube Delta with an area of 5640 km2, the second largest delta in Europe. The Danube Delta is also vulnerable to changing climatic parameters and their effects on marine processes and the Danube River (Bănăduc et al. 2023), such as the rising of the sea level. The Danube Delta evolved in a natural regime until 1860 (Bănăduc et al. 2023), with the main branches (Chilia, Sulina and Sfântu Gheorghe from north to south) maintaining their natural structure until the beginning of the 20th century, when the direction of the Sulina branch was changed to allow navigation to the sea (Armaş and Avram 2009). In the second half of the twentieth century, the delta’s inland water network underwent significant changes through the opening of navigation channels and the removal of large areas from the floodplain. The change in the flood regime led to changes in the natural dynamics of the entire delta system, increasing its vulnerability to flooding. Major floods occurred in 1942, 1970, 1975, 1981, 1988, 2005, 2006 and 2010 accordingly to the publicly available data at Ceatal Ismail.

In the Danube Delta, the frequency of floods has increased over the last decades favored by the geographical position, the hydrological specificity of the area, but also by extreme meteorological phenomena caused by climate change (Crăciun et al. 2022). The extent of flooding in the Danube Delta is directly proportional to the flow/level of the Danube’s waters as they flow into the Black Sea. The hydrological regime of the Danube Delta is primarily influenced by the water discharge of the Danube River, which varies significantly throughout the year. The average annual discharge at the entrance of the delta (Ceatal Izmail) is approximately 6,500 cubic meters per second (m³/s), with seasonal peaks during spring and early summer (April–June) due to snowmelt and rainfall in the Danube Basin. Minimum discharges typically occur during late summer and early autumn, and can drop below 2,000 m³/s in dry years. Water distribution within the delta is managed through three main branches: Chilia, Sulina, and Sfântu Gheorghe, with the Chilia branch carrying the largest share (more than 60% of the total flow). The variable discharges influence sediment transport, water levels, and the ecological dynamics of the delta’s wetlands. Human interventions, such as upstream dams and channel modifications, also impact natural flow patterns, affecting both flood risk and ecosystem health in the region.

The vulnerability of the Danube Delta to flooding can thus be determined on the basis of hydraulic modeling of the hydrological regime of the Danube, identifying both the extent of the flood band and the water depth within it. One of the well-known hydraulic modeling software is HEC-RAS (Hydraulic Engineering Center River Analysis System), developed by the US Army Corps of Engineers (Peker et al. 2024). This software was used, having a 2D configuration for the study of the flood hazard of the Danube Delta by delineating a number of three flood inundability bands for flows with 0.1%, 1% and 10% probabilities of occurrence calculated based on observations at the Ceatal Ismail station between 1971 and 2005.

A short review of the methods used to determine flood inundability in the Danube Delta shows that the techniques applied so far are based on methods such as hydro grades analysis (Mierla et al. 2015), detection of the extent of flood inundability bands using RADAR or optical imagery (Niculescu et al. 2015), as well as 1D hydraulic modeling (Bănescu et al. 2020). In contrast, the present study proposes, for the first time, the use of 2D hydraulic modeling to analyze an extended area of the Danube Delta.

In the next sections the methods used in the study are described together withdata sources used to configure the 2D model and to calculate the return periods for Ceatal Ismail cross-section, which is upstream of Danube Delta branching. Next, the results of the flood modeling and the analysis of the results are presented followed by conclusions and discussions.

Materials and methods

Data

The two-dimensional (2D) hydraulic modeling of the Danube Delta was carried out on a Digital Terrain Model (DTM) with a resolution of 2 m obtained from LiDAR flight data collected from 4 sectors of the delta. The sectors between the Sf Sfântu Gheorghe and Sulina inlets were modeled at 2 m resolution, and the sectors between the Sulina and Chilia inlets were delimited by the state border between Romania and Ukraine at 5 m resolution (Fig. 1). The uncovered areas were complemented with 25 m resolution DTM data from EU-DEM. The resulting DTM covers the entire Danube Delta, including the Chilia Arm on Ukrainian territory. The stereographic projection Pulkovo 1942/Stereo 70 was used to project this model in the RAS Mapper application. Subsequently, a series of processing was necessary to correct the errors related to the main channels by lowering the bed of the riverbed according to bathymetric measurements along these arms, and by using the 1:25000 topographic map to correct the talvegue of the main lakes and channels taking into account the bathymetry of this map.

The hydrographs used in the report are based on the characteristics of the 2006 flood. The 2006 flood is the largest flood recorded to date, with discharges of 15900 m3/s at the Ceatal Ismail station (Fig. 2), corresponding to a return period of once in 200 years. Analysis of the 2006 flood hydrograph shows that discharges with a 10-year return period (above 13250 m3/s) had a duration of about 2 months. Discharges with a 100-year return period (15055 m3/s) had a duration of approximately 20 days, and those corresponding to a 0.1% discharge (16160 m3/s) were recorded over a period of one day, with the current scenarios attempting to replicate these durations.

Data regarding the terrain roughness characteristics and slopes of the various drainage sectors were also used to configure and calibrate the hydraulic model, influencing the flood speed on the channels and delta.

Fig. 3 shows the classification of terrain roughness in the Danube Delta, based on the classes recommended in the literature (Ye et al. 2018). For the main branches of the Danube Delta, an average value of 0.0035 was used, while lake/marsh surfaces have higher values ​​of this coefficient, resulting in a slower water flow outside the main branches.

Along with the flow rates, the slope of the terrain is one of the essential components of the hydraulic model configuration, used to define the algorithm for water propagation in the river bed and on the terrain in the study area. The slope influences the modelling of the different volumes of water that pass through a reach, and the mode of passage is influenced by the time step used to run the model.

The reference slope of the main branches was extracted from the Digital Terrain Model (DTM) based on the height of the ‘water gloss’ at the time of LiDAR data acquisition. As water is a poor reflector of LiDAR waves, it appears to have a relatively uniform elevation across the surface and is therefore considered to be a flat surface. Subsequent interpolation errors can occur due to the disturbance of the water gloss flatness caused by navigation or different vessels from the canals, so the total difference between upstream and downstream was taken into account when extracting the slope.

Figure 1. 

Complete extent of Danube Delta Digital Elevation Model.

Figure 2. 

Flood hydrograph from March to May 2006 at Ceatal Ismail station.

Figure 3. 

Spatial distribution of Manning roughness coefficient across Danube Delta.

Model configuration

The modeling was prepared using the River Analysis System (RAS) developed by the Hydraulic Engineering Center (HEC). HEC-RAS is a widely used hydraulic software for 1D steady and unsteady flow modeling, 2D unsteady flow hydraulic calculations, sediment transport modeling, and water quality analysis (Ongdas et al. 2020). The capabilities of HEC-RAS software allow its connection with specific Geographic Information Systems (GIS) tools, considerably reducing the working time for obtaining input data into the hydraulic model (Zainal and Abu Talib 2024).

HEC-RAS 2D uses equations that describe the motion of water associated with velocity and depth in the 2D plane in response to the forces of gravity and friction. These equations represent the conservation of mass and momentum in a plane. The finite volume method used in HEC-RAS is advantageous due to its conservative nature, geometric flexibility, and conceptual simplicity (Quirogaa et al. 2016).

Vt+(V)V+fck×V=gzs+1h(vthV)τbρR+τsρh (1),

where:

V – water velocity;

zs – water level;

g – gravity;

vt – turbulent viscosity;

h – water depth;

R – hydraulic range;

fc – Coriolis parameter;

τb – friction force at the riverbed level;

τs – friction force at the level of water surface.

In order to capture the water flow in the Danube Delta as well as possible, a 2D model was chosen. The modelled area is between the main Danube downstream of Isaccea, the mouth of the main branches before their contact with the Black Sea or in the area of the connecting channels with the Razim-Sinoe lake complex, covering an area of approximately 3509 km2 of the Danube Delta territory (significantly smaller than the official area).

The flooding modelling of the Danube Delta was carried out with a grid resolution of 400 m, including numerous refinement areas where the cell resolution was reduced to 50 m or even 25 m for some levees (Fig. 4). Thus, the mesh used in the final configuration has an approximate number of 186000 computation points. The boundary condition was given by the slope of the river bed near the outlets, extracted from the DTM, and the marine influence of sea level was not taken into account in these simulations.

Figure 4. 

Geometry configuration used in hydraulic modeling. a. Extent of the hydraulic model geometry; b, d. Details regarding the mesh refinement areas for the Danube branches and c. For interior enclosures.

Results and discussion

The results of the simulations on the floodplains showed a possible evolution of the flooded area within the Danube Delta, depicted in Figs 57 and summarized in Table 1. An effective method of analyzing floodability is to compare the values for scenarios with similar return periods, in order to observe the variations in the intensity of the phenomenon. Thus, in the case of simulations for a return period of 100 years, often used in hazard analyses, a significant increase in the area covered by water is observed. In the reference period (1971–2005), this was approximately 2100 km2.

Table 2 shows the absolute and percentage distribution of areas occupied by different water depth classes. For the 0–0.1 m class, the Q10-year flood occupies about 19.3% of the modeled area with an area of 346.5 km2. At Q100 years, the percentage decreases to 10.4% and the area to 218,551 km2. At Q1000 years, the percentage is 4.3% with an area of 94.1 km2. Here, a steady decrease in the share of this class is observed with increasing return period. This could indicate that shallower areas are more prone to frequent floods, but less affected by rare events. Continuing with the 0.1–0.2 m class, the percentages are 19.5% (Q10 years), 15.5% (Q100 years) and 9.2% (Q1000 years), and the corresponding areas are 349.9 km2, 324,851 km2 and 203.2 km2. Here, too, a decrease in the share is observed, but less accelerated than in the case of the previous class. The 0.2–0.5 m class is the most dominant for Q10 years with 24.0% and 426.9 km2. At Q100 years, the percentage increases significantly to 38.5% and the area to 809,281 km2, and at Q1000 years it decreases to 30.0% with 660 km2. This suggests that this depth class is the most affected by floods with a 100-year return. The intermediate classes (0.5–0.75 m, 0.75–1 m) show interesting increases. For Q1000 years, the 0.5–0.75 m class increases to 21.1% (465.6 km2) compared to 7.7% (138.3 km2) for Q10 years, and the 0.75–1 m class increases to 8.6% (206.2 km2) compared to 5.0% (89.6 km2). These increases indicate a trend towards intermediate depths for rare events. The larger depth classes (1–1.5 m, 1.5–2 m, 2–3 m, 3–5 m and over 5 m) show smaller percentage variations, but still a slight increase in areas at Q1000 years compared to Q10 years. For example, the 2–3 m class increases from 5.0% (89.3 km2) to 7.9% (174.8 km2). This could signal that severe flooding affects deeper areas. For example, the 2–3 m class increases from 5.0% (89.3 km2) to 7.9% (1748.8 km2). This could indicate that severe flooding affects deeper areas. It is also important to note that the total flooded area increases from Q10 years (1792.2 km2) to Q100 years (2101.9 km2) and then to Q1000 years (~2203.3 km2), confirming that rarer events cover a larger area.

Table 1.

Characteristics of floods according to different scenarios.

No. Hydraulic simulation scenarios for flows of different probabilities Water depth [m] Maximum water depth [m] Flooded surface [km2]
1 QObs 1000 years (1971–2005) 0.833 18.894 2203.065
2 QObs 100 years (1971–2005) 0.829 15.718 2101.965
3 QObs 10 years (1971–2005) 0.814 15.508 1792.247
Figure 5. 

Flood hazard map in the Danube Delta for the 100-year return period determined by observations during 1971–2005.

Figure 6. 

Flood hazard map in the Danube Delta for the 10-year return period determined by observations during 1971–2005.

Figure 7. 

Flood hazard map in the Danube Delta for the 1000-year return period determined by observations during 1971–2005.

Table 2.

The share of flooded areas and the surface covered for different water depth classes in the study area.

Water depth [m] Flood with the 10-year return period Flood with the 100-year return period Flood with the 1000-year return period
[%] [km2] [%] [km2] [%] [km2]
0–0.1 19.3 346.5 10.4 218.551 4.3 94.1
0.1–0.2 19.5 349.9 15.5 324.851 9.2 203.2
0.2–0.5 24.0 426.9 38.5 809.281 30.0 660.1
0.5–0.75 7.7 138.3 6.1 127.308 21.1 465.8
0.75–1 5.0 89.6 6.1 127.47 8.6 188.5
1–1.5 7.6 137.1 6.8 143.552 7.8 172.5
1.5–2 6.2 111.1 6.1 128.937 5.7 126.3
2–3 5.0 89.3 5.4 114.245 7.9 174.8
3–5 2.9 52.5 2.5 53.575 3.0 66.4
over 5 2.8 51.0 2.6 54.195 2.3 51.5

Conclusions

The study conducted through 2D hydraulic modeling with HEC-RAS software highlighted the dynamics of flood risk in the Danube Delta (Figs 57), for different return periods, taking into account the most accurate topography of the area. The main results indicate a significant increase in floodable areas with a decrease in the probability of occurrence of events (from 10 to 1000 years). For the 1000-year return period, the flooded area reached approximately 2203 km2, compared to 1792 km2 for decadal events. These differences highlight the increased vulnerability of the delta to extreme phenomena.

The analysis of water depth revealed that areas with intermediate depths (0.2–0.5 m) are predominantly affected by 100-year return period floods, while rare events (1000 years) extend the impact to greater depths (0.5–1 m) and larger areas. Also, the decrease in the share of shallow depth classes (0–0.1 m) at lower probabilities suggests that marginal areas are exposed more frequently, but with limited intensities.

The hazard maps generated constitute an essential tool for risk management, facilitating the identification of critical areas and the implementation of adaptation strategies. Ecological restoration of wetlands and policies to reduce the impact of climate change are confirmed as vital measures to protect local communities and the deltaic ecosystem.

The limitations of the study, such as the exclusion of marine influence and the variable resolution of the digital terrain model, indicate the need to improve future approaches by integrating additional factors (e.g., Black Sea level variations). Further research could include climate projections and socio-economic analyses to optimize adaptive management plans. In conclusion, the application of 2D modeling in HEC-RAS has demonstrated its efficiency in hydrological hazard assessment, providing a solid basis for policy decisions and sustainable protection of the Danube Delta.

Additional information

Conflict of interest

The authors have declared that no competing interests exist.

Ethical statement

No ethical statement was reported.

Use of AI

No use of AI was reported.

Funding

This research was funded by the Ministry of Research, Innovation, and Digitization within the framework of Nucleus Program “Danube Delta 2030” PN 23 13, 2023–2026—Nucleus Project: “Research on the contribution of ecological restoration activities in the management of environmental risks caused by global climate change in the Danube Delta Biosphere Reserve—PN 23 13 02 01”.

Author ORCIDs

Nicu Ciobotaru https://orcid.org/0000-0002-6052-985X

Anca Crăciun https://orcid.org/0000-0003-1113-906X

Romulus-Dumitru Costache https://orcid.org/0000-0002-6876-8572

Author contributions

Nicu Ciobotaru: conceptualization, methodology, software, investigation, writing—original draft preparation, writing—review and editing, visualization; Anca Crăciun: conceptualization, methodology, software, investigation, writing—original draft preparation; Romulus-Dumitru Costache: conceptualization, methodology, software, investigation, writing—original draft preparation.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  • Arvidsson B, Johansson J (2024) Flood risk assessments—Exploring maturity and challenges in Sweden. Journal of Flood Risk Management 17(2): e12973. https://doi.org/10.1111/jfr3.12973
  • Bănăduc D, Afanasyev S, Akeroyd JR, Năstase A, Năvodaru I, Tofan L, Curtean-Bănăduc A (2023) The Danube Delta: The Achilles heel of Danube River–Danube Delta–Black Sea region fish diversity under a Black sea impact scenario due to sea level rise—A prospective review. Fishes 8(7): 355. https://doi.org/10.3390/fishes8070355
  • Bănescu A, Arseni M, Georgescu LP, Rusu E, Iticescu C (2020) Evaluation of different simulation methods for analyzing flood scenarios in the Danube Delta. Applied Sciences 10(23): 8327. https://doi.org/10.3390/app10238327
  • Chen X, Zhang H, Chen W, Huang G (2021) Urbanization and climate change impacts on future flood risk in the Pearl River Delta under shared socioeconomic pathways. Science of the Total Environment 762: 143144. https://doi.org/10.1016/j.scitotenv.2020.143144
  • Crăciun A, Costache R, Bărbulescu A, Pal SC, Costache I, Dumitriu CȘ (2022) Modern techniques for flood susceptibility estimation across the Deltaic Region (Danube Delta) from the Black Sea’s Romanian Sector. Journal of Marine Science and Engineering 10(8): 1149. https://doi.org/10.3390/jmse10081149
  • Leduc C, Pulido-Bosch A, Remini B (2017) Anthropization of groundwater resources in the Mediterranean region: processes and challenges. Hydrogeology Journal 25(6): 1529. https://doi.org/10.1007/s10040-017-1572-6
  • Liu D, Gong H, Li J, Liu Z, Wang L, Ouyang Z, Xu L, Wang T (2024) Continuous crop rotation increases soil organic carbon stocks in river deltas: A 40-year field evidence. Science of the Total Environment 906: 167749. https://doi.org/10.1016/j.scitotenv.2023.167749
  • Mierla M, Romanescu G, Nichersu I, Grigoras I (2015) Hydrological risk map for the Danube Delta—A case study of floods within the fluvial delta. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(1): 98–104. https://doi.org/10.1109/JSTARS.2014.2347352
  • Nandam V, Patel PL (2025) Comprehensive analysis of data aggregation techniques for flood vulnerability and bivariate flood risk mapping of a coastal urban floodplain. International Journal of Disaster Risk Reduction 119: 105330. https://doi.org/10.1016/j.ijdrr.2025.105330
  • Niculescu S, Lardeux C, Hanganu J, Mercier G, David L (2015) Change detection in floodable areas of the Danube delta using radar images. Natural Hazards 78: 1899–1916. https://doi.org/10.1007/s11069-015-1809-4
  • Ongdas N, Akiyanova F, Karakulov Y, Muratbayeva A, Zinabdin N (2020) Application of HEC-RAS (2D) for flood hazard maps generation for Yesil (Ishim) river in Kazakhstan. Water 12(10): 2672. https://doi.org/10.3390/w12102672
  • Peker İB, Gülbaz S, Demir V, Orhan O, Beden N (2024) Integration of HEC-RAS and HEC-HMS with GIS in flood modeling and flood hazard mapping. Sustainability 16(3): 1226. https://doi.org/10.3390/su16031226
  • Quirogaa VM, Kurea S, Udoa K, Manoa A (2016) Application of 2D numerical simulation for the analysis of the February 2014 Bolivian Amazonia flood: Application of the new HEC-RAS version 5. Ribagua 3(1): 25–33. https://doi.org/10.1016/j.riba.2015.12.001
  • Velegrakis AF, Chatzistratis D, Chalazas T, Armaroli C, Schiavon E, Alves B, Grigoriadis D, Hasiotis T, Ieronymidi E (2024) Earth observation technologies, policies and legislation for the coastal flood risk assessment and management: a European perspective. Anthropocene Coasts 7: 3. https://doi.org/10.1007/s44218-024-00037-x
  • Wang B, Hua L, Mei H, Wu X, Kang Y, Zhao N (2024) Impact of climate change on the dynamic processes of marine environment and feedback mechanisms: An overview. Archives of Computational Methods in Engineering 31(6): 3377–3408. https://doi.org/10.1007/s11831-024-10072-z
  • Ye A, Zhou Z, You J, Ma F, Duan Q (2018) Dynamic Manning’s roughness coefficients for hydrological modelling in basins. Hydrology Research 49(5): 1379–1395. https://doi.org/10.2166/nh.2018.175
  • Youssef YM, Gemail KS, Atia HM, Mahdy M (2024) Insight into land cover dynamics and water challenges under anthropogenic and climatic changes in the eastern Nile Delta: Inference from remote sensing and GIS data. Science of the Total Environment 913: 169690. https://doi.org/10.1016/j.scitotenv.2023.169690
  • Zainal NN, Abu Talib SH (2024) Review paper on applications of the HEC-RAS model for flooding, agriculture, and water quality simulation. Water Practice & Technology 19(7): 2883–2900. https://doi.org/10.2166/wpt.2024.173
login to comment