Flood Propagation Research Articles

Flow-tub model: A modified bathtub flood model with hydraulic connectivity and path-based attenuation

Global climate change and sea level rise are increasing the risks of flooding for coastal communities. Probabilistic coastal flood risk analysis at regional or global scales requires flood models with relatively low data requirements and low computational costs. Bathtub inundation models, which compute flood depth as the difference between water level and ground elevation, are well-suited for large-scale flood risk analysis. However, these models may overestimate floods because they do not capture some of the relevant underlying hydrodynamic processes that govern flood propagation on land.We present Flow-Tub, a modified bathtub inundation model that integrates two hydrodynamic processes to improve the accuracy of the bathtub inundation model while retaining computational efficiency: hydraulic connectivity and path-based attenuation.1.Hydraulic connectivity ensures that inundation is restricted to areas connected to the water source.2.Path-based attenuation ensures that the modeled flood water depths are reduced along the flow paths to represent the effects of surface friction and the temporary nature of storm surges.We validate the Flow-tub model against a hydrodynamic model. We also compare results of the bathtub model and the Flow-Tub model, highlighting the improved accuracy in the estimation of flood depths in the latter.

Assessing temporal changes in the quantity and quality of shallow groundwater in the Biebrza valley in the 21st century

Wetlands play a crucial role in the hydrological cycle, controlling flood generation, dry season flows, and water quality. This emphasizes the part of the Biebrzański National Park in protecting naturally valuable habitats. Our research aimed to assess (quantitatively and qualitatively) the state of groundwater affecting the condition of wetlands. The analyses carried out in 2021 were compared with the results of hydrological and hydro-chemical mapping of the first groundwater level from 1998.Quaternary formations serve as the main groundwater reservoir in the Biebrza Valley. These formations consist of pore water located at shallow depths, usually ranging from 0.5 to 10.95 meters. Most often, the first aquifer occurred at 1–3 meters deep. No significant reduction was observed when comparing the current water table levels with data from 1998. More than half of the surveyed dug wells are used for economic purposes. The Biebrza River is an outflow for shallow groundwater, as the hydroizohypses system indicates.The shallow groundwater resources in the Biebrzański National Park include mainly low and medium mineralization waters. A significant increase in the concentration of nitrogen compounds (NH4+-N, NO2−-N, and NO3–N), phosphorus, and dissolved organic carbon was recorded. This trend is evident in areas with intensive cattle breeding and is associated with excessive use of manure and slurry. The research confirmed the mosaic nature of the chemical composition observed in 1998 and the wide range of variability of the chemical properties of shallow groundwater.

The testing of a multivariate probabilistic framework for reservoir safety evaluation and flood risks assessment in Slovakia: A study on the Parná and Belá Rivers

Abstract Intense floods represent a challenge to risk management. While they are multivariate in their nature, they are often studied in practice from univariate perspectives. Classical frequency analyses, which establish a relation between the peak flow or volume and the frequency of exceedance, may lead to improper risk estimations and mitigations. Therefore, it is necessary to study floods as multivariate stochastic events having mutually correlated characteristics, such as peak flood flow, corresponding volume and duration. The joint distribution properties of these characteristics play an important role in the assessment of flood risk and reservoir safety evaluation. In addition, the study of flood hydrographs is useful because of the inherent dependencies among their practice-relevant characteristics present on-site and in the regional records. This study aims to provide risk analysts with a consistent multivariate probabilistic framework using a copula-based approach. The framework respects and describes the dependence structures among the flood peaks, volumes, and durations of observed and synthetic control flood hydrographs. The seasonality of flood generation is respected by separate analyses of floods in the summer and winter seasons. A control flood hydrograph is understood as a theoretical/synthetic discharge hydrograph, which is determined by the flood peak with the chosen probability of exceedance, the corresponding volume, and the time duration with the corresponding probability. The framework comprises five steps: 1. Separation of the observed hydrographs, 2. Analysis of the flood characteristics and their dependence, 3. Modelling the marginal distributions, 4. A copula-based approach for modelling joint distributions of the flood peaks, volumes and durations, 5. Construction of synthetic flood hydrographs. The flood risk assessment and reservoir safety evaluation are described by hydrograph analyses and the conditional joint probabilities of the exceedance of the flood volume and duration conditioned on flood peak. The proposed multivariate probabilistic framework was tested and demonstrated based on data from two contrasting catchments in Slovakia. Based on the findings, the study affirms that the trivariate copula-based approach is a practical option for assessing flood risks and for reservoir safety.

Is the LSTM Model Better than RNN for Flood Forecasting Tasks? A Case Study of HuaYuankou Station and LouDe Station in the Lower Yellow River Basin

The long short-term memory network (LSTM) model alleviates the gradient vanishing or exploding problem of the recurrent neural network (RNN) model with gated unit architecture. It has been applied to flood forecasting work. However, flood data have the characteristic of unidirectional sequence transmission, and the gated unit architecture of the LSTM model establishes connections across different time steps which may not capture the physical mechanisms or be easily interpreted for this kind of data. Therefore, this paper investigates whether the gated unit architecture has a positive impact and whether LSTM is still better than RNN in flood forecasting work. We establish LSTM and RNN models, analyze the structural differences and impacts of the two models in transmitting flood data, and compare their performance in flood forecasting work. We also apply hyperparameter optimization and attention mechanism coupling techniques to improve the models, and establish an RNN model for optimizing hyperparameters using BOA (BOA-RNN), an LSTM model for optimizing hyperparameters using BOA (BOA-LSTM), an RNN model with MHAM in the hidden layer (MHAM-RNN), and an LSTM model with MHAM in the hidden layer (MHAM-LSTM) using the Bayesian optimization algorithm (BOA) and the multi-head attention mechanism (MHAM), respectively, to further examine the effects of RNN and LSTM as the underlying models and of cross-time scale bridging for flood forecasting. We use the measured flood process data of LouDe and HuaYuankou stations in the Yellow River basin to evaluate the models. The results show that compared with the LSTM model, under the 1 h forecast period of the LouDe station, the RNN model with the same structure and hyperparameters improves the four performance indicators of the Nash–Sutcliffe efficiency coefficient (NSE), the Kling-Gupta efficiency coefficient (KGE), the mean absolute error (MAE), and the root mean square error (RMSE) by 1.72%, 4.43%, 35.52% and 25.34%, respectively, and the model performance of the HuaYuankou station also improves significantly. In addition, under different situations, the RNN model outperforms the LSTM model in most cases. The experimental results suggest that the simple internal structure of the RNN model is more suitable for flood forecasting work, while the cross-time bridging methods such as gated unit architecture may not match well with the flood propagation process and may have a negative impact on the flood forecasting accuracy. Overall, the paper analyzes the impact of model architecture on flood forecasting from multiple perspectives and provides a reference for subsequent flood forecasting modeling.

Comparing Flood Damages to an Industrial Region in Turkey Using Several Methods

Floods are one of the disasters that cause the greatest damage to social life, living health, economy and environment. This paper reveals the calculation of the economic damage of the commercial areas located near the creek due to floods in Sakarya, Dinsiz Stream. In this study, first, flood propagation maps were produced according to 50, 100, 200 and 500 years of flood flow periods that may occur in the study area. The HECRAS program was used to produce the flood maps and a 2D model was created from these maps, water level maps were obtained and then depth damage curves were used to figure out the economic losses leading to flood. In addition to the Huizinga, van Eck and Kok, ICBR, Pistrika and Jonkman flood damage assessment methods, which are frequently used in the literature, the HAZUS-MH method was used to calculate the economic losses that may occur in commercial areas. While HAZUS has functions that make separate calculations for each commercial sector, in other methods, calculations are made over the total area without sector discrimination. In addition, HAZUS has more detailed ranges of flooding water depths and therefore the calculation of damage rates corresponding to water depths can be done with higher precision than other methods. According to the data obtained as a result of the study, the losses exceeded million euros in all methods, while the highest values were in the Pistrika and Jonkman methods.

The Role of Geomorphology on Flood Propagation in a Large Tropical River: The Peculiar Case of the Araguaia River, Brazil

In large rivers, floods are affected by the mosaic of geomorphic and geologic settings of the fluvial corridor. Here, we assess the role of geomorphology on the downstream flood dynamics of the Araguaia River, the largest free-flowing river in Central Brazil. The study integrates and advances existing flood-type classifications. We assess the factors that govern flood hydrograph properties and their downstream propagation by using flow time series, conducting statistical analysis, and evaluating geomorphic and flood metrics. Our findings highlight the role of geomorphology in the transmission of floods. In the upper and lowermost fluvial segments, the geological characteristics of the valley are a major factor. In the intermediate section, two main factors modulate the floods. The wide and complex floodplain plays a major role through storage and buffer effect for floods, and water diversion from the main system to a huge abandoned channel by avulsion governs seasonal flow transfers. The Araguaia is the most geodiverse floodplain of the Amazon–Cerrado ecotone, and floods play a fundamental ecological role in the river–floodplain environments. The combination of diverse factors controlling the flood mechanisms has to be considered when implementing conservation plans for the fluvial corridor and effective river management strategies.

Patterns and drivers of evapotranspiration in South American wetlands

Evapotranspiration (ET) is a key process linking surface and atmospheric energy budgets, yet its drivers and patterns across wetlandscapes are poorly understood worldwide. Here we assess the ET dynamics in 12 wetland complexes across South America, revealing major differences under temperate, tropical, and equatorial climates. While net radiation is a dominant driver of ET seasonality in most environments, flooding also contributes strongly to ET in tropical and equatorial wetlands, especially in meeting the evaporative demand. Moreover, significant water losses through wetlands and ET differences between wetlands and uplands occur in temperate, more water-limited environments and in highly flooded areas such as the Pantanal, where slow river flood propagation drives the ET dynamics. Finally, floodplain forests produce the greatest ET in all environments except the Amazon River floodplains, where upland forests sustain high rates year round. Our findings highlight the unique hydrological functioning and ecosystem services provided by wetlands on a continental scale.

Developing synthetic sewer pipe system for data-scarce domains in application for urban flood modeling

Abstract In urban flood modeling, the accuracy of surface and subsurface flow calculations greatly depends on the parameterization of the drainage system. Incorporating the influence of the sewer pipe system is, therefore, integral to accurately simulating urban inundation during short-duration rainfall events. However, obtaining comprehensive data on sewer systems in developing countries is currently challenging. To mitigate this situation, we propose a method for developing a synthetic sewer network to supplement the representation of the sewer system in urban flood models, particularly in data-scarce domains. The model implements the concept of shallow water equation for surface flow and a 1D slot model for pipe flows with an interaction equation between them. We compare case studies with and without discharge interaction between the surface and hypothetical sewer system for the 2020 flood event in an urban subcatchment within the Marikina Basin, Philippines. Results show that the synthetic sewer pipe integration can capture the urban flood propagation more appropriately. Information such as flood depth and pipe flow discharge can aid in identifying flood-prone areas where sewer system parameters may require modifications. The proposed method can be used as an alternative to performing high-resolution urban flood simulations with limited availability of sewer network data.

Flood Risk and Vulnerability from a Changing Climate Perspective: An Overview Focusing on Flash Floods and Associated Hazards in Jeddah

Natural hazard threats have grown as a result of climate change, fast demographic development, and major urbanization. Devastating floods have occurred in several areas of the world recently, including the Kingdom of Saudi Arabia, which is located in a region with a dry environment. In arid or semi-arid regions, rapidly forming flash floods associated with debris flowing down over dry water courses leading to a potential threat to both lives and property. Being located at the coastal plain of western Saudi Arabia, Jeddah City has witnessed an unexpected amount of rainfall events in recent years. Such extreme rainfall events, integrated with other factors, namely topography, land use, surface runoff, etc., have led to flood generation, which is alarming indeed. Herein, this paper addresses the varying climatic classifications of the Kingdom, its risk and vulnerability, followed by reasoning about the impact of flash flood events and the associated casualties and property losses. Further, it reports about the existing strategies of the government and proposes a systematic way forward on how to alleviate such events in future. Thus, risk variables have been discovered and integrated in the context of climate change and rising anthropogenic strain on coastal communities to give planners and decision makers tools to assure effective and appropriate flood risk management.

2D and 3D Numerical Simulation of Dam-Break Flooding: A Case Study of the Tuzluca Dam, Turkey

Unlike river floods, floods caused by dam breaks occur much more abruptly and at higher water velocities. The failure of a dam due to any reason can pose a significant threat to settlements in the downstream area due to the high volume of water in its reservoir. In this case study, 2D and 3D numerical failure simulations of Tuzluca Dam, to be built in the Igdir province of Turkey, was performed using the Flow3D Hydro software. The Shallow Water and Reynolds-Averaged Navier-Stokes (RANS) equations were used to simulate flood propagation. In the numerical models, RNG k-ε was chosen as the turbulence model. In the analyses carried out under different scenarios, it was observed that in both methods (2D and 3D), significant flood depths would occur in two downstream village settlements. Within the scope of the study, the mortality rates in different dam-break scenarios of the Tuzluca Dam were also investigated. It has been observed that the dam failure time and breach geometry have a significant impact on the flood propagation and the loss of life in settlements. Additionally, a dam-break experiment in literature dam-break experiment was numerically solved using the Flow3D Hydro software to validate the numerical model, and a satisfactory harmony was observed between the experimental results and the numerical models. Although the 3D analysis provided a more accurate representation of the experimental results, it took approximately 20 times longer to complete the dam failure simulation in the case study compared to the 2D model. As a result, it has been determined that for comprehensive studies such as those of dam failures, 2D analyses may be more practical, while for smaller-scale scenarios or situations requiring greater precision, 3D modelling is appropriate.

Are the magnitude and frequency of floods increasing in Iran due to climate change? Implications from a 50-year analysis

ABSTRACT The correlation between extreme precipitation and flood magnitude is still poorly understood because of the complex mechanisms controlling flood generation. In this study, we used 50 years of precipitation and streamflow data across Iran to analyse the spatial distribution, slope, and significance of long-term trends in extreme precipitation compared to the spatial distribution of long-term trends for flood magnitude and frequency. Despite the decreasing trend of extreme precipitation in 60% of Iran’s sub-basins, the flood magnitude showed an increasing trend. In particular, the number of flooding days with a return period of 25~50 years and >50 years in 2010s has increased by 1.3 and 2.2 times, respectively, compared to that in 2000s. We attributed the above contrasting relationship between extreme precipitation and flood magnitude to the influence of an increase in short-duration extreme precipitations, extensive land use and land cover change, and reduced soil infiltration due to long-term droughts.

Experimental study on the buffering effects of urban trees group in dike-break floods

The process of dike-break flood propagation in typical urban street is highly complex. The presence of buildings and trees groups in urban street profoundly alters the flood dynamics, impacting the drainage capacity of the area. In this study, a generalized sink model representing a typical urban street was established, including trees groups, buildings, sidewalks, and stormwater drainage systems. The study measured the fluctuation of water levels within the street block and the pressure variation in the pressurized stormwater drainage network during the dike-break flood propagation. Furthermore, it conducted a comparative analysis to assess the influence of different arrangements of trees groups on the maximum water depth in buildings and the discharge capacity of the pressurized stormwater drainage network. Dike-break floods give rise to large-scale water leaps and the formation of thin layer water sheets near the buildings under the influence of buildings, water tank sidewalls, and tree groups. The water leap zones exhibit lateral migration and superposition on the sidewalks during the flood propagation, gradually dissipating and disappearing in the longitudinal direction of the street. In the presence of tree groups, the water levels significantly decrease in buildings and downstream street, while the discharge capacity of the pressurized stormwater drainage network shows a slight improvement as the road’s flood-carrying capacity increases. The pressure in the main pipes fluctuates due to the switching of the grate inlet drainage mode and the hydraulic transition process in the branch pipes. The research findings not only provide valuable validation data for numerical simulations but also offer theoretical guidance for urban flood management and landscape design.

Dam breach analysis of Kibimba Dam in Uganda using HEC-RAS and HEC-GeoRAS

Dam failures have severe consequences on human life and property. In the case of an earth filled Kibimba Dam located in Eastern Uganda, the occurrence of a flood equal to or larger than the probable maximum food (PMF) could result in catastrophic economic losses including loss of human life. This study utilized the USACE Hydrologic Engineering Center's River Analysis System (HEC-RAS) and Hydrologic Engineering Center’s Geographic River Analysis System (HEC-GeoRAS) to analyze the potential dam break of Kibimba Dam, considering overtopping and piping failure scenarios. The results of the analysis revealed that the spillway of Kibimba Dam possesses sufficient capacity to safely discharge a flood resulting from a probable maximum flood peak of 400 m3/s. Therefore, the dam is not susceptible to breach under the overtopping failure mode. However, the dam failed under the piping failure mode. To assess the downstream impact of the dam break, the breach hydrographs resulting from piping failure were examined. Consequently, the study investigated the effects of flood propagation downstream of the dam. This resulted in varying inundation depths of up to 6 m and velocities ranging from 1.2 to 10 m/s. These findings highlight the devastating consequences of Kibimba Dam's failure, particularly affecting rice field plantations, infrastructure, and other economic activities in the downstream area. Therefore, the outcomes of this study are crucial for the development of Emergency Action Plans that incorporate dam breach and flood routing analyses specific to the affected downstream regions.

Quantifying the relative contributions of different flood generating mechanisms to floods across CONUS

The occurrence of flooding in a catchment is attributable to various mechanisms. Several researchers have used linear models to quantify the relative contributions of different flood generating mechanisms. However, the use of linear models for this quantification may not be suitable given the complex and nonlinear processes from climate to floods. In this study, we used nonlinear machine learning models with interpretability methods to quantify the contributions of multiple flood generating mechanisms to floods across the continental United States (CONUS). Four flood generating mechanisms were considered comprehensively, which varied in terms of the influence of antecedent soil moisture condition or snowmelt on flood generation. These mechanisms involved three common mechanisms (rainfall, rainfall excess, and snowmelt/rain on snow) and one complex mechanism (effective precipitation) that accounts for snowmelt/rain on snow lost to unsaturated soil zone. Consistent with previous studies, we observed that rainfall alone (i.e., without considering other hydrometeorological processes) is seldom the dominant mechanism for flood generation. Floods in most catchments are largely attributable to rainfall excess and snowmelt. Unlike previous studies, we noted that in the midwest and northeastern CONUS, snowmelt/rain on snow upon saturated soil was the greatest contributor to local flood generation. This finding highlights that both snowmelt and soil moisture condition affect flood generation in the midwest and northeastern CONUS, instead of only snowmelt as has been reported previously. Overall, this study provides new insights into flood generating mechanisms in CONUS and demonstrates the potential of applying interpretable machine learning to examine flood generating mechanisms.

Momentum and mass transport and flow structure characteristics for the unsteady flow in compound channel

In recent decades, the study of steady flow in the compound channel has received much attention, while the flow characteristics of flood in the compound channel are rarely reported. In this paper, the characteristics of the flood propagation under different initial main channel depths are studied using the laboratory experiments and numerical simulation. Results show that the overflowing water from the main channel soon forms the reverse flow after hitting the floodplain sidewall. This reverse flow influences the subsequent overflowing process and significantly enhances the bed shear stress on the floodplain. However, this effect gradually decreases with the flood evolution distance and the increase of the initial downstream water depth. Unsteady transverse transport during flooding inhibits the formation of coherent eddies at the interface between the main channel and floodplain, while the high shear region will extend to the internal of the main channel or floodplain. Complex multi-vortex structures are found on the floodplain due to transverse interaction behavior. The main transverse mass transport takes place in the first half of the period after the flood arrival. It is found that the weir flow equations used in the previous studies are unable to accurately describe the transverse mass transfer between the main channel and floodplain. Secondary currents have a little contribution to the unsteady transverse momentum transport, while the transverse currents and transverse Reynolds stresses have a significant effect. The time when the peak transverse current arrives is later than that when the peak transverse Reynolds stresses does in the current study.

RETRACTED: Forecasting the Landslide Blocking River Process and Cascading Dam Breach Flood Propagation by an Integrated Numerical Approach: A Reservoir Area Case Study

This paper aims to introduce a numerical technique for forecasting the hazard caused by the disaster chain of landslide blocking river-dam breach floods through an integration of the distinct element method (DEM) and a well-balanced finite volume type shallow water model (SFLOW). A toppling slope in a reservoir area, the southeastern Tibetan Plateau, was chosen for the study. Creep has been observed in the potential instability area, and a possible sliding surface was identified based on the data collected from adits and boreholes. Catastrophic rock avalanches may be triggered after reservoir impoundment, and the associated landslide disaster chain needed to be predicted. First, the landslide blocking river process was modeled by the DEM using the three-dimensional particle flow code (PFC 3D). The landslide duration, runout distance, and kinematic characteristics were obtained. In addition, the landslide dam and barrier lake were constructed. Then, the cascading dam breach flood propagation was simulated using the self-developed SFLOW. The flow velocity, inundation depth, and area were obtained. The hazard maps derived from the combined numerical technique provided a quantitative reference for risk mitigation. The influences of two involved parameters on the final hazard-affected area are discussed herein. It is expected that the presented model will be applied in more prediction cases.

Integrated Approach for the Study of Urban Expansion and River Floods Aimed at Hydrogeomorphic Risk Reduction

Urbanization in flood-prone areas is a critical issue worldwide. The historical floods, the urban expansion in terms of building footprint, the extent and construction period of inundated buildings with reference to two representative floods (5–6 November 1994 and 24–25 November 2016), and the ground effects and dynamics of these events were investigated in the cities of Garessio, Ceva, and Clavesana, along the Tanaro River (NW Italy). An integrated approach based on historical data analysis, photograph interpretation, field surveys, and GIS investigations was adopted, and novel metrics for quantitative analysis of urbanization and flood exposure at the individual-building scale were introduced. The considered cities were hit by damaging floods several times over the last centuries and experienced an increase in built-up surface after the mid-19th century, especially between the 1930s and 1994. The 1994 and 2016 high-magnitude floods highlighted that urban expansion largely occurred in flood-prone areas, and anthropogenic structures conditioned flood propagation. One of the rare Italian cases of the relocation of elements exposed to floods is documented. This research aims to emphasize the relevance of information on past floods and urbanization processes for land planning and land management and the need for land use planning for flood control to forbid new urban expansion in potentially floodable areas. The outcomes represent an essential knowledge base to define effective and sustainable management measures to mitigate hydrogeomorphic risk.

Hydrodynamic modeling of ephemeral flow in the Iishana channel systems of the Cuvelai Basin—Northern Namibia

AbstractThe transboundary region of the Iishana system in the western Cuvelai Basin, between southern Angola and northern Namibia, is frequently affected by floods at irregular intervals. As a result, the predominantly rural, subsistence farming population has experienced crop failures, human, and economic losses. To date, very little is known about the generation of floods, flood concentration, and stormwater drainage dynamics in this region. In this study, 2D‐hydrodynamic modeling was applied to reconstruct one of the latest major flood events during the rainy season from November 2008 to March 2009 in order to study the runoff behavior and interconnectivity of the Iishana system. The model focused on the eastern part of the Iishana system, which was most affected by floods and flood damage due to the high population density in and around Oshakati, the regional capital. Two main streams were identified noteworthy because they merge and subsequently affect Oshakati. Regarding the simulated flood event water depths vary from 0.1 m to 14 m, with an average of 0.2 m, while water depths above 5 m were attributed to borrow pits. The inundation area ranged up to 1860 km2 and the amount of water left after the rainy season on March 25th, 2009, was determined between 0.116 and 0.547 km3, depending on the amount of evapotranspiration considered in the model. Thus, in the Angolan part of the Iishana system, significantly larger quantities of water are available for longer periods of time during the subsequent dry season, whereas the system in Namibia stores less water, resulting in a shorter water retention period.

Is there a consistency in basin morphometry and hydrodynamic modelling results in terms of the flood generation potential of basins? A case study from the Ulus River Basin (Türkiye)

Floods are natural phenomena that increase their impact every year due to increasing natural and anthropogenic variables, which are effective individually or together. Many research studies have focused on understanding the causative factors. This study aims to reveal whether there is a consistency in the results of the basin morphometry and hydrodynamic model used to understand the flood generation potential of river basins. Both analyses have been discussed individually in many papers but are not comprehensively compared. The Ulus settlement (Türkiye), where Ulus upstream, Suleyman, Alpi, and Eldes tributaries converge, was chosen as a study area. The results of the two analyses were evaluated in terms of their potential ability to produce floods over the subbasins and the Ulus settlement. Eight basin morphometric parameters were applied to the 10 m resolution TopoDEM data, and the results were evaluated according to the Normalised Morphometric Flood Index (NMFI) method, which helps decrease subjectivity in ranking the results. Flow data of the ungauged subbasins were produced using the SWAT rainfall-runoff model, and 2, 5, 10, 20, 50, 100, 200, 500, and 1000 years maximum flow data were generated using flood frequency analysis, and the different flow data were modelled based on 1 m LiDAR DEM using the LISFLOOD-FP 2D-hydrodynamic model. According to the results, the Suleyman subbasin has the highest flood generation potential in basin morphometry and hydrodynamic modelling. It is followed by the Alpi subbasin at high potential, Ulus upstream and Eldes subbasins at medium potential. As a result, we determine there is a consistency in basin morphometry and hydrodynamic modelling results. The basin morphometry and the developed NMFI can be used to determine and understand the flood-generating potential of basins or subbasins in data-scarce regions regarding flood modelling.

Model-based assessment of flood generation mechanisms over Poland: The roles of precipitation, snowmelt, and soil moisture excess

Hydrometeorological variability, such as changes in extreme precipitation, snowmelt, or soil moisture excess, in Poland can lead to fluvial flooding. In this study we employed the dataset covering components of the water balance with a daily time step at the sub-basin level over the country for 1952–2020. The data set was derived from the previously calibrated and validated Soil & Water Assessment Tool (SWAT) model for over 4000 sub-basins. We applied the Mann Kendall test and circular statistics-based approach on annual maximum floods and various potential flood drivers to estimate the trend, seasonality, and relative importance of each driver. In addition, two sub-periods (1952–1985 and 1986–2020) were considered to examine changes in flood mechanism in the recent decades. We show that floods in the northeast Poland were decreasing, while in the south the trend showed a positive behavior. Moreover, the snowmelt is a primary driver of flooding across the country, followed by soil moisture excess and precipitation. The latter seemed to be the dominant driver only in a small, mountain-dominated region in the south. Soil moisture excess gained importance mainly in the northern part, suggesting that the spatial pattern of flood generation mechanisms is also governed by other features. We also found a strong signal of climate change in large parts of northern Poland, where snowmelt is losing importance in the second sub-period in favor of soil moisture excess, which can be explained by the temperature warming and diminishing role of snow processes.