2D Hydraulic Model Research Articles

Vegetation disturbances and flood energy during an extreme flood on a sub‐tropical river

AbstractThe advent of 2D hydraulic modelling has improved our understanding of flood hydraulics, thresholds, and dynamic effects on floodplain geomorphology and riparian vegetation at the morphological‐unit scale. Hydraulic concepts of bed shear stress, stream power maxima, and energy (cumulative stream power) have been used to characterize floods and define their geomorphic effectiveness. These hydraulic concepts were developed in the context of reach‐averaged, 1D hydraulic analyses, but their application to 2D model results is problematic due to differences in the treatment of energy losses in 1D and 2D analyses. Here we present methods for estimating total and boundary resistance from 2D modelling of an extreme flood on a subtropical river. Hydraulic model results are correlated with observations of the flood impacts on floodplain geomorphology and the riparian vegetation to identify thresholds and compute variants of flood energy. Comparison of LiDAR data in 2011 and 2014 shows that the 2011 flood produced 2–4 m of erosion on floodplain bars that were previously forested or grass‐covered. Deposition on flood levees, dunes, and chute bars was up to 3.4 m thick. Various hydraulic metrics were trialled as candidates for thresholds of vegetation disturbance. The accuracy of thresholds using metrics extracted at the flood peak (i.e. boundary resistance and stream power maxima) was similar to that using energy as a threshold. Disturbance to forest and grass on vegetated bars was associated with stream powers of >834 W/m2and unit flows of >26 m2/s, respectively. Correlation of the hydraulic metrics with erosion and deposition depths showed no substantial improvement in using flood energy compared to metrics extracted at the flood peak for describing erosion and deposition. The extent of vegetation disturbances and morphological adjustments was limited for this extreme flood, and further 2D studies are needed to compare disturbance thresholds across different environments.

A paradigm of extreme rainfall pluvial floods in complex urban areas: the flood event of 15 July 2020 in Palermo (Italy)

Abstract. In the last few years, some regions of the Mediterranean area have witnessed a progressive increase in extreme events, such as urban and flash floods, as a response to the increasingly frequent and severe extreme rainfall events, which are often exacerbated by the ever-growing urbanization. In such a context, the urban drainage systems may not be sufficient to convey the rainwater, thus increasing the risk deriving from the occurrence of such events. This study focuses on a particularly intense urban flood that occurred in Palermo (Italy) on 15 July 2020; it represents a typical pluvial flood due to extreme rainfall on a complex urban area that many cities have experienced in recent years, especially in the Mediterranean region. A conceptual hydrological model and a 2D hydraulic model, particularly suitable for simulations in a very complex urban context, have been used to simulate the event. Results have been qualitatively validated by means of crowdsourced information and satellite images. The experience of Palermo, which has highlighted the urgent need for a shift in the way stormwater in urban settlements is managed, can be assumed to be a paradigm for modeling pluvial floods in complex urban areas under extreme rainfall conditions. Although the approaches and the related policies cannot be identical for all cities, the modeling framework used here to assess the impacts of the event under study and some conclusive remarks could be easily transferred to other, different urban contexts.

A Conflict between Traditional Flood Measures and Maintaining River Ecosystems? A Case Study Based upon the River Lærdal, Norway

Floods are among the most damaging of natural disasters, and flood events are expected to increase in magnitude and frequency with the effects of climate change and changes in land use. As a consequence, much focus has been placed on the engineering of structural flood mitigation measures in rivers. Traditional flood protection measures, such as levees and dredging of the river channel, threaten floodplains and river ecosystems, but during the last decade, sustainable reconciliation of freshwater ecosystems has increased. However, we still find many areas where these traditional measures are proposed, and it is challenging to find tools for evaluation of different measures and quantification of the possible impacts. In this paper, we focus on the river Lærdal in Norway to (i) present the dilemma between traditional flood measures and maintaining river ecosystems and (ii) quantify the efficiency and impact of different solutions based on 2D hydraulic models, remote sensing data, economics, and landscape metrics. Our results show that flood measures may be in serious conflict with environmental protection and legislation to preserve biodiversity and key nature types.

Coupling a 1D-local inertia 2D hydraulic model for flood dispatching simulation in a floodplain under joint control of multiple gates

Coupling a 1D-local inertia 2D hydraulic model for flood dispatching simulation in a floodplain under joint control of multiple gates

Uncertainties in Riverine and Coastal Flood Impacts under Climate Change

Climate change can affect different drivers of flooding in low-lying coastal areas of the world, challenging the design and planning of communities and infrastructure. The concurrent occurrence of multiple flood drivers such as high river flows and extreme sea levels can aggravate such impacts and result in catastrophic damages. In this study, the individual and compound effects of riverine and coastal flooding are investigated at Stephenville Crossing located in the coastal-estuarine region of Newfoundland and Labrador (NL), Canada. The impacts of climate change on flood extents and depths and the uncertainties associated with temporal patterns of storms, intensity–duration–frequency (IDF) projections, spatial resolution, and emission scenarios are assessed. A hydrologic model and a 2D hydraulic model are set up and calibrated to simulate the flood inundation for the historical (1976–2005) as well as the near future (2041–2070) and far future (2071–2100) periods under Representative Concentration Pathways (RCPs) 4.5 and 8.5. Future storm events are generated based on projected IDF curves from convection-permitting Weather Research and Forecasting (WRF) climate model simulations, using SCS, Huff, and alternating block design storm methods. The results are compared with simulations based on projected IDF curves derived from statistically downscaled Global Climate Models (GCMs). Both drivers of flooding are projected to intensify in the future, resulting in higher risks of flooding in the study area. Compound riverine and coastal flooding results in more severe inundation, affecting the communities on the coastline and the estuary area. Results show that the uncertainties associated with storm hyetographs are considerable, which indicate the importance of accurate representation of storm patterns. Further, simulations based on projected WRF-IDF curves show higher risks of flooding compared to the ones associated with GCM-IDFs.

Accurate Open Channel Flowrate Estimation Using 2D RANS Modelization and ADCP Measurements

Boat-mounted Acoustic Doppler Current Profilers (ADCP) are commonly used to measure the streamwise velocity distribution and discharge in rivers and open channels. Generally, the method used to integrate the measurements is the velocity-area method, which consists of a discrete integration of flow velocity over the whole cross-section. The discrete integration is accomplished independently in the vertical and transversal direction without assessing the hydraulic coherence between both dimensions. To address these limitations, a new alternative method for estimating the discharge and its associated uncertainty is here proposed. The new approach uses a validated 2D RANS hydraulic model to numerically compute the streamwise velocity distribution. The hydraulic model is fitted using state estimation (SE) techniques to accurately reproduce the measurement field and hydraulic behaviour of the free-surface stream. The performance of the hydraulic model has been validated with measurements on two different trapezoidal cross-sections in a real channel, even with asymmetric velocity distribution. The proposed method allows extrapolation of measurement information to other points where there are no measurements with a solid and consistent hydraulic basis. The 2D-hydraulic velocity model (2D-HVM) approach discharge values have been proven more accurate than the ones obtained using velocity-area method, thank to the enhanced use of the measurements in addition to the hydraulic behaviour represented by the 2D RANS model.

Using decades of spawning data and hydraulic models to construct a temperature-dependent resource selection function for management of an endangered salmonid

In North America, impassable, man-made barriers block access to salmonid spawning habitat and require costly restoration efforts in the remaining habitats. Evaluating restored spawning habitat quality requires information on salmon water velocity and depth preferences, which may vary in relation to other variables (e.g., water temperature). We demonstrate a generalizable, low-cost method to gather and analyze these data by combining aerial redd surveys of winter-run Chinook salmon (Oncorhynchus tshawytscha), 2D hydraulic modeling, and generalized linear models to calculate spawning resource selection functions (RSFs). Our method permits the examination of interactions between environmental variables and habitat selection, which are frequently treated as independent. Our methods resulted in an RSF that shows interactions between both velocity and depth preference with changing temperature. Preferred depth increased and preferred velocity decreased with increasing temperature. Spawning RSFs for environmental variables may change as other environmental conditions (i.e., water temperature) change; thus, it is important to account for potential interactions when using or producing RSFs.

Towards a management strategy for microplastic pollution in the Laurentian Great Lakes - Monitoring (Part 1)

Plastic contamination extends across all Great Lakes ecosystems, including in wildlife, with the potential for risk based on laboratory experiments and risk assessment. Due to widespread contamination, and based on evidence suggesting measurable risk, it is time for policy-makers to develop and implement monitoring programs to guide management . Here, we discuss the need for a monitoring strategy with clear guidelines. We synthesize the research that has been published across the Great Lakes, reporting on contamination, regions that have been the focus of study, and the methods used across matrices. Based on our findings, we suggest how research may inform guidelines and next steps – especially if microplastics are to be considered as a Toxic Chemicals sub-indicator under the Great Lakes Water Quality Agreement. Future monitoring, using standard and/or harmonized protocols for sampling and analysis, should build baselines across the basin and begin tracking how contamination changes to assess the health of the Great Lakes, to inform source-reduction, and to measure the effectiveness of policies aimed at reducing emissions of plastics to freshwater.

Modeling spatial distribution of flow depth in fluvial systems using a hybrid two-dimensional hydraulic-multigene genetic programming approach

Modeling spatial distribution of flow depth in fluvial systems is crucial for flow mitigation, river rehabilitation, and design of water resources infrastructure. Flow depth in fluvial systems can be typically estimated using hydrological or physics-based hydraulic models. However, hydrological models may not be able to provide satisfactory predictions for catchments with limited data because they normally ignored the strict conservation of momentum. Traditional fully physics-based hydraulic models are often very computationally expensive, limiting their wide usage in practical applications. In this study, a novel method, based on a hybrid two-dimensional (2D) hydraulic-multigene genetic programming (MGGP) approach, is proposed and employed to model the spatial distribution of flow depth in fluvial systems. A 2D hydraulic model was constructed using the TELEMAC-2D software and validated against field measurements. The validated model was then assumed to reflect the real physical processes and utilized to carry out additional computations to obtain spatial distribution of flow depth under different discharge scenarios, which provided a sufficient synthetic dataset for training machine learning models based on the MGGP technique. The study area (a segment of the Ottawa River near the island named Île Kettle) was divided into 34 sub-regions to further reduce the computational costs of the training processes and the complexity of the evolved models. The numerical data were distributed to the corresponding sub-regions, and an MGGP-based model was trained for each sub-region. These models are compact explicit arithmetic equations that can be readily transferable and can immediately output the flow depth at any point in the corresponding sub-region as functions of the flow rate, longitudinal, and transversal coordinates. The best MGGP model for each sub-region amongst all the generated models was identified using the Pareto optimization approach. The results showed that the best MGGP models satisfactorily reproduced the training data and predicted the testing data (the root mean square errors were 0.303 m and 0.306 m, respectively), demonstrating the predictive capability of the approach. A comparison between MGGP and single-gene genetic programming (SGGP) approaches and confidence analysis were also reported, which demonstrated the good performance of the proposed approach. Furthermore, it took about 53 min for the hydraulic model to complete each simulation, but it took only about 0.56 s using the final model; the total size of the hydraulic output files for 12 different sizes was 432, 948 KB, but the total size of the script file for the final model was only about 46 KB. Therefore, the present study found that the hybrid 2D hydraulic-MGGP approach was satisfactorily accurate, fast to run, and easy to use, and thus, it is a promising tool for modeling spatial distribution of flow depth in fluvial systems.

Reconstructing the peak flow of historical flood events using a hydraulic model: The city of Bath, United Kingdom

AbstractHistorical flood events on the River Avon in the city of Bath were reconstructed using a 1D hydraulic model. The model represents the river prior to the completion of the Bath flood defence scheme and was developed based on archived data on archival materials including historical cross sections of channel geometry, technical drawings of hydraulic structures, descriptions of floodplain extent, epigraphic markings and photographs. The model was calibrated on two historical floods for which peak flow values were available from hydrological data (March 1947 and December 1960) and the calibration was based on adjustment of Manning's n as well as the introduction of floodplains identified from historical maps and photos. Subsequently, the peak flow was assessed for a total of 16 events for which flood marks existed in the centre of the city. A composite annual maximum series of peak flow was created upstream of Bath city centre and presented a flow series consisting of data from 1866 to present day. Finally, flood frequency analysis was undertaken on the dataset, showing that the inclusion of historical floods increased the 1 in 100 year design flood by up to 30%, that is, a substantial influence.

Usando modelado hidráulico en 2D junto con SfM y YouTube para estimar caudal pico

espanolA pesar de los grandes danos causados por los eventos de lluvia de El Nino-Oscilacion del Sur (ENSO), sigue habiendo una escasez de registros de caudales de inundaciones repentinas en Manta, una de las ciudades mas grandes de Ecuador. Para abordar tal brecha de datos, esta investigacion presenta una nueva linea de flujo de trabajo para hacer uso de datos de fuentes multiples; en especifico, combinamos modelos hidraulicos bidimensionales (2D) convencionales con Structure-from-Motion (SfM) y videos de YouTube para obtener estimaciones indirectas fiables de caudal maximo para un rio efimero no aforado. Las estimaciones se realizan posterior a las inundaciones. Se obtuvo un modelo de elevacion digital (DEM) de resolucion submetrica del tramo del rio utilizando SfM; los niveles de agua maximos observados de los videos de YouTube se compararon con varias simulaciones hidraulicas en 2D para encontrar el mejor ajuste dentro de 0.43 m. Las observaciones de la velocidad del agua confirmaron esas estimaciones de caudal. La investigacion en este documento indica que los flujos de trabajo novedosos que incluyen datos de codigo abierto disponibles gratuitamente en las plataformas de redes sociales pueden proporcionar estimaciones indirectas de caudales maximos y, en lo posterior, pueden convertirse en una herramienta para gestion de riesgo de inundaciones. EnglishDespite the major damages caused by El Nino South Oscillation (ENSO) rainfall events, there remains a paucity of discharge records for flash floods in Manta, one of Ecuador’s largest cities. To address this data gap, this research presents a new workflow pipeline to make use of crowd-sourced data; specifically, we couple conventional two dimensional (2D) hydraulic modelling with Structure-from-Motion (SfM) and YouTube videos to obtain reliable post-flood, indirect estimates of peak discharge for an ungauged ephemeral river. A sub-metre-resolution Digital Elevation Model (DEM) of the river reach was obtained using SfM; the estimated “observed” high water levels from YouTube videos were compared against several 2D hydraulic simulations to find the best fit of 0.43 m. Water velocity observations confirmed these discharge estimates. The research herein indicates that novel workflows, including open-source data freely available on social media platforms, can provide indirect peak discharge estimates and, looking further ahead, can become a tool for flood risk management.

Development and classification of flood hazard map using 2D hydraulic model

A flood happens when water floods wet land. In Iraq, there have been floods several times in the Tigris River, but the flood in 2019 was one of the major events that have greatly affected Maysan city. This paper shows the study of Maysan’s extreme flood with hydraulic models. HEC-RAS two dimensional has been utilized to model the action of the study area from the downstream of Kut Barrage to Al-Musandaq escape, at the Tigris River. The model includes descriptions of simulated temporal parameters such as water depth and flow velocity. HEC-RAS Validation of simulated flood outcomes was done by correlation coefficient (r) Equation Between simulated and observed data, where the coefficient of r for calibrating the Tigris River and the Al-Musandaq escape was 0.995 and 0.991 in an appropriate range, respectively. The validation results demonstrated that the HEC-RAS model performance is highly efficient and can be implemented for design and production by hydrologists or water resources engineers.

Flood Hazard Assessment for the Tori Levee Breach of the Indus River Basin, Pakistan

Levee breaches are some of the most common hazards in the world and cause the loss of lives, livelihoods, and property destruction. During the 2010 flood in Pakistan, the most devastating breach occurred at Tori Levee on the right bank of the Indus River, downstream of the Guddu Barrage, which caused residual floods in northern Sindh and the adjoining regions of the Balochistan province. In this study, 2D unsteady flow modeling performed for Tori Levee breach computed residual flood inundation by coupling a HEC-RAS (Hydrological Engineering Centre—River Analysis System) 2D hydraulic model with remote sensing and Geographic Information System techniques. The model performance was judged by comparing the observed and simulated water levels (stage) during peak flow at seven different gauging stations located within the Indus River reach and daily flood extents and multi-day composites. The quantitative values for the calibration and validation of the HEC-RAS model showed good performance with a range of difference from 0.13 to −0.54 m between the simulated and observed water levels (stage), 84% match for the maximum flood inundation area, and 73.2% for the measure of fit. The overall averages of these values for the daily flood comparison were 57.12 and 75%, respectively. Furthermore, the simulated maximum flow passed through the Tori Levee breach, which was found to be 4994.47 cumecs (about 15% of peak flow) with a head water stage of 71.56 m. By using the simulated flows through the Tori Levee breach, the flood risk maps for the 2010 flood identified hazard zones according to the flood characteristics (depth, velocity, depth times velocity, arrival time, and duration). All the flood risk maps concluded the fact that the active flood plain was uninhabitable under flood conditions.

Field based index of flood vulnerability (IFV): A new validation technique for flood susceptible models

The flood hazard management is one of the major challenges in the floodplain regions worldwide. With the rise in population growth and the spread of infrastructural development, the level of risk has increased over time. Therefore, the prediction of flood susceptible area is a key challenge for the adoption of management plans. Flood susceptibility modeling is technically a common work, but it is still a very tough job to validate flood susceptible models in a very rigorous and scientific manner. Therefore, the present work in the Atreyee River Basin of India and Bangladesh was planned to establish artificial neural network (ANN), radial basis function (RBF), random forest (RF) and their ensemble-based flood susceptibility models. The flood susceptible models were constructed based on nine flood conditioning parameters. The flood susceptibility models were validated in a conventional way using the receiver operating curve (ROC). To validate the flood-susceptible models, a two dimensional (2D) hydraulic flood simulation model was developed. Also, the index of flood vulnerability model was developed and applied for validating the flood susceptible models, which was a very unique way to validate the predictive models. Friedman test and Wilcoxon Signed rank test were employed to compare the generated flood susceptible models. Results showed that 11.95%–12.99% of the entire basin area (10188.4 km2) comes under very high flood-susceptible zones. Accuracy evaluation results have shown that the performance of ensemble flood susceptible models outperforms other standalone machine learning models. The flood simulation model and IFV model were also spatially adjusted with the flood susceptibility models. Therefore, the present study recommended for the ensemble flood susceptibility prediction and IFV based validation along with conventional ways.

Flood risk modeling in the watershed of Charâa stream, Province of Berkane (North-Eastern Morocco)

The knowledge on floods in Morocco is sporadic and scattered between historical writings and natural events following each other in time and space. In this context, the identification of areas likely to be affected by floods is essential for better management of this risk. The present study aims to model the floods at the level of the two sides of the Charâa stream (the side of Berkane and Sidi Slimane Charâ). The methodology followed in this modeling consists of determining the geomorphology of the watershed and studying its hydrology. 2D hydraulic modeling by Iber software makes it possible to follow the Spatio-temporal evolution of the characteristics of a flood. In addition, it allows us to map the hazard. Furthermore, to assess vulnerability to flooding, we referred to land use (physical vulnerability) to study the behavior of runoff water in the face of socioeconomic issues such as buildings, facilities, and the road network. The results showed that: (1) - A predominance of high-intensity flood hazard in the floodplain; (2) - Land with medium and high vulnerability successively constitutes 46.50% and 31.10% of the total studied watershed area.

Using 2D HEC-RAS Modeling and Embankment Dam Break Scenario for Assessing the Flood Control Capacity of a Multi-Reservoir System (NE Romania)

Using hydraulic modeling techniques (e.g., one-dimensional/two-dimensional (1D/2D) hydraulic modeling, dam break scenarios) for extracting the flood settings is an important aspect of any action plan for dam failure (APDF) and flood mitigation strategy. For example, the flood hydraulic models and dam break scenario generated based on light detection and ranging (LiDAR)-derived digital elevation models (DEMs) and processed in the dedicated geographic information systems (GIS) and hydraulic modeling software (e.g., HEC-RAS—Hydrologic Engineering Center River Analysis System, developed by USACE HEC, Davis, CA, USA) can improve the flood hazard maps in case of potentially embankment dam failure. In this study, we develop a small-scale conceptual approach using 2D HEC-RAS software according to the three embankment dam break scenarios, LiDAR data (0.5 m spatial resolution), and 2D hydraulic modeling for the Başeu multi-reservoir system which belongs to the Başeu River (NE Romania) including R1—Cal Alb reservoir, R2—Movileni reservoirs, R3—Tătărăşeni reservoirs, R4—Negreni reservoirs, and R5—Hăneşti reservoirs. In order to test the flood control capacity of the Bașeu multi-reservoir system, the Cal Alb (R1) dam break scenario (piping failure) was taken into account. Three 2D stream flow modeling configurations based on R1 inflow rate with a 1% (100 year), 0.5% (500 year), and 0.1% (1000 year) recurrence interval and the water volume which can be accumulated with that specific inflow rate (1% = 10.19 × 106 m3; 0.5% = 12.39 × 106 m3; 0.1% = 17.35 × 106 m3) were computed. The potential flood wave impact was achieved on the basis of different flood severity maps (e.g., flood extent, flood depth, flood velocity, flood hazard) generated for each recurrence interval scenario and highlighted within the built-up area of 27 settlements (S1–S27) located downstream of R1. The results showed that the multi-reservoir system of Bașeu River has an important role in flood mitigation and contributes to the APDF in the context of climate change and the intensification of hydrological hazard manifestation in northeastern Romania.

Hydraulic Modelling of Riverbed Embankment Under the Hričov Weir

The weir of the Hričov water structure has an untypical shortened stilling basin, which affects significant scour development in the downstream riverbed. A rockfill embankment structure adjacent to the stilling basin was constructed to prevent the formation of scours in the riverbed. However, increased flows at the weir erode this fortification and it is necessary to replenish the material back to the embankment after the flow situations. A 2D hydraulic model constructed in a flume of the Hydraulic laboratory was used for the research of new downstream fortification, which would be better resist the scouring effects. The model was created according to Froude’s modelling similarity as a 2D model of the weir structure with control gates and part the downstream riverbed consisting of gravel. Different designs of the embankment were not allowed to interfere with the existing construction of the water structure. The construction of the embankment was designed as a concrete “secondary” stilling basin adjacent to the existing one. Tested variants of the embankment were of different length and depth of the stilling basin. The length varied from 11 to 24 m and the depths varied from 0 to 1,8 m. Overall 11 different design of the embankment were investigated. Each design was tested for three different flow rates on the model simulating common and extreme flow situations at the weir. The flows were selected to simulate also different hydraulic phenomena at the weir – overflow, outflow, and free overflow. After each flow simulation the scour in the riverbed was measured. The measured scour parameters were depth of the scour, the distance of the deepest point from the existing water structure and the amount of the material carried away. The resulting parameters were assessed with respect to each other for the corresponding flow rates. The best results in scour reduction were achieved for horizontal embankment with the depth of 0 m. The designs with increased depth were causing secondary hydraulic jump in the riverbed which increased the scours. The tested designs of the embankments were able to reduce scour size by up to 45% for the outflow, by less than 20% for free overflow and by more than 80% at the overflow.

A new average wave overtopping prediction formula with improved accuracy for smooth steep low-crested structures

Wave overtopping is a key process in coastal protection and its assessment defines the design of the sea defence structures. An existing knowledge gap in wave overtopping prediction is identified for steep low-crested structures, i.e., structures with steep slopes up to the limit case of vertical structures, with small relative freeboards down to the limit case of zero freeboards. This type of structure is increasingly relevant in a sea level rise context due to climate change. Additionally, steep low-crested structures are also of interest when used as overtopping wave energy converters. To cover the identified knowledge gap, more than 900 2D hydraulic model tests have been performed in the wave flume of the Department of Civil Engineering at Ghent University. Wave conditions and the overtopping performance have been measured. After analysing the average overtopping rates of the new tests, we found that there is a lack of accuracy of the recommended EurOtop 2018 manual overtopping prediction formulae for steep low-crested structures. Based on the new tests, a new average overtopping prediction formula for steep low-crested structures is obtained. This formula improves the prediction accuracy of the average overtopping rates for steep low-crested structures with respect to the recommended predictions in the EurOtop 2018 manual by reducing the RMSE by 35% for zero freeboards, by 16% for very small relative freeboards, by 31% for very steep slopes and by 24% for vertical structures. The accuracy of the EurOtop 2018 manual predictions for other structural types is maintained.

New Insights on Flood Mapping Procedure: Two Case Studies in Poland

The use of the Mike11 one-dimensional (1D) hydraulic model, together with official hydrology, represents a standard approach of the National Water Management Authority (NWMA) in Poland for flood mapping procedures. A different approach, based on the hydrological Event-Based Approach for Small and Ungauged Basins (EBA4SUB) model and the Flood-2 Dimensional (FLO-2D) hydraulic model has here been investigated as an alternative procedure. For the analysis, two mountainous rivers in Poland were selected: Kamienica Nawojowska is characterized by a narrow valley, while Skawinka has a broad valley. It was found that the flood zones can enormously differ locally, with larger zones generated by the Mike11/NWMA model in some cases and by the EBA4SUB/FLO-2D model in other situations. The benefits of using the two-dimensional (2D) model are consistent in areas without drainage and where the connection to the main channel is insufficient. The use of 1D modeling is preferred for the possibility of mapping the entire river network in a short computational time.

A deep convolutional neural network model for rapid prediction of fluvial flood inundation

Most of the two-dimensional (2D) hydraulic/hydrodynamic models are still computationally too demanding for real-time applications. In this paper, an innovative modelling approach based on a deep convolutional neural network (CNN) method is presented for rapid prediction of fluvial flood inundation. The CNN model is trained using outputs from a 2D hydraulic model (i.e. LISFLOOD-FP) to predict water depths. The pre-trained model is then applied to simulate the January 2005 and December 2015 floods in Carlisle, UK. The CNN predictions are compared favourably with the outputs produced by LISFLOOD-FP. The performance of the CNN model is further confirmed by benchmarking against a support vector regression (SVR) method. The results show that the CNN model outperforms SVR by a large margin. The CNN model is highly accurate in capturing flooded cells as indicated by several quantitative assessment matrices. The estimated error for reproducing maximum flood depth is 0–0.2 m for the 2005 event and 0–0.5 m for the 2015 event at over 99% of the cells covering the computational domain. The proposed CNN method offers great potential for real-time flood modelling/forecasting considering its simplicity, superior performance and computational efficiency.