Coupled 1D 2D Research Articles

The Development of Coupled 1D–2D Hydrodynamic Flood Model by Using HEC-RAS: a Case Study of the Panchganga River Basin, Kolhapur District, Maharashtra, India

The Development of Coupled 1D–2D Hydrodynamic Flood Model by Using HEC-RAS: a Case Study of the Panchganga River Basin, Kolhapur District, Maharashtra, India

Comparison of 1D, coupled 1D–2D, and 2D shallow water numerical modeling for dam-break flow analysis of Way-Ela dam, Indonesia

This study analyzes the flood inundation area using shallow water numerical modeling with HEC-RAS 6.3 software by comparing 1D, coupled 1D–2D, and 2D approaches. As a case study, the 2013 Way-Ela dam-break event in Indonesia is selected. Way-Ela Dam naturally formed by landslides in 2012, collapsed due to a piping mechanism after a heavy rainfall event. To estimate the breach outflow hydrograph, an empirical parametric model based on regression formula is used. Compared with the observed data, the numerical results show the 2D model produces the most accurate results among others, with reasonable computational time, while the 1D model, despite being computationally very efficient, misinterprets the flood extent map. The coupled 1D–2D model produces results similar to that of the 2D model; however, this coupled approach, which is expected to be more computationally efficient than the 2D one, interestingly yields a significantly longer calculation time. Some possible reasons are thus discussed. Additionally, comparisons for the water level and velocity are also presented in several locations to point out the difference between each model. Our finding informs the selection of an appropriate hydrodynamic model for dam-break simulations, balancing the result accuracy and computational cost.

Application of machine learning-based surrogate models for urban flood depth modeling in Ho Chi Minh City, Vietnam

Rapid flood prediction in coastal urban areas is an important but challenging task. However, multi-driver floods in coastal areas and their non-linearity in physical processes are hard to represent in physics-based numerical models (PBNMs). In this study, we investigated the performance of surrogate machine learning (ML) models and their flood prediction capability. Initially, we utilize the MIKE+ coupled 1D–2D model to simulate coastal urban flooding in one of the severely flood-affected areas of Ho Chi Minh City (HCMC), Vietnam. Then, nine ML models, including AdaBoost (AB), Decision Tree (DT), Gaussian Process (GP), k-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), Neural Network (NN), Random Forest (RF), and Support Vector Machine (SVM) are employed to surrogate the PBNM flood prediction performance and engaged to predict flood depths of the study area domain. 806 simulation scenarios of MIKE+ modeling having a spatial grid of 1107 ×1513, grid size = 2 m, extracting 270,000 inundation points to generate input data for nine ML models are used to simulate surface flood depths for the study area. Results show three ML models, GP, RF, and NN, outperform the remaining models, with R2 value of 0.997, 0.996, and 0.995, respectively. Thus, applying ML models can significantly reduce the simulation time by a PBNM, improve accuracy, and potentially be adopted for real-time forecasting and emergency management.

Process‐Based Flood Risk Assessment for Germany

AbstractLarge‐scale flood risk assessments are crucial for decision making, especially with respect to new flood defense schemes, adaptation planning and estimating insurance premiums. We apply the process‐based Regional Flood Model (RFM) to simulate a 5000‐year flood event catalog for all major catchments in Germany and derive risk curves based on the losses per economic sector. The RFM uses a continuous process simulation including a multisite, multivariate weather generator, a hydrological model considering heterogeneous catchment processes, a coupled 1D–2D hydrodynamic model considering dike overtopping and hinterland storage, spatially explicit sector‐wise exposure data and empirical multi‐variable loss models calibrated for Germany. For all components, uncertainties in the data and models are estimated. We estimate the median Expected Annual Damage (EAD) and Value at Risk at 99.5% confidence for Germany to be €0.529 bn and €8.865 bn, respectively. The commercial sector dominates by making about 60% of the total risk, followed by the residential sector. The agriculture sector gets affected by small return period floods and only contributes to less than 3% to the total risk. The overall EAD is comparable to other large‐scale estimates. However, the estimation of losses for specific return periods is substantially improved. The spatial consistency of the risk estimates avoids the large overestimation of losses for rare events that is common in other large‐scale assessments with homogeneous return periods. Thus, the process‐based, spatially consistent flood risk assessment by RFM is an important step forward and will serve as a benchmark for future German‐wide flood risk assessments.

Estimation of rainfall threshold for flood warning for small urban watersheds based on the 1D–2D drainage model simulation

Flood warning systems can provide an effective and low-cost solution to protect urban residents especially in developing countries suffering from severe flood damages caused by weak capacity of flood defense structures. Rainfall Threshold for Flood Warning (RTFW) is an essential key of accurate flood warning system. This study proposed an easy-to-use mathematical equation for RTFW for small urban watersheds based on computer simulations. First, a coupled 1D–2D dual-drainage model was used to simulate the flooded area in nine watersheds of Seoul, Korea corresponding to 540 scenarios of various synthetic rainfall events and watershed imperviousness. Then, the results of the 101 simulations that caused the critical flooded depth (0.25 m–0.35 m) were used to develop the equation that relates the value of RTFW to the rainfall event temporal variability (represented as coefficient of variation or CV) and the watershed imperviousness (represented as NRCS Curve Number or CN). The results suggest that (1) RTFW exponentially decreases as the rainfall CV increases; (2) RTFW linearly decreases as the watershed CN increases; and that (3) RTFW is dominated by CV when the rainfall has low temporal variability (e.g., CV < 0.2) while RTFW is dominated by CN when the rainfall has high temporal variability (e.g., CV > 0.4). For validation, the proposed equation was applied for the flood warning system with two storm events occurred in 2010 and 2011 over 239 watersheds in Seoul. The system showed the hit, false and missed alarm rates at 69% (48%), 31% (52%) and 6.7% (4.5%), respectively for the 2010 (2011) event.

Simulation of the Hydrodynamic Functioning of the Cavally River Using a Coupled 1D-2D Model in the Ity Area (Zouan-Hounien in C&amp;#244;te d’Ivoire)

In recent years, the Cavally River has been subject to multiple activities, including the construction of diversion channels and a bridge that makes it vulnerable to flooding. In order to assess the impact of these hydraulic structures on the river hydrodynamic functioning, a 1D-2D model was realized. The implementation of the 1D-2D model consisted of first running the 1D model, then the 2D model, and finally in coupling them. The 1D-2D model was designed with the 1988 flood hydrograph, a Manning’s coefficient of 0.052 m1/3/s for the minor bed and 0.06 m1/3/s for the major bed. The results of the hydraulic model show that the velocities are almost identical to those of the Cavally in natural operation. The values of the velocities are included between 0.4 m/s and 1.3 m/s at the level of the minor bed of the river and between 0.06 m/s and 0.71 m/s at the level of the floodplains. The average water level for flood propagation is 262.37 ± 0.44 m before construction of the structures and 262.23 ± 0.85 m after construction of the structures. The 0.41 m reduction in water level due to the diversion canal and bridge is negligible compared to the total fluctuations of the Cavally River, which vary from 6 to 7 m over the year.

Case Study of HEC-RAS 1D–2D Coupling Simulation: 2002 Baeksan Flood Event in Korea

Recent studies strongly suggest the possibility of more frequent extreme events as a result of the changing climate. These weather extremes, such as excessive rainfall, result in debris flow, river overflow and urban flooding, which can pose a substantial threat to the community. An effective flood model is therefore a crucial tool in flood disaster control and mitigation. A number of flood models have been established in recent years. However, the major challenge in developing effective and accurate flood models is the disadvantage of running multiple models for separate, individual conditions. Among the solutions in recent research is the development of combined 1D–2D flood modeling. Coupled 1D–2D flood modeling allows the channel flows to be represented in 1D and the overbank flow to be modeled in 2D. In order to test the efficiency of the approach, this research aims to assess the capability of the U.S. Army Corps of Engineers Hydrologic Engineering Center River Analysis System (HEC-RAS) model’s implementation of the combined 1D–2D hydraulic computation in simulating river overflow inundation. For verification, the simulation is applied to the Baeksan river levee breach event in South Korea in 2011. The simulation results show similarities of the observed data and the outputs from widely used flood models. This proves the applicability of the HEC-RAS 1D–2D coupling method as a powerful tool in simulating accurate inundations for flood events.

High-resolution flood hazard mapping based on nonstationary frequency analysis: case study of Ho Chi Minh City, Vietnam

ABSTRACT Flood modelling inputs used to create flood hazard maps are normally based on the assumption of data stationarity for flood frequency analysis. However, changes in the behaviour of climate systems can lead to nonstationarity in flood series. Here, we develop flood hazard maps for Ho Chi Minh City, Vietnam, under nonstationary conditions using extreme value analysis, a coupled 1D–2D model and high-resolution topographical data derived from LiDAR (Light Detection and Ranging) data. Our findings indicate that ENSO (El Niño Southern Oscillation) and PDO (Pacific Decadal Oscillation) influence the magnitude and frequency of extreme rainfall, while global sea-level rise causes nonstationarity in local sea levels, having an impact on flood risk. The detailed flood hazard maps show that areas of high flood potential are located along river banks, with 0.60 km2 of the study area being unsafe for people, vehicles and buildings (H5 zone) under a 100-year return period scenario.

Hyper-resolution 1D-2D urban flood modelling using LiDAR data and hybrid parallelization

Coupled 1D-2D modelling is a widely used approach to predict water movement in complicated surface and subsurface drainage systems in urban or peri-urban areas. In this study, a hybrid parallel code, H12, is developed for 1D-2D coupled urban flood modelling. Hybrid-1D-2D, or H12, enables street-resolving hyper-resolution simulation over a large area by combining Open Multi-Processing (OpenMP) and Message Passing Interface (MPI) parallelization. Variable grid sizing is adopted for detailed geometric representation of urban surfaces as well as efficient computation. To assess the capability of H12, simulation experiments were carried for the Johnson Creek Catchment (∼40 km2) in Arlington, Texas. The LiDAR-derived digital elevation model (DEM) and detailed land cover map at 1-m resolution are used to represent the terrain and urban features in flood modelling. Hybrid parallelization achieves up to a 79-fold reduction in simulation time compared to the serial run and is more efficient than either OpenMP or MPI alone especially in hyper-resolution simulations.

A Coupled 1D-2D Hydrodynamic Model for Urban Flood Inundation

Hydrodynamic models were commonly used for flood risk management in urban area. This paper presents initial efforts in developing an urban flood inundation model by coupling a one-dimensional (1D) model with a two-dimensional (2D) model to overcome the drawbacks of each individual modelling approach, and an additional module is used to simulate the rainfall-runoff process in study areas. For the 1D model, the finite difference method is used to discretize the Saint-Venant equations. An implicit dual time-stepping method (DTS) is then applied to a 2D finite volume model for an inundation simulation to improve computational efficiency. A total of four test cases are applied to validate the proposed model; its performance is demonstrated by a comparison with an explicit scheme and previously published results (an extensive physical experiment benchmark case, a vertical linking example, and two real drainage cases with actual topography). Results demonstrate that the proposed model is accurate and efficient in simulating urban floods for practical applications.

Large-scale flood risk assessment using a coupled model chain

Large-scale flood risk assessments are needed for a number of purposes, such as national strategic planning or re-insurance purposes. However, large-scale assessments are typically limited to hazard assessment and/or they are pieced together from smaller-scale assessments, leading to spatially inconsistent hazard and risk estimates. We present the coupled model chain RFM (Regional Flood Model) which is able to derive spatially consistent hazard and risk estimates for large scales (several 100,000 km2 ). It consists of a hydrological model, a coupled 1D–2D hydrodynamic model and a flood loss model. This model chain can be driven by observed meteorology, output from regional climate models or a weather generator. In this application, we demonstrate for river basins in Germany that this approach is able to provide spatially consistent large-scale patterns of hazard and risk. A multi-site, multi-variate weather generator provides 10,000 years of spatially consistent weather at daily resolution which is used as input for the model chain. This approach allows deriving discharge, inundation and damage patterns which respect spatial interactions within and beyond catchment boundaries.

Flood Inundation Analysis and Mitigation with a Coupled 1D-2D Hydraulic Model: A Case Study in Kochi, Japan

Coupled one and two-dimensional (1D-2D) hydraulic models play a significant role in analyzing flooding problems to find possible solutions as they can reproduce the actual situations relatively accurately. This paper summarizes approaches to flood inundation analysis and mitigation with coupled 1D-2D hydraulic models of a small mountain watershed in Japan. A detailed flood inundation model including the effects of drainages, pumping, inflow from mountain sub-watersheds and flood gates is developed using coupled 1D-2D hydraulic models. The model is applied to the inundation in Kubokawa, a small town in Kochi Prefecture, Japan on August 9-10, 2014. Simulated and observed maximum water levels along the river and maximum inundations in the flood plain are compared and found to be consistent. Causes of the flooding and percentage of contribution are quantitatively identified, and countermeasures to reduce the effects of flooding are proposed.

Conservative 1D–2D coupled numerical strategies applied to river flooding: The Tiber (Rome)

Coupled 1D–2D numerical strategies are presented in this work for their application to fast computation of large rivers flooding. Both 1D and 2D models are built using explicit upwind finite volume schemes, able to deal with wetting-drying fronts. The topography representation is described via cross sections for the 1D model and with quadrilateral/triangular structured/unstructured meshes for the 2D model. The coupling strategies, free of hydraulic structures and tuning parameters, are firstly validated in a laboratory test dealing with a levee break and its flooding into a lateral plane. The numerical results are compared with a fully 2D model as well as with measurements in some gauge points giving satisfactory results. The simulation of a real flooding scenario in the Tiber river near the urban area of Rome (Italy) is then performed. A lateral coupling configuration is provided, in which the flood wave propagation in the main channel is simulated by means of a 1D model and the inundation of the riverside is simulated by means of a 2D model. On the other hand, a frontal coupling, in which the flood wave is simulated in a 1D model first and then it is propagated into a 2D model, is also performed. The flooding extension is almost well captured by all the schemes presented, being the 1D–2D lateral configuration the most confident with speed-ups of around 15x.

Spatially coherent flood risk assessment based on long-term continuous simulation with a coupled model chain

Summary A novel approach for assessing flood risk in river catchments in a spatially consistent way is presented. The approach is based on a set of coupled models representing the complete flood risk chain, including a multisite, multivariate weather generator, a hydrological model, a coupled 1D–2D hydrodynamic model and a flood loss model. The approach is exemplarily developed for the meso-scale Mulde catchment in Germany. 10,000 years of meteorological fields at daily resolution are generated and used as input to the subsequent models, yielding 10,000 years of spatially consistent river discharge series, inundation patterns and damage values. This allows estimating flood risk directly from the simulated damage. The benefits of the presented approach are: (1) in contrast to traditional flood risk assessments, where homogenous return periods are assumed for the entire catchment, the approach delivers spatially heterogeneous patterns of precipitation, discharge, inundation and damage patterns which respect the spatial correlations of the different processes and their spatial interactions. (2) Catchment and floodplain processes are represented in a holistic way, since the complete chain of flood processes is represented by the coupled models. For instance, the effects of spatially varying antecedent catchment conditions on flood hydrographs are implicitly taken into account. (3) Flood risk is directly derived from damage yielding a more realistic representation of flood risk. Traditionally, the probability of discharge is used as proxy for the probability of damage. However, non-linearities and threshold behaviour along the flood risk chain contribute to substantial variability between damage probabilities and corresponding discharge probabilities.

A coupled 1D–2D hydrodynamic model for flood simulation in flood detention basin

A coupled 1D–2D hydrodynamic model linking the channel and flood detention basin for flood simulation with complex topography and irregular boundary was presented in this paper. The 1D Saint-Venant equations were used for governing flows in channel, and the four-point implicit Preissmann scheme was used for discretization. To simulate floods in flood detention basin, the 2D shallow equations were adopted as governing equations, and a well-balanced, unstructured finite-volume method was proposed for the numerical resolution. The 2D model is based on a new formulation of the classical shallow water equations in hyperbolic conservation form. The numerical fluxes are computed by HLLC algorithm, and the MUSCL–Hancock predictor–corrector scheme is used to achieve high-accuracy and high-resolution results. A simple and efficient method was proposed to reflect the coupled hydraulic connection between the channel and the flood detention basin. The novelties of the proposed model include (1) a robust method for wetting/drying treatment and (2) an efficient way to link the 1D and 2D models. The 1D, 2D, and coupled models are all tested through some benchmark cases, and numerical results validated the accuracy of the models. Furthermore, the coupled 1D–2D model was used for a real flood simulation in Jiakouwa flood detention basin, China. The flood-risk information including flood arrival time and maximal water depth was mapped using GIS. Those flood-risk maps can be used as an important decision-making basis of flood control and rescue for the flood control departments at all levels.

Comparing modelling techniques for analysing urban pluvial flooding

Short peak rainfall intensities cause sewer systems to overflow leading to flooding of streets and houses. Due to climate change and densification of urban areas, this is expected to occur more often in the future. Hence, next to their minor (i.e. sewer) system, municipalities have to analyse their major (i.e. surface) system in order to anticipate urban flooding during extreme rainfall. Urban flood modelling techniques are powerful tools in both public and internal communications and transparently support design processes. To provide more insight into the (im)possibilities of different urban flood modelling techniques, simulation results have been compared for an extreme rainfall event. The results show that, although modelling software is tending to evolve towards coupled one-dimensional (1D)-two-dimensional (2D) simulation models, surface flow models, using an accurate digital elevation model, prove to be an easy and fast alternative to identify vulnerable locations in hilly and flat areas. In areas at the transition between hilly and flat, however, coupled 1D-2D simulation models give better results since catchments of major and minor systems can differ strongly in these areas. During the decision making process, surface flow models can provide a first insight that can be complemented with complex simulation models for critical locations.

Comparison of hydrodynamic models of different complexities to model floods with emergency storage areas

AbstractA flood emergency storage area (polder) is used to reduce the flood peak in the main river and hence, protect downstream areas from being inundated. In this study, the effectiveness of a proposed flood emergency storage area at the middle Elbe River, Germany in reducing the flood peaks is investigated using hydrodynamic modelling. The flow to the polders is controlled by adjustable gates. The extreme flood event of August 2002 is used for the study. A fully hydrodynamic 1D model and a coupled 1D–2D model are applied to simulate the flooding and emptying processes in the polders and flow in the Elbe River. The results obtained from the 1D and 1D–2D models are compared with respect to the peak water level reductions in the Elbe River and flow processes in the polders during their filling and emptying. The computational time, storage space requirements and modelling effort for the two models are also compared. It is concluded that a 1D model may be used to study the water level and discharge reductions in the main river while a 1D‐2D model may be used when the study of flow dynamics in the polder is of particular interest. Further, a detailed sensitivity analysis of the 1D and 1D–2D models is carried out with respect to Manning's n values, DEMs of different resolutions, number of cross‐sections used and the gate opening time as well as gate opening/closing duration. Copyright © 2008 John Wiley &amp; Sons, Ltd.

A comparison of one‐ and two‐dimensional approaches to modelling flood inundation over complex upland floodplains

AbstractA much understudied aspect of flood inundation is examined, i.e. upland environments with topographically complex floodplains. Although the presence of high‐resolution topographic data (e.g. lidar) has improved the quality of river flood inundation predictions, the optimum dimensionality of hydraulic models for this purpose has yet to be fully evaluated for situations of both topographic and topological (i.e. the connectivity of floodplain features) complexity. In this paper, we present the comparison of three treatments of upland flood inundation using: (a) a one‐dimensional (1D) model (HEC‐RAS v. 3·1·2) with the domain defined as series of extended cross‐sections; (b) the same 1D model, but with the floodplain defined by a series of storage cells, hydraulically connected to the main river channel and other storage cells on the floodplain according to floodplain topological characteristics; (c) a two‐dimensional (2D) diffusion wave treatment, again with explicit representation of floodplain structural features. The necessary topographic and topological data were derived using lidar and Ordnance Survey Landline data. The three models were tested on a 6 km upland reach of the River Wharfe, UK. The models were assessed by comparison with measured inundation extent. The results showed that both the extended cross‐section and the storage cell 1D modes were conceptually problematic. They also resulted in poorer model predictions, requiring incorrect parameterization of the main river to floodplain flux in order to approach anything like the level of agreement observed when the 2D diffusion wave treatment was assessed. We conclude that a coupled 1D–2D treatment is likely to provide the best modelling approach, with currently available technology, for complex floodplain configurations. Copyright © 2007 John Wiley &amp; Sons, Ltd.