Two-dimensional Hydraulic Model Research Articles

Using social cartographies for the calibration of two-dimensional hydraulic flood models

Using social cartographies for the calibration of two-dimensional hydraulic flood models

Flood scenario spatio-temporal mapping via hydrological and hydrodynamic modelling and a remote sensing dataset: A case study of the Basento river (Southern Italy)

Today, hydrological and hydraulic modelling are essential tools for flood risk management, although these models are still affected by elements of uncertainty that needs to be reduced by optimizing their results. The present research aims to implement an operational mechanism on the Basento river basin in Southern Italy based on the cascading use of a physically based concentrated-parameter hydrological model for the estimation of flood hydrographs, and a two-dimensional hydraulic model for flood mapping. The calibration of the hydrological model uses physical information to reduce the initial range of the set parameter values, and an automated optimisation procedure based on a genetic algorithm to find optimal values of the model parameters by comparing simulated and observed data for the 2013 flood event. To calibrate the hydraulic model, a series of flood maps extracted from multi-temporal SAR images was used. In addition, validation of the hydrological and hydraulic models was carried out on March 2011 flood event. The results show the reliability of the models during both calibration and validation, with the hydrological model achieving a Nash-Sutcliffe Efficiency coefficient between 0.86 and 0.91, and the hydraulic model leading to results with an accuracy close to 70 %. Considering the significance of the results, the developed modelling chain was used to simulate future event scenarios for risk management assessment and could operate as an early warning system.

Assessing the Efficiency of Fully Two-Dimensional Hydraulic HEC-RAS Models in Rivers of Cyprus

Floods are among the most widespread and recurrent natural disasters globally. In the European region, climate change leads to an increase in the incidence and intensity of flooding. For effective management of the phenomenon, the European Union instituted Directive 2007/60/EC for the assessment and management of flood risks in order to reduce the negative consequences of flooding on human health, economic activities, the environment, and cultural heritage. Cyprus, as a member of the European Union, had to comply with the provisions of the directive. Within the second implementation of the directive, combined 1D/2D hydraulic models were conducted. These data served as a benchmark for the present research, in which the differences in the inundated area, depths, and simulation time are investigated using a full 2D hydraulic simulation. The present research examines two Areas of Potentially Significant Flood Risk, one in an urban and one in a rural area. Overall, the proposed 2D methodology was found to represent inundated areas to a good extent with almost zero deviation in comparison to the 1D/2D method. This study demonstrated the adequacy of the 2D hydraulic simulation method, which offers greater flexibility in modeling a variety of hydraulic scenarios, enabling planning and flood risk management that is vital for protecting communities, infrastructure and the environment from the devastating impacts of floods.

Influence of breach parameter models on hazard classification of off-stream reservoirs

The classification of dams or off-stream reservoirs concerning potential hazards in the event of failure often involves the use of two-dimensional hydraulic models for computing floodwave effects. These models necessitate defining breach geometry and formation time, for which various parametric models have been proposed. These models yield different values for average breach width, time of failure, and consequently, peak flows, as demonstrated by several researchers. This study analyzed the effect of selecting a breach parametric model on the hydraulic variables, potential damages, and hazard classification of structures. Three common parametric models were compared using a set of synthetic cases and a real off-stream reservoir. Results indicated significant effects of model choice. Material erodibility exerted a significant impact, surpassing that of failure mode. Other factors, such as the Manning coefficient, significantly affected the results. Utilizing an inadequate model or lacking information on dike material can lead to overly conservative or underestimated outcomes, thereby affecting hazard classification.

Seepage propagation simulation of a tunnel gasketed joint using the cohesive zone model

The gasketed joint plays a critical role in the waterproof or water-leakage resistance performance of tunnel segmental linings. This study presents a novel numerical simulation method based on the cohesive zone model (CZM) to accurately analyze the seepage phenomena along the interface of elastic sealing gaskets in shield tunnel joints. While traditional finite element methods are widely used, they cannot simulate interface opening, limiting their applicability. To overcome this challenge, the proposed method leverages the concept of hydraulic fracturing and redefines the seepage problem as a seepage problem of elastic impermeable media. By establishing a two-dimensional hydraulic fracturing model using the CZM, this study conducts a comprehensive sensitivity analysis of the cohesive element parameters and validates the accuracy and effectiveness of simulating seepage along the interface of elastic impermeable media. Based on the insights gained from the sensitivity analysis, a seepage calculation model is successfully developed, considering the unique characteristics of elastic sealing gaskets. The model is applied to three cross-sectional shapes of elastic sealing gaskets, and their seepage characteristics are analyzed based on the interface opening displacement and liquid pressure distributions during seepage. The results highlight the SC3 cross-sectional shape, which exhibits minimal opening displacement and the highest net water pressure at the moment of seepage occurrence, demonstrating superior waterproof performance compared to other forms. Through the introduction of the CZM, comprehensive parameter analysis, validation, and practical application, this study overcomes the limitations of traditional finite element methods in simulating interface opening. The proposed model, which more accurately captures seepage characteristics than other methods, provides an optimized simulation method for analyzing hydraulic coupling issues related to seepage at shield tunnel joints and is a significant contribution to the field, enhancing our understanding and enabling more accurate analyses of seepage phenomena in shield tunnel joints using elastic sealing gaskets.

Evaluation of pavement resilience to flooding with inverted pavement structure

Conventional pavement structures are vulnerable due to degradation of unbound materials after water inundation. Inverted pavement structure has been proven to be cost-effective and energy efficient, while its resilience has not been investigated. This study is aimed at assessing the resilience of inverted pavements to flooding events using an integrated hydraulic and mechanical modelling approach. Two-dimensional hydraulic models were established to analyse flooding-induced moisture variations in the pavements. Based on the moisture distribution results, three-dimensional mechanical models were developed to calculate critical pavement responses under moving load. The results show that the subgrade with higher groundwater table or larger hydraulic conductivity was more likely to be invaded by water. Compared with conventional pavement, the increases of critical pavement responses in inverted pavement were significantly smaller after long-period flooding, which indicates the potential benefits of inverted pavement in enhancing the resilience to flooding impact.

Hydrological risk assessment for Mangla Dam: compound effects of instant flow and precipitation peaks under climate change, using HEC-RAS and HEC-GeoRAS

Dams play a pivotal role in water resource management by storing and supplying water for a multitude of purposes. However, the looming threat of dam breach floods necessitates meticulous research and the simulation of potential failure scenarios. These endeavors are essential not only for comprehending the gravity of dam break floods but also for identifying vulnerable regions and informing emergency response strategies and land-use planning initiatives. This study employs a two-dimensional hydraulic model within the HEC-RAS (Hydrologic Engineering Center and River Analysis System) software to conduct an extensive dam breach analysis specifically focusing on the Mangla Dam located in Azad Kashmir, Pakistan. The analysis encompasses the prediction of various breach parameters, including the hydrograph of the breach flood, peak flow rates, arrival times of the flood, and the creation of inundation maps. Of primary concern is the Probable Maximum Floo, which drives the dam collapse model under unsteady flow conditions, accounting for both piping and overtopping failure scenarios. This study discerns the breach outflow hydrograph through the utility of HEC-RAS tools and evaluates hydraulic conditions at critical downstream locations. To dynamically route flood waves, the breach outflow hydrographs are harnessed. Furthermore, the HEC-RAS model is executed with breach parameters derived from five distinct empirical approaches, with ensuing outcomes subjected to rigorous comparative analysis. A comprehensive sensitivity study pertaining to breach parameters is also carried out to ascertain the sensitivity of peak flow and maximum stage. The results reveal peak flow rates of 174,850 m3/s and 177,850 m3/s in the downstream vicinity adjacent to the dam, translating into corresponding flooded areas of 379 km2 and 394 km2 attributable to piping and overtopping failures, respectively. The analysis of Land Use Land Cover data demonstrates that in the event of piping failure, 217 km2 of agricultural land and 56 km2 of urban areas would be completely submerged. Conversely, overtopping failure would inundate 220 km2 of agricultural land and 59 km2 of urban areas. The utilization of advanced remote sensing data, combined with flood modeling insights, equips engineers and stakeholders with invaluable knowledge. This knowledge, in turn, underpins strategic planning and well-informed decision-making processes, essential for addressing the potential global repercussions of similar catastrophes.

Environmental Flow Assessment using multiple criteria: A case study in the Kumbih river, West Sumatra (Indonesia)

Water withdrawal from rivers is a key resource for agriculture, industry, and power generation. However, in order to maintain riverine ecosystem, withdrawal should not exceed certain thresholds, and normally a requirement is made that a certain amount of water be left in the river, to be assessed via Environmental Flow Assessment (EFA) procedure. In spite of the crucial importance of this task, little or no international standard exists to assess minimum values of the EF. Rather, general guidelines are provided, with large subjectivity entailed. Here, focusing on the case study Kumbih river, in Sumatra, Indonesia, we apply a multiple criteria approach to EFA procedure, testing the values of EF assessed with hydrological methods in a previous study, with a focus on a relevant target species, i.e. the fish Tor Soro. Based upon a two-dimensional hydraulic model, we explore 6 indicators, covering some most important criteria to ensure the welfare of the fish fauna. Indicator II, weighed usable volume, slightly modifies the well-known method PHABSIM. Indicators IIi.IIIII target water depth needed to ensure welfare of target species, whereas criteria IIV-VI target flow velocity, and sediment removal. Use of multiple indicators as shown here, albeit still subjective, may provide more consistent values of EF, and even an outlook of the disparity in terms of flow requirements given by the several criteria. Here we found that the maximum estimated EF under IV (flow velocity), is over twice as large as the flow estimate from II. Overall however, initial EF estimates from the hydrological criterion seem adequate against the criteria proposed. Our study is among the few covering EF for Indonesia, and the only one regarding Kumbih river, and our results are of interest, also as a benchmark for other EFA studies in the region.

Application of Two-Dimensional Hydraulic Modelling of Hydrological Risk Related to Urban Flood. A Case of the Taza City, Morocco

Application of Two-Dimensional Hydraulic Modelling of Hydrological Risk Related to Urban Flood. A Case of the Taza City, Morocco

A Probabilistic Approach for Off-Stream Reservoir Failure Flood Hazard Assessment

Off-stream reservoirs are hydraulic structures that might cause severe flood damages in case of failure or improper operation. Their safety regulations usually require hydraulic studies for flood hazard and inundation zone mapping. The selection of the break point is not trivial because the topography in its surroundings is commonly highly anthropic. A wrong selection would not provide the worst scenario in terms of maximum flood hazard extent. This work presents a probabilistic approach based on a stochastic definition of the break point along the dyke. A number of failure scenarios are generated automatically, corresponding to different breach formations. Then, an in-cascade calculation process simulates each scenario, providing a framework to carry out statistical analysis. The simulation of the breach formation and the flood wave propagation is performed through a GPU parallelised two-dimensional hydraulic numerical model, which provides a probabilistic inundation zone and flood hazard mapping of all scenarios simulated in a suitable timeframe.

Flood hazard assessment in Montenegro through the application of two-dimensional hydraulic modelling

Floods, induced partly by climate change and partly by the negative impact of human actions, may be regarded as the most common type of natural catastrophe in Montenegro, causing significant economic, ecological, social, and health damage yearly. Therefore, the focal point of flood risk assessment is reflected in properly determining flood hazards. However, within the Montenegrin National flood risk assessment, which is entirely scenario-based, the hazard is treated only by estimating the occurrence probability of a specific scenario. The paper provides an overview of recent efforts to overcome the potential weaknesses of scenario-based risk assessment by constructing hazard maps for all areas of potential significant flood risk in Montenegro. Hazard maps are intended to visualise different flood intensities (e.g., flood depth, velocity, etc.) for selected return periods. Such outputs are generated by two-dimensional hydraulic modelling, which requires extensive work on gathering the available field data, calculating hydrological inputs, building and calibrating the model, and defining uncertainties that may affect the results. The final production of the hazard maps is conveyed by post-processing the computation results in GIS-based software.

Analysis of Downstream Flood Risk in the Failure of Batman Dam with Two-Dimensional Hydraulic Modeling and Satellite Data

Baraj yıkılmalarına bağlı taşkınların mansap bölgesine etkilerinin belirlenmesi afete hazırlık çalışmaları için önem arz etmektedir. Bu çalışmada, Batman Barajı’nın yıkılması durumunda mansabındaki yerleşim yerlerinin taşkın risk durumu incelenmiştir. Çalışma, HEC-RAS modeli içerisinde bütünleşik çalışan iki aşamadan oluşmaktadır. İlk aşamada, trapez gediklenerek baraj yıkılması sonucu oluşacak taşkın hidrografı elde edilmiştir. İkinci aşamada, taşkının Batman Nehri ve civarında yayılım simülasyonu 2 Boyutlu hidrodinamik modeli ile yapılmıştır. Modelin en önemli girdisi olan arazi bilgisi, 30 m mekânsal çözünürlüklü SRTM ve 12,5 m mekânsal çözünürlüklü ALOS-PALSAR uydu ürünü Sayısal Yükseklik Modeli (SYM) verilerinden temin edilmiştir. Elde edilen sonuçlar (su derinliği, su hızı, varış süresi ve tehlike haritaları) Harita Genel Müdürlüğünden sağlanan 5 m mekânsal çözünürlüklü Sayısal Arazi Modeli (SAM) tabanlı referans model sonuçları ile karşılaştırılmıştır. Taşkın debisi 3-4 saat içerisinde Batman Havaalanı’na varmakta ve nehir yatağında su hızları 5 -10 m/s arasında değişmektedir. Uydu ürünü SYM tabanlı modeller referans modele yakın (R2=0.79) sonuçlar üretebilmektedir. Maksimum su seviyesi F-indeks performansına göre referans model ile aralarındaki uyum %92 mertebesindedir. SRTM uydusu düşük mekânsal çözünürlüğüne rağmen ALOS-PALSAR’a göre düşük/benzer hata değerine (RMSE ve MAE) sahiptir. Taşkın debisinin şehre ulaşmadığı, fakat Atıksu Arıtma tesisi ile Batman Havaalanına kısmi etki edebileceği; kırsal bölgede 10.985 kişinin taşkın riski altında olacağı öngörülmektedir.

Can hydraulic measures of river conditions improve our ability to predict ecological responses to changing flows? Flow velocity and spawning of an iconic native Australian fish

Ecological responses to changing riverine flows are often evaluated by describing the relationship between river discharge and response. However, aquatic organisms experience the hydraulics (i.e. velocity, shear stress, depth) of a river, not its discharge. Hydraulic characterizations of riverine habitats may improve our ability to predict ecological responses. We used two-dimensional hydraulic models to translate river discharge into flow velocity. We used discharge and reach-averaged velocity, along with water temperature and 8 years of field observations of fish spawning, to develop predictive models of the spawning of golden perch (Macquaria ambigua) in the Goulburn River, south-east Australia. Probability of spawning was positively related to both discharge and reach-averaged velocity. Water temperature was critical for enabling the flow response, and antecedent flows prior to spawning had a weak positive effect. Against expectations, there was little difference in predictive uncertainty for the effect of flows when reach-averaged velocity was used as the main predictor rather than discharge. The lower Goulburn River has a relatively simple channel and so discharge and velocity are monotonically related over most flows. We expect that in a more geomorphically complex environment, improvement in predictive ability would be substantial. This research only explores one example of a hydraulic parameter being used as a predictor of ecological response; many others are possible. The extra effort and expense involved in hydraulic characterization of river flows is only justified if our understanding of flow-ecology relationships is substantially improved. Further research to understand which environmental responses might be best understood through different hydraulic parameters, and how to better characterize hydraulic characteristics relevant to riverine biota, would help inform decisions regarding investment in hydraulic models. Regardless, hydraulics offers a more process-based assessment of ecological responses to changing flows, has the potential to facilitate mechanistic understanding rather than just associations, and provides the opportunity to translate hydraulic metrics that drive ecological responses across river systems of differing sizes. However, while considering ecological responses in terms of river hydraulics is more physically realistic, our results suggest that average hydraulic conditions may not result in an improved ability to predict the effects of changing flows.

Two-dimensional convolutional neural network outperforms other machine learning architectures for water depth surrogate modeling

Rapid prediction of spatially distributed hydrological variables, such as water depths in rivers, is an important but challenging task. This study proposes a novel matrix-based deep learning approach for predicting spatial distribution of water depths in rivers. The proposed approach was constructed based on a two-dimensional (2D) convolutional neural network (CNN) with a new architecture that was specifically designed for providing spatial distribution maps. A numerical dataset was established based on a field cruise and two-dimensional hydraulic modeling for different scenarios, and numerical experiments were designed to predict spatial distribution of water depths for different scenarios using the adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM), genetic programming (GP), multi-gene genetic programming (MGGP), one-dimensional CNN (1D-CNN), and the proposed CNN algorithms. The results showed that the proposed CNN approach captured both the large-scale and small-scale spatial patterns remarkably well, and it outperformed the other approaches. This study shows that the 2D CNN algorithm is better than the classical machine learning (ML) algorithms for inundation modeling. The proposed approach is thus a promising tool for providing rapid predictions of spatial distribution of water depths in river systems and can potentially be leveraged to predict other spatially distributed hydrological variables.

Impacts of Vegetation Removal on Urban Mediterranean Stream Hydrology and Hydraulics

Given the widespread presence of non-native vegetation in urban and Mediterranean watersheds, it is important to evaluate how these sensitive ecosystems will respond to activities to manage and restore native vegetation conditions. This research focuses on Del Cerro, a tributary of the San Diego River in California, where non-native vegetation dominates the riparian zone, creating flooding and fire hazards. Field data were collected in 2018 to 2021 and consisted of water depth, streamflow, and stream temperature. Our data set also captured baseline conditions in the floodplain before and after the removal of burned non-native vegetation in November 2020. Observed changes in hydrologic and geomorphic conditions were used to parameterize and calibrate a two-dimensional hydraulic model to simulate urban floodplain hydraulics after vegetation removal. We utilized the U.S. Army Corps of Engineers’ Hydrologic Engineering Center River Assessment System (HEC-RAS) model to simulate the influence of canopy loss and vegetation disturbance and to assess the impacts of vegetation removal on stream restoration. We simulated streamflow, water depth, and flood extent for two scenarios: (1) 2019; pre-restoration where non-native vegetation dominated the riparian area, and (2) 2021; post-restoration following the removal of non-native vegetation and canopy. Flooding after restoration in 2021 was more frequent compared to 2019. We also observed similar flood extents and peak streamflow for storm events that accumulated half the amount of precipitation as pre-restoration conditions. Our results provide insight into the responses of small urban stream reaches to the removal of invasive vegetation and canopy cover.

Implementation of heuristic search algorithms in the calibration of a river hydraulic model

In this contribution, two heuristic search algorithms, (1) particle swarm optimization (PSO) and (2) genetic algorithm (GA) are used to calibrate the iRIC, a two-dimensional hydraulic model for a test case on the Green River in Utah. The goal of the search algorithms was to find the combination of roughness values that minimized model error compared to the measured water surface elevation. An artificial neural network (ANN), which was trained based on the simulated water surface profiles obtained from iRIC, was used to measure the fitness of each solution. Implementation of PSO and GA both improved the accuracy of the calibration by 34 and 30 percent respectively relative to the trial and error. This research demonstrates that the implementation of heuristic search models provides an objective methodology for the calibration of hydraulic models with improved performance when compared to models calibrated via trial and error.

A Machine Learning-Based Surrogate Model for the Identification of Risk Zones Due to Off-Stream Reservoir Failure

Approximately 70,000 Spanish off-stream reservoirs, many of them irrigation ponds, need to be evaluated in terms of their potential hazard to comply with the new national Regulation of the Hydraulic Public Domain. This requires a great engineering effort to evaluate different scenarios with two-dimensional hydraulic models, for which many owners lack the necessary resources. This work presents a simplified methodology based on machine learning to identify risk zones at any point in the vicinity of an off-stream reservoir without the need to elaborate and run full two-dimensional hydraulic models. A predictive model based on random forest was created from datasets including the results of synthetic cases computed with an automatic tool based on the two-dimensional numerical software Iber. Once fitted, the model provided an estimate on the potential hazard considering the physical characteristics of the structure, the surrounding terrain and the vulnerable locations. Two approaches were compared for balancing the dataset: the synthetic minority oversampling and the random undersampling. Results from the random forest model adjusted with the random undersampling technique showed to be useful for the estimation of risk zones. On a real application test the simplified method achieved 91% accuracy.

Unpiloted Aerial Vehicle (UAV) image velocimetry for validation of two-dimensional hydraulic model simulations

Non-intrusive image-based techniques for measuring surface river velocities have rapidly evolved as a cost-effective and safe means for quantifying flow patterns. Large-scale particle image velocimetry (LSPIV) can provide instantaneous surface velocities over a large spatial footprint rapidly and with little pre-calibration as compared to traditional techniques. Assessment of the spatial distribution of flow velocities in hydraulic models has been comparatively harder to achieve than assessment of depth due to logistical challenges but would be aided using large observational datasets that represent the variability and distribution of flow hydraulics. Additionally, the efficacy of image velocimetry in assessing the accuracy of outputs from 2D hydraulic models has not been addressed. Here, we demonstrate how LSPIV can be used to calibrate and validate 2D model predictions in a gravel bed river reach. LSPIV velocities are depth-averaged using standard velocity coefficients (α) and then using the Probability Concept (PC) - a probabilistic formulation of velocity distributions that accounts for non-standard velocity profiles, typical in field settings. UAV surveys were used to acquire video for LSPIV and imagery for Structure from Motion (SfM) topographic modelling. We use spatially dense acoustic doppler current profiler (aDcp) velocity data for benchmark assessment of the velocity outputs of HEC-RAS 2D model simulations. 2D model prediction error, based on seeded LSPIV velocities, was within range (4.2%) of the aDcp parametrised model, with improvements in modelled versus predicted velocity correlations (up to 7.7%) when using PC to depth average LSPIV velocities. Validation bias reduced significantly (11%) with tighter error distributions when compared to the aDcp based model. Although additional hydraulic measurements are required to parametrise the Probability Concept algorithm, the performance of 2D hydraulic models calibrated/validated with LSPIV velocities is on par with traditional techniques, demonstrating the potential of this non-intrusive, low-cost approach.

Application of Remote-Sensing-Based Hydraulic Model and Hydrological Model in Flood Simulation

Floods are one of the main natural disaster threats to the safety of people’s lives and property. Flood hazards intensify as the global risk of flooding increases. The control of flood disasters on the basin scale has always been an urgent problem to be solved that is firmly associated with the sustainable development of water resources. As important nonengineering measures for flood simulation and flood control, the hydrological and hydraulic models have been widely applied in recent decades. In our study, on the basis of sufficient remote-sensing and hydrological data, a hydrological (Xin’anjiang (XAJ)) and a two-dimensional hydraulic (2D) model were constructed to simulate flood events and provide support for basin flood management. In the Chengcun basin, the two models were applied, and the model parameters were calibrated by the parameter estimation (PEST) automatic calibration algorithm in combination with the measured data of 10 typical flood events from 1990 to 1996. Results show that the two models performed well in the Chengcun basin. The average Nash–Sutcliffe efficiency (NSE), percentage error of peak discharge (PE), and percentage error of flood volume (RE) were 0.79, 16.55%, and 18.27%, respectively, for the XAJ model, and those values were 0.76, 12.83%, and 11.03% for 2D model. These results indicate that the models had high accuracy, and hydrological and hydraulic models both had good application performance in the Chengcun basin. The study can a provide decision-making basis and theoretical support for flood simulation, and the formulation of flood control and disaster mitigation measures in the basin.

Hydrological Topography Data Set (HTD)— the Data Set for High Resolution 2D Urban Flood Modeling

This study investigated the demand of data for better high resolution two-dimensional (2D) hydraulic modeling and proposes a data set named "Hydrological Topography Data Set" (HTD for short) for this purpose. Derived from airborne lidar point cloud, the HTD comprises three parts: (1) High Resolution Hydraulic Three-Dimensional Features: high resolution three-dimensional vector data that preserves the locations and elevations of topography breaklines, (2) Hydraulic Digital Elevation Model: high resolution (1 × 1 m) DEM enhanced by the terrain breaklines to preserve the landscape characteristics, and (3) Hydraulic Digital Surface Model: high resolution (1 × 1 m) DSM conditioned by removing the height of vegetation and temporary objects. With HTD, hydraulic features such as drainages with 10 m of width can be identified and properly set up in numerical models, thus can help simulating and access- ing the flood in urban area more in detail. Through case studies we demonstrate how HTD can affect the results of hydraulic modeling. The results show that HTD can help modelers to construct proper mesh (or computational grids) for 2D hydraulic modeling, and pre- serve topography characteristics (i. e., shape and elevation), which improves the modeling results in terms of spatial resolution and physical rationality, while still keeping the computation efficient.