Detailed Hydraulic Model Research Articles

Opportunities for Leveraging Existing Hydrologic and Hydraulic Models Developed for Water Quantity Management to Mitigate Flooding Due to Extreme Precipitation

With a focus on a specific flood-prone community in Camden, NJ, this research utilizes a detailed hydraulic and hydrologic (H&H) model to assesses the impacts of climate change on Combined Sewer Overflows (CSOs) and localized flooding under two different infrastructure scenarios. In the US, the Clean Water Act compels regulated utilities to develop Long-Term Control Plans to reduce combined sewer overflows (CSOs), but there is no parallel mandate to simultaneously reduce flooding within the associated service areas. With different control measures in place, H&H models are frequently used to evaluate CSO volumes and frequencies under historical climate conditions. However, precipitation intensification and sea level rise (SLR) will also modify CSO volumes. This study uses a calibrated and validated 1D and 2D Personal Computer Stormwater Management Model (PCSWMM) simulation to predict both CSO discharges and flooding under different climate and infrastructure scenarios. A total of ten climate change scenarios comprising a range of plausible climate futures are considered. The infrastructure scenario that is tested would divert stormwater generated in an upstream municipality (Pennsauken, NJ) away from Camden’s combined sewer system. Without the disconnection, increases in precipitation will increase CSOs, whereas SLR primarily increases flooding. The proposed mitigation strategy can immediately reduce both CSOs and flooding, but with diminishing effectiveness over time, as climate change demonstrates the need for supplemental measures. Areas for further analysis regarding alternative mitigation methods and future research are outlined.

Selecting and refining suitable methods of developing digital elevation models to represent geomorphic features and characteristics of smaller wetlands in data-scarce environments

Land surface geomorphology plays an important role in water and sediment dispersal processes in wetlands. For wetland practitioners and researchers to engage with these processes in time and space, they require topographic data in order to derive wetland surface gradient, cross-sectional shape and area, surface and subsurface hydrological connectivity, and hydraulic characteristics. A range of data options, with varying spatial resolutions, are available, ranging from free national and global resources (e.g. contour data and global elevation models) to project-specific high-resolution surveys (e.g. Differential Global Positioning Systems (DGPS), Photogrammetry, Light Detection And Ranging (LiDAR)). Due to the scarcity of high-resolution and high-accuracy data, especially in developing countries, data gathering and processing costs can be significant. This paper presents a commentary on a range of topographic data and processing options for a relatively small (~ 40 ha) floodplain wetland in the Eastern Cape, South Africa. It critically reviews the usefulness and shortfalls of various wetland-related applications ranging from gradient calculations to more detailed hydraulic modelling, and the data resolution required for each application. Free, low-resolution, datasets have a limited representation of geomorphology at this scale due to the relatively low-resolution and large vertical error. Field-based surveys (using survey-grade equipment such as a DGPS) have the benefit of providing accurate terrain results in areas with dense vegetation and surface water, while photogrammetry and LiDAR data are useful to represent the higher resolution morphology across the wetland, despite shortcomings regarding the penetration of dense vegetation and surface water. However, combining DGPS data with LiDAR proves to yield the best model for detailed process modelling for wetlands at the local scale.

Neural networks for fast fluvial flood predictions: Too good to be true?

AbstractAccurate models with low computational times are required to predict the consequences of fluvial floods in real‐time. Even though detailed hydraulic models can predict flood water levels and corresponding inundation extents with high accuracy, their computational times limit their applicability to being used as a flood early‐warning system. Therefore, conceptual models were developed in the literature for many years. These types of models do not attempt to represent the complex dynamic flood generation processes but are based on simplified hydraulic concepts, generally only using a digital elevation model as input. However, a shift in this research field is currently present from conceptual models to data‐driven models, and more specifically to neural networks. This paper discusses the benefits and drawbacks of both modelling approaches and speculates which method is most promising to be used as a flood warning system to predict the consequences of fluvial floods in real‐time.

Cross-waves and pulsating flows in the side-channel spillway – an experimental approach

Potentially hazardous side-channels of complex geometry need to be investigated using detailed hydraulic physical models. This study aims to analyse the cross-waves pattern and pulsating flow using a side-channel spillway physical model. This study compares the cross-waves pattern were measured using an experimental installation set to generate cross-waves on the surface (original series) with another structure that did not produce cross-waves (modified series). The results showed that the geometry of the left wall caused instability in flow patterns and secondary flows. The starting point of Q 2 discharge was detected by minor turbulence on the water surface near the left wall at a water depth of 3.3 m at the starting point of the wall, but with no overtopping. Cross-waves formed downstream at the right wall crosswise, lower than at the left wall. The height of the cross-wave increased substantially from Q 100 to Q 1000 discharges leading to overtoppings near the left wall at a water depths of 4.2 and 5.0 m at the starting point of the wall, and near the right wall at a water depths of 3.8 and 4.0 m at the upstream point of the wall. The modifications provided optimal hydraulic conditions, i.e. elimination of cross-waves and non-uniform flows. The Vedernikov and Montouri numbers showed that both original and modified series did not enter the area where the pulsating flow occurred. This indicated that both series were free from the pulsating flow.

Hydroelectricity Modeling for Low‐Carbon and No‐Carbon Grids: Empirical Operational Parameters for Optimization and Dispatch Models

AbstractHydroelectric power has unusual technical characteristics that could become more valuable as the penetration of variable generation renewables grows, but its use for electricity generation is constrained by complex physical, safety, and socioenvironmental considerations. Hydroelectricity can therefore be difficult to represent in national‐scale energy models, and is frequently presumed to be either overly flexible or inflexible. While a few grid models address this complexity via detailed hydraulic process models, more simplified optimization and dispatch models could benefit from the use of empirical parameter values. In this study, we combine a new data set comprising 7.8 million flow‐hours of data from 2011 to 2016 at 158 dams across the United States with monthly and hourly generation data from the U.S. Energy Information Administration (EIA) to elucidate such empirical constraints for the continental United States. We introduce an approach for estimating power generation from hourly water discharge, then present regionally resolved interannual seasonal and diurnal generation patterns; frequency analyses of ramp rates; minimum and maximum generation rates; daily reversals; and load duration curves, all available interactively with a new data visualization tool. We suggest that due largely to hydropower's role as power generation that also serves non‐energy purposes, it acts as a predictable variable generator with constrained dispatchability, more like a supply side analog to demand response resources than like a battery. This observation is particularly relevant for high penetration renewable energy scenarios, given hydroelectric generators' expected value for grid stabilization and load balancing.

Estimation of Scottish Pluvial Flooding Expected Annual Damages Using Interpolation Techniques

Flood modelling and mapping, underpinned by hydraulic modelling, are typically used to define flood hazard and allow a quantification of risk and associated Expected Annual Damages (EAD). At a regional or national scale, such modelling is often a lengthy process, which does not allow changes in risk resulting from new science such as revised rainfall frequency estimates or climate projections to be readily quantified by policy makers. A framework of interpolation and extrapolation methods has been developed in the R language via practical application to the city of Perth in central Scotland. These methods allow existing flood mapping, design rainfall estimates and property receptor datasets combined with revised design rainfall estimates to be used to rapidly assess the consequences of change in risk and EAD. The results are evaluated against detailed hydraulic modelling and are shown to provide a good approximation of changes in flood depth and EAD for properties previously modelled as at risk of flooding, particularly residential properties, with lower confidence for non-residential properties. In the Scottish context, the methods are considered to be robust for regional and national scale application and would allow policy makers with a means to rapidly determine the consequence of changes in design rainfall estimates without the immediate requirement to undertake complex hydraulic modelling.

Predicting Outflow Hydrographs of Potential Dike Breaches in a Bifurcating River System Using NARX Neural Networks

Early flood forecasting systems can mitigate flood damage during extreme events. Typically, the effects of flood events in terms of inundation depths and extents are computed using detailed hydraulic models. However, a major drawback of these models is the computational time, which is generally in the order of hours to days for large river basins. Gaining insight in the outflow hydrographs in case of dike breaches is especially important to estimate inundation extents. In this study, NARX neural networks that were capable of predicting outflow hydrographs of multiple dike breaches accurately were developed. The timing of the dike failures and the cumulative outflow volumes were accurately predicted. These findings show that neural networks—specifically, NARX networks that are capable of predicting flood time series—have the potential to be used within a flood early warning system in the future.

Application of time-of-day and day-of-week-based hazard in dam break assessments

The consequences of failure for dams upstream of urban areas are usually considered to be severe, which can be reflected in a detailed hazard assessment as part of a dam break mapping exercise. These urban areas are usually populated with differing types of commercial and residential properties, all of which have different usage and occupancy both throughout a typical day and over a typical week. This study details a case study for a UK reservoir dam break model and documents – and discusses the differences between the often-adopted time-averaged values of population at risk and average societal loss of life, and an alternative proposed time-of-day and day-of-week consequence assessment technique. The study makes use of detailed two-dimensional hydraulic modelling techniques, and occupancy data from online application programming interfaces and other mass data collection surveys. The ramifications of the additional detail provided by the alternative approach are discussed and contextualised.

Increase in flood risk resulting from climate change in a developed urban watershed – the role of storm temporal patterns

Abstract. The effects of climate change are causing more frequent extreme rainfall events and an increased risk of flooding in developed areas. Quantifying this increased risk is of critical importance for the protection of life and property as well as for infrastructure planning and design. The updated National Oceanic and Atmospheric Administration (NOAA) Atlas 14 intensity–duration–frequency (IDF) relationships and temporal patterns are widely used in hydrologic and hydraulic modeling for design and planning in the United States. Current literature shows that rising temperatures as a result of climate change will result in an intensification of rainfall. These impacts are not explicitly included in the NOAA temporal patterns, which can have consequences on the design and planning of adaptation and flood mitigation measures. In addition there is a lack of detailed hydraulic modeling when assessing climate change impacts on flooding. The study presented in this paper uses a comprehensive hydrologic and hydraulic model of a fully developed urban/suburban catchment to explore two primary questions related to climate change impacts on flood risk. (1) How do climate change effects on storm temporal patterns and rainfall volumes impact flooding in a developed complex watershed? (2) Is the storm temporal pattern as critical as the total volume of rainfall when evaluating urban flood risk? We use the NOAA Atlas 14 temporal patterns, along with the expected increase in temperature for the RCP8.5 scenario for 2081–2100, to project temporal patterns and rainfall volumes to reflect future climatic change. The model results show that different rainfall patterns cause variability in flood depths during a storm event. The changes in the projected temporal patterns alone increase the risk of flood magnitude up to 35 %, with the cumulative impacts of temperature rise on temporal patterns and the storm volume increasing flood risk from 10 to 170 %. The results also show that regional storage facilities are sensitive to rainfall patterns that are loaded in the latter part of the storm duration, while extremely intense short-duration storms will cause flooding at all locations. This study shows that changes in temporal patterns will have a significant impact on urban/suburban flooding and need to be carefully considered and adjusted to account for climate change when used for the design and planning of future storm water systems.

Manage Sewer In-Line Storage Control Using Hydraulic Model and Recurrent Neural Network

This paper described manage sewer in-line storage control for the city of Drammen, Norway. The purpose of the control is to use the free space of the pipes to reduce overflow at the wastewater treatment plant (WWTP). This study combined the powerful sides of the hydraulic model and neural networks. A detailed hydraulic model was developed to identify which part of the sewer system have more free space. Subsequently, the effectiveness of the proposed control solution was tested. Simulation results showed that intentionally control sewer with free space could significantly reduce overflow at the WWTP. At last, in order to enhance better decision making and give enough response time for the proposed control solution, Recurrent Neural Network (RNN) was employed to forecast flow. Three RNN architectures, namely Elman, NARX (nonlinear autoregressive network with exogenous inputs) and a novel architecture of neural networks, LSTM (Long Short-Term Memory), were compared. The LSTM exhibits the superior capability for time series prediction.

Flood Mapping Tools for Disaster Preparedness and Emergency Response Using Satellite Data and Hydrodynamic Models: A Case Study of Bagmathi Basin, India

Northern Bihar is one of the major flood prone region in India affecting thousands of human lives and livelihoods during the recurrent floods occurring due to the monsoonal rains. While it is impossible to prevent the occurrence of extreme flood events, disaster planning can help in mitigating its detrimental effects. Monitoring flood extent using satellite observations just after the flood disasters is a core component of rapid emergency response process, which enables the emergency rescue teams to prioritize their efforts in critical areas to save lives and protect health, in addition to providing near real-time flooding information to the decision makers and planners. The main objective of this study is to demonstrate the utility of less data intensive, but equally robust hydrodynamic models to develop flood extent maps in conjunction with freely available remote sensing imageries at different scales. MODIS TERRA satellite data was used to map flood extent from 2001 to 2016 for entire Bihar. Two hydraulic models namely FLDPLN and RRI applied for the Bagmathi basin to evaluate our objectives. Both these models are of varying complexity but generate flood extent patterns with minimum amount of input data. The proposed approach is suited for mapping flood extents to provide an input information in near real time (h) when there is no availability to detailed hydraulic models and satellite datasets. Flood inundation extents from FLDPLN and RRI models were validated with Landsat-7 and MODIS TERRA derived flood extents for model performance. The results show acceptable spatial agreement between model predicted and Landsat-7 observed flood extents, denoting the utility of these tools for flood mapping application in data scarce environments.

The role of Greater Copenhagen Utility in implementing the city's Cloudburst Management Plan

This paper describes Greater Copenhagen Utility's role in planning, coordinating and implementing Copenhagen's Climate Change Adaptation Plan and Cloudburst management strategy. Detailed hydraulic modelling of the seven catchments in the city resulted in the preparation of a cloudburst management plan with more than 350 interventions, at a budget of EUR 1.3 billion. Among the planned projects are designated cloudburst boulevards, retention spaces, green roads and cloudburst tunnels. The joint efforts in coordinating climate change adaptation with city planning and infrastructure implementation, are shown to be key to succeeding with the projects. Stakeholder involvement in preparing the cloudburst management strategy is important in identifying the optimal solutions.

Impact of Short Duration Intense Rainfall Events on Sanitary Sewer Network Performance

Short duration intense rainfall causes an increase in rainfall derived infiltration and inflow (RDII) into aging sewer networks, which leads to Sanitary Sewer Overflows (SSOs). This study presents a generalised framework for assessing and mitigating the impacts of intense rainfall on sanitary sewer networks. The first part of the proposed framework involves a detailed hydraulic modelling to evaluate the performance of the sewer network. The second part deals with the development of SSO mitigation strategies based on Water Sensitive Urban Design (WSUD) approaches. This paper also demonstrates the application of the first part of the proposed framework for a case study catchment in Melbourne, Australia. The hydraulic performance of the case study sewer network during a wet and a dry year is presented. The analysis found that for the wet year, 11 manholes had sewer overflows, whereas 53 of 57 manholes in the network of 3.2 km had surcharges. Such a study will benefit the water authorities to develop mitigation strategies for controlling SSOs in their sewer systems.

Model Predictive Control of a Large-scale River Network

This study investigates the use of Model Predictive Control (MPC) for regulation of river flows. During the past decade, MPC has emerged for controlling open water systems, such as irrigation and drainage channels. Compared to a full river network, irrigation and drainage systems are of relatively small scale. The aim of the present work is to investigate MPC as a tool for control of releases from gates and dams in a large-scale river network using the Murrumbidgee River in New South Wales, Australia, as case study. The Murrumbidgee River has around 1300 kilometers of river reaches, and the travel time through the valley is of the order of one month. The research has focused on four points: 1) Configuring linear surrogate models to describe the characteristics of reaches and weir pools; 2) Formulating the control problem and its objectives; 3) Using MPC with a receding horizon to solve the control problem; and 4) Testing the accuracy of the calculated control action, by using it as forcing in a detailed hydraulic model. The tests show that a reliable computation of optimal releases from regulators throughout the river is obtained, despite the linear approximation of the dynamics. The tests also show that the computation time for setting up and solving the optimization problem is no more than a few minutes on today's laptops.

USE OF INFORMATION SYSTEMS TO IMPROVE THE EFFICIENCY OF WATER SUPPLY COMPANIES (THROUGH THE EXAMPLE OF TUMEN VODOKANAL)

In the article the steps required to create a detailed hydraulic model of the water network Tumen with the use of geographic information systems (GIS) Zulu are described. The effectiveness of the design scheme for solving a number of applied problems of water utility network optimization, implementation of programs to reduce pressure and planning for a case of emergency are shown. Real-life experience of GIS using for accidents analyze, certification, introduction of the water supply objects single classifier are presented. Perspective ways of information system development are viewed.

Evaluating rain gardens as a method to reduce the impact of sewer overflows in sources of drinking water

The implications of climate change and changing precipitation patterns need to be investigated to evaluate mitigation measures for source water protection. Potential solutions need first to be evaluated under present climate conditions to determine their utility as climate change adaptation strategies. An urban drainage network receiving both stormwater and wastewater was studied to evaluate potential solutions to reduce the impact of combined sewer overflows (CSOs) in a drinking water source. A detailed hydraulic model was applied to the drainage basin to model the implementation of best management practices at a drainage basin scale. The model was calibrated and validated with field data of CSO flows for seven events from a survey conducted in 2009 and 2010. Rain gardens were evaluated for their reduction of volumes of water entering the drainage network and of CSOs. Scenarios with different levels of implementation were considered and evaluated. Of the total impervious area within the basin directly connected to the sewer system, a maximum of 21% could be alternately directed towards rain gardens. The runoff reductions for the entire catchment ranged from 12.7% to 19.4% depending on the event considered. The maximum discharged volume reduction ranged from 13% to 62% and the maximum peak flow rate reduction ranged from 7% to 56%. Of concern is that in-sewer sediment resuspension is an important process to consider with regard to the efficacy of best management practices aimed at reducing extreme loads and concentrations. Rain gardens were less effective for large events, which are of greater importance for drinking water sources. These practices could increase peak instantaneous loads as a result of greater in-sewer resuspension during large events. Multiple interventions would be required to achieve the objectives of reducing the number, total volumes and peak contaminant loads of overflows upstream of drinking water intakes.

Ecohydraulic-driven real-time control of stormwater basins

Control of stormwater basins can be a competitive measure to improve the ecohydraulics of urban rivers by increasing the removal efficiency of particles and agglomerated contaminants like heavy metals and by decreasing hydraulic peak flows. In this paper, we present a simulation study that evaluates the potential of ecohydraulic-driven real-time control of stormwater basins to improve water quality and decrease hydraulic stress in the receiving water body. Nine different static and dynamic control scenarios were analysed based on a detailed hydraulic and quality model of an existing small urban catchment equipped with a stormwater basin at its outlet. Under dynamic control, an outlet valve was manipulated to increase retention time. The removal efficiency for suspended solids could be significantly increased by all control strategies and the hydraulic peaks were reduced by at least 50%. At the same time, overflow of the basin is avoided to prevent flooding. The developed dynamic control strategies proved to be advantageous as they provide significantly higher removal efficiency for suspended solids and a possible flexible adaptation to future demands. The findings of this study have been confirmed by field experiments.

Hydraulic analysis of the Wendelstein 7-X cooling loops

Actively water cooled in vessel components (IVC) are required for the long pulse operation of the stellarator Wendelstein 7-X (W7-X). In total, the cooling pipes have a length of about 4.5km, supplying the coolant via 304 cooling circuits for the IVC. Within each cooling loop, the IVC are organized mostly in parallel. A homogeneous flow through all branches or at least the minimum specified flow in all of the branches of a circuit is crucial for the IVC to withstand the loading conditions. A detailed hydraulic simulation model of the W7-X cooling loops was built with the commercial code Flowmaster, which is a 1-D computational fluid dynamics software. In order to handle the huge amount of pipe-work data that had to be modelled, a pre- and post-processing macro was developed to transfer the 3D Catia V5 CAD model to the 1-D piping model. Within this model, the hydraulic characteristics of different types of first wall components were simulated, and compared with their pressure drop measurements. As a result of this work, the need for optimization of some cooling loops has been identified and feasible modified solutions were selected.

Macrochannels and their significance for flood-risk minimisation: examples from southeast Queensland and New South Wales, Australia

Understanding the frequency and causes of extreme events is crucial for environmental, social and economic protection and planning. In Australia this was never more apparent than January 2011 when widespread flooding across Queensland, New South Wales (NSW), and Victoria resulted in the loss of human lives and devastating impacts to infrastructure and local economies. However, understanding the interplay between the geomorphology of catchments and their hydrology remains poorly developed in floodplain planning guidelines. This paper seeks to explain spatial patterns of flood inundation in terms of downstream variations in channel morphometry; and to discuss the significance of these findings within the context of improving flood risk avoidance strategies and environmental outcomes for urban streams. A prominent characteristic of streams draining catchments in the Lockyer Valley south east Queensland and the Illawarra region of NSW, for example, are well developed macrochannels that have formed in mid-catchment zones. Detailed hydraulic modeling using HEC-RAS, HEC-GeoRAS and ArcGIS indicates that these macrochannels are scaled to accommodate high magnitude floods by operating as ‘bankfull’ channels during such events. In south east Queensland, locations where macrochannels debouch onto unconfined low gradient floodplains appear especially vulnerable to catastrophic flooding because of the efficient delivery and minimal attenuation of flood peaks generated in headwater catchments. Macrochannels and associated landforms can be clearly distinguished and mapped on fine-scale digital elevation models, offering the opportunity to integrate analyses of fluvial landforms and channel processes into hydraulic modeling studies, and ultimately, flood-risk avoidance strategies. Such an approach has the potential to improve on traditional flood risk avoidance methods that are focused primarily on design-flood heights by enabling the interpretation of hydraulic modeling outputs in the context of fluvial landforms that exert a significant control on flood behaviour.

Simulation Study to Evaluate Temporal Aggregation and Variability of Stochastic Water Demands on Distribution System Hydraulics and Transport

AbstractAs utilities move toward more detailed hydraulic and water quality network models, the potential for the stochastic nature of consumptive demands having an effect on transport characteristics increases. A nonhomogeneous Poisson rectangular pulse model (PRPsym) was used to generate stochastic water demands aggregated at 1-min, 10-min, and 1-h time steps for a small skeletonized network and a large all-pipe network; results were then linked with EPANET to simulate the impacts of water-demand variability on the underlying transport and water quality. In general, the impacts of temporal aggregation—as represented by flow rate and concentration variability and arrival times—increased as the evaluations moved from the main trunk lines toward dead-end nodes or pipes. More specifically, analysis of a Monte Carlo ensemble of results demonstrated that (1) a 10-min temporal aggregation captured most of the arrival time variability relative to the 1-min aggregation step; (2) hourly demand variability (e.g., f...