World Environmental and Water Resources Congress 2017: Hydraulics and Waterways and Water Distribution Systems Analysis

Channel responses were documented over a decade for a relocated stream channel in central Pennsylvania. The case study illustrates channel responses when a “natural channel design” incorporated hard points to reduce uncertainties and hold the channel in place. In particular, the study focused on the effect of the hardpoints had on channel development. Current conditions were compared with those from a survey taken 10 years prior, as well as the results from a sediment transport model that had been used to predict changes over a 50-year period. The survey measurements were used to assess the ability of the model to predict those changes. In-stream structures include rock vanes at the head and tail of riffles, root wads and rock linings at the outside of meander bends, and J-hooks used to reduce near bank velocity. Results show that the model did a good job of predicting the changes in the channel provided that the in-stream structures remained in place.

In this paper, we report studies to understand the linkage between complex flow patterns and fish movement behaviour at the junction of the Georgiana Slough and the Sacramento River, near Walnut Grove, California. The flows at the junction are oscillatory and complex due to tidal influence. A 3D CFD model is developed to predict the flow patterns at the junction; the model is then validated by comparing with ADCP field data. An Eulerian-Lagrangian-agent method (ELAM) model is used to systematically analyze how measured fish movement, from acoustic-tag telemetry, may be linked to the water flow patterns. The developed too will ultimately be used to forecast how fish may respond to different guidance structure designs under varying river conditions.

Engineered log jam (ELJ) is widely used in the United States for stream and watershed restoration projects. It is economical as the materials are locally available. ELJ itself becomes a natural habitat for aquatic life. The use of ELJ in streams, however, introduces concerns with regard to its safety and impacts on local stream morphology. Design guidelines are still lacking. Laboratory or field study is difficult or costly due to irregular nature. Computational modelling, therefore, becomes an attractive alternative. In this study, a practical, semi-automatic, 3D numerical model is developed to simulate complex flow patterns produced by an ELJ. The ELJ is also placed in a large flume so that velocity is measured and used to verify the numerical model. The ultimate goal is the ability to predict complex river flows and morphological changes induced by in-stream ELJ structures in the field.

This paper presents a probabilistic approach to quantify uncertainties of shoreline changes (accretion and erosion) by using Monte Carlo simulations. A shoreline evolution model, GenCade, is used to simulate longshore sediment transport and shoreline changes induced by random waves from offshore. A probability density function is developed to capture stochastic features of wave heights under both fair weather and extreme weather conditions. It produces time series of wave heights including small and extreme waves based on their probabilities (or frequencies of appearance). This will generate uncertainties in prediction of annual maximum shoreline erosions in different return periods (years). The developed Monte Carlo Model for GenCade can be used to assess reliability and uncertainty of prediction in shoreline changes in natural coasts.

Overtopping is one of the major causes of dam and levee earthen embankment failures. The mechanism of breach caused by overtopping erosion is a complicated process but commonly modelled as either head-cut starting from the toe of the embankment slope progressing upward, or as surface erosion starting from the embankment crest. The two mechanisms are modelled for cohesive and non-cohesive soils, respectively. However, the distinction between the two types of soils from the erodibility aspect is not well established. In this paper, overtopping erosion of different soil mixes is addressed through sediments transport models. The paper presents results from small scale breach experiments on a levee section constructed from four compacted soil mixes of clayey and silty sand with and without fine gravel. Simulation of the small scale tests was performed using two dimensional shallow water (2DSW) hydrodynamic model and a sediment transport library (SEDLIB). The experiment results indicate that for silty sand mixes, erosion start at the crest and progresses downward, while erosion for the clayey sand mixes starts close to the toe and progresses upward. The presence of pea gravel size particles in the mixes slows down the erosion process and time to breach as they do not erode at the same rate as the finer particles. 2DSW-SEDLIB simulation results are presented and compared to the experimental results.

A variety of hydrodynamic and transport codes based on the solution of shallow water equations exist. These codes are predominantly based on the finite difference (FD) or finite volume (FV) method, though finite element method (FEM) codes are gaining in popularity. This paper presents the development and application of an unstructured fluid (and constituent transport) mass conservative three dimensional (3D) FEM code for multi scale flows.

A one-dimensional sediment transport model is updated to simulate a sediment sluicing/flushing plan with the proposal of outlet works modifications. Paonia Reservoir is located on Muddy Creek in western Colorado, and nearly 25% of its original capacity of 20,950 acre-feet has been lost to sediment deposition. In the Fall of 2014, Paonia Dam became partially blocked with sediment and debris. Assuming the reservoir outlet works can be modified to pass woody debris and sediment, a proposed sediment sluicing/flushing plan was conceptualized to lower the reservoir pool in the early spring and to sluice and flush sediment with high spring run-off flows through the outlet works before closing the gates to refill the pool for irrigation season. For this reason, the numerical model is modified to include a user-defined set of reservoir operation rules, which is implemented to assess the long-term effects of managing inflow and sediment deposition in Paonia Reservoir. The numerical model is calibrated by the 2015 reservoir survey and incoming and outgoing suspended sediment concentrations from April 2013 to June 2015, and is used to predict the reservoir sedimentation with a long term simulation in the next 20 years.

Flow at a spillway can be classified into four conditions: submerged weir, free weir, submerged orifice and free orifice. There is also a transition between any two adjacent flow conditions. Since the early 1930s, extensive investigations on spillway flow computation have been conducted, resulting in a plethora of equations for each of the flow conditions. At the transition between two flow conditions, computed discharges for the two conditions are not consistent. Ansar and Chen (2009) proposed a new generalized flow equation, which is applicable to all flow conditions at a spillway, including transitional flows. This paper presents comparison results between computed discharges at spillways using the generalized flow equation and measured discharges in the field in south Florida and the Utah Water Resources Laboratory. The computed discharges agree well with flow measurements.

Sediment transported along with extreme flooding may greatly affect flood conveyance and associated operations and management in the lower cache creek system. In this study, the relative sediment capture and transport in lower cache creek, under current bathymetric conditions and one modification alternative (2A), is evaluated. Sediment dynamics in the lower cache creek system, which includes a floodplain and settling basin, are evaluated under extreme flow events. Of particular interest is the sediment trap efficiency of the cache creek settling basin (CCSB) under different flood scenarios. The CCSB was designed as a retention basin to capture sediment and reduce sediment loading into the Yolo Bypass, therefore preserving flood conveyance of the bypass. Sediment dynamics for each flow event, under both the current condition and 2A, are simulated with the CCHE2D model, a two-dimensional depth-averaged flow and sediment transport model. The simulations allow relative comparison of the sediment trapping performance of the current condition and 2A. Preliminary simulation results are presented here.

This paper uses the Henry problem to examine the conditions at which uncoupled models can be used to predict flowrates, flow directions, and saltwater intrusion in coastal aquifers when saltwater intrusion takes place. The SEAWAT model is used to determine results under both coupled and uncoupled conditions under various scenarios by changing: (a) the hydraulic conductivity anisotropy ratio K_r, defined as the ratio of the horizontal to the vertical hydraulic conductivity, K_h/K_v, from 1 in the original Henry problem to 1000, (b) the freshwater recharge rate Q_f from the original value of 5.702 m^3/day to 50% and 75% lower at different K_r conditions. The discrepancy between isochlor locations, groundwater flow directions, and the percent of recirculated seawater by the coupled and uncoupled models, decreased substantially with increasing K_r values. Even a K_r value of 20 produced very similar results. The discrepancy between the two sets of results, coupled versus uncoupled, increases when Q_f is reduced. However, the results from the two models match well for K_r = 100 even if Q_f is reduced by 75% of the original value used in Henry problem. It may be possible to use uncoupled models if the K_r = 100 or higher regardless of the freshwater recharge.

This study quantified sediment transport processes and geomorphic trends along the lower American River, California, for evaluating impacts of the Folsom Dam Modification Project on channel morphology. The analysis used a HEC-6T sediment transport model of the 22-mile reach of the American River below Nimbus Dam and the adjoining 32-mile reach of the Sacramento River. Model geometry was based on 1997 and 2006 bathymetric surveys. Bed material characteristics in the model were specified from a surface and sub-surface sampling program and geotechnical investigations of erosion-resistant stratigraphy. The model was calibrated to measured sediment loads and bed profiles. The calibrated model was then used to simulate long-term morphological changes in the lower American River under existing and project hydrologic conditions. The model results obtained for existing conditions indicated active degradation of the American River below Nimbus Dam and predominant aggradation in the downstream reach, which is consistent with field measurements. The project condition results, which include higher flow releases through the new auxiliary spillway, indicated increased channel degradation immediately below Nimbus Dam and showed no significant changes in bed profile in reaches further downstream to the confluence with the Sacramento River.

The California Department of Transportation (Caltrans) District 7 North Fork Matilija Creek (NFMC) Geomorphology, Fish Passage, and Engineering Project protects local steelhead trout habitat while repairing erosion along State Route 33. This project was unique in that the existing step-pool system provided excellent rearing habitat for juvenile steelhead. The steepness of the canyon limited the potential approaches that would be compliant with existing environmental guidelines. Engineers demonstrated that although the 5-foot drops were outside the recommendations of the design manuals, they were within the steelheads’ capabilities. After demonstrating that adult fish could pass through the step-pools, further analysis determined that the channel widening would not fill the juvenile rearing pools with sediment. Trees, riparian habitat, and habitat structures were added to keep the stream cool and provide cover and shelter for the fish. The system protects the juvenile fish rearing pools and will help the steelhead population increase within the creek.

The history of physical model studies to study hydrodynamic process is well documented in the literature and has long been an acceptable methodology to study river behavior, geomorphic processes, and the interaction of civil infrastructure with the river environment. Early on, before the advent of numerical models, it was the only way evaluate the complex interactions between water, channel and structure. In the Authors’ careers, there has been an inevitable ebb and flow of opinion between computational and physical modeling supporters. During periods of time where computational improvements are significant, there are many that opine that we no longer need physical models. Yet our experience is that even now; with the significant advances in computational speed, massive storage capability, and rapid realistic graphical rendering of results; that tactile physical models remain as a potent analysis tool for the study of complex flow patterns that exist in nearly every water resources project. It is the intent of this paper to make a case for continued reliance on physical models into the foreseeable future. It is our experience and opinion that the digital and physical approach, when employed together provide significantly improved hydraulic designs that significantly reduce overall project costs. Many believe that usage of advanced computational methods (i.e. 2-dimensional models) or physical models should be reserved for large costly infrastructure projects. However, it is our experience that a combined physical model/numerical model approach can significantly improve cost and performance for modest-sized projects as well. As such we believe that this approach should be employed more frequently, as it is our experience that the added analysis costs are modest, and more than offset by project savings that result from a significant reduction in uncertainty. Our experience runs counter to the idea that physical models are large, costly endeavors, and can only be accomplish in one of the few hydraulic labs in the country. While it is true that a model of a section of the a large river such as the Missouri, Mississippi, or Ohio River likely needs the resources of a large lab, most river related projects are of a much more modest size. Rivers as large as 200 feet wide can be easily modeled in a relatively small laboratory or commercial space. As proof of these assertions, this paper documents three modest sized physical models which were conducted in a joint effort between Water Resources Solutions and Engineering Department at the University of Missouri-Kansas City. Each of these models has refined the modeling approach that we believe efficiently integrates numerical and physical modeling on a scale that can be completed in a reasonably sized laboratory. In each case, the approach has been refined and the models have clarified uncertainties such that project savings have been witnessed in the range of 30-70 percent of original budget.

Oxygenation efficiency has gained more and more attention in water bulk with a fine bubble aeration diffuser system operating. To enhance the oxygenation efficiency, one of the important researches is to explore the respective impact of different sources and the key factors on dissolved oxygen mass transfer, which will in turn be better for the design and operation of the fine bubble aeration diffuser system. A series of laboratory experiments for re-oxygenation were carried out in a glass tank, the fine bubble aeration diffusers were used to generate abundant fine air bubbles. There were two regions, i.e. the air bubbles and the non-bubbles zones in the experimented water bulk. According to the mass balance theory, the bubble-water surface mass transfer, turbulence diffusion mass transfer, global mass transfer and their oxygen utilization rates were achieved. The results showed that the values of oxygen volume mass transfer coefficient in air bubbles zone are smaller than the values of global oxygen volume mass transfer coefficient. The global oxygen utilization rate is greater than the oxygen utilization rate of bubble-water surface mass transfer. The impact of key factors on the global mass transfer are the bubble rise velocity, water velocity, submerged water depth, air flow rate, bubble diameter and water volume. The important factors improving aeration efficiency are the bubble rise velocity, bubble diameter and water velocity.

Recently, a one-mile long bridge (OMB) was built on the Florida’s Tamiami Trail to enhance water deliveries to the Northeast Shark River Slough (NESRS) in the Everglades National Park (ENP). The OMB changed point inflows through culverts across the old Trail embankment to sheet flow through the bridge. Current guidelines for designing and assessing whether structural changes of this type conform to restoration expectations are seldom based on field studies. We present a field study aimed at evaluating of the flow distribution through the OMB based on acoustic doppler current profiler (ADCP) measurements and to identify the feasibility and potential challenges of long-term monitoring of the flow under the bridge. Our field data showed that spatial variability of the vegetation type and density in the ENP near the downstream side of the bridge and the resulting non-uniform vegetative resistance affects the distribution of the flow through the bridge. Moreover, our field data, along with analyses of other data obtained by the United States Geological Survey (USGS), showed that the flow distribution through the bridge is also affected by the presence of remnant flow paths through the natural marsh and wind speed acting upon the flow in the L-29 canal on the north side of the bridge.

CFD (computational fluids dynamics) analyses are playing more and more important roles in water resource related problems. However, the analyses are often time-consuming when the numerical models are applied to large-scale, long-term, and computation-intensive problems. The situations become more challenging in the era of mega data, when huge amounts of data require efficient computation, treatment and interpretation. The numerical modeling systems developed at National Center for Computational Hydro-science and Engineering (NCCHE) provide efficient modeling solutions for a variety of research objectives. 1D model is the most suitable and efficient tool for hydrology/hydraulic solutions to large-scale and long-term problems. A parallel computing module of CCHE2D using GPGPU (general-purpose computing on graphics processing unit) has been developed for both general flow and dam-break flow/flooding simulations. This parallel computing capability enable us to significantly enhance efficiency by distributing computation loads to multiple processers working in the same time. To improve the computation efficiency of 3D models for large domains, a novel sub-domain method has been developed for CCHE3D. The method allows us to obtain high resolution and sophisticated local 2D/3D results efficiently at the interested locations in a large domain covered with a coarse mesh.

The Puyallup and White Rivers in western Washington are high gradient, high supply systems with downstream water surface elevation controls. Both rivers are actively aggrading and include gradual cobble-gravel and abrupt gravel-sand transitions. Aggradation increases flood risk along both rivers. Therefore any future flood risk projections or examination of flood mitigation alternatives requires morphological analysis. The U.S. Army Corps of Engineers (USACE) developed a Hydrologic Engineering Center, River Analysis System (HEC-RAS) sediment models of the White and Puyallup rivers to assess non-stationary benefits of flood risk management alternatives in these morphologically dynamic systems. However, it was not sufficient to calibrate these models to standard volume change metrics. These models demonstrate sediment transport’s propensity for equifinality errors and the importance of multiple calibration metrics when evaluating sediment transport calibrations. This paper will overview the development of the Puyallup and White River sediment models, describe the calibration parameter evaluation and selection process, and demonstrate how multiple calibration evaluation metrics (e.g. volume change and bed gradation) avoided potential equifinality errors (i.e. errors emerging from non-unique solutions in multiple parameter models).

The current version (5.0) of the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) and the imminent version (5.1) include an array of new sediment transport capabilities. Previous HEC-RAS versions were limited to quasi-unsteady flow and vertical bed change. HEC-RAS 5.0 and later versions eliminate each of these limitations, including unsteady flow capabilities, lateral cross section change with the USDA-ARS bank stability and toe erosion model (BSTEM), and several other features that expand the model’s applicability. Coupling sediment transport with the HEC-RAS unsteady flow capabilities also leverages unsteady capabilities for sediment analysis, including mixed flow regimes, lateral and inline structures, and operational rules. Additionally, recent versions of HEC-RAS include new bed change algorithms, cohesive transport approaches, armoring methods, and an array of new output options. This paper will highlight the new one-dimensional (1D) sediment capabilities in recent versions of HEC-RAS.

Climate and land cover changes have the potential to intensify rates of soil erosion and sedimentation in large watersheds, which can adversely affect aquatic life and poses a critical challenge for water treatment and reservoir management. The goal of this research is to develop a modeling ensemble for estimating sediment transport within large-scale mountainous catchments (>1000 km²). The results from four sediment modules inserted into a common hydrologic framework are presented to quantify uncertainty and improve predictability. The ensemble includes empirical modules: monovariate rating curve (MRC) and the modified universal soil loss equation (MUSLE), a stochastic module: multi-variate regression using a generalized linear model (GLM) and a physically-based module: distributed hydrology soil vegetation model (DHSVM) sediment model. Calibration results from a multi-objective optimization routine are presented that optimize parameters and identify performance tradeoffs. The GLM module had the overall highest performance for both daily (NSE=0.84) and event-based (NSE=0.99) predictions. The MRC module performed well under both time steps (NSE=0.64, NSE=0.91). The MUSLE module had the highest performance in percent bias (−0.56%) of all the modules, though it performed poorly in timing and variability for both time steps (NSE=0.22, NSE=0.49). The DHSVM module performed the poorest under the daily simulation (NSE=−0.24), but the skill was greatly enhanced for event-based predictions (NSE=0.96) reflecting the influence of temporal discretization. This work highlights the tradeoffs in sediment prediction across a range of model structures with key differences in daily versus event-based model performance.

At the Great Lakes Water Authority (GLWA) Water Resource Recovery Facility (WRRF) in Detroit, Michigan, primary and secondary treated effluent is discharged to the Detroit River Outfall (DRO) and Rouge River Outfall (RRO). The most recent national pollutant discharge elimination system (NPDES) permit requires GLWA to disinfect all flow discharged from the plant. Currently only the existing DRO system is equipped with disinfection facilities. A comprehensive hydraulic evaluation was required to determine whether sufficient chlorine disinfection contact times could be achieved for the RRO system given its much shorter length. This evaluation was a hybrid approach that utilized a combination of physical, analytical and computational fluid dynamics (CFD) modeling. This paper reviews how the modeling tools were used to demonstrate that the NPDES permit requirements could be met.

The operational issues created by episodes of storm water geysering have drawn researchers and engineers’ attentions in the past 20 years. However, only recently that more insights has been obtained in the geysering events caused by uncontrolled release of trapped air pockets in a water-filled vertical shaft. With better understanding upon the key factors affecting geyser intensity, it is possible to determine practical ways to mitigate negative effects of air release, which leads to geysering. This manuscript evaluates in a preliminary fashion the strategy of extending the lower rim of vertical shafts to the springline of horizontal tunnels/sewers as a means to reduce the capture/scooping of air pockets that travels in these conduits as gravity currents. The strategy is evaluated for a simple geometry by applying the CFD tool OpenFOAM to model the passage and interaction of the air pocket with the vertical structure of the extended shaft. Different configurations with different shaft geometries are simulated and compared with conditions in which these extensions are not used. The results will guide the development of experiments that will evaluate this strategy in a laboratorial setup.

The climate change and land use change have raised the challenges associated with increased runoff and flood management. The risks associated with flooding have been increasing with development in flood plain and changing climate resulting in increase in inundation of flood plain. The current study will help to evaluate the extent of flood plain in the study area–copper slough watershed (CSW) in Champaign, Illinois; utilizing the known precipitation and land use. The study of CSW is taken into account, as this is the largest watershed of Champaign City and had undergone major land use change increasing the flooding issues in the region. The conducted research utilizes the hydrologic engineering center-hydrologic modelling system (HEC-HMS) and Hydrologic Engineering Center–River Analysis System (HEC-RAS) as the modelling tool to develop runoff and floodplain inundation evaluation model for known precipitation. The model also incorporates aeronautical reconnaissance coverage geographic information system (ARCGIS) extensions-HEC-GeoRAS and HEC-GeoHMS for the spatial analysis of the watershed. The hydrologic analysis is performed using HEC-HMS while the hydraulic modeling is done using HEC-RAS. Forcing the model with forecasted precipitation can also help with flood warning system by generating pre-flood inundation maps.

In the United States, one component of the detailed flood study is to outline the floodway. In floodway boundary determination, encroachment is applied at every cross section to where the rise in water surface is kept just below an allowable threshold while preserving the same flow state as in the floodplain model. Determination of optimal floodway boundaries can be tedious and time consuming if done manually. However, good floodway boundaries provide valuable information to regulating agencies and engineers aiding them in decision making, planning and management of floodplain development activities. This study introduces the automated floodway optimizer for HEC-RAS (AFORAS). AFORAS uses the standard HEC-RAS hydraulic model and the isolated-speciation-based particle swarm optimization (ISPSO) algorithm to produce reach-wide optimal floodway boundaries. The proposed method was developed to automate the determination of optimal floodway boundaries such that the resulting floodway will occupy minimal footprint area without violating user-specified hydraulic constraints. Preliminary simulations show that, once setup, AFORAS was able to produce optimal floodways without user intervention. The model was also observed to be robust and capable of handling cases with different boundary conditions. AFORAS shows promise as a tool for automating the floodway for practical use. In addition, the model was designed to tightly couple with the standard HEC-RAS hydraulic model and, therefore, can be a useful tool for the floodplain modeling community as well as regulating agencies.

The study demonstrates from theoretical considerations as well as using numerical examples that while a flood wave characterized by the form of kinematic wave used in the development of Jones formula is not necessarily a kinematic wave which is characterized by insignificant magnitude of the non-dimensional longitudinal water surface gradient (1/S₀)∂y/∂x, where S_o is the bed slope of the river; y is the flow depth and x is the variable denoting the spatial length, implying insignificant size of hysteresis of the rating curve under flood conditions. The paper demonstrates that the hysteresis size of the rating curve formed during flood flow is directly proportional to the absolute magnitude of (1/S₀)∂y/∂x characterizing a flood wave and the absence of subsidence of a flood wave may be attributed either to the insignificant magnitude of (1/S₀)∂y/∂x or due to forcing the diffusion coefficient of the equation governing flood wave to be zero. The study proves the point that the Jones formula developed using the form of kinematic wave equation is logically correct contrary to the viewpoint expressed in the literature.

River ice cover is a reoccurring phenomenon in the Northern United States every year. Sheets and layers of ice result in a rise of water surface elevation and may lead to ice jams in a river. This research explains the modeling of a river reach through Northern Illinois containing a structural weir and how the water profile is effected during ice cover and ice jam events. The Hydraulic Engineering Center’s River Analysis System was used in conjunction with Esri ArcMap software to model a portion of the river for analysis. The study area of the Rock River flowing through Oregon, IL, is known to freeze and ice over during the winter months in Northern Illinois. Data from the United States Geological Survey and National Oceanic and Atmospheric Administration were utilized to obtain cross-section and discharge measurements. The impacts of an ice jam occurring upstream of the weir and downstream of the weir were studied. The effects of the ice jam on the upstream water levels were also evaluated to observe if any flooding may occur inside the town or even farther upstream. Results of the ice cover and ice jam data were then compared to those of the Rock River under normal open flow conditions thus observing the change in water level, Froude number, and flow velocity. Results from this study help to point out the significance of ice jam occurrences and their effects on inline structures and future flooding concerns in the surrounding area.

Every Year, flooding causes a calamitous impact on the people, economy, and environment all over the world. In recent years, the flood-related damages have been increasing in the United States regardless of several investments in the flood control measures. Floodplain mapping is an important tool for management that aids in the planning of infrastructures within the floodplain zone. With the magnifying effects of climate change on the hydrological cycle the study of floodplain is becoming a key tool in the water management. Federal Emergency Management Agency has recently updated their floodplain standard as per the presidential executive order 2015 on the Federal Flood Risk Management Standard. This study incorporates the newly updated floodplain mapping standard in the flood risk assessment of approximately 11.2 km stretch of the Patapsco River near Ellicott City. Hydrologic Engineering Center’s River Analysis System (HEC-RAS) with the conjunction of geographical information systems were used in the floodplain analysis. The different return period flows (2, 5, 10, 25, 50, 100, and 500) were used from the frequency analysis. These flows were routed through the selected reach of Patapsco River and the vulnerability assessment of the nearby existing infrastructures was conducted. This study can assist the decision makers and planner for the implementation of flood protection measures near the Ellicott City.

Present study uses two dimensional flow routing capabilities of Hydrologic Engineering Center’s River Analysis System (HEC-RAS) for flood inundation mapping in lower region of Brazo River watershed subjected to frequent flooding. For analysis, river reach length of 20 km located at Richmond, Texas, was considered. Detailed underlying terrain information available from digital elevation model of 1/9-arc second resolution was used to generate the two-dimensional (2D) flow area and flow geometrics. Streamflow data available from gauging station USGS08114000 was used for the full unsteady flow hydraulic modeling along the reach. Developed hydraulic model was then calibrated based on the manning’s roughness coefficient for the river reach by comparison with the downstream rating curve. Corresponding water surface elevation and velocity distribution obtained after 2D hydraulic simulation were used to determine the extent of flooding. For this, RAS mapper’s capabilities of inundation mapping in HEC-RAS itself were used. Mapping of the flooded areas based on inflow hydrograph on each time step were done in RAS mapper, which provided the spatial distribution of flow. The results from this study can be used for flood management as well as for making land use and infrastructure development decisions.

A process-based approach to designing perennial secondary channels in alluvial gravel-bed rivers was developed for Sonoma County Water Agency’s Dry Creek Habitat Enhancement Project. Under natural conditions secondary channels are part of a complex geomorphic feature commonly known as an anabranch. The morphology of anabranching secondary channels hinges on complex sediment deposition and erosion processes at the bifurcations and confluences, and sediment routing processes through the secondary and main channels. Environmental Science Associates took a nested approach to secondary channel design to influence multiscale geomorphic processes through topographic manipulations, construction of riffle-pool features, and the placement of large wood structures to create self-maintaining secondary channels under dynamic conditions. The design basis relied heavily on recent scientific research of processes for anabranching channels, bifurcations, confluences, riffle-pool units, and large wood. The design was analyzed with a two-dimensional hydraulic model to test processes responsible for self-maintenance over a range of flows.

Irrigation reservoirs are widely used in the Mississippi River alluvial floodplain to supplement limited groundwater resources. Constructed using local soils that are often low in clay content, the earthen embankments of these reservoirs are susceptible to wave erosion. This paper presents the findings of laboratory experiments carried out to quantify wave induced erosion and retreat of a model erodible embankment, made of natural soil, under the action of regular waves. A standardized packing procedure was developed to establish the model embankment in the wave tank. Particle size distribution, critical shear stress and the packed density of the model embankment were measured. The model embankment was exposed to wave action for up to 48 hours, and the amount of eroded material and retreat were monitored. Relationships were established between erosion, retreat rate, and incident wave characteristics. The waves quickly undercut the upper part of the embankment face and formed a scarp, which retreated in discrete slump failures until an equilibrium profile was established. The results of the experiments showed that eroded volume was linearly related to retreat distance for the conditions of this study. A unified empirical relationship was established for erosion and retreat rates, which depended only on wave height for the tested embankment characteristics.

Frequency analysis of runoff is one of the major approaches in modeling and estimating the probabilistic behavior of discharge in rivers. Two intermittent rivers, one in Turkey another in Iran, Shahar-Chay and Akarcay both located between 30°–40° Northing latitude are selected for comparative investigations. Both rivers show similar behavior in moments and properties of distribution. A set of common 40 year of monthly recorded data between 1961-2000 is selected. Comparative frequency analysis is done on the data by dividing the time series into two-time intervals between 1961-1980 and between 1981-2000. Results indicate an alteration in low and medium range flows in Akarcay. Both stations show that droughts are becoming more frequent while the frequency and the magnitude of the extreme events are increasing. It is also concluded that the seasonal properties of partial-auto-correlation and auto-correlation coefficients have been altered for both of rivers.

The watershed erosion model for the Barry M. Goldwater Range (BMGR)-West was developed by using the automated geospatial watershed assessment (AGWA) modeling tool. AGWA is a GIS-based hydrologic modeling tool that uses commonly available GIS data layers to fully parameterize, execute, and spatially visualize results for several watershed runoff and erosion models, including SWAT2005 and KINEROS2. SWAT2005 is an annualized erosion assessment model, while KINEROS2 is an event-based hydrology and erosion model that simulates sediment yield from each storm event. The range consists of three major watersheds, and each watershed was further delineated into many sub-watersheds. Precipitation, soil, and landuse data were obtained from the NOAA, STATSGO, and USGS public databases, respectively. The results from the SWAT2005 and KINEROS2 models showed the erosion and deposition depth at each basin depends on basin slope, elevation, soil type, and landuse.

The complexity of flow area determination in compound channels may lead to errors in flow estimation. Although the uniform flow formulae, such as Manning’s equation, are widely used to determine flows through open channels having simple cross-sections, this may lead to considerable errors in the case of compound channels. This paper evaluates various alternatives to account for flood plain conveyance in non-symmetrical trapezoidal compound channel cross-section. Evaluations are based on applying several traditional discharge estimation methods to a field data aiming at determining the best interface plane arrangement leading to flow estimation for different flow depths. Six interface and one other standard method for computing discharge in open channels were compared. Each interface method uses a particular arrangement of imaginary interface planes to artificially sub-divide the compound flow field into homogeneous zones. These methods are named for the particular interface plane arrangement adopted. The standard method does not involve interface planes. Computed discharges were compared and evaluated by applying various statistical measures to determine the degree of goodness-of-fit between computed and observed discharges. In terms of overall performance, the weighted extended side slope method proved to correctly predict the discharge. However, the vertical interface planes method produced the most accurate computations among the methods tested for the non-symmetrical trapezoidal compound channel cross-sections under consideration.

Flood wave propagation is simulated due to a hypothetical ash dyke failure, in this work. Effect of breach parameters, bed roughness, and rheological parameters on the propagated flood is studied. For the cases considered, maximum flood depth at a downstream location (1.5 km from ash dyke) increases by approximately 10 per cent, when the breach width is doubled. However, the maximum flood depth is increased by 25 percent when the breach depth is doubled. It is found that the breach time and bed-roughness do not affect the results significantly. Simulated results suggest that viscosity has insignificant effect on flood wave propagation. However, both specific gravity and shear stress have a strong bearing on the results. A 50 per cent increase in the specific gravity results in 15 per cent increase in maximum flow depth. Similarly, the maximum flow depth is increased by 30 per cent when shear stress is doubled.

The present paper presents a dam-breach study in support of Shelby County Department of Development Services for developing emergency action plans and for other planning purposes. The study involved two-dimensional numerical modeling of four dams located in the Oak Mountain State Park, which are within the Cahaba Valley Creek Basin (a.k.a. Bishop Creek): Double Oak Lake, Lake Tranquility, Beaver Lake, and Lunker Lake. The modeling and simulations were carried out using the DSS-WISE software and included the sunny day breach and probable maximum flood (PMF) breach scenarios. A PMF base scenario with no dam breaches was also simulated. The simulations included individual breaching of each dam as well as the cascading failure of the Lunker Lake and Beaver Lake Dams. Modeled PMF conditions were based on the inflow design flows generated by the 90% of the probable maximum precipitation (PMP) distributed over the upstream drainage basins of the dams. Hydrologic analyses were carried out using USACE HEC-HMS model to estimate inflows to the lakes. Hydrologic data for Bishop Creek was obtained from a hydrologic study performed as part of FEMA’s flood insurance study. The paper presents the results of the hydrologic study and the two-dimensional modeling of cascading and individual dam-breach flood modeling and inundation mapping. It discusses how the simulation results were used by the county for the development of emergency action plans and for other purposes.

Dynamic ice accumulation within hydraulic structures in rivers and streams can have a significant impact on the connected natural habitat and adjoining transportation infrastructure. Excessive ice formation within culvert barrels reduces the available cross section area and increases the wetted surface subject to flow. These conditions reduce the overall capacity of culverts and can increase the potential for overtopping and subsequent road surface failure, especially during rapid thawing. Excessive ice formation was observed in several culverts of various design methods throughout the Superior National Forest in northeastern Minnesota. Air and water temperature sensors combined with time-lapse cameras indicate that culvert design characteristics such as available freeboard combined with repetitive temperature cycles above and below freezing contributed to excessive ice accumulation within the barrel of the study culverts. The objective of the study was to identify culvert characteristics conducive to dynamic ice formation and determine designs critical for mitigating culvert failure.

Scour around abutments is one of the main causes of failure at bridge foundations. Hence, it is important to cater for scour around these structures to an acceptable safety level. The design of scour countermeasures around abutments needs an estimate of the temporal variation and characteristics of the scour hole formed. This study focuses on the scouring around 45° wing wall setback abutments in a compound channel. As literature showed previous studies were mainly on scour depth around thin vertical abutments in rectangular channels. The measurements of the scour depth, length, width, surface area and volume of the scour hole at different time intervals until its equilibrium scour conditions have been conducted. The effect of abutment length and time on the characteristics of the scour hole is analyzed, and the prediction of scour hole dimensions at equilibrium is proposed based on dimensional analysis. It is found that the influence of increasing the abutment length on the depth and width of the scour hole is greater than on scour length. Furthermore, the influence of this parameter on surface area is greater than on scour volume.

Two-dimensional numerical models in hydraulics often utilize LiDAR-based digital elevation models (DEMs) in order to establish a high-resolution floodplain topography. Conventional LiDAR operates at wavelengths in the near-infrared region, and it is mostly absorbed by water leaving gaps in the generated point cloud data. The lack of underwater topography is also a problem when working with DEMs generated by other methods. Therefore, additional data is required to correctly represent the riverbed topography. One of the data sources that can be used to generate the riverbed topography is the surveyed river cross-sections. Due to the nature of the cross-section data, the measurement points are much closer in the cross-stream direction than in the stream-wise direction. Natural shape of the riverbed also shows a similar anisotropy, such that the topography varies more abruptly in the cross-stream direction. Therefore, special methods are required to generate a realistic riverbed topography using cross-section data. This paper presents techniques that were used to generate riverbed topography using cross-section data, which is then burned into a DEM. First, cross-section points are transformed to a channel-fitted curvilinear coordinate system. The scales in the stream-wise and cross-stream directions are adjusted to account for the anisotropy in the topographic variations. Then, DEM elevations are interpolated in the transformed space using the cross-section points and a set of points along the bank lines extracted from the DEM. The successful use of the method is demonstrated by applying it to generate the two-dimensional riverbed topography for a 187.4-mile-long stretch of Ohio River including man-made structures and natural islands.

State Route 107 (SR 107) crosses the Chehalis River just downstream of Montesano, Washington. Upstream of the bridge, a meander bend threatens to cut off and there is concern that this might worsen the hydraulic conditions at the SR 107 crossing and increase scour potential at the bridge. A high-flow bypass channel across the bend is proposed to prevent the cut off. To analyze the effects of these scenarios on the scour potential at the SR 107 Bridge, we developed a two-dimensional model of the area using the sedimentation and river hydraulics–two-dimensional (SRH-2D) model developed by the Bureau of Reclamation. The model found that the upstream avulsion would not have a significant effect on bridge hydraulics, while the proposed bypass changed both the flow dynamics and scour potential at the bridge. Additional investigation is required to ensure that the bypass does not have a detrimental effect on bridge hydraulics.

Changing climate and topography gradients are factors that collectively account for the variability in water and sediment fluxes in large agricultural systems. This variability hinders the effective management and monitoring of water quality and nutrient cycling, and emanates from the characteristic spatiotemporal scales of runoff and sediment processes for both the smaller and larger systems. The aim of this study is to describe these characteristic spatiotemporal scales at the plot scale by accounting for the interplay between relevant erosion processes and the forcing characteristics. Two experimental cases with uniform slope are considered, rainfall simulators are used to generate rainfall, and runoff and sediment are continuously measured at a downstream weir. Our results show how the coevolution of the aforementioned processes affect the characteristic spatiotemporal scales of runoff and sediment transport. A qualitative assessment of the coevolution of the dominant processes and their impact on the hydrologic response and landscape evolution at the plot scale, combined with the observed spatial features of the plot throughout the rainfall event provide insight into the interplay between these processes. This study is a step towards understanding patterns of runoff and sediment and the associated propagation across scale, as well as informing sediment transport modeling.

In the 1980s the International Joint Commission listed Lower Green Bay and the Fox River as an Area of Concern. Problems that needed priority attention included contaminated sediment, poor water quality, and lost or altered habitat. The transport of nutrients, sediments and contaminants plays an important role on the biogeochemistry, ecology and health of the bay. Local, state and federal agencies have studied the problems caused by excessive nutrients and contaminated sediments. In 1989 Gottlieb et al. deployed tracked drifters from six locations in the bay to map flow patterns. In 2015 Hamidi et al. examined the role of circulation and heat fluxes in the formation of stratification and hypoxia in the bay. Their hydrodynamic model calculates horizontal dispersion using the Smagorinsky turbulence closure model. In 2014 Nguyen et al. used a hydrodynamic model to examine circulation and exchange in the Saginaw Bay-Lake Huron system. Their model was tested against data from a Lagrangian drifter experiment. For this study drifters were deployed in the bay in 2014. Locations of drifters were tracked using GPS transmitters, and those locations were used to calculate one-point dispersion statistics. A Lagrangian particle-tracking model was used to simulate the drifter trajectories. Cross-bay and along-bay velocities were used to compute diffusivities in those directions for observed and simulated drifter tracks. Diffusivity values were estimated using statistical analysis of particles released from a point source in isotropic turbulent flow. The field-data validated diffusivities will be used to improve predictions of the transport and fate of nutrients and sediments in the bay.

When using a hydraulic model with pressure dependent demands (PDD), the PDD function relating demand vs. pressure must represent a collection of orifices (e.g. sinks, toilets, showers, etc.) with a wide variety of orifice coefficients located at different elevations operating at different times. Modeling every orifice for every user is impractical, but some type of effective PDD function relating pressure and water use must be provided. This paper presents several approaches for creating functions that represent water use at the model node and reasonably approximate actual water consumption. When the elevation of the water using orifices differs from the elevation of the model node, the function that represents water use tends to vary from the expected exponent of 0.5, especially at low pressures. This paper explains those findings using both manual calculations and a hydraulic model.

The analysis of water distribution systems (WDS) is carried out under the premise that the flow that passes through the network’s components remains in steady state, i.e., that its conditions are stable over time. However, flow and pressure conditions are very susceptible to changes in the hydraulic elements of the system, so that any variation that occurs in operational patterns of the network immediately modifies this initial premise. This forces us to study the flow under new conditions in which the possibility of changes in the parameters is admitted. This new state is known as transient flow. Closing regulation valves can be included in the necessary operational changes for the proper functioning of a network. Nevertheless, such activity generates pressure waves that can cause deterioration of the network. This paper attempts to find the optimal closure curve for valves in WDS minimizing both abrupt changes in pressure of system’s nodes and the amount of water allowed to pass during closure. Once the results of this optimization process were obtained, the second objective of this research was to prove the existence of the marginal time in a WDS. The use of HAMMER, a computational tool to model transient flow and its effects, was required to accomplish this. Additionally, SPEA 2, a multi-objective genetic algorithm, was implemented to reach an optimal solution for the problem. The methodology was applied in a WDS of Bogota, Colombia, and the research found that the marginal time does exists in small WDS.

In this paper we explore the potential of deep learning for real-time detection of cyber-physical attacks on water distribution systems. Deep learning methods represent the state-of-the-art of artificial intelligence, and they have been successfully employed for solving classification and regression problems in many fields of engineering. We focus on AutoEncoders (AE), which are multi-layered artificial neural networks trained to reconstruct their own inputs. During the training process, the weights of the AE are tuned to minimize the reconstruction error computed for all training patterns. This entails that when used on new input data, anomalous patterns containing outliers are coarsely reproduced by the AE—with a corresponding higher reconstruction error. When employed for attack detection on water distribution systems, the AE are trained to map the status of the network by using the readings of the deployed sensors as both inputs and outputs of the model. If the training data are representative of normal operations, the AE return high reconstruction errors when fed with sensor readings recorded during the course of an attack. The detection performance is evaluated on a test dataset featuring several classes of plausible attacks—simulated with EPANET—and quantified with two evaluation criteria accounting for detection accuracy, false alarms and the time needed to identify a threat. We also carry out a sensitivity analysis to determine the effect of data availability and model complexity on AE detection performance.

A water distribution system is designed to deliver sufficient quantities of high quality water to consumers. The quality of water delivered in a WDS is difficult to maintain and monitor, as water quality can degrade within a water distribution system’s pipes. A network of online monitoring stations designed to sample water quality in real-time, and to be strategically placed in a water distribution system has proven an effective method to monitor water quality and provide early warning of a contaminant intrusion. A difficult task for an online monitoring station is to distinguish natural variability in water quality from variability caused by the presence of a contaminant in the water. Prior studies have shown how common water quality indicators (free chlorine, pH, conductivity, total organic carbon) respond to contaminants, and methods to ease the task of recognizing true contaminant presence. This work proposes an objective function incorporating the uncertainty in a monitoring station’s detection employed in the framework of a genetic algorithm to place sensors at locations which minimize the expected consequence of a contamination event, and where water quality data are most indicative of true contamination events. Early warning systems composed of fixed water quality stations and inline mobile water quality sensors are designed in a multi-objective framework for a sample water distribution system.

A goal of water distribution system security is to ensure that clean water is delivered to consumers. Potential for contaminations and cross connections make it difficult to ensure that the water being delivered to consumers is truly of high quality. The placement of water quality monitoring stations within a WDS system has proven a successful method to prevent the delivery of contaminated water. The locations of monitoring stations in a WDS is critical to the performance of a water quality monitoring station network (early warning system or EWS); ideally sensors will be placed at a limited number of locations which can quickly detect all contamination events. Designing a EWS to protect against every possible contamination event is computationally infeasible; however it is crucial that high impact contamination events will be detected. In this study a contamination event is defined as an intrusion taking place at a specific junction and time in a WDS. A probability distribution is generated according to the portion of a network’s population served by water that flows “downstream” from a specific junction at a specific time, within a defined interval of time; this portion of population would be most at risk to exposure of the corresponding junction and time. The newly generated probability distribution is then used for sampling a set of contamination events used to design an EWS. The downstream nodes are calculated using breadth first search and the nodal populations are calculated according to the temporal demands. The relative consequence of a junction being contaminated is calculated using steady state and dynamic hydraulic models; elevating the need to perform numerous complex water quality simulations. Monitoring station networks designed using the proposed importance sampling technique and traditional random sampling are compared.

Short-term water demand forecasting is a required procedure for the optimal real-time control of water distribution systems when, for example, reducing operational costs associated with pumping. The forecasting literature presents a variety of methods ranging from linear seasonal ARIMA models to non-linear support vector regression to black box artificial neural networks. In general, hourly water demand time series are characterized by a strong double seasonal dependency and a non-linear temporal correlation. Therefore, in order to obtain the most suitable representation one needs to select a time series model that respects these features. This paper intends to evaluate the k-nearest neighbor (kNN) approach to forecast the short-term water demand time series. The kNN approach is a pattern recognition algorithm where the forecasted values are directly determined by the most similar past observations. To assess performance, robust evaluation criteria such as reliability and sharpness will be used to evaluate the kNN approach compared with the traditional seasonal ARMA model.

A new dynamic methodology is presented to attack network clustering and network aggregation problems. The aim of water network clustering and aggregation is to have better understanding of water distribution and network behavior and assist in the development of engineering tools to increase network optimal performance, supply quality and water safety. Clustering techniques take use of the water network topology and flow regime to group nodes with pre-determent properties in such way that a new, aggregated and simplified, network is created without the loss of network hydraulic characteristics and performance. A connectivity based methodology for network clustering is chosen in this work as the clustering method and a new dynamic approach is demonstrated through a series of cases and algorithms on a sample network.

The ability to provide high water quality distribution from sources to consumers is a foremost objective in water distribution systems security. Different techniques based on physical, chemical, and other methods constitute a variety of solutions for the layout, design, and operation of water networks, all aimed at decreasing the risk of supplying contaminated water to consumers. This study presents a new analysis approach based on clustering insights of water distribution networks connectivity for enhancing its security. Clustering is utilized herein for dynamically exploring the system behavior. Through clustering formations, addition of network components such as pipes and tanks for the layout problem, and valves for its operation–contamination spreading is controlled and contained. The developed methodology is demonstrated on several example applications, showing its capabilities to provide a decision support tool for contaminant control and containment in water distribution systems.

California’s water infrastructure entails significant operational and managerial responsibilities related to the need to safeguard public health. To help meet its complex water-related challenges, the California Water Service Company (Cal Water) is developing a water mains integrity management program (WMIMP) to (i) reduce life cycle costs (affordability), (ii) quantify and manage risk, (iii) renew infrastructure elements, and (iv) consistently deliver excellent service to customers. This paper describes the implementation of a spatio-temporal analysis based on information contained in a geographic information system (GIS) to identify high risk zones and predict failures based on the relevant parameters, which will help manage risk and support a high level of confidence in the decision making process. This is currently a work in progress and a comprehensive report will be presented at a later date once the project’s outcomes can be fully evaluated. The authors believe that this project will lay the foundation for a standardized platform of sustainable life cycle assessments for individual elements of the water infrastructure based upon a systematic approach.

Contamination warning systems (CWS) are strategies to lessen the effects of contamination in water distribution systems by delivering early indication of events. A critical component of CWS, online quality monitoring, involves a network of sensors that assess water quality and alert an operator of contamination. Utilities developing these monitoring systems are faced with the decision of what locations are optimal for deployment of sensors. The TEVA-SPOT software was developed to analyze the vulnerability of systems and aid utilities in designing sensor networks. However, many small utilities do not have the technical or financial resources needed to effectively use TEVA-SPOT. As a result, a sensor placement algorithm (i.e. water quality sensor placement tool–WQSPT) was developed and implemented in a commercial network distribution modeling software (i.e. KYPIPE) as a simple tool to aid small utilities in sensor placement. The developed tool was validated using 12 small distribution system models and multiple contamination scenarios for the placement of one and two sensors. Results were compared with data from identical simulations runs in TEVA-SPOT to verify the effectiveness of the proposed algorithm. Because the proposed algorithm uses a simple complete enumeration strategy for sensor placement, the algorithm was able to select the same or superior nodes to those selected by TEVA-SPOT.

This study focused on a performance assessment of individual districts of a California water utility (California Water Service Company; Cal Water) in order to provide a general understanding of the utility’s overall performance. A methodology based on two-stage data envelopment analysis (DEA) was applied. In the first stage, a bootstrap technique involving the construction of confidence intervals was implemented to overcome the deterministic nature of conventional DEA. In the second stage, a number of exogenous variables via double bootstrap truncated regression were incorporated into the model to help identify the factors affecting technical efficiency. Two different DEA models were designed to compare efficiencies from both financial and production perspectives. Results showed Cal Water’s high overall performance, although there are suboptimal districts from a production perspective. These districts are recommended for enterprise-level managerial strategies, as well as for constructing policies to address these inefficiencies.

Air valves characterization is critical for proper design of pipeline systems, mainly for the processes of filling and emptying. However, knowing this capacity is not a simple matter. Technical information provided by manufacturers is often insufficient or inaccurate. Moreover, experimental determination of the behavior of these elements requires large infrastructures either for pumping air either for storage it. In this paper an alternative methodology for testing air valves is presented. The procedure is based on testing the elements using water instead of air, measuring the flow through the element for different differential pressures. Subsequently, the application of techniques based on the hydrodynamic similarity allows extrapolating the performance characteristics of these valves with air. Finally, the proposed methodology has been validated with four air valve models. These valves have been tested with water. Later, the results obtained by similarity are compared with those obtained from tests in specialized laboratories.

In recent years, water utilities have placed a greater emphasis on the reliability and resilience of their water distribution networks. This focus has increased due to the continuing aging of such infrastructure and the potential threat of natural or man-made disruptions. As a result, water utilities continue to look for ways to evaluate the resiliency of their systems with a goal of identifying critical elements that need to be reinforced or replaced. Most research in the past has assumed that pipe breaks can be characterized as the loss of a single pipe element. This assumes that each pipe has an isolation valve on both ends of the pipe that can be readily located and operated under emergency conditions. This is seldom the case. The proposed methodology takes into account that multiple pipes may be impacted during a single failure as a result of the necessity to close multiple isolation values in order to isolate the “segment” of pipes necessary to contain the leak. This paper presents a simple graphical metric for use in evaluating the performance of a system in response to a pipe failure using three different performance metrics: percent loss of system demand, percent loss of acceptable pressures, and percent loss of adequate water age. The associated metric is applied to three different water distribution systems in an attempt to illustrate the fact that different pipe segments may impact system performance in different ways. This information is critical for use by system managers in deciding which segments to prioritize for upgrades or replacement.

Water distribution systems are critical infrastructures that can be the subject of various types of attacks. Concerns range from biological and chemical intrusions in pipelines to operational issues in water control assets. Cyber-attacks have also turned today into a crucial issue to consider. In highly automatized infrastructures, cyber-attacks can be considered as non-planned actions changing system operation to non-expected scenarios. They can potentially produce unavailability of enough water appropriated for public consumption or critical services such as firefighting. This work proposes to tackle the identification of cyber-attack scenarios through an early-alarm system able to recognize patterns corresponding to abnormal working conditions of the system. Firstly, an on-line forecasting model is developed that is based on the water system expected state regarding nodal pressures, tank water levels and control device flows. Then, an approach based on non-linear autoregressive networks with exogenous inputs (NARX) is proposed to take advantage of both their computational efficiency and the strong influence of the periodicity of the inputs under study. Finally, an analysis of abrupt change point, conducted in a time series composed by the differences between the observed measurements and the expected data, is built on top of the forecasting model.

Distribution system modeling simplifies pipe network in skeletonization and simulates the flow and water quality by using generalized water demand patterns. While widely used, the approach has not been examined fully on how it impacts the modeling fidelity. This study intends to evaluate these consequences in a typical water distribution system. We first analyzed tracer test data at 13 locations using a calibrated EPANET model with generalized water demand patterns. Modeling results agree with actual measurements in six locations with high water demand and flow velocity near the storage tank, while fail to replicate the variations in network abundant of dead-ends and Tee/Cross junctions. Then we further investigated the causes of model inaccuracy using real-time water demand data covering ~35% water users. This paper compares several levels of pipe skeletonization and water demand aggregation in water age simulation, and shows significant impacts on water age results because of discrete water demand at pipe nodes. The analysis reveals varying flow properties and the movement of highly aged water parcels in two types of pipe configurations. These results have the implications on network modeling and further studies of water quality simulations.

Demand estimation has long been an important topic that has recently received increased interest due to the development of real-time network modeling. For implementation to real networks, demand estimation is challenged by limited indirect hydraulic measurements (e.g., flow). Also, since many real network models have 10⁴–10⁵ demand nodes but only have hydraulic measurements in the range of 10¹–10², the demand estimation problem must be reduced to ensure that the problem is not under-determined. One approach to reduce the scale of the problem has been to generate clusters of nodes such that the demands for each cluster, rather than each individual node, can be estimated. Our recent research has shown that the resulting demand estimation problem can be sensitive to the availability and location of observed measurements as well as the clusters generated. Thus, the objective of this study is to provide a more in-depth understanding of the relationship between these two components in order to further develop real-time demand modeling capabilities. The research will evaluate the impacts of measurement locations and cluster generation on the demand estimation problem through more in-depth evaluations using the theoretical foundations of non-linear parameter estimation approaches to assess the identifiability of the resulting demand estimation problem. The expectation of this research will be a deeper understanding of the relationship between measurement locations and cluster approaches to generate adequate demand estimates. The insight gained is expected to improve our ability to generate cluster demands and provide improved metrics for placing additional measurement locations.

Vulnerability of water infrastructure to cyber-attacks is proliferated as the operation of these systems is automated using networked systems. Reports of several cyber-attacks to water systems such as the 2006 Pennsylvania Water Company hack and the 2012 Tijuana River sewage spill has proven the water community concerns for the security of these systems. This study proposes a machine-learning-based anomaly detection methodology for early cyber-attack detection and warning that is tailored to water distributions systems security. Attacks are assumed to be manifested as man-induced anomalies in SCADA time series data that should be detected in a short time with low false negative/positive rates. The methodology is trained by and examined on the BATtle of the Attack Detection ALgorithms (BATADAL) dataset.

Water distribution systems are vulnerable of being intentionally or accidentally contaminated. In the case of a contamination event the contaminated section of the water distribution system should be located, isolated and cleaned before it can be returned to regular service. Depending on the specific contaminant, the cleaning process mainly includes flushing and disinfection. All of the disinfection methods (for example: tablet, continuous and slug) require that the disinfectants will have minimal contact time (T) in a predefined concentration (C) with the pipes and the system’s apparatuses. The regulatory agencies, such as the Ministry of Health in Israel or the American Water Work Association, publishes procedures for the disinfection of water systems in which usually only a single water main is considered and no specific procedures are given for larger portions of the water system. This paper presents an optimal operation plan for the disinfection of water distribution systems using the slug feed method while considering the injection times, flow rates and drainage locations while keeping variable disinfection C*T values in different areas of the network. The method is a two stage GA-EPANET procedure. It is demonstrated on a small real-world network section.

As the irreplaceable natural resource, water plays an important part in human life. It’s necessary to establish of a set of water quality early warning system which can quickly and accurately identify contamination. The existing anomaly detection methods are either simple fusion of abnormal judgment results from single index, or correlation analysis of multiple parameters at the cost of high time complexity. Aimed to solve these problems, this paper describes a multivariate correlation analysis method based on the longest common subsequence (LCSS) analysis combined with Dempster-Shafer (D-S) evidence theory. The proposed method utilizes adaptive sliding window scale to acquire water quality parameter time sequence, LCSS to describe similarity between different water quality series fluctuation, and D-S evidence theory to calculate abnormal probabilities. The ROC curve is introduced to verify the algorithm performance. Tested by data from the laboratory contaminant injection experiment, this approach shows nice ability in dealing with time series deformation problem rapidly, which to a certain extent can improve the reliability of multi-index correlation degree analysis, and ultimately reduce the abnormal water contamination event detection false alarm rate.

Pressure reducing valves (PRVs) are a widely used device for controlling water distribution systems. The behavior of these valves is based on a chamber where inlet and outlet water are controlled. Proportional pressure reducing valves (PPRVs) are a variation of PRVs where the control system is a direct connection between the chamber and the point downstream the valve. They are used where large pressure reductions are required. Traditional characterization of PPRVs considers a constant ratio between the input and the output pressure (λ). In this paper an alternative approach based on an experimental analysis of λ has been performed. The tests show that λ parameter cannot be considered constant. Thus, to characterize these PPRVs a mathematical model has been developed. This model can explain λ variations with pressure and flow rate becoming certainly in a more complete way of representing this kind of valves.

In this paper, we investigate the historical development of complex network topologies in urban water distribution networks (WDNs) and urban drainage networks (UDNs). The analyses were performed on time-stamped network data of an Alpine case study, which represent the evolution of the town and its infrastructure over the past 106 years. We use the dual representation of the network, where pipes are considered as nodes and intersections as edges, respectively. The functional topologies of the networks are analyzed based on the dual graph, providing insights beyond a conventional graph (primal mapping) analysis. We observe that the WDNs and UDNs show scale-free network characteristics and evolve with consistent patterns over time. However, structural differences between both network types are found in the node degree distributions and the characteristic path lengths, resulting from different functionalities of the systems. Finally, we show the remapping of the dual network characteristics to the spatial map and discuss possibilities for further applications.

Modern water distribution networks (WDN) are evolving into cyber-physical systems comprising physical components, such as valves and pumps, and a cyber-layer of computing, sensing and communication devices. It is recognized that these cyber-components are vulnerable to malicious attacks that can range from sensor data manipulation to alteration of the control laws that govern the operation of physical components. This paper presents a data-driven, model-free optimization-based solution to the BATtle of the Attack Detection Algorithms (BATADAL) competition that aims to investigate various approaches for the detection of cyber-attacks in WDNs. Leveraging machine learning and system identification, this paper develops algorithms for detection of cyber-attacks on WDNs. The methodology relies on unveiling low dimensionality components in the sensory data as well as on the sparse nature of anomalies a natural property of cyber-attacks against large volumes of data. The chief computational instrument is convex optimization, for which computationally efficient solvers are available. The proposed methods are tested on simulated cyber-attacks from the C-Town network in EPANET and the provided data-sets.

Automated monitoring and operation of modern water distribution systems (WDSs) are largely dependent on an interconnected network of computers, sensors, and actuators that are jointly coordinated by a supervisory control and data acquisition (SCADA) system. Although the implementation of such embedded systems enhances the reliability of the WDS, it also exposes it to cyber-physical attacks that can disrupt the system’s operation or compromise critical information. Hence, the development of attack detection algorithms that can efficiently diagnose and identify such assaults is crucial for the successful application of these automated systems. In this study, we developed an algorithm to identify anomalous behaviors of the different components of a WDS in the context of the Battle of the Attack Detection Algorithms (BATADAL). The algorithm relies on using multiple layers of anomaly detection techniques to identify both local anomalies that affect each sensor individually, as well as global anomalies that simultaneously affect more than one sensor at the same time. The first layer targets finding statistical outliers in the data using simple outlier detection techniques. The second layer employs a trained artificial neural networks (ANNs) model to detect contextual anomalies that does not conform to the normal operational behavior of the system. The third layer uses principal component analysis (PCA) to decompose the high-dimensional space occupied by the given set of sensor measurements into two sub-spaces representing normal and anomalous network operating conditions. By continuously tracking the projections of the data instances on the anomalous conditions subspace, the algorithm identifies the outliers based on their influence on the directions of the principal components. The proposed approach successfully predicted all of the pre-labeled attacks in the validation data set with high sensitivity and specificity. However, for all the detected attacks, the algorithm maintained a false “under attack” status for a few hours after the threat no longer existed.

Increased urbanization, land development and changing population significantly impact the natural environment and urban water cycle. To tackle these challenges, new sustainable water management strategies, like water sensitive urban design (WSUD), have been gaining increasing interest in the last couple of years. The software tool UrbanBEATS (Urban Biophysical Environments and Technologies Simulator) supports decision makers in the planning and implementation of such WSUD strategies, by combining and processing spatial and non-spatial data (e.g. land use, population, elevation, rainfall/climate). In the field of water distribution system (WDS) analysis, the implementation of decentralized rainwater harvesting or gray water reuse measures can strongly influence the water quality performance of an existing central pipe system. Here, we show how demand reduction scenarios modelled with UrbanBEATS through the implementation of different water efficiency or water use restrictions impact WDS quality analysis undertaken in Epanet2.

The dependency of modern water distribution systems (WDS) on computer and cyber control make the systems more susceptible to cyber-physical attack. While the cyber-physical attacks can be classified into several categories such as direct and indirect, the main purpose of the attack is to disrupt the operation of the WDS. Attack changes normal flow patterns and operations of the system leaving its signature behind in the datasets. Understanding normal system operations and hydraulics and system relationships are thus important to identify any anomalous behavior in the system. This paper presents an algorithm where three modules are developed based on the consistency and pattern of data and hydraulics and system relationships. These modules are interlinked with some logical statements to identify, detect, and quantify the magnitude of any cyber-physical attack. The algorithm which has been applied to a mid-sized network known as C-Town network can successfully characterize and detects the cyber-physical attacks. The location (WDS component), duration, and the magnitude of the cyber-physical attack are identified through the use of the algorithm.

Check valves, depending on their closure characteristics, may introduce significant transient pressures after pump shutdown. Therefore, appropriate representation of these devices in water hammer models is important for simulating accurate transient response. However, the lack of check valve closure characteristics data makes modeling of these devices prone to inaccuracy. This paper investigates the calibration of a water hammer model where check valves are present. The model was developed for a force main system located east of Brevard County, Florida, using Pipe2000. The system consists of approximately a 21.3 km and an 8 km long two parallel force mains consisting mainly of 508-610 mm ductile iron and polyvinyl chloride pipe sections. A high speed data acquisition system was used to capture steady state and transient field pressure traces during normal pump shutdowns. The model was calibrated and validated to match steady state and transient field-measured pressures. Results showed that check valves can be modeled accurately by: (1) recording shutdown-induced field transient pressures at the pump station where check valve is installed, and (2) conducting sensitivity analysis during which, check valve closure time is adjusted until the predicted transient pressure traces are mapped into field-measured pressures. Inaccurate modeling of check valve closure characteristics was found to significantly over or under predict pressure spikes following pump shutdown. Excluding the check valve from the model when flow reversal is not enough to activate the valve closure in the field was found to be appropriate to avoid model instabilities and predict accurate pressure responses.

Water distribution systems (WDSs) operation relies on a set of rules and conditions aimed at maintaining a reliable water supply. The WDS operation is often controlled by supervisory control and data acquisition (SCADA) and programmable logic controllers (PLCs). As such, with the SCADA becoming a central component of WDSs these systems can be subjected to cyber-attacks. This paper offer a methodology for identifying cyber-attacks based on logical rules that are based on detailed hydraulic understanding of the WDS combined with a machine learning event detection system for identification of complex cyber-attacks that cannot be fully identified by the hydraulic based rules alone.