World Environmental and Water Resources Congress 2022: Adaptive Planning and Design in an Age of Risk and Uncertainty

Internet of Things (IoT) is an evolving, cutting-edge technology that integrates sensors, hardware, and software, and other technologies that connect and exchange data with other devices and systems via the Internet. The present paper discusses an integrated hardware and software framework using IoT technology to remotely release water from ponded systems such as reservoirs, detention ponds, and wetlands using siphons and conventional drainage systems. The hardware platform consists of devices such as sensors, bilge pump, air-vent, and actuated butterfly valve installed in the field. These devices collect field information and transfer it to the remote center via programmable logic control (PLC) and virtual private network (VPN) router. The VPN router employs a 4G/5G cellular connection to remotely transfer the field information. All the devices are powered by a battery, which gets recharged with the solar panels. The software platform replicates the entire field setup in the software interface developed by users. Hence, real-time activity can be controlled (manually and automatically) and monitored using the software interface. A prototype setup has been established in the laboratory of Florida International University (FIU), and multiple experimental results verify the efficacy of the proposed system. The present paper can open new avenues for applying the latest technologies in the area of civil and environmental engineering.

Remote operation of drainage systems like a siphon and conventional drainage systems can be employed for several occasions. For example, it can alleviate floods and maintain water in the wetlands for ecological and environmental purposes. This paper presents a remotely operated framework based on software defined radio (SDR) technology to release water from a network of storage units (wetlands, reservoirs, and detention ponds). SDR is a radio communication system that contains master and slave SDRs connected with circular monopoles. The framework consists of an integrated hardware and software architecture that performs a remote operation using a 4G/5G cellular connection. The hardware architecture consists of components such as water level sensors, actuated butterfly valve, air vent, and bilge pump installed in the field. These components are connected to the programmable logic control (PLC), which collects field data. The collected data is then transferred to a control center via a virtual private network (VPN) using a 4G/5G cellular connection. The data gets processed at a control center, and a decision is communicated back through the same channel that gets implemented in the field. Single and multiple prototype experiments have been performed at the laboratory of Florida International University. This approach could open doors to cutting-edge technologies applied in civil and environmental engineering that can be used for multiple purposes.

In collaboration with APTIM, under contract with the US Environmental Protection Agency, Unilever R&D, Mumbai, India, has evaluated the performance of four household point-of-use (POU) devices. Pureit Marvella UV, Marvella Sleek, Excella, and Marvella Slim RO water purifiers were evaluated for removal of Cryptosporidium parvum oocysts (a protozoan cyst), Escherichia coli (as a surrogate for bacteria), and male specific 2 bacteriophage (as a surrogate for viruses). Performance was monitored throughout the life of the water treatment systems for compliance with the Guide Standard and Protocol for Testing Microbiological Water Purifiers of 3-log reduction of cyst, 6-log reduction of bacteria, and a 4-log reduction of virus and World Health Organization treatment guidelines for the performance of microbial treatment in household systems. This paper summarizes novel aspects of the Unilever household water systems and their microbial removal results.

Excessive nutrients and organic wastes by Hurricane Harvey have caused the Neches River tidal section impaired for bacteria. To quantify the nonpoint pollution, the 15-min interval water quality data, including dissolved oxygen (DO), turbidity, total algae/fluorescence/chlorophyll, conductivity/temperature, total dissolved solids (TDS), pH, and pressure/water depth, were collected using YSI EXO2 sonde installed at the Saltwater Barrier from 2020 to 2021. The objective of this study is to forecast water quality by applying AI tools with the water quality data collected using the YSI wireless sensors. The data were firstly preprocessed by detecting outliers, validating with different standard deviation levels, and filling the missing values using the Python interpolation. The hourly data were rearranged with the preprocessed 15-min interval data and applied with the Pearson’s correction model to demonstrate corrections among the parameters. The correction coefficients of > 0.5 or < –0.5 were considered to develop AI tools for water quality forecasting. The 90% of hourly DO data were trained with the long short-term memory network (LSTM) AI tool, and the rest of data were used to validate the model performance. The DO value in the next hour was predicted with the data in the previous 4 h. The mean absolute error (MAE) value of 0.19, mean squared error (MSE) of 0.078, and root mean squared error (RMSE) of 0.36 demonstrate that the LSTM has a good agreement with the observation. The ongoing effort is to predict other water quality parameters with the LSTM AI tool.

Soil moisture is one of the important parameters in the hydrological cycle to drive weather conditions, plant growth, groundwater storage, overland streamflow; thus, it has a role in global climate. Despite the great importance and high value of soil moisture data, this information is not widely available because field sampling is relatively expensive, and it is not routinely measured in many developing regions. Currently, several satellite missions provide global surface soil moisture products such as the soil moisture active passive (SMAP). However, the spatial resolution of soil moisture obtained from remote sensing is insufficient for hydrological and water resources’ management applications. This paper is an extension of a data-driven model to estimate soil moisture that uses ancillary data such as normalized difference vegetation index (NDVI), altitude, slope, cumulative precipitation, and air temperature. The difference between the ANN-based prediction and the in-situ soil moisture is utilized. A cross-variogram between the resampled soil moisture estimates by ANN Kriging and SMAP 36-km soil moisture data, 1-km resolution data is obtained. Using the developed methodology to downscale the SMAP data, stations with better performance and good spatial distribution are selected as representatives for future reassessment of downscaled data and updating base information more frequently for utilizing SMAP data.

As the world navigates the COVID-19 pandemic, the surge in waste generation, the varied composition of waste, and its subsequent management has presented several challenges to many communities. Waste management techniques and cultivating an awareness of the environmental and health impacts of mismanaged wastes have varied with location, economics, and priorities of the region. Risk mitigation efforts including the wearing of masks, lockdowns, and stay at home orders intended to contain the spread of the virus have resulted in several unintended environmental implications. With the rise in consumer plastic consumption, single use PPE, take away food orders, and online shopping, many households across the globe have reported an increase in waste. While developed countries have been able to approach the surge by utilizing and expanding current municipal waste management programs, countries lacking this existing infrastructure battle an increased risk of continued infection and magnified environmental issues through open landfills, groundwater contamination, and limited community awareness. Adopting appropriate methods of risk communication and encouraging participation from the public to manage waste issues is critical to protecting the environment by limiting contamination, improving community involvement in reducing landfill waste, and encouraging recycling. It is imperative to develop waste management solutions while continuing the promotion of sustainable habits, combating the current pandemic situation, and preparing for future episodic events. Our study focuses on analyzing episodic waste generation during the pandemic, management strategies adopted globally, and identifying areas of possible improvement and alternate strategies that can be implemented.

Enormous amounts of carbon dioxide have been emitted into the environment in recent decades, primarily due to the fuel combustion. The rise in carbon dioxide concentration in the atmosphere is one of the basic reasons for the global changes like global warming, change in the quantity of rainfall, change in the sea levels, and the increase in the bush forest fires around the world. One of the possible solutions for reducing these global changes is to capture the excessive quantity of carbon dioxide from the atmosphere and inject it to the natural deep underground sedimentary reservoirs. During the geological storage process, carbon dioxide is pumped at greater inlet pressure, causing excess pressure building and potentially reactivating pre-existing faults in the reservoirs and caprock. The deposited carbon dioxide will flow to the top layers once the pre-existing faults are re-activated. A combined geomechanical and fault activation modeling for the Dhruma reservoir in Saudi Arabia is presented in this paper. The fault that runs through the Dhruma and Hanifa Tuwaiq strata is also taken into account during the combined geomechanical and fault activation modeling. The magnitudes of the reservoir pore pressure and ground uplift were computed during carbon dioxide injection into the reservoir. The Mohr-Coulomb failure criterion was used to assess the reservoir’s stability. The magnitudes of the reservoir pore pressure and ground uplift were used to determine acceptable carbon dioxide injection variables in the present analysis.

Sand and sodium chloride have been used for deicing in United State since the 1930s. The harmful impacts of deicing salts to environment, human health, and ground water systems are widely known. However, the benefit of using deicers during winter season cause continuous use deicer salts. More than 10 million tons of deicing salt is used in USA annually. The USEPA estimates average 6.5 million metric dry tons of wastewater sludge is produced in the US annually. The research tries to find sustainable option of biosolid without environmental concern. Biosolids were tested for the potential to being biochar. The biochar was produced from sludge obtained from the Back River Wastewater Treatment Plant in Baltimore, Maryland. The biochar was produced at 300^°C through slow pyrolysis. The research accessed biochar for the effectiveness to reduce deicer concentration in melted snow and ice. Biochars were evaluated to assess physical properties to apply the BMP systems, which could reduce runoff, improve water holding capacity, enhance pollutant removal, reduce sandy content, and promote plant growth. The assessment for biochar application as filtration media were performed. Adsorption tests were conducted, including different concentrations. These effects are examined based on change in the concentration after the deicer solution is mixed with biochar and clay minerals. The findings of this project are used to demonstrate the application of biochar and clay mineral in removing salts from the deicer to address the environmental challenges of using deicer salts.

Floating treatment wetland (FTW) systems are designed for water treatment and provide an effective treatment option for urban streams by improving the water quality by way of nutrient removal and filtration. Nutrients from agricultural waste and lawn chemicals, such as nitrogen and phosphorus, are impacting streams in North Dakota. Most of these nutrients promote and support the growth of algae and result in poor odor and colorization of water. In this research, the feasibility of a FTW system in a cold climate region was studied to determine the potential of this treatment method in the English Coulee, an urban stream passing through Grand Forks. The biggest threat to the watershed of the English Coulee can be traced to the pollutants found in stormwater runoff, and chemicals used on lawns specially during drier times, which concentrates pollutants. In addition, the improper management of green spaces and buffer zones, aggressive flood control methods, and high nutrient content may be a significant factor of algal blooms leading to poor odor, decolorization, and low dissolved oxygen of water bodies. The objective is to determine the feasibility of FTW in a cold climate region by observing the survival rates of different plant species commonly used in treatment wetlands and native to the region. This study will also look at existing information on FTW construction practices to assess practicality of their use in the English Coulee. Currently, two pilot scale FTW islands have been set up in the coulee for this project, and nutrient levels up and downstream of the treatment wetlands are being monitored. This data is analyzed alongside the plant survival rate data and hydraulic information to evaluate and provide insight to the potential utilizing FTWs in the English Coulee.

The COVID-19 pandemic has emphasized the importance of effective crisis communication. Specifically, varied regional crisis communication has caused a substantial impact on how communities perceive the virus and its risks. Our research analyzes the COVID-19 crisis communication responses seen in the United States, Canada, France, Spain, Croatia, Israel, Belgium, and the Netherlands. Several pandemic specific societal norms were analyzed for positive and negative trends to capture population outrage, based on the various crisis communication measures implemented. The norms focused on include political intervention, mask use, travel restrictions, e-commerce, vaccination rates, and demand for disinfectants. These norms were identified because of their considerable uptick in heightened awareness in the public eye in light of the pandemic. The trends seen in these pandemic specific norms affected each population uniquely due to varying strategies adopted for crisis communication. Differences in crisis communication methods can lead to distinctive responses in outrage caused by the pandemic. For example, the United States’ and the New Zealand’s populations starkly juxtapose one another’s crisis communication methods based on their outrage to pandemic specific societal norms. Our study investigates the influence that crisis communication has on the overall perception of the pandemic. Determining the influence that crisis communication has on population outrage can help improve future pandemic crisis communication to eventually bridge the gap between public outrage and the true risk at hand.

Nipawin Hydroelectric Station is located on the eastern side of the Saskatchewan Province and has a total combined installed capacity of nearly 250 MW. A study conducted by the Fisheries and Oceans of Canada concluded that in the interest of fish and fish habitat, a varied minimum annual flow regime should be possibly implemented to better mitigate the effects of these hydroelectric stations. This report aims to study a new approach that was developed to capture some of the impacts that power distributors and other upstream users would potentially experience if the minimum flow requirement were to be enforced. Distributors such as this would need to reshape their power generation strategy using more costly forms of energy to meet the required demand during high load periods, and also curtail generation from its low-cost coal thermal stations during low load periods. Looking at the costs associated with each type of generation in the system, a net resulting potential cost was estimated. Results of this study may not only help distributors develop a modified minimum flow criteria to enhance fish habitat and increase the endangered Lake Surgeon population, which might be attainable, but it would also help such organizations’ future water management and balance model to some practical degrees.

This study analyzes some of the best strategies and techniques to increase water savings by using the concept of sustainable development. This study evaluated major observations to promote economic growth, advance energy solutions, and improve students’ healthy lives and well-being. Quantitative data was retrieved to evaluate water using various self-monitoring, analysis, and reporting technology (S.M.A.R.T.) equipment for an observation. The economic analysis provided a positive return on investment (ROI), while saving energy and improving the student well-being. A survey was formulated to measure student satisfaction and to add credibility to research. It has been proven with credible qualitative surveys that when students see and feel better, they are likely to improve academically. COVID 19 effects are examined into the end of the research to discover its effect on campuses utility usage. It is concluded from all the results of the testing that the findings demonstrate the social and economic goals of the university projects depend on the environment. The larger implications of the findings were that sustainability for a campus can benefit any size university. However, other lower budget institutions interested in initiating campus energy efficiency goals might benefit from undertaking low-cost educational strategies and techniques. This study builds on prior research that can offer a different type of vision on how to develop a culture of sustainability for any university.

During in situ remediation of contaminated groundwater, a chemical or biological amendment is introduced into the contaminant plume to react with the contaminant. Reactions occur only where the amendment and contaminant are in contact with each other, so active spreading has been proposed to increase the contact area between the two reactants. With active spreading, wells are installed in the vicinity of the contaminant plume and are operated in a pre-defined sequence of injections and extractions to create a spatio-temporally varying flow field that changes the shapes of the reactant plumes, generally leading to an increase in contact area and therefore an increase in reaction. The design of the active spreading system depends on the reaction chemistry of the contaminant. This study considers active spreading scenarios for contaminants with three different types of reactions: (1) non-sorbing aqueous contaminant, A, that degrades irreversibly to a benign chemical, C, through reaction with a non-sorbing aqueous amendment, B; (2) sorbing contaminant, A, that degrades irreversibly to a benign chemical, C, through reaction with a non-sorbing aqueous amendment, B, where sorption of A is independent of the concentration of B; and (3) contaminant, A, that exhibits reversible equilibrium surface complexation with concentrations in the mobile and immobile phases dependent on the concentration of the amendment, B. We compare the active spreading strategies for these three types of reactions and identify the characteristics of each strategy that lead to enhanced removal of groundwater contaminants.

During in situ groundwater remediation, a chemical or biological amendment is introduced into the aquifer to react with and remediate the contaminated groundwater. The success of this type of remediation depends on the degree to which the amendment is in contact with the contaminant. Remediation reactions only occur where the amendment and contaminant molecules are sufficiently close that they can be brought together by mixing, i.e., processes such as molecular diffusion and small-scale mechanical dispersion that lead to smoothing of concentration gradients at the interface between the amendment and contaminant plumes. One process that is known to promote mixing in groundwater is spreading, which is the reconfiguration of the plume shape due to spatially varying velocity. This reconfiguration can elongate the plume interface and can increase concentration gradients along the interface, both of which lead to enhanced mixing. Spreading can be passive or active. Passive spreading occurs where the heterogeneity inherent in the porous material produces spatially varying velocity. Active spreading occurs where spatially varying velocity is created by injecting or extracting water in one or more wells within or near the contaminant plume. We use numerical simulations of solute transport to evaluate the combined effect of active and passive spreading on contaminant degradation. We consider zonal heterogeneity and smoothly varying hydraulic conductivity fields. We investigate how the local plume geometry and the local velocity field affect the overall degradation rate, and we provide guidelines for designing active spreading pumping scenarios based on site-specific heterogeneity patterns and the associated uncertainty.

The water retention capability of soil significantly impacts plant growth. A scarcity of water in agricultural soil may cause low crop productivity, potentially leading to critical food-deficit problems in arid areas with increasing populations such as central California. New ways to enhance the water retention capability of soil to enable farmers to utilize water more effectively are thus urgently needed. Research has shown that hydrochar, which is produced by hydrothermal carbonization (HTC), can potentially improve soil quality by enabling it to hold water for longer periods. This study therefore explored how the addition of hydrochar affects water retention capacity in the root zone using soil experiments. For the experiments, a column filled with sample sandy soil but without hydrochar, which was used as a control. Meanwhile, 8% weight of hydrochar were mixed with soil at the top of soil columns to investigate how the presence or absence of hydrochar affected: (1) the temporal variation of soil moisture vs depth; (2) the temporal variation in the water’s potential head vs. depth at different times; and (3) the distribution of soil moisture vs the water’s potential head. The results of these experiments can be utilized to show the agricultural benefit gained by soil amendment with a certain amount of hydrochar.

Even though managed aquifer recharge (MAR) helped effectively in increasing aquifer storage and improving groundwater quality in many arid regions worldwide, its feasibility remains an open question in Qatar. Qatar is a hyper-arid country with minimal natural water resources, high per-capita water consumption, and over-exploited aquifers—the only water source for agriculture. During the last two decades, the country had a significant increase in population and urbanization, which posed extra stress to the aquifers. This paper discusses MAR feasibility and highlights possible factors for aquifer management and sustainability in Qatar. Outcomes showed that, among MAR methods, the aquifer storage and recovery (ASR) could help augment Qatar aquifers if technical and socioeconomic aspects were guaranteed. Considering 2016 as an example, injecting the unutilized treated sewage effluent (TSE; estimated by ~500 million m³ in 2017) in aquifers can strike a balance in Qatar’s water system if a recovery rate of 30% was achieved in the ASR wells. Under future projections of population and consumption increase, abstraction from aquifers will rise significantly through the 21st century, which requires looking for alternative water resources. The analysis also revealed unclear measurements for aquifers abstraction. Using smart water meters to measure abstraction quantities is, therefore, a dire need.

By assent of ASCE’s Board of Direction, Wyoming’s Pathfinder Dam was designated a National Historic Civil Engineering Landmark on July 16, 2021. Named for John C. Fremont, the “Pathfinder of the West,” Pathfinder Dam is the centerpiece of the North Platte Project. The project irrigates 335,000 acres of agricultural land in Wyoming and Nebraska. Pathfinder was the first large dam project undertaken by the United States Reclamation Service—later the Bureau of Reclamation. Its designers utilized the arch and crown-cantilever method of analysis in the development of its geometry. This innovative analysis methodology was the precursor to the trail load method widely used later. Pathfinder Dam was completed in 1909 and created the largest artificial impoundment of water in the US at that time. Its completion also established the Reclamation Service’s reputation as a premier dam design and construction organization.

Thermal gradients in rivers provide the diversity of aquatic conditions that enables freshwater biomes to thrive. Riverine pools are a primary source of enhanced thermal gradients. Through vertical thermal stratification, pools provide adult salmon the cold water needed for holding in summer at depth and provide juvenile salmon warmer water near the pool surface for maximizing their growth. In this study, a 3D computational fluid dynamics (CFD) temperature model is developed to investigate the thermal stratification characteristics of pools on the Trinity River, California. The model is capable of simulating both the stable and unstable stratifications, as well as transition between these states under the combined influence of diurnal temperature variation and river flows. Two pools are selected for the study: one with and one without temperature stratification. The model is verified and validated against the field measured data. It is shown that the 3D model reproduces the measured flow and thermal processes well.

Sewer overflows, which often occur during heavy rainfall events, threaten public health and the environment, contributing to drinking water contamination and other concerns. Knowing ahead of time the location and volume of overflows is critical for sewer operators to make decisions to mitigate these overflows. Accurate and ultrafast models to predict the location and volume of sewer overflows are essential for optimal sewer operation (e.g., by load balancing). Machine learning (ML) is a rising field with an excellent capacity for predicting outcomes in different applications. This paper proposes a new methodology that bridges big data algorithms and physics-based numerical models to improve sewer overflow predictions. The combined sewer system (CSS) of the Puritan-Fenkell 7-mi facility in Detroit, MI, is chosen as the prototype in this study. Our model used deep learning (DL) approach for time-series forecasting. The rainfall-overflows relationship in this study is predicted by various deep learning models. This data-driven model is trained on various return period data sets and tested by an unused return period data set. Overall, our ML framework can accurately predict the location and time traces of sewer overflow volumes in a time frame of seconds.

The peak-peak meander cycling of a sample of first order and higher order streams (second and above) was analyzed for the Brazos River basin. A mechanical analogue for distributed vibrating systems is used to derive a relationship between the fundamental meander frequency (lateral cycling/minute) and stream parameters using Rayleigh’s approximation. Cycling frequency is estimated from the number of peak-peak lateral migrations divided by the travel time of a bank full flood wave using a combination automated routing in GIS followed by manual checking of the detection of peak-peak migration. The flood wave is estimated from watershed parameters required to fix the median group velocity for streams in 12-digit sub-watersheds in the Brazos to that of historical median flood wave velocities determined from nationwide USGS gauges. The validity of the relationship when tested for the sampled Brazos streams showed that the meander frequency could be explained by the kinetic energy and a tractive force acting against flow.

Many hydraulic structures such as barrages and bridges on alluvial rivers require substantial recurring expenditure in training the river to maintain its course through the designated waterways during floods. Cost of flood fighting during the life span can exceed several times the construction cost of the structures. Erratic approach flow condition can result in the transport of unwarranted silt loads in the off-taking irrigation canals from barrages reducing their capacities and requiring costly silt removal. Gudu Barrage located in province of Sindh, Pakistan, experiences silting issues during high flows. The approach flow conditions at Gudu Barrage have been a cause of great concern for the engineers of Sindh Irrigation Department since its commissioning in 1963. A 1:400 horizontal scale physical model was developed for Gudu Barrage. Physical model was calibrated to reproduce flow pattern and sediment deposits. Different river training work formations (spurs at various angles) were evaluated to check the sediment depositions and erosion at the Gudu Barrage. Evaluation of different scenarios indicate that two submerged silt guide vanes in right pocket and one in left pocket to control silt entry in the Canals was the best option to control siltation. This arrangement is effective in pushing heavy sediment bed load away from the canals, and increasing velocity along the divide wall averts silt accumulation along the wall. Results indicate that the upstream approach flow conditions govern downstream channel morphology.

Flood control is one of the primary mission areas for the US Army Corps of Engineers (USACE) districts and divisions. Towards meeting the needs of the flood control mission, USACE relies on HEC-RAS for inland flood inundation mapping for standard or routine events. Recently there has been an interest in the investigation of HEC-RAS to perform more complex hydrodynamic simulations such as those that occur in estuaries and bays. Simulation of geophysical flows in estuaries and bays is complex. This complexity is imparted from not only the complex bathymetry but also the interwoven flow pathways that are common in tidal wet- and marshlands. These complexities are not easily translated to inland hydraulic simulation codes such as HEC-RAS, and therefore there is a need to investigate and document the ability of HEC-RAS to accurately, efficiently, and robustly simulate these complex flows. The behavior of estuaries and bays is often governed by the type of tides they experience. For example, the tides on the Gulf Coast are micro-tidal, the East Coast are meso tidal, and the West Coast experiences meso to macro tides. Tidal bores are frequent occurrences in several estuaries/bays such as the Cook Inlet and Bay of Fundy. To have confidence that a numerical model can successfully simulate these tidal conditions and associated wetland hydrodynamic processes requires the application of the model to all tidal ranges. This study will apply the release version of HEC-RAS Version 5.0.7 to the simulation of tidal movements in Cook Inlet, Alaska, and will seek to show what HEC-RAS is capable of in a large bay and what deficiencies it has.

The Bureau of Reclamation has been injecting gravel downstream of the Goodwin Dam to increase the salmon spawning habitat area. Gravels added to the river can make up for the sediment deficit caused by the dams and maintain a mobile bed suitable for salmon spawning. Currently, the dams trap nearly all the sediment supplied from the watershed. SRH-1D was used to simulate historical gravel augmentations and seven future gravel augmentation scenarios. Baseline conditions in the past and in the future with no gravel augmentation were also simulated for comparison. Water surface elevations at the required floodway protection level (8,000 cfs) will be compared before and after the gravel augmentation to estimate the river response resulting from these different actions. The numerical model results will help understand the river’s geomorphic response to gravel augmentation and its impact on channel capacity for flood protection.

There are great concerns that current and future seasonal temperature changes impact water depth and velocity in rivers in cold-weather regions. This paper presents an analysis of seasonal changes, velocity, and depth at Red River station near Grand Forks, North Dakota. The focus is on seasonal velocity and bathymetry variability in two different seasons, summer and fall, using a novel autonomous surface vehicle (ASV) named HYCAT. HYCAT is a multiparameter, portable survey ASV designed specifically to give surveyors access to data in remote areas that have previously been difficult, expensive, or impossible to acquire. The HYCAT autonomous surface vehicle generates high-resolution water quality, bathymetry, and flow data at once along the river. Flow measurements in rivers such as the Red River are challenging due to the technical difficulties associated with large ranges in water temperature and floating ice in spring melt period. This paper presents analyses of velocity and depth in river flow under various temperature conditions in different seasons. To achieve these goals, the velocity and bathymetry data in two distinct seasons of summer and fall were collected using a Sontek M9 device mounted on HYCAT.

Outlet works transitions redirect flow from multiple rectangular culverts housing gates to a circular conduit, which requires intricate geometry consisting of curvilinear lines that minimize flow separation and cavitation potential. Presented here and conducted at the Engineering Research and Development Center is the evaluation of two different transitions for the new Rough River Dam outlet works design and uses a Froude scaled 1:25.85 physical model. Tested over a range of flows is both the Singh (1969) design and the US Army Corp of Engineers USACE EM 1110-2-1602 design. Evaluated first is the Singh (1969) transition design, and while Singh (1969) is more efficient, there is concern for cavitation potential and flow separation downstream of the center divider wall. Thus, the selection of the EM 1110-2-1602 transition is the final design to reduce cavitation potential and flow separation along with further compliance with USACE published guidance.

Low-head dams can produce dangerous conditions for recreational river users when a nearly inescapable reverse-flow condition (a “roller”) develops below the dam due to a submerged hydraulic jump. A national task force is using aerial imagery to identify potentially dangerous structures, but a more definite determination requires field data and analysis of hydraulic conditions for a range of flow rates. To aid this effort, a straightforward analysis procedure has been implemented in a spreadsheet application. The upstream head and ideal (non-submerged) hydraulic jump conditions are computed for the range of likely flow rates. Downstream river channel conditions are then used to identify the flow rates for which dangerous degrees of submergence will occur, based on experimental work by Hans Leutheusser and colleagues beginning in the early 1990s. The reverse-flow velocity in the roller and the limiting tailwater conditions for a plunging jet and reverse flow are estimated. The spreadsheet is valuable for analysis of specific sites, and general application provides insight into common characteristics of dangerous dams.

In this study, a two-dimensional hydrodynamic model was developed using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) to evaluate notch impacts on water levels and sedimentation processes. The study site includes an approximately 2-mi stretch of the Missouri River with a dike field, including eight spur dikes with notches and three spur dikes without notches. Elevation contours of the existing condition digital terrain model were modified by performing geospatial operations in the vicinity of each notch to create two additional terrain conditions—proposed conditions 1 (filled notches with filled scour holes downstream of each notch) and proposed conditions 2 (filled notches with existing scour holes downstream of each notch). Four flow events were modeled at each terrain condition to account for different dike overtopping ratios. The model results of each proposed condition were compared with the existing condition near the dike, at the downstream riverbank, and at the navigation channel for each notched dike. Results indicated that filling the notch and scour hole causes higher degradation rates in the navigation channel, decreased bank scour downstream of each notch, and high variability in hydraulic stresses on the dike structures.

Cost-effective energy dissipation design of low-head hydraulic structures is one of the challenging engineering tasks in South Florida. In many circumstances, the need to pass extreme large volume of discharge during tropical storms and hurricane events may not satisfy the hydraulic structure’s energy dissipation requirement, as well as downstream canal bed erosion control. Traditionally, physical scale models are the most reliable way to evaluate the efficiency of energy dissipation and performance of hydraulic design. However, this approach is usually cost- or time-consuming. In this paper, applications of computational fluid dynamics (CFD) to the hydraulic design of two low-head gated spillways S-333N and S-71 in South Florida were presented. Based on detailed flow hydrodynamics, the CFD-based approach has successfully been used to optimize the general layout of the canal and new S-333N structure and resolve its energy dissipation issues. Several energy dissipation alternatives were proposed and evaluated, which included flow deflector to prevent the high flow jet from plunging to the bottom, and flow separation island to avoid flow jets from existing and new spillways from competing with each other and inducing biased flow and large eddy circulation at the downstream. This optimization design has been validated with field measurements after it was constructed. A similar CFD-based design approach was adopted for S-71. This study demonstrated the potentials of CFD to help accelerate the hydraulic design process and improve the hydraulic design to satisfy the multipurpose engineering requirements.

The abundance of freshwater mussels has been declining worldwide, especially in North America. This increased vulnerability presents dangers to the ecosystems that rely on mussels as ecosystem engineers. In an attempt to investigate local flow fields around freshwater mussels, specifically Elliptio complanata, a sequence of mesohabitats were created in an open-channel flume. The setup contains a sand-gravel mixture bed with a riffle, run, pool, and glide mesohabitat sequence based on measurements from the nearby Grannis Brook, located in Canton, NY. Within each simulated mesohabitat, weight adjusted mussel shells were first placed on the bed, and then velocity profiles in each mesohabitat, as well as near-bed velocity time-series, were taken in the vicinity of the mock mussels. Measurements were taken for three scenarios by varying flow rates. For all scenarios, measured velocity profiles were compared with the logarithmic profile. Additionally, reach-averaged and local bed shear stresses around the mussels in each mesohabitat were examined. Generally, as was expected, lower velocities and bed shear stresses were observed in the run and pool mesohabitats while they were higher in the riffle and glide. This suggests that more favorable mussel habitats can be expected in runs and pools where sediment deposition is greater. The results of this study may help to improve restoration of degraded freshwater mussel habitats.

Microplastics (MPs), plastic particles that range from 1 to 5 mm in size, are a growing concern in the oceans worldwide. The abundance of MPs particles in marine and riverine environments presents a risk to aquatic ecosystems, species, and food webs, and therefore a threat to human food safety. Rivers are critical carriers of almost 70%–80% of the plastic waste that reaches the oceans from land based sources. Recognizing the increasing environmental concern of MPs, it becomes vital to understand the dynamics of MPs in the riverine ecosystem systems. This particular study investigated the impact of vegetation on the transport and retention patterns of MPs in an open channel. Several experimental scenarios, with and without vegetation under high and low Reynolds numbers, were conducted in the eco-hydraulics flume to examine the flow hydrodynamics and the transport and retention pattern of MPs. For vegetation scenarios, plastic aquarium plants were attached to the flume bed with different vegetation densities and arrangements, for example, disperse vegetation and vegetation along sides in the observation area. An acoustic Doppler velocimeter (ADV) was utilized to measure the flow hydraulics in the observation area. The retention and transport of MPs was appeared to be more prominent for large vegetation density and low flow velocity. The relationship of hydraulic parameters like average turbulence kinetic energy, average shear velocity, and average flow velocity with retention coefficient was pretty good for disperse vegetation arrangement as compared to the vegetation along the sides.

Hydraulic geometry (HG) theory has been applied to characterize the morphological changes that a river undergoes as a result of changes in discharge. Furthermore, HG has been used in a variety of studies including indirect discharge estimates, habitat assessment, and flow resistance analysis. Since a river is always evolving towards a morphological equilibrium, HG relations are obtained based on measured data that relate top width, mean flow depth, and mean velocity with discharge. At-a-station and downstream HG have been defined to characterize river development at a cross-section and reach scales, respectively. Dimensionless forms of downstream HG relations have been proposed to capture the physics of river morphology. Median sediment diameter d₅₀ has been used as the characteristic diameter to put HG relations in dimensionless form. However, for rivers with coarse bed material, it has been shown that the characteristic diameter may be greater than d₅₀. In the present study, field measurements from a high gradient (slopes from 2% to 10%) gravel bed river (d₅₀ from 4 to 25 mm), the Tabacay River, are used to establish the downstream HG relations and to determine the impact of the characteristic diameter by considering d₈₄ and d₉₀ as characteristic diameters. Additionally, based on these relations, regime equations are obtained for the Tabacay River to compare the performance of each characteristic diameter. The results helped to define the appropriate characteristic diameter to make HG relations and regime equations more representative of measured data.

In an alluvial channel, the work of transporting sediment is primarily done by sediment waves that form on the channel bed and by the associated, turbulent structures that suspend sediment within the water column. The sediment waveform (i.e., bedforms) strongly influences flow resistance as the result of drag forces. Engelund and Hansen theorized an energy equation based on the relationship between sediment transport and the sediment waveform. Based on this theory, Cotton developed an alluvial flow resistance equation that is applicable to all bedform regimes. In this paper, the sediment celerity of the sediment waveform is formulated and compared to flume data. Research on large-scale surface turbulence is reviewed and the relationship to flow characteristic such as velocity, waveform, and sediment transport. It is proposed that there is an opportunity to extend new technologies for the measurement of surface turbulence and flow velocity to also provide estimates of sediment transport.

River morphodynamics deals with the evolution of river geometry, flow path, and associated sediment/alluvial depositions. A concise understanding of the river dynamics and spatio-temporal analysis of river morphology is a primary prerequisite for waterway development, waterbody restoration, and flood hazard mitigation. A high degree of unplanned urbanization, human settlements on the floodplains, climate change, and natural disasters have altered the course and morphodynamics of many rivers in the world. This has destroyed the natural biodiversity and has resulted in frequent floods and degradation of water quality. The present study focuses on analyzing morphodynamic changes of the Adyar River flowing through the Chennai city of Tamil Nadu state in India. Temporal evolution for the past 30 years is assessed using Google Earth Engine (GEE) platform and image processing techniques. Cloud masked Landsat satellite images are analyzed using Modified Normalized Difference Water Index, Normalized Difference Vegetation Index, and Enhanced Vegetation Index to extract the annual river channels and alluvial deposits. Results show a slight shift of the flow path and increased deposition of sediments towards the river mouth, where it joins the Bay of Bengal in the Adyar Estuary. This may be attributed to the high degree of unplanned urbanization and floodplain encroachments in the past decades. The morphological changes over time have worsened the damages during the frequent flood events in recent times. The results of this study can be used to regain the health of the Adyar River and consequently reduce the damages caused by floods in the future.

The Big Bar landslide occurred on a remote section of the Fraser River, 64 km north of Lillooet, British Columbia, and created a barrier to the vital seasonal northward Fraser River salmon migration. Intensive efforts were made by Canada Department of Fish and Oceans in 2019 as an emergency response to stabilize the slide source and to remove large boulders and rockfall debris from the river. Early in 2021, Kiewit design teams had nearly finalized plans for construction of a roughened embankment for volitional passage and a concrete fish ladder. However, ongoing rockfall hazards prevented any work commencing on the fish ladder structure. The roughened slope design was largely completed as this embankment was planned to support the concrete fish ladder. In lieu of the fish ladder, the slope of the roughened embankment was extended. Construction of the roughened embankment consisted of large riprap with a characteristic size of 1.5 m with rock material produced from on-site sources. Modeling of the hydraulic performance was accomplished with depth-averaged two-dimensional analysis (USBR SRH-2D). Spatial distributions of shear stress and velocity were computed over the embankment for determination of riprap stability as well as provide an environment for volitional fish passage. A thorough inspection and testing protocol (ITP) for rock material and placement were followed. ITP implementation included use of image segmentation gradation analysis and other testing methods. Heroic construction efforts through the winter of 2020–2021 in the tough environment of the Fraser River completed the roughened embankment in time for the spring freshet. Flow in the Fraser River in June of 2021 peaked at approximately 6,100 m³/s with the roughened embankment remaining completely stable.

This paper presents two application cases about long-term shoreline evolution modeling by using the GenCade shoreline model, which includes an empirical model for predicting volumetric changes of inlet morphology elements (shoals and bars). The two cases are to reproduce long-term variations of shoreline positions around Indian River Inlet, DE, and Absecon Inlet, NJ. Both included coastal structures (jetties, groins, piers, and outfalls) and non-structural protections such as beach fills, sand nourishment, sand bypassing operation, and dredging. This paper also provides the setup of complex model input parameters for configuring those structures and non-structural protection measures using GenCade interface built in SMS software. Simulation results indicate that the model is applicable to reproduce shoreline evolution with large variations due to severe erosion by storms and beach fills. The model is capable of predicting long-term evolution of inlet morphology elements including dredging on shoals and bars, which gives better understanding of sediment pathways through inlet shoals and adjacent shorelines. These capabilities for assessing impacts of structure and non-structural protection measures and inlet morphological changes will facilitate finding best solutions of combined erosion protection strategies on barrier islands.

The measurement of velocity distribution and flow visualization of water is important for predicting phenomena, such as violent geyser in a storm sewer and stratified flow in a pipe. Flow features such as velocity field and strain rate distribution are calculated using visualization techniques such as PIV (particle image velocimetry), PTV (particle tracking velocimetry), and LDV (laser Doppler velocimetry). However, such techniques require expensive setups and one-time usable expensive seeding particles. This article first proposes an affordable water PIV technique using simple off-the-shelf potato starch and laser diodes. Secondly, we assess the capability of smartphones for low-speed water PIV. Finally, the results show the parabolic velocity profile for laminar and piston type profile for the near turbulent flow, validating our claims.

The Big Bar landslide occurred on a remote section of the Fraser River, 64 km north of Lillooet, British Columbia, and created a barrier to the vital seasonal northward Fraser salmon migration. Intensive efforts were made by Canada Department of Fish and Oceans in 2019 as an emergency response to stabilize the slide source and to remove rockfall debris from the river. In 2020, Kiewit was awarded a contract to undertake additional remediation of the landslide and final design of a fishway structure and a volitional passage. Due to continuing rockfall through the winter of 2020–2021 the construction effort was limited to the volitional embankment with a temporary slope extension taking the place of the proposed fishway structure. The basis of the design used a combination of the USBR’s SRH-2D two-dimensional depth-averaged computations and grading design with the objective of creating a uniform gradient with an ample corridor for volitional passage with a mean velocity of less than 2.0 m/s. Given the use of large size riprap (1.5 m characteristic size) and the shallow flow depths associated with volitional pathway, the determination of velocity utilized research by Blodgett at the USGS to develop depth-varying boundary roughness relationships. The design process led to a unique grading configuration for the embankment. While considered a temporary configuration, the grading design worked successfully through the spring and summer freshet of 2021 permitting the unimpeded passage of chinook and sockeye salmon with little use of alternative transport means.

Stormwater infrastructure and canal restoration have a need for simulating the vegetation flow in most cases. In this study, a simplified approach was applied to simulate the lateral flow from L-6 Canal into high vegetated Water Conservation Area 2 (WCA-2) in Florida using a power law-based equation. A HEC-RAS model was constructed with a lateral weir whose rating curve was defined by Lal’s three parameters for vegetative flow. Parameter Estimation Tool (PEST), a model-independent auto-calibration software, was linked with the HEC-RAS model attempting to calibrate the three parameters through historical matching. A prediction-based methodology in PEST was used to provide the 95% confidence intervals of the calibrated rating curve of the lateral weir. Then the HEC-RAS model with the calibrated rating curve and the estimated uncertainty intervals were applied to the hydraulic design of a culvert S-620 at downstream. This estimated uncertainty intervals are very helpful to ensure that the culvert S-620 is neither over- nor under-designed. The approach used in this study is recommended for other vegetative water areas as well.

Regional flood frequency analysis (RFFA) is widely applied in hydrology to estimate flood quantiles for ungauged catchments. Most of these RFFA techniques are developed using flood quantiles estimated by annual maximum (AM) model. Recently, a RFFA technique has been recommended in Australian Rainfall and Runoff (ARR) based on the AM model, which does not include very frequent floods. In this study, at-site flood quantile estimates from 67 gauged catchments in south-east Australia based on peaks-over-threshold (POT) model are used to develop a RFFA technique for “very frequent” and “frequent” flood ranges. Very frequent design rainfall and baseflow index data from ARR are used as independent variables in this new RFFA. Based on an independent validation, it is found that the new POT based RFFA models can provide quite accurate flood quantile estimates for ungauged catchments in the very frequent and frequent flood range. These frequent design flood estimates can be used in urban stormwater management, environmental, and ecological studies in the study area.

Surface water discharge measurements are critical for water management, public safety, improving the understanding of hydrologic processes, and understanding how climate change is impacting the water cycle. Surface water instrumentation is costly, and the distribution of stream gage networks across the world is not all-encompassing and is diminishing. This study reviews remote sensing methods of estimating channel geometry, inundation extent, and velocity in order to compute surface water discharge with or without supplemental field instrumentation. The data sets used include satellite altimetry, gravity field measurements, optical imagery, synthetic aperture radar, and non-contact radar. This study explores the challenges facing discharge estimates such as the spatial distribution, frequency, resolution, cloud obscuration, vegetation interference, and terrain distortions. It also addresses the ability of synthesis of different data sets to reduce some of these shortcomings. This review compares the performance of remote sensing data sets and discusses future deployments of missions and their potential to improve discharge estimations.

River erosion is a problem all over the world. A new hybrid approach, Technology for Integrated Groyne-Vetiver Erosion Reduction (TIGER) method, was developed. The method includes combining groynes at the toe of the riverbank to reduce toe erosion in the channel and planting a buffer strip with vetiver grass to reduce erosion caused by over land flow. A case study was done in the village of Fode Binea in Senegal, West Africa, to reduce stream erosion. Groynes of large rocks were installed at a riverbend with particularly high erosion. Vetiver grass was installed in a buffer strip along the top of the outside bend of the river. Erosion was measured for several months. It was found that there was a reduction in stream erosion. Therefore, this method shows promise of reducing stream erosion since it works, is low-cost, and made of inexpensive local materials. Further study should be undertaken to fully understand how the stream performs under normal conditions as well as monitoring the new method once it is implemented.

Aquatic plant communities both affect and are affected by their physical, chemical, and biological environments. Understanding tightly coupled plant and flow processes is especially important in rivers, in which management actions such as water withdrawals, reservoir operations, or in-channel structures can cause strong and rapid feedback cycles. Numerical models provide an important mechanism for understanding and forecasting these dynamics in complex environments. Here, we describe the need for improved models of aquatic macrophytes in rivers. First, we review the role of river macrophytes through the lenses of their ecological roles (e.g., habitat cover), riverine functions (e.g., nutrient processing, hydraulic roughness), and conservation needs (e.g., imperiled species management). Second, we review existing models of riverine macrophytes and put forth a conceptual framework for developing new models. Third, we develop a conceptual model of a common macrophyte as a means to understand the broader functions of aquatic plants. Specifically, we focus on the effects of water management on hornleaf riverweed (Podostemum ceratophyllum Michx.) in the Middle Oconee River in Georgia, incorporating relevant predictors of macrophyte growth as well as the potential for feedback between macrophyte growth, hydraulic flow, and nutrient spiraling.

The increase in temperature has posed decline in winter snowpack over Western US reducing spring-summer streamflow in the snow fed watersheds of the region. The climate variables such as sea surface temperature, pressure, specific humidity, and the wind velocity across Pacific Ocean highly determine the winter snow precipitation of the region thus affecting stream-summer streamflow volume. Thus, understanding the time lagged spatiotemporal correlation between winter climate variabilities and spring-summer streamflow can unveil the underlying physical processes that drive the hydrology of the region. In current study, the spring-summer streamflow of San Joaquin and Sacramento watersheds (SSW) was spatiotemporally correlated with the climate variables of Pacific Ocean [sea surface temperature, 500 mbar geopotential height (H₅₀₀)] along with specific humidity and U-wind corresponding to H₅₀₀. Singular value decomposition showed teleconnections associated with the climate parameters and streamflow for SSW watershed which can provide a foundation for improving streamflow forecasting over the conventional method of using predefined indices.

Hydrologic analysis is very essential and foremost step that directs towards ensuring proper planning and management of water resources. Flooding is one of the hazards that is prominent along Big Muddy River in Murphysboro located in Southern Illinois. Changes in land cover patterns, watershed hydrology is affected that necessitates hydrological. In the current study, the Hydrologic Engineering Center Hydrologic Modeling System model was used to compute the runoff at the basin outlet. To analyze the discharge, the current study used different metrological, soil characteristics, and land cover of the basin. The impervious surface was found to be the most sensitive data set that brought significant changes in peak discharge. The hydrological analysis is very essential as it helps in designing hydraulic and other flood control structures required within the basin. Increasing the previous surfaces might help in reducing peak discharge and increase the lag time to prevent damages to life and properties.

This study is motivated by quantifying potential evapotranspiration (PET) evolution under climate change in the Arabian Peninsula. It implements climatic data in the Penman approach to investigate the development in PET values through the 21st century. Climatic simulations were obtained from 10 global circulation models in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Analysis showed that PET losses are projected to increase between 0.18 mm and 0.96 mm/year through the end-21st century, under the shared socioeconomic pathway SSP5-8.5. The warming trend over the Arabian Peninsula seems to be the primary driver of PET increases. These results imply severe consequences for the Arabian Peninsula countries, which have indeed a very high water deficit. Therefore, sustainable management and augmentation of water resources should be prioritized in future agendas.

This research applies hydrologic and hydraulic modeling to test the individual and combined impacts of climate change and urbanization on peak discharges and bridge overtopping rates for Cedar Creek in Harris County, Texas. The results demonstrate that the combined effect of urbanization and climate change can cause the 2% annual exceedance probability (AEP) peak discharge to increase above the historical 1% AEP discharge. The research furthermore reveals that changes in precipitation have a more substantial impact on peak flow and bridge overtopping than changes in land use. Peak flows for the 1% AEP in 2100 increase by approximately 7% when considering land use changes and 18% when considering precipitation changes. Corresponding bridge overtopping rates approach 50% and 57%, respectively. Ultimately, the results of this study show that both climate change and urbanization will influence the likelihood of bridge overtopping and therefore should be carefully accounted in the design of bridges.

Management of water uses requests to harmonize demands and needs which are getting more and more complex and sophisticated especially with the growing urbanization. The current situation, characterized by the fast increase of monitoring devices mainly in urban environments, requests an integration of the modeling tools into the information systems that are dedicated to the global management of urban environments and related services. Decisions supports systems that may integrate various components both for real-time monitoring and forecast through models appear as one of the most relevant answers to the urban environment management’s expectations. Within this approach, the choice of the relevant hydrological modeling tools is a key element. The selected ones should be able to provide the relevant information, on time and with the relevant accuracy for the decision makers. The hydrological deterministic models have reached today a sufficient maturity to provide an accurate representation of the processes. As demonstrated with AquaVar approach implemented over various catchments on the French Riviera, France, several models can be orchestrated within a single environment that can address the diversity of the water related issues like water supply, flood forecasting, and water quality monitoring. The paper focused on model’s selection, the needed orchestration between the different tools and the operational implementation within a challenging context combining natural hazard mitigation and water services dedicated to the population.

The case study presented here is the Vila Leopoldina catchment, located in the city of São Paulo, Brazil. The basin is located in the west region of the city and suffers every year with floods. This area is highly sensitive because of its occupation for housing, mobility, services, and it also contains the largest wholesale food center of Latin America. This paper presents a complete plan for short-, medium-, and long-term improvements to solve urban drainage issues. The solution herein proposed consists of the increase in drainage capacity, construction of small detention reservoirs, and one dike. The solution was simulated in the SWMM rainfall-runoff model and was tested with an observed event that caused devastation in this area. The presented study supports the development of public urban policies related to drainage systems planning and management. This study was also applied as a basis for planning investments from international funds that finance the proposed improvements.

In deciding sizing of roadway cross-drainage structures, engineers generally use a design-discharge estimate calculated for a specified return period (expressed in years) where such return periods are essentially measures of specific annual exceedance probabilities (AEP). However, road agencies often ask for addressing extreme flood events and to account for climate change factors. This necessarily warrants a risk analysis using a general exceedance probability (Poisson probability distribution) consideration rather than the AEP. It is, however, imperative that any such risk-triggered solution has to be weighed against economic-viability and be sustainable solutions to those responsible for planning and preparation of road infrastructure projects. Presently, applicable codes and specifications very often limit the solutions to some prescribed percent increase to the design-discharge estimates to account for extreme flood events. This paper addresses the issue using stochastic analysis of the catchments’ response to the rainfall, using the first order reliability method (FORM). Such a risk-estimation approach for recommendations on sustainable solutions to address extreme flood event bases itself on historical rainfall data for specific catchments.

Cyclone Amphan made landfall on the Indian state of West Bengal on May 20, 2020, during the initial phase of the COVID-19 pandemic. It passed through the western edge of the Sundarbans mangrove forest following a north-north-eastern track affecting neighboring Bangladesh as well. The overlapping of this cyclone during the pandemic made emergency response especially challenging for two of the most densely populated countries in the world. Nevertheless, remote sensing has been extremely useful in such scenarios where accessibility and in situ data-sharing are compromised. The application of multispectral satellite imagery is especially common in large-scale impact assessment following natural events, but the presence of clouds during cyclones makes these images often less effective. Sentinel 1 synthetic-aperture radar (SAR) imagery thus can be very useful due to its cloud penetration capability. This study shows that this freely available global data can provide back-of-the-envelope damage assessment using minimal computational facilities. Therefore, the objective is to perform an inundation assessment in coastal districts (level-2 administrative area) of India and Bangladesh due to Cyclone Amphan using Sentinel 1 SAR imagery.

This paper highlights the flood and bank erosion problems of the complex Brahmaputra River system, which flows through parts of three countries (China, India, and Bangladesh) covering a distance of 2,880 km with a focus on erosion of its banks and taking away valuable lands of the Majuli Island in Assam, India. The Core Professional Group for the Brahmaputra (CPGB), a non-government organization (NGO) formed in 2010 by a group of experienced international river management professionals, took an initiative to review the chronic flood and river bank erosion that has occurred in Assam, and the control measures adopted by the authorities during the last six decades. CPGB identified possible mitigation of flooding and erosion of the Majuli Island as a pilot project. CPGB has submitted several proposals of the pilot project to the Government of India. Tasks from the proposals, including data gathering, geology and geomorphological study, mathematical modelling of river hydraulics and sediment transport, and sustainable design solutions, are described in the paper. The paper is to be construed as a technical exchange forum between CPGB and river engineering experts at an independent session on the Brahmaputra River in the EWRI Congress, 2022.

The Brahmaputra River, a large river system in Asia, has been causing serious flooding and bank erosion damages in its nearly 800 km reach in the Indian state of Assam. To assist in creating solutions to the cited problems, the Core Professional Group for the Brahmaputra (CPGB), a non-government organization (NGO), was formed. The specific area of flooding and bank erosion related to this presentation is near Majuli Island. The overall plan of action developed by the CPGB related to erosion control and subsequent flood control consists of four major activities: (1) data gathering, (2) geology and geomorphology study, (3) mathematical modeling, and (4) sustainable design solutions. This presentation concentrates on the sustainable structural aspects of erosion control in item 4 (sustainable design solutions), specifically within the river itself. This portion of the overall project consisted of three phases: Phase 1: Using the results of the fluvial geomorphology study, possible candidate erosion control locations will be identified; Phase 2: Once candidate locations are identified, detailed hydraulic information will be gathered from the hydraulic modeling effort; and Phase 3: With additional design information presented and input again to the decision matrix, the top two or three possible solutions will be presented to the CPGB team. The potential solutions, with pros and cons, are presented, with illustrations of the measures.

The Brahmaputra River, a large river system in Asia flowing 2,880 km from the Upper Himalayas to the Bay of Bengal through China, India, and Bangladesh, has been causing serious flooding and bank erosion damages in its nearly 800 km reach in the Indian state of Assam after its steep fall (~3 km) through approximately 250 km long narrow gorge crossing the China-India border. Unlike flooding, damages caused by erosion of the banks, including taking away residential properties, schools, cultural establishments, agricultural and industrial lands, and forests (state and national) serving homes for animals with endangered species, and even the flood control levees protecting the above, are permanent. Therefore, adequate erosion-control measures must be placed at active bank erosion sites to protect the above. There are many scientific challenges as the river is uniquely large and unstable. It has four constrictions playing major roles. A mathematical model of the river is needed to carefully study the river, account for effects of the constrictions and other features, and use it to design and align an adequate and stable channel of the river with sufficient capacity to convey the incoming flows of water and sediment. Next the stable and optimally aligned channel must be built and maintained using bank stabilization technologies and minimal dredging. In this paper and presentation, brief descriptions of the Brahmaputra River, its flooding and bank erosion problems, some of the challenges in solving those, and an approach as eluded above with the help of a mathematical model to overcome the challenges are presented and discussed.

The Nile basin is one of the transboundary basins without water sharing and water management agreement while population growth and water demand is increasing. Ethiopia is building the Grand Ethiopian Renaissance Dam (GERD), a hydroelectric power dam, 81% completed, on the main source of the Nile, the Blue Nile River. The 74 billion cubic meter (bcm) storage and total installed power capacity of 6,000 MW dam is to alleviate critical power needs of Ethiopia. Since the beginning, negotiations on the filling and operation of the GERD have been going between Ethiopia, Egypt, and Sudan without reaching agreement with signals of water conflict. The main cause of the disagreement is Egypt’s effort of inserting clauses in draft agreements that will preserve the status quo water use, 100% of the Nile water between Egypt and Sudan. Ethiopia contributes 86% of the Nile water. In the meantime, Ethiopia has completed the first two years of the first phase filling of the dam with no downstream impact.

This paper discusses the motivations and implementation process for a mobile application (app) that provides lawn watering recommendations in the Brazos Valley, Texas. The app is a free service provided by the BVWaterSmart campaign. Since 2012, BVWaterSmart has applied data mining and statistical techniques to identify candidates from more than 16,000 single-family residential households for conservation messaging and interventions. These activities have helped the City of College Station conserve the equivalent of three months of summer usage over seven years. With smartphones becoming more affordable and commonplace, mobile applications such as the BVWaterSmart app have the potential to provide watering recommendations and local rainfall statistics directly to residents to help them water their landscapes more efficiently. The BVWaterSmart app accesses neighborhood-level rainfall data from a server that receives data in real-time from a network of rain gauges and uses this data to provide watering recommendations for different types of sprinklers. The app, along with the underlying theoretical models, rain gauge infrastructure, rainfall data collection methods, data processing techniques, and educational interventions developed by BVSmartSmart, can be applied in other cities to realize critical water savings.

In September 2019, the Environmental Protection Agency (EPA) released the first draft of the Water Reuse Action Plan (WRAP), a collaborative initiative that will facilitate water reuse nationwide through the development of partnerships across the water spectrum including federal, state, tribal, and water sector stakeholders. Collaboration among these participants resulted in the release of the finalized version of WRAP in February 2020. This paper examines the 37 specific action plans outlined in WRAP to determine which actions focus on the obstacles to water reuse. Highlighting and emphasizing the appropriate actions will help overcome these barriers to solidify water reuse in irrigation as an important part of our water portfolio.

The current practice of evapotranspiration (ET) based method for irrigation amount estimation in many cases uses a historical fixed crop coefficient that may cause under and/or over water applications. Among others, two distinct sources of uncertainties are involved in this procedure: (1) uncertainty from ET itself and (2) the uncertainty from crop coefficient. Due to these uncertainties, plants either suffer from water stress or the additional water percolates through the root zone causing waste of water and embedded energy involved in water delivery process. To reduce and in some cases to eliminate the uncertainties associated with the historical fixed crop coefficient, a field specific customized plant water intake (PWI) curve can be constructed. This curve will represent the actual water intake by the plants for any given condition including plant physiology, soil condition of the field, and the weather variabilities. A numerical water balance model for soil-water-plant continuum has been developed based on field soil moisture data to calculate and hence construct the plant water intake (PWI) curve. Results show that the peak PWI varies by day with an average intake rate of 0.015 in./h–0.019 in./h for a summer day and field conditions considered in this study. The methodology presented in this study has been applied to an olive field located in the University Agricultural Laboratory (UAL) at the California State University, Fresno.

Improving irrigation water management through scheduling is key to securing water and soil resources in agriculture. This study compared the performance of two crop coefficient (K_c) approaches for maize evapotranspiration with a one-source surface energy balance. Also, we evaluated an updated FAO-56 PM crop coefficient approach using remotely sensed K_c using an Eddy Covariance system. A surface irrigated maize field near Fort Collins, Colorado, was the study area. A constellation of space borne remote sensing microsatellites were used to obtain multispectral images to map actual evapotranspiration (ET_a). Preliminary results indicate that the single source surface energy balance performed better than the ReSET and FAO-56 crop coefficient approaches by 57% on average. Further, the updated FAO-56 approach, adjusted with remotely-sensed K_c values, showed the potential to augment irrigation scheduling tools. There was a 46% error reduction in maize ET_a when the FAO-56 standard crop coefficient curve was improved with K_c values derived from the single source surface energy balance ET_a estimates.

Assessment of water district evapotranspiration (ET) is important for monitoring, managing, and forecasting crop water use. Remote sensing offers the only practical way to provide periodic ET assessments: satellites can observe vegetation cover repeatedly at high spatial resolution. Several ways to use remote sensing for ET estimation exist. One of these is to use crop type maps, crop coefficients (Kc), and weather data within the FAO-56 framework. This approach has been demonstrated by the US Bureau of Reclamation through their annual ET reports for the Lower Colorado River. The method is practical and direct. However, the implementation uses dated crop growth duration (L) parameters. This shortcoming can be addressed by using higher resolution satellite data, now available at 10 m resolution every 3–5 days. The images enable crop growth tracking of locally relevant “L” values. When segregated by quantiles, the vegetation index NDVI resolves initial, development, mid-season, and senescent growth phases. By averaging and filtering NDVI values at plot scales, full-season daily Kc curves can be created and partitioned into the four FAO-56 growth phases. In a study conducted over the Lower Colorado River for crops grown during 2018–2020, we used hundreds of Sentinel 2 NDVI images, crop type maps—each consisting of over 14,000 plot polygons—and local weather data, to estimate daily ET. Data processing was made possible using the Google Earth Engine platform. Results from the updated “L” values significantly reduced total ET for wheat and alfalfa, by 25% and 44%, respectively, highlighting the ability of remote sensing observations to quickly and accurately update crop ET.

Army installations, comprised of infrastructure, operations, and services, face countless risks to facilities’ supporting military missions. Resiliency to disruptions is necessary to perform these missions. Disruptions include degradation/obsolescence, natural disasters, or adversary attacks. To mitigate risk and ensure energy and water (E&W) security and resiliency, army installations must develop installation energy and water plans (IEWPs). IEWPs provide a road map for improving security and resiliency of installations. An essential IEWP component is the development of courses of action (COAs) to address deficiencies, improving an installation’s future condition, E&W security, and resilience during normal operations and emergency situations. The objective of this paper is to document water resiliency improvements in military installations by applying critical facilities demand estimation planning tools, completing courses of action reviews, and factoring in climate change. In doing so, the IEWP process improves US Army military readiness through state-of-the-art solutions for improved security, resilience, readiness, and mission assurance.

Due to increasing water use, water resources are progressively concerned with sustainable development. Water accounting (WA) as a tool for economic analysis of water-related issues can be coupled with a system dynamics (SD) model for evaluating water resources’ growth patterns and vulnerabilities. Carrying capacity as the carrier’s ability to support the bearing object is complex. The complexity of the water resources’ carrying capacity (CC) estimation stems from the enormity of components’ interrelationships. The socio-economic aspects can be represented by suitable indicators to be used for simulation purposes. The SD model is designed for simulating the feedback loops and stock-flow diagrams. In this study, the selection of different scenarios is examined for water availability, and then the procedure to determine the limit to the growth of a water system is evaluated for finding the trade-off between its drivers/pressure component (socio-economic) and the supporting (environmental) components.

In November 2014, former California governor Jerry Brown signed the Sustainable Groundwater Management Act (or SGMA) establishing a new structure for sustaining groundwater in California. SGMA requires several key steps, including the formation of groundwater sustainability agencies (or GSAs) charged with the preparation and implementation of groundwater sustainability plans (or GSPs) to achieve and maintain groundwater basin sustainability. The first GSPs, prepared for basins designated as critically-overdrafted, were due to the state by January 31, 2020, with implementation beginning February 1, 2020. Early implementation of the GSPs has been mixed. While there have been areas of success, specific challenges facing GSAs include funding for plan implementation, determining how to meet new requirements for managing interconnected surface waters and addressing inelastic land subsidence, filling data gaps, and addressing inconsistences in water budget components and sustainability indicators across basin borders. This paper provides a high-level overview of the status of the early years of GSP implementation.

Technological advancements and management adaptations have improved engineered system functions in response to flooding. Other natural and anthropogenic disturbances, including pandemics, utility hijacking, infrastructure destruction, and biochemical releases, can stress a system beyond acceptable limits or novel ways. Resilience-based approaches acknowledge that multiple disruptions to the system will occur while focusing on the recovery and maintenance of critical functions such as interaction of impending hurricanes and evacuation complications due to pandemic. However, a method for evaluating the resilience of the system must be developed. The system can be stressed with multiple disturbances to determine its capacity to resist and recover. Analysis of these capacities or subsequent failures can then be used to determine the resilience of the system and provide insight into remedial actions or improvements. In order to demonstrate this, hypothetical flooding is combined with hypothetical vehicle bridge failure (New York City, USA) and hypothetical point-source contaminant releases (New Orleans, USA). Resilience for these scenarios was defined as the ability for the population to avoid flooding given certain transportation pathways being denied due to compounded disturbances.

Urban drainage systems are essential for life in urban areas. The aging of this infrastructure and challenges like urbanization and climate change can lead to loss of functionality and serviceability. Hence, efficient design and analysis techniques for drainage networks are required. Hydrodynamic modelling method, which is mostly used in literature, is data intensive and requires high computational burdens, especially for large networks. In this study, a new graph-based approach called hydraulically informed graph analysis is explored. Two applications for this purpose are chosen, namely, identification of pipe criticality and pipe design whose results are compared to those from hydrodynamic modelling. Results indicate that the graph method is very accurate in estimating critical pipes while it underestimates pipe diameters. The graph-based method is much faster in execution and has a factor for computational time gain of 324 and 31 as compared to hydrodynamic approach for identification of pipe criticality and pipe design, respectively. This enables a broad field of applications, especially when many evaluations are required, the investigated networks are very large, or for preliminary analysis where only limited data is available.

Carroll County Water Authority of Georgia has proposed a water supply reservoir, Indian Creek Reservoir, to address its water supply needs. Indian Creek Reservoir has been under regulatory review by federal and state authorities. The regulatory review process involves a Clean Water Act (CWA) Section 404 permit from the Army Corps of Engineers (Corps), an associated CWA Section 401 Water Quality Certification from the state of Georgia, and a water withdrawal permit from the state of Georgia. Even though these regulatory review processes are under different legal authorities, the overall objective is consistent: addressing the needs of the applicant and eliminating or reducing negative environmental impacts. In Georgia Environmental Protection Division’s (EPD’s) water withdrawal application review, three major factors have been considered: needs, capacity of the source to provide, and downstream impacts. While the first one involves careful review of planning done by local authorities and Georgia’s Regional Planning Councils, the latter two involves modeling and other technical analyses, including biological considerations. In this case, biological consideration involved detailed modeling by Georgia Department of Natural Resources, Wildlife Resources Division (WRD) on fishery responses to the reservoir’s mode of operation. This consideration resulted in the first instance of a set of monthly varying pumping limitations at the reservoir’s refilling intake. The comprehensive approach also benefited regulatory processes under CWA Sections 401 and 404, including a neighboring jurisdiction determination that ultimately gave green light to the proposed reservoir project.

When crises occur (e.g., disasters, public health emergencies), water infrastructure systems are often forced to operate outside the conditions for which they were designed. Hydraulic models can provide utilities with essential information in a crisis, allowing for near real-time system performance evaluation and informing management response. However, hydraulic modeling remains inaccessible to many water utilities due to extensive data, software, and skilled personnel requirements. Data needs are particularly troublesome because the water sector lags behind other industries in embracing advanced data management and analytics. Researchers have outlined steps to increase data analytics in the water sector and put forth new data management systems in areas such as hydrology and asset management. Notably, a classification system for hydraulic modeling data needs has not been developed. To address this gap, we documented the development of a hydraulic model of the water distribution system serving the University of Texas at Austin. In this study, we (1) classify hydraulic modeling data needs, (2) demonstrate model applications in both a crisis scenario and routine system management, and (3) assess key challenges in modeling. We found that the model can provide helpful insight in a range of management scenarios (e.g., identifying areas of poor system performance), but data-related challenges such as lack of standardization and extensive processing requirements hinder model development. As such, we recommend policy changes that incorporate model development into emergency response plans, ensuring they are in place before a crisis occurs.

The Expected Moments Algorithm (EMA) codified in Bulletin 17C and implemented in the US Army Corps of Engineers Statistical Software Package (HEC-SSP) and the US Geological Survey Flood Frequency Analysis Software (PeakFQ) significantly improves flow frequency analysis. Several years of experience within USACE has identified multiple opportunities to incrementally improve the implementation procedures. Under certain conditions, each of the changes presented in this paper can improve the accuracy and credibility of a flow-frequency analysis. First, the procedure in the current software calculates a new weighted skew value after each EMA iteration resulting in an incorrect value for the final weighted skew estimate. Second, the current software does not report the effective record length (ERL) value needed for a typical stochastic flood hazard analysis when historical, censored, or regional skew information is included. Third, the current software uses the geometric mean of the low and high flow values to calculate plotting positions for flow interval data resulting in a lack of transparency and an interdependency between plotting position and distribution fitting calculations. Fourth, the current software does not calculate or report an estimate of the expected probability curve, which is needed for risk informed decision making. Fifth, recoding of potentially influential low floods (PILF) can result in unrealistic values for the mean square error (MSE) of the at-site skew, confidence intervals, and ERL. This paper provides examples and proposed solutions for each of these items.

Georgia has been at the forefront of water loss control for almost a decade now, beginning with the passage of the Georgia Water Stewardship Act of 2010. This act recognized the imminent need to create a culture of water conservation in the state of Georgia and to plan for water supply enhancement during future extreme drought conditions and other water emergencies. Over the past 10 years, this legislation has allowed Georgia to collect water efficiency data for hundreds of public water systems across the state. Other states, after reviewing Georgia’s publicly available data, are now evaluating similar legislation or programs in their own states. This data has offered insight on both the utility and state levels about water efficiency and continues to inform how the Georgia Environmental Protection Division (EPD) approaches implementation of the act. Within the past three years, EPD has begun using water efficiency data as part of the water withdrawal and drinking water permitting processes. During the spring and summer of 2019, representatives of EPD traveled to multiple conferences across the state to provide information on this process and answer questions in order to better prepare and inform the regulated community. That presentation focused on the history, benefits, current status, and next steps for water loss tracking in Georgia. Since that time, EPD has expanded its outreach to include information about Water Loss Control Programs (WLCPs) and how the different requirements under Georgia rules work together to create a comprehensive approach to encouraging water supply efficiency improvement in the state.

Advancing social equity and overcoming historical inequities are often central to urban water policy. However, water managers have struggled to include equity in decisions due to a lack of clear planning frameworks and quantitative metrics. In this paper, two stream restoration case studies are described in which equity played a prominent role in decision making. First, census-based equity metrics were used to contextualize decisions and communicate restoration project benefits in the Bronx River in New York City, New York. Second, qualitative equity metrics were used to inform stream restoration decisions in the Beargrass Creek watershed in Louisville, Kentucky. These cases are compared and contrasted relative to the approach for assessing equity, metrics used, decision making methods, complexity of the equity assessment, and gaps in the methods. Ultimately, a set of lessons learned are identified for using equity metrics in complex urban water management decisions.

Engineered systems are designed for a specific operating context based on assumptions about the population served. In turn, management of these systems can be stressed during population shifts (and corresponding demand shifts), such as those seen during both discrete (e.g., hurricanes) and protracted (e.g., pandemics) events. For instance, the COVID-19 pandemic caused drastic changes in society, consequentially changing spatial and temporal water use as people worked from home. In another example, Winter Storm Uri led to utility service disruptions throughout Texas, causing people without power and water to seek shelter, leading to spatial changes in water use in conjunction with physical damage. This sheltering occurred during the COVID-19 pandemic, leading to increased uncertainty in demand and challenges to shelter while ensuring social distancing. Researchers have studied disaster scenarios independently, but there is a gap surrounding compounding disasters as human-infrastructure interactions are likely altered. Here, we assess water demand changes during Winter Storm Uri (which occurred during the COVID-19 pandemic) at the building level. We performed k-means clustering on demand data from four buildings at the University of Texas, Austin. Three buildings showed different daily demand profiles during the storm compared to the spring semester. Interestingly, there were demand increases in buildings not being used as warming centers, perhaps indicating increased occupancy. This trend reveals that people do not necessarily choose to shelter in places that are formally organized. In a museum, water use decreased compared to the already reduced demand during the pandemic, possibly leading to water stagnation and quality concerns.

The Metropolitan Region of São Paulo (MRSP) water supply system in Brazil is one of the largest in the world. It supplies water to 21.5 million inhabitants and is upstream of the Metropolitan Region of Campinas. The region has 3.1 million inhabitants in the Piracicaba, Capivari, and Jundiaí River basins (PCJ). The water supply system consists of seven main reservoir subsystems and is currently recovering from the worst drought in history. Cantareira subsystem is the largest in both water supply and storage capacity. It transfers water from the PCJ to the MRSP. There are two newly built water transfer systems: one from the Jaguari Reservoir, directly linked to the Cantareira subsystem, and another from the São Lourenço Reservoir, which is connected to a new water treatment plant. Both water transfer systems operate at very high energy costs. Additionally, there exist conflicts among all water users. The primary role of the two new water transfer systems was to increase water security. Since 2017, the newly imposed minimum required flows at PCJ increased the releases from Cantareira subsystem by 5 m³/s. But this increase necessitates both São Lourenço and Jaguari to operate at almost full capacity as well as at much higher energy cost, while the less expensive Cantareira subsystem stands operating with idle capacity to sustain higher required downstream releases. Currently, Brazil is facing a new record-breaking drought, now in the southeast region, with simultaneous water and energy crisis. In this paper we use SISAGUA, a previously developed nonlinear optimization model, to evaluate the impacts of the modified constraints on the management of the MRSP water supply system, considering energy consumption, operational costs, and water security.

Technological advancement has opened up new opportunities for smart water networks (SWNs), including real-time management of stormwater runoff such as Open Storm, an open-source end-to-end platform for real-time monitoring and controlling stormwater. With the increasing popularity of SWNs, they also become increasingly complex with a wide range of components. Such complexity leads to inadvertent points of compromise in terms of both cyber and physical safety. We assessed the robustness of the Open Storm framework for an upgrade to stormwater controls with real-time mechanisms for the management of innovative and sustainable urban water resources. Based on the components in our planning project and the literature review, we identified various points of failure ranging over four layers of the cyber-physical system (CPS). In addition, we investigated the levels of risk and possible workarounds comprehensively to help researchers and developers strengthen future smart water projects in urban ecosystems.

Smart rainwater harvesting (RWH) systems can automatically release stormwater prior to rainfall events (based on weather forecasts) to increase detention capacity on a household level. However, the impacts and benefits of widespread implementation of smart RWHs are often unknown. This work aims to investigate the effect of a large-scale implementation of smart RWH systems on urban drainage resilience and to determine the influences of digital parameters (e.g., accuracy of weather forecasts or reliability of data communication). As a case study, an Alpine municipality (2,500 inhabitants) is hypothetically retrofitted with smart rain barrels. The reference state (without any extensions) has a resilience index of 0.626 (0 and 1.0 represent the complete failure and perfect system, respectively), which could be increased by up to 0.701 through smart RWH systems depending on the degree of implementation. However, sufficient consideration of digital uncertainties was of greatest importance as such uncertainties could reduce/eliminate the gained performance improvements.

Flood and erosion warning through communication of real-time flood risk in the case of flooding and mapping of erosion prone areas can be an effective tool for improved safety and reduction of economic loss from flooding. In this paper, past and ongoing experiences in the City of Fort Worth to install, operate, and maintain a flood warning system to reduce flood risk is discussed. Mapping of erosive areas helps communicate landscape loss risk and set geographically targeted development standards.

Philadelphia Water Department’s (PWD) Green City, Clean Waters program is in its 10th year of implementation. Thus far, the program has been instrumental in managing runoff from 485 hectares (1,200 acres) using green stormwater infrastructure (GSI) implemented through public funding, private funding, and partnerships. While PWD is required to evaluate multiple future scenarios that include both GSI and traditional infrastructure in support of long-term planning under the Green City, Clean Waters initiative, GSI performance evaluation using mathematical models is computationally intensive and time consuming. To make these evaluations more efficient, a hydrograph interpolation tool that approximates runoff hydrographs from sewersheds using existing EPA SWMM (stormwater management model) simulations of green infrastructure practices was developed. Given an estimate of the area to be controlled using GSI, the interpolation tool helps quickly approximate potential runoff time series from a specified sewershed. These interpolated flows can serve as inputs to SWMM models of the combined sewer system. Analogous to painting by numbers, using this interpolation tool facilitates assembly and evaluation of dozens of citywide green infrastructure combinations that can be used to estimate combined sewer overflow reductions at regulator, interceptor, drainage district, and citywide scales. The tool ultimately provides insight into green infrastructure placement strategy.

Low impact development (LID) techniques have been widely applied as stormwater control measures (SCMs) to mimic the pre-development hydrologic regime, by restoring the natural water cycle and enhancing water quality. A full-scale LID testbed was implemented at the University of Texas at San Antonio (UTSA) to evaluate performance of various LID designs. The LID testbed is composed of six parallel cells containing three different soil mixtures including one traditional sand media and two bioretention soil mixtures. The hydrologic and treatment performance of the LID testbed was monitored under two phases, assessing the impact of internal water storage on the pollutant removal efficiencies. The first monitoring phase was carried out over the duration of 1.5 years (May 2019–December 2020) without submerged zone, while the second phase with elevated outlet and internal submerged zone is still ongoing. As suggested by previous studies, enhanced pollutant removal was observed in presence of submerged zone; however, considerable variations are evident between different designs and different types of pollutants, which emphasizes the significance of media properties and design characteristics on the performance of LIDs. The findings of this study enhance our understanding of the treatment processes within the LID systems, which accordingly promotes effective design recommendations for enhanced LID practices.

The watershed of Verde Stream, located in São Paulo, Brazil, is the object of projects that aim to minimize flood events’ damage, due to high slopes, consolidated urbanization, and few available areas for detention reservoirs. A locally well-known alternative for minimizing flood impacts is the Abegoária Reservoir. Despite its hydraulic benefits, population is resistant to its construction, allegedly associated with the imperviousness of green areas and the loss of space for social interaction. This study considers a new reservation approach that preserves permeability and multiple use of space, serving as both flood control system during rainy season and recreational area during dry periods. The average imperviousness rates were evaluated for the current scenario and two other reservoir conceptions, considering different types of ground coverage. Results showed that the presented reservoir would promote an increase in permeable surfaces by 35%. Average impermeability would only be increased if an impermeable underground reservoir was implemented.

The effort for restoring Chesapeake Bay has focused on developing and implementing NPDES MS4 program and tracked the TMDL pollutants to the Chesapeake Bay. Baltimore City has plans and goals to restore 20% of the city’s impervious. The restorative efforts LID strategies and the implementation of BMPs. The research assessed the impact of LID practices at Baltimore City. L-THIA used to model runoff and pollutants in an idealized and pre-developed Baltimore City. This data was compared with data from 1973 and 2017. In addition, the model was also used to evaluate the various impacts of LID practices that would restore an equivalent 2.5%, 5%, 10%, and 20% of the impervious land cover by use of various BMPs and access Baltimore City BMP practices. The results will allow Baltimore City to meet its environmental stewardship mandate and will address the performance prospects.

Since 2001, the Metropolitan North Georgia Water Planning District (District) has coordinated strategies to protect watershed conditions and manage stormwater in conjunction with existing regulatory requirements. However, despite these efforts, urban stormwater runoff remains a leading cause of nonpoint source pollution and flooding in the District, leaving watershed managers with ongoing challenges related to water quality, streambank erosion, and nuisance flooding. Historically, managers have primarily focused on strategies to address water quality rather than water quantity, even though they are fundamentally linked. For these reasons, the District has developed a novel water quantity-based indicator, called the Stormwater Forecast (Forecast), as part of the integrated 2022 Water Resources Management Plan. The Forecast is a planning-level estimate of the total potential runoff management volume from development, calculated at the basin scale using site-scale post-construction stormwater performance standards. With this approach, the Forecast represents a full accounting of the runoff volume from developed lands that have the potential to be managed by stormwater control measures (SCMs), for example, traditional stormwater ponds or bioretention basins, if current post-construction stormwater management standards were fully in place. Future use of the Forecast is intended to complement and support the implementation of existing water quality and flood reduction goals in the District.

Living shorelines and other nature-based solutions have become more widely accepted as a cost-effective, multi-functional, and sustainable approach to coastal resilience. However, in spite of growing stakeholder support, a planning-level understanding of the hydrodynamic impact of living shorelines is not well developed. Not only do these features vary in size, shape, and structural characteristics, but the wave environment in which they exist can be quiescent or extreme. In a series of Simulation WAves Nearshore (SWAN) simulations, we investigated the effect of wave period, wave height, slope, living shoreline feature length, and feature friction coefficient on wave attenuation. Results showed that higher wave period, higher wave height, milder slopes, longer feature lengths, and higher feature roughness largely correlated with higher wave attenuation. However, only on mild slopes did additional feature lengths result in appreciable additional attenuation. Characteristic lengths were thus computed to better illustrate the cost-effectiveness of additional feature lengths given a particular wave environment. In this way, regardless of the particularities of individual project sites, planners can better assess potential living shoreline projects before pursuing more detailed, costly analyses.

Climate change is the most challenging issue in our time. The study of weather extremes like heat waves, droughts, and flooding is important as they pose a significant threat to life, property, and economy. Many deadly natural hazards such as bushfire over the last century in Australia have been caused by the heat waves, which is directly related to the increase in temperature. This study examines the daily maximum temperature data at Australian capital cities. Statistical and graphical goodness-of-fit (GOF) tests are adopted to identify the best-fit distribution probability distributions for the selection of weather stations. The statistical GOF test reveals that Beta, Gamma (3P), Kumaraswamy, and Pearson 5 (3P) distributions generally provide best-fit to the daily maximum temperature data of the selected stations. Results obtained from the graphical GOF test are compared with those from statistical GOF tests. The findings of this study would be useful for engineers, scientists, and planners to investigate the characteristics of the extreme temperature in Australian capital cities. This will assist in achieving sustainable developments in relation to urban heat island effects and other high temperature related problems.

Despite the vast research in sustainability, very little is known about providing “sustainable management” strategies for a student at a university. The motivation for this study is to examine one of the best strategies and techniques to advance a sustainable management strategy for a campus. Establishing sustainable management strategies can increase students’ well-being and performance. This study was conducted at Morgan State University (MSU) in the Center for the Built Environment and Infrastructure Studies (CBEIS) and Mitchell/Schaefer Building. The results proved the CBEIS classroom meets the requirements of specific standards on thermal comfort and can maintain its required internal temperature and humidity for the students, whereas the classroom in the Schaefer Building without the LEED certification could not maintain its required internal temperature and humidity despite having a classroom without a student load. Both classrooms’ temperature and relative humidity in the rooms were greatly influenced by the weather outside. The major implications of the findings were that sustainable management strategy such as maintaining a prescribed comfort zone could provide economic and environmental benefits while improving the student well-being at any size university. However, any institutions interested in initiating a sustainability management strategy might benefit from undertaking them in an educational setting. This paper offers a different type of vision on how to develop a culture of sustainable management strategy and technique for any university.

For a reliable water supply, it is of great relevance to provide water with sufficient quantity and quality. The assessment of water quality with modelling is state of the art. However, it is more computationally intensive compared to e.g., solving the hydraulic equations. Therefore, water quality issues are often neglected or simplified when conducting experiments which are already computationally intensive (e.g., uncertainty/scenario analysis, evolutionary optimization). In this work, a complex network approach is presented, which is capable of conducting water quality estimations in large WDNs in a very computational efficient manner (2.4 × 10⁵ times faster than the state-of-the-art model). The proposed model is based on identifying the shortest residence time in the flow path from a source to the sink and then adjusts this minimal residence time with a pattern and topology correction. When comparing the results of the proposed graph model with the results of extended period simulation with Epanet2, R² values up to 0.99 were achieved (in median 0.95–0.97 depending on the case study).

The measurement of water quality parameters, such as chlorine and trihalomethane (THMs) concentrations, is usually performed in only some points of water distribution networks. Therefore, models are created to obtain an approximation to the real behavior of the system. However, in the trunk network of Bogota’s water distribution system, the measurements are reported with a frequency greater than the retention time of the network, and they are only performed in a few points throughout the system, which limits model creation. Consequently, this document proposes a non-formal calibration using Monte Carlo simulations for a multispecies model of this network built in EPANET-MSX. The first-order models were adopted for the bulk and wall reactions of chlorine decay, and the linear model was used for TTHMs formation. The methodology consisted in the calibration of the yield of TTHMs coefficient, which was calculated for each pipe depending on a tracer analysis performed for the three water treatment plants (WTPs) of the network. The objective function was built in terms of descriptive statistics given the scarcity of measured data. In this manner, even though the calibration performance was satisfactory, it was found that the parameters for two of the WTPs are not identifiable nor sensitive. Moreover, given the limitations of the method and the scarcity of information, the estimated parameters are considered to have a high uncertainty level. Hence, a higher frequency of measurements is required for a more thorough and less uncertain calibration.

Water distribution systems are critical infrastructure that deliver high quality drinking water to its consumers. Contamination events in water distribution systems (WDS) are emergencies that can cause distress in the population and require quick response from the responsible utility manager. While regular water quality parameters are monitored at water treatment facilities, it is still a challenge to monitor water quality in the WDS itself. Various models have been developed to explore the reactions and interactions of relevant stakeholders during a contamination event including agent-based modelling. Furthermore, recent research has shown that water demands have significantly changed during the COVID-19 pandemic, and these changes can affect the operation and management of water infrastructure. In this study, an agent-based modelling framework is developed to explore social dynamics and reactions of water consumers and a utility manager during a contamination event, while considering a pandemic demand scenario. Furthermore, innovative response and recovery methods to a contamination event are explored for rehabilitating the water network after a water quality deterioration. Graph theory algorithms are used to place mobile sensor equipment for surveying the water quality in specific network parts, and the distribution system is clustered by the status of endangerment. The Bayesian Belief Network (BBN) was developed using survey data around risk perceptions and social distancing behaviour that were collected during the COVID-19 pandemic. The agent-based model (ABM) was developed using output from the BBN and water use data that were collected during the COVID-19 pandemic. The ABM is coupled with hydraulic simulation of the water infrastructure to evaluate changes in hydraulic performance. The model can be used to explore long and short-term consequences of the pandemic on water distribution systems’ management, design, and operations; develop and optimize strategies of how to deal with changes in around water distribution systems due to the pandemic; and investigate how resilient water utilities can cope with additional catastrophic events such as a contamination of a water system during a global or local pandemic related shutdown.

The water distribution systems (WDS) analysis focuses to develop optimal designs that allow implementation of water supply systems with quantity and quality needed for the human community consumption; therefore, it is necessary to characterize system topology and hydraulic variables. For identification of the most sensitive parameters involved in population density changes, three comparisons are presented related to (1) hydraulic gradient surfaces, (2) pressure surfaces, and (3) specific power maps. According with this, behavior patterns can be defined based on the networks’ characterization and alterations that may occur verifying minimum design conditions of compliance and operation. The results show hydraulic gradient surface changes are proportional to demand growth, highest and lowest pressure nodes remain same for near locations, and the spend energy tends to be constant when taking a relative percent difference.

The multi-objective design of water distribution networks (WDNs) is a very challenging task and can be addressed with evolutionary algorithms. Especially for large WDNs, such a process is very computationally demanding, and it is difficult to assess if the obtained solutions could be further optimized. In other words, due to the stochastic nature of evolutionary algorithm, it is not straighforward to recognize whether the solutions are optimal or further generations need to be processed. Characteristics of the network graphs could reveal the progress of the optimization process. For optimal WDNs, the primal graph characteristics and network patterns have already been explored. However, literature is missing a dual graph approach to investigate the properties of optimal WDNs in a dual space. Such a dual graph approach is developed in this work. Therewith, the trajectories of the optimization process from random initialization to the (final) optimal generation are described and systematically investigated. With that the answer to the question is successfully addressed: When is an optimal stage at the optimization achieved, and how can that be assessed and predicted?

Water distribution networks (WDN) need to be analyzed multiple times for optimal design. Analyzing WDN requires solving non-linear simultaneous equations. For this purpose, many algorithms and models are developed. By using these algorithms several simulators (both freely available and commercial) are developed for analyzing WDN. In this paper, by using the analogy between electrical and hydraulic networks, hydraulic elements such as pipes, meters, valves, and pumps are modeled in Verilog-A. The reservoirs are replaced with voltage sources and demands with current sources. An electrical freeware called QucsStudio is chosen for implementing the hydraulic networks. The applicability of the electrical simulator through Verilog-A coding to analyze realistic WDNs is demonstrated. EPANET simulation results are taken as reference values for accuracy verification of the proposed scheme. The electrical simulator is shown to be providing sufficiently accurate results in terms of heads at junctions and discharges through pipes. It is found that the electrical simulator takes less simulation time than the EPANET. Also, other electrical analysis techniques and equivalent electrical parameter extraction schemes (such as finding Thevenin or Norton equivalents, source and impedance transformation, etc.) can be easily executed using an electrical circuit simulator. Therefore, hydraulic engineers can use a circuit simulator using the proposed methodologies for quick analysis of WDNs.

Regulatory guidelines implementation for per- and polyfluoroalkyl substances (PFAS) is getting attention globally due to the rising concern about its presence in water sources, direct exposure, and toxic properties. The majority of the legal frameworks primarily emphasize perfluorooctanoic acid (PFOA), an anionic organic PFAS. Latest studies found polyfluoroalkyl amides (FA) as a central precursor to PFOA formation in aquatic systems and established the Hofmann-type rearrangement as the dominant PFOA formation pathway during the chlorination of zwitterionic/cationic FA. Intriguingly, higher PFOA concentrations have been identified in water treatment plants after disinfection also. Hence, there is a probability of transforming FA to toxic PFOA during delivery via water distribution systems (WDS). The PFOA formation in the WDS could become an indirect PFAS exposure source and a probable cause for acute and chronic health risks to the communities. We aim to evaluate the involvement of WDS as an exposure pathway for PFOA. We examined the kinetics of PFOA formation during chlorination in aquatic systems. The kinetic relationships were transformed into mathematical equations and were applied to develop an EPANET-MSX-based WDS quality model. Uncertainty analysis was incorporated into the mechanistic modeling using the Monte Carlo method. The data set obtained on model application to a real WDS was applied for human health risk assessment by calculating the daily intake of PFOA contaminated water using USA population parameters. Our study found the one to eight years old age group to be most susceptible to PFASs exposure beyond the tolerable limit of 3 ng/kg/day.

Imprecision and unpredictability in both future water consumption and pipe roughness coefficients in optimal design of water distribution networks (WDNs) are considered using fuzzy random variables for the first time in this study. The optimal design problem is defined as a two-objective optimization problem, with the objectives of minimizing total design cost and maximizing system performance. Dempster-Shafer theory of evidence is used to represent an acceptable degree of proof, i.e., a degree of necessity or belief. An efficient algorithm based on Monte Carlo procedure is developed to assess the fuzzy random system reliability and derive a Pareto front for optimal design using the cross entropy (CE) optimization. Two case studies are used to demonstrate the methodology. The results from both the cases indicate that the new methodology is capable of effectively accommodating and managing a variety of fuzzy and random sources of uncertainty and providing optimal design solutions.

Concerns about reducing greenhouse-gas emissions, and the requirements for improving the quality of service to customers, have driven energy water quality management systems (EWQMS) to be one of the top priorities for water utilities nowadays. Storage tanks and pump operation/scheduling have been instrumental in driving optimal energy cost and associated energy consumption operational plans and policies. However, recent successes in water conservation have raised the subject of water age as an issue in these systems. Therefore, we need holistic solutions to manage these operations and to mitigate possible water quality issues. In this paper we employed a multi-objective simulation-optimization model to handle the challenge between energy cost and water quality management in distribution networks. Variable speed pump (VSP)/tank flush scheduling were used to manage the network. Applying the procedure on an example showed that the VSP scheduling could not find reliable solutions (in terms of water quality) without the accompaniment of tank flush scheduling.

Water distribution systems’ (WDS) quality analysis is a complex exercise due to the many constraints and decision variables, the nonlinearity, the non-smoothness of the head–flow–water quality governing equations, and the inter-complexity of WDS behavior. Classically, the WDS quality models operate the time-series output of the hydraulic models, typically EPANET, as its time-series input. Apart from hydraulic input, the other inputs include contamination characteristics (location, type, and duration) and the equilibrium/kinetic relationships defining the reactions within the WDS domain. EPANET-MSX has now become a familiar tool for WDS quality modeling owing to its collaboration with EPANET. The challenging tasks in applying EPANET-MSX are conceptualizing the exchanges between WDS components and water quality parameters and evolving scientific descriptions of the water chemistry stoichiometric interactions. Besides, the EPANET-MSX application necessitates programming skills for successful implementation from a software engineering viewpoint due to its uneasy user interface. We aim to overcome these challenges of applying EPANET—EPANET-MSX for WDS quality modeling by developing EPANET-C, an umbrella simulation platform for simulating numerous accidental/intentional WDS contamination events. It employs a simple command-line interface and avoids the programming requirements almost entirely. EPANET-C synergizes EPANET and EPANET-MSX by employing the in-built and customizable directories of conceptual and mathematical models abstracting the physical, chemical, and biological reactions and designing the equilibrium/kinetic relationships corresponding to several possible WDS contamination scenarios. Due to its flexibility, EPANET-C can become a de facto standard tool in WDS quality modeling study for both the industry and academia.

Hydraulic-based optimization methodologies are reliable and computationally effective techniques to determine a least capital cost design in water distribution networks. Some of these approaches rely on the calculation of the optimal hydraulic gradient surface (OHGS), a geometrical body that establishes the way in which the available hydraulic head should be spent within a network to ensure the calculation of a minimum capital cost diameter configuration. Given its amorphous morphology, the fractal dimension can be used as a parameter to understand the mathematical and physical properties of the OHGS. In the present study, the OHGS of a variety of theoretical and real water distribution systems is calculated by employing the optimal power use surface optimization methodology. The fractal analysis is then carried out by an image fractal dimension estimator algorithm, including the examination of random non-optimal designs. Moreover, the fractal dimension of the topology, flow, and energy distribution of the optimized networks was also calculated by a box-covering algorithm and compared to the fractal dimension of the OHGSs. The results show that the energy dissipation pattern in an optimal design exhibits certain fractal properties that can be used to distinguish it from more expensive diameter configurations. In addition, it was found that the fractal properties of the OHGS and of the topology, flow, and energy distribution inside the studied networks are somehow related. These findings may be applied in prospective optimization methodologies, operational improvement, or renewal procedures.

Given the growth of urban population, water distribution networks (WDNs) are stressed and may lose hydraulic performance while supplying citizens. WDNs should be modified by civil engineering interventions such as water network rehabilitation, aimed at recovering the originally designed hydraulic performance. In this work, a set of expansion scenarios are evaluated under hydraulic (resilience, pressure uniformity, and water quality) and complex network (centrality, average shortest path) indexes for better understanding the impacts of demand increasing in a water network. This first analysis allows to map the risk of demand increases at each district metered area, resulting in more suitable regions for demand expansion. In a second step, rehabilitation of water network based on changes of main pipes is proposed. Structural interventions from the civil engineering point of view are proposed. Since each intervention results in economical costs as well as in recovery performance, solutions are also evaluated under hydraulic indexes, whose degrees of importance may be established by means a preference-based approach and feedback exchanges with experts in the field. In this context, a multicriteria technique is applied for ranking solutions, leading to a map of expansion-solutions for WDN managers. The complex network and WDN hydraulic analyses have been performed in Phyton programming and, respectively, by means of the packages NetworkX 2.5 and WNTR 0.3.0. TOPSIS multicriteria analysis method is lastly used to classify the expansion solutions.

This study presents the potential of hydraulic ram pumps in managing excess pressure and reducing energy costs in modern water distribution systems (WDSs). A hydraulic ram pump (or Hydram for short) is a cyclic water pump powered by hydropower, generally used to pump drinking and irrigation water in mountainous and rural areas having short of power. This study introduces Hydrams as a low-cost alternative solution in addition to the more conventional pressure reducing valves (PRVs) approach for managing pressure zones in WDSs. Unlike PRVs, where the pressure is lost and not put into good use, Hydrams mitigate excess pressure at high-pressure zones and direct it to much-needed low-pressure zones. In addition, Hydrams require little maintenance, are cheap, simple, and environmentally friendly. The proposed system integrates a Hydram in parallel to the original centrifugal pump, where they can be operated interchangeably according to the system’s hydraulics. Nevertheless, it is vital to correctly size the Hydram at the feed line and accompanying it with a storage tank at the low-pressure zone. The storage tank serves as a buffer between the intermittent water supply and consumer demand pattern. Moreover, the tank introduces flexibility into the system that allows more sustainable operating schedules. Two case study applications of increasing complexity are presented to demonstrate the potential of this approach. The Hydram and tank sizing is done by a simple heuristic approach, while the operation of the system is dictated by a genetic algorithm. The results demonstrate the potential of integrated Hydrams in reducing excess pressures and energy costs.

This study examines the destructive potential of the hydraulic transient in water distribution systems and the role it can play in future cyber-attacks. It demonstrates the use of hydraulic transients to induce great pressure spikes that will compromise the system integrity and disrupt water supply. The purpose of the study is to present a framework where distribution system vulnerabilities are analyzed for better protection against intentional pressure surges. The danger lies in the variety and simplicity of introducing sudden changes to the system, hence inducing pressure surges. In addition, pressure surges travel at high speeds (~1,000 m/s in steel pipes) and propagate throughout the network, thus exposing the whole system to extreme pressures. Therefore, a more thorough analysis of the network is done to examine the vulnerable components and give a better estimation of the network’s impregnability. The proposed method excites different transient events along the system and simulates the pressure surge response. The phases between the events can dramatically affect the pressure at different locations. Therefore, the optimal phases for achieving the highest pressure, that is the worst-case scenario, are examined. A case study application is presented to demonstrate the potential of this approach. The results demonstrate the destructive potential of a deliberate hydraulic transient that can cause severe damages and even put the system out of use.

Water distribution networks (WDNs) are comprised of various components interacting in a complex way. Minor disturbances in them, like a pipe failure, could trigger cascading events causing crucial impacts on the well-being of residents. Therefore, the resilience of WDNs under different failure modes needs to be proactively investigated to ensure that they can cope with disruptive events. This paper introduces a hydraulically informed graph-based approach (HGA) to assess the resilience of WDNs in case of pipe failures. The aim is to rank critical pipes without conducting any hydraulic simulations, solely utilizing topological features and mimicking hydraulic behavior. The suggested method focuses on resistance, capacity, and connectivity of pipes. The results of applying HGA to two networks show that more than 95% of critical pipes identified by it are all top-ranked in a hydraulic-based model. The proposed approach can be upgraded to combine multiple and simultaneous failures, which cannot be investigated in acceptable execution time with hydraulic models.

Air is present in pressurized water systems for a variety of reasons, including incomplete removal during filling, air entrainment at intakes or entrances, air admission during draining operations, or air exchanges due to transient events such as power failure or pipe burst. Each of these sources or events creates specific design and operational challenges, issues that often require thoughtful and sometimes expensive approaches to avoid serious upsets or accidents. Indeed, the design and operational challenges must collectively be blended to produce a robust and economical design that is valid for all foreseeable operational and emergency actions that might involve the presence of air, whether the air is admitted, expelled, or merely present in the flow system. This paper summarizes the key findings that relate to the presence of air in pressurized flow systems. The focus is on the available research and operational experience regarding the challenges and strategies for coping with residual air, for removing air, or for admitting air into the conveyance system. The emphasis is on practical recommendations but also highlights some of the key uncertainties that remain when dealing with the full range of design and operational challenges confronting those seeking to safeguard the long-term performance of pressurized water conveyance systems. One of the persistent challenges is to select suitable design events since the conditions a pipeline will experience over life are inevitably both highly varied and somewhat uncertain.

The purpose of a water distribution network is to supply the required water at sufficient pressures. Water requirement/demand at the nodes is uncertain and can vary erratically. The network design should be able to meet this variation in demand. In addition to this variation in demand, the network should also be resilient to failure. When there is some leakage in a pipe, the network should have surplus energy to meet the required pressure demands at nodes. A new methodology is proposed for the multi-objective combinatorial and discrete water distribution network (WDN) design under uncertainty problem. The proposed methodology uses a combination of popular robust-counterpart (RC) techniques to handle the uncertainty and a meta-heuristic named multi-objective cuckoo search algorithm to handle the discrete combinatorial search space. The uncertain parameter considered here is the nodal demands. The objectives considered for the problem are minimizing construction cost and maximizing resilience index. The proposed methodology is applied to the Hanoi water distribution network. The obtained designs are compared with the standard designs obtained without considering uncertainty. Furthermore, the effect of variation in the uncertainty set of the demands is also reported and discussed.

The formation of district metered areas (DMAs) aims to improve the efficiency of water distribution network (WDN) management. In recent times, this technique has widely gained attention of researchers and water utility engineers due to its ability to provide better operational control over system leakage, pressure management, and non-revenue water (NRW) related aspects. DMA formation involves closure of a few pipes to partially isolate areas (or sectors) to form single or multi-feed DMAs. In the latter, flowmeters are installed to monitor the inflow and outflows. This paper presents a multi-step methodology to identify DMAs based on a community detection algorithm in the first step. The second step focuses on boundaries fixation using a many objective optimization tool (NSGA-III algorithm). The economic criteria, water quality, resilience, and network pressure are simultaneously optimized to arrive at a set of feasible solutions. In the last step, a multi-criteria decision making (MCDM) tool is used to find a unique solution based on users’ preference of weightages assigned to different objectives. The methodology has been tested on a medium sized water network, and the results are discussed. It is found that the proposed methodology can reasonably identify feasible solutions to optimally partition the network into DMAs.

A water distribution system (WDS) comprises several uncertain parameters. This uncertainty makes the optimal management and design of a WDS a complex problem. Often parameters that explicitly affect water quality are ignored. The contaminant mixing at a junction is assumed to be uniform and instantaneous. Multiple studies prove this assumption wrong, and new water quality modelling methodologies are proposed. The exact computation of the mixing level is complicated and computationally expensive. This study focuses on obtaining the optimal treatment levels at the sources, assuming the mixing levels as uncertain/unknown. A robust optimization approach is proposed to handle this uncertainty. The proposed methodology is explained using an illustrative example 4 × 4 grid network. The objective of the problem is to obtain the water treatment levels at the sources to satisfy the water quality requirements at the demand nodes and be immune to variations in mixing levels at cross junctions. The results showed a significant variation in cost between complete mixing and non-uniform mixing. The obtained treatment levels were verified through Monte-Carlo simulations.

Water main deterioration is a global challenge which can jeopardize the ability of water systems to deliver clean water safely. A variety of factors can affect pipe breakage, yet previous research has focused on different subsets of data. The key objective of this study is to identify the most important factors in predicting water main failure across multiple Canadian cities. The study included data organizing, data cleaning, and dimensionality reduction analyses. Two approaches were applied to analyze the importance of factors affecting water main rate of failure, factor analysis of mixed data (FAMD) and random forest. Data from 12 water utilities across Canada were analyzed, containing information on pipe physical characteristics, historical information, protection activities, environmental factors, and operational condition. Available attributes were different for each city. Overall, the two methods rated failure month and protection as the most important factors. While random forest consistently found age to be the most important attribute, FAMD results indicated that either failure month or material was the most important factor. Random forest results were observed to be biased as they consistently rated numerical attributes as more important than categorical. Thus, FAMD results are expected to be more reliable. Future data collection should focus on pipe characteristics and protection activities. Next steps of the project will include conducting other dimension reduction approaches and running correlation analyses. Findings will support the development of a framework for pipe and break data collection. This will help water utilities develop cost-effective and accurate water main deterioration models, enabling more reliable renewal strategies for water distribution systems.

If some measurements of system reliability are not included, a least-cost optimization of a water distribution system (WDS) leads to a branched network. Utilizing network subsystems that provide an explicit level of system redundancy is one way to improve the performance of WDS networks. In this approach, the whole system is subdivided into two subsystem networks. Then, during the optimization phase, the two subsystems are simultaneously optimized so that each can provide some level of service to the consumer. Optimization results are ultimately determined by the pair of subsystems used. Unfortunately, there is little to no literature on the optimization of the selection of subsystems. The present study examines both the selection of subsystems and the optimization of the component sizes in designing a level-1 redundant network. Candidate subsystems are generated using graph theory where st numbering for the network is assigned first, and then the subsystems are generated following the decrement and increment orders of the node’s st-numbering. The optimization problem is solved using a genetic algorithm for backup selection and linear programming to compute optimal component sizes.

The study area is the lake located within the Karagöl-Sahara National Park, which is one of the important tourism regions of Turkey. This area, with its rich biodiversity and natural selection forests, is located in the Caucasus hotspot, which is defined as one of the 35 biodiversity hotspots in the world by the Conservation International. The aim of the study was to evaluate the water quality of Karagöl using the trophic state index (TSI) and multivariate statistical analysis. For this purpose, water samples were taken from six points on the lake surface from July to August in 2021. Water samples were taken from points where polluting factors are concentrated. Parameters measured to assess water quality are total nitrogen (TN), total phosphorus (TP), secchi disc (SD), chlorophyll (Chla), pH, electrical conductivity (EC), dissolved oxygen (DO), suspended solids, and turbidity. The index proposed by Carslon was used for the trophic classification of the lake ecosystem. This index is evaluated by considering the relationships between chlorophyll (Chla), total phosphorus (TP), and secchi disc depth (SD) for lakes. Relationships between data were evaluated using multivariate statistical analysis. Statistical methods used in the evaluation of data are principal component analysis (PCA). With the trophic status index, the water quality of the lake was found to be close to the mesotrophic level. As a result of the PCA analysis, it was calculated that two important factors are important in the lake water quality.

Water distribution systems (WDSs) function to deliver high-quality water in major quantities. While standard water quality parameters are monitored at waterworks, it is still a challenge to monitor water quality in the WDS network itself. Only hydraulic parameters are frequently monitored and modeled in drinking water networks in Germany. Moreover, the majority of German drinking water utilities does not disinfect when the product leaves the waterworks. This is also common practice in Northern European countries. It is thus important to monitor specific organic and bacteriological water quality parameters which define the system state. This study develops an experimental and simulation integrated framework for continuously monitoring and simulating selected organic and bacteriological water quality parameters, so abnormal deviations in water quality behavior can be detected and responded to in real time. A simple reproducible bacteria regrowth model was taken to initialize the validation of experimental values in a water quality model simulation. Batch experiment measurements from a flow cytometer are analyzed to establish an interface between laboratory values and water quality simulations. Monod kinetics are utilized to describe the bacterial growth rate according to the respective substrate for modeling the bulk species in the water network. Experimental values are incorporated in the simulations for validation. The simulation of bacterial growth is conducted firstly on a network model of a real-life test bed and on various selected distribution system models of different sizes and complexities. First results of the water quality simulations show a successful transition of experimental analysis into water quality simulations and give a promising outlook for developing an online-monitoring and prediction methodology for detecting water quality anomalies efficiently in real time.

Water quality-related issues are becoming a global concern due to the fast pace at which water bodies are deteriorating. The deterioration continues to worsen due to climate change, urbanization, and human activities. Several parameters affect the quality of water. One of such parameters is total dissolved solids (TDS) also known as salinity. It is estimated that salinity in the Colorado River causes close to $400 million in economic damages to the United States every year. This work aims to employ remote sensing techniques, which unlike in situ measurements have been proven to be economical and effective means of water quality monitoring. The overarching goal of the study is to detect salinity in the Colorado River using Landsat 8 Operational Land Imager (OLI) satellite data. The objective of this research was therefore to develop a mathematical relation between remote sensing spectral indices and TDS for the prediction of TDS concentration at the Imperial County Section, AZ-CA, of the Colorado River. Spectral indices were extracted from the satellite data using different 30 m resolution reflectance combinations within the ArcGIS Pro software. The study developed univariate regression for the spectral reflectance and indices and ground truth data of TDS. Both data sets were acquired from the United States Geological Survey (USGS). Results produced R² of 0.62 to 0.74 for different bands and indices. It was established through sensitivity analysis that one salinity index offers the best model for salinity estimations for the study area with an absolute percentage error of 1.76%. Results offer a possibility of using Landsat 8 OLI for the estimation of TDS in the Colorado River Basin (CRB).

Supplying high-quality water is the key task of water distribution systems (WDSs). Although in Germany and some other countries chlorine is no longer used, it remains as a major disinfectant in WDSs worldwide. Therefore, chlorine concentration represents an important parameter for determining the water quality; that is, we should ensure the chlorine concentration within a reasonable range in a WDS. However, due to the complexity of the network structure and nonlinear behavior of the system, the control of chlorine concentration in WDSs imposes a challenging task. In this study, a model-based optimal control strategy is developed to address this problem. The mass and energy conservation laws are used to describe the hydraulic properties of WDSs. The one-dimensional advective transport model is simplified to describe the decay of chlorine in the pipelines. The chlorine concentration limits at the nodes are formulated as inequality constraints which will be satisfied by manipulating the flows and their directions in the pipelines. As a result, a nonlinear optimization problem is formulated and solved to achieve the specified chlorine concentration. For verifying our approach, we deliver the computed results for benchmark networks as input to the simulation model in EPANET, and the simulation gives satisfactory values of the specified chlorine concentration in the network.

Guaranteeing the high-quality of water in water distribution networks (WDSs) is a priority when it comes to ensuring public health. Since the majority of German water utilities (and also other EU countries) do not chlorinate, controlling of nutrients in WDSs such as assimilable organic carbon (AOC) and monitoring of microbiological activities is indispensable. Conventional methods to characterize microbiological activity and dissolved organic matter are time-consuming and labor-intensive. This study presents data on flow cytometry and fluorescence spectroscopy as leading-edge technologies for real-time analysis of drinking water quality in WDS. Flow cytometry is a sensitive method which can be applied in online modus for accurate detection of bacterial cell numbers. Furthermore, fluorescence spectroscopy is a rapid and quantitative technique for detailed characterization of dissolved organic carbon (DOC) including fractions of natural organic matter (NOM). The integration of both techniques is promising for real-time water quality analysis and as a supporting tool for quality control. In the initial step of this research, an experimental laboratory setup of simultaneous analysis is developed. Thus, the goal is to achieve knowledge about possible relations between water quality parameters, more precisely bacterial regrowth potential and the character of dissolved organic constituents. In continuous measurements, the initial state of microbiological growth is to be determined based on flow cytometric data. Due to fluorescence spectroscopy data the microbiological regrowth potential will be predicted. This will be achieved by online detecting of certain organic fractions of the DOC which can be utilized as nutrients by present bacteria. The overall project goal is the establishing of an interface between monitoring parameters and water quality simulation models for the WDSs. First promising results show the successful utilization of adapted AOC as regrowth potential parameter, which can be used for water quality simulations in a WDS.

Circulation within the Mississippi River Delta region, including the Lake Pontchartrain Basin and Mississippi Sound, was investigated with a 3D numerical model (Delft3D-FM) that encompasses 500 km of shoreline from Texas to Florida. Besides the Mississippi River, with an average discharge of approximately 20,000 m³s^–1, several other major and minor freshwater inputs influence the region and are considered within the modeled circulation. The 2018 and 2019 modeled water levels and salinity, both extreme flood years for the Mississippi River, are validated against a suite of National Oceanographic and Atmospheric Administration (NOAA) and US Geological Survey (USGS) observations. Highly resolved estuarine bays and hydraulic connections with the Pontchartrain Basin and Mississippi Sound will allow for a detailed examination of freshwater residence times and freshwater provenance. Future directions for improving the model as a tool to provide unprecedented insight into the complicated circulation patterns of the Mississippi River Delta region are discussed.

Geysers in storm sewer systems occur due to the uncontrolled release of trapped air through dropshafts. This study presents an unsteady three-dimensional (3D) computational fluid dynamics (CFD) model to simulate the two-phase flow dynamics of geysers starting with partially filled dropshafts. The CompressibleInterFoam (CIF) solver of OpenFOAM is used in the geyser simulations due to its suitability for modeling two compressible and immiscible fluids. The successive mixing of air and water entering the dropshaft causes a reduction in the density of the air-water mixture. Also, the non-uniform and chaotic mix of air and water in the dropshaft may lead to small bursts in the dropshaft that may cause depressurization in the dropshaft. This, in turn, could lead to rapid changes in the velocity of mostly the air and in a lesser degree of the water in the horizontal pipe. The increase in the relative velocities of air and water inside the horizontal pipe causes the transition from stratified to wavy and ultimately to slug flow. This results in successive eruptions as a result of the blowout of slugs through the dropshaft. Besides providing insights into the geyser processes, the present study provides criteria for performing a computationally efficient numerical simulation of geysers.

The Hyperion Water Reclamation Plant (HWRP), operated by LA Sanitation & Environment (LASAN) within the City of Los Angeles, has gone through upgrades and different phases to protect the environment through sustainable practices and meeting stringent permit regulations. Aside from the proper primary and secondary water treatment, HWRP is currently implementing an advanced system with the goal to be 100% recycled water by 2035 as part of Los Angeles (LA’s) Green New Deal. For the plant upgrade and average dry weather capacity of 450 mgd, this will require a large input of electrical power in the future. HWRP is currently 100% electrically self-reliable (cogeneration) by the Hyperion Bioenergy Facility (HBEF), which was commissioned in early 2017 at cost of $170M. HBEF uses dual fuel (biogas and natural gas) to power two gas turbine electrical generators for the production of electricity on site amounting up to 27 megawatts (MW) of power generation and 70,000 pounds of steam per hour for solids digestion process. Biogas from HWRP is treated with vessels containing a special adsorption media to remove siloxanes, volatile organic compounds, and other impurities in the gas. HBEF incorporates catalytic oxidation and selective catalytic reduction systems for carbon monoxides and oxides of nitrogen emission control, respectively. The South Coast Air Quality Management District (SCAQMD) administers treatment plants’ USEPA Title V Air Emissions Permit. The NOx and CO limits are 18.8 ppmvd (12.60 lb/h) and 60 ppmvd (24.55 lb/h), respectively, which the HWRP has met. Four and half years of performance data, air emissions numbers of the two turbines, operations and maintenance (O&M) challenges, and future plant upgrading will be presented to elucidate LASAN’s renewable energy source.

Siphons are often used for releasing water by gravity, especially from shallow ponds. This paper investigates the hydrodynamic characteristics of the flow in a siphon under leakage (e.g., pipe puncture) and no-leakage conditions using the OpenFOAM Computational Fluid Dynamics (CFD) package. The volume-of-fluid (VOF) method was used to solve the air-water two-phase flow, and the standard k-ε model was used to model the turbulence. The CFD model was assessed using experimental measurements for the no-leakage condition. The simulations for the leakage condition focused on investigating the siphon flow break phenomenon as a function of leakage location. The results show the impact of leak position on the siphon flow break and the suitability of OpenFOAM for simulating the complex two-phase flow dynamics that occurs in a siphon.

Section 303(d) of the Clean Water Act requires US states to establish total maximum daily loads (TMDL) for water bodies that have been identified as impaired according to specific water quality criteria. Because enaction of this program is at the state level, the approaches to assess water bodies, identify impairments, and develop TMDLs can vary from state to state. While the technical aspects of generating TMDLs are well defined, an analysis of the variation of TMDL enforcement and the socioeconomic aspects that might influence state level programs are underexplored. This study seeks to fill this gap by analyzing the TMDL process across states to evaluate progress overall and determine how socio-economic factors may contribute to the process of developing and implementing TMDLs. To do so, data gathered from EPA ATTAINS database, including TMDL progress and impairment causes, were collected for each state and analyzed to assess spatiotemporal trends in monitoring, assessment, and implementation. To evaluate how these trends correlate with socioeconomic indicators, data was collected for each state including US Census data (e.g., gross domestic product, educational attainment levels, etc.) and regionalization (e.g., EPA region, climatic region, etc.). The study found that the percentage of waters that have been assessed within a state is negatively related to state land area while it is positively related to the percentage of population with bachelor’s degrees or higher. Optimized hot spot analysis done using ArcGIS shows clear spatial clustering in TMDL progress where the East Coast of the nation has completed a higher percentage of TMDL assessments (average of 74.2%) compared to the mid-southern states (average of 22.7%). These findings, among others, demonstrate the influence that socioeconomic and geographic influences have on the monitoring, assessment, and implementation of TMDL programs.

TOPMODEL is a widely used, physically based distributed rainfall-runoff model developed in the 1970s that has been used to model multiple watersheds from the Latin American sphere. However, to the best of our knowledge, it has not been applied in Peruvian watersheds. This contribution reports (1) the adequation of the particle swarm optimisation (PSO) for automatic calibration of TOPMODEL, and (2) the application of TOPMODEL to the Chillón and Cañete watersheds, Perú. The following metrics were obtained in the validation stage: Nash-Sutcliffe = 0.85 and Kling-Gupta = 0.87 (Cañete); and Nash-Sutcliffe = 0.79 and Kling-Gupta = 0.84 (Chillón). Under the light of these results, we believe that (1) PSO represents a reliable calibration method for TOPMODEL, which currently relies in the generalised likelihood uncertainty estimation (GLUE) methodology to that end, and (2) TOPMODEL successfully modelled the hydrologic processes at that study catchments at both daily and monthly basis.

Despite growing science and policy attention on “resilient cities,” spatially explicit estimates pinpointing the flood susceptibility of critical infrastructure (CI) are yet to be developed for US cities. CI including road network, water and energy distribution hubs, hospitals, fire and police stations can be highly vulnerable to flood inundation. Yet, the existing susceptibility estimates in US are confined to 100-year floodplains, which naturally overlook CI outside the pre-determined flood zones and largely underestimate the total magnitude of their susceptibility. This research aims to develop a new index capable of estimating and ranking flood susceptibility of CIs in any US city irrespective of the CI locations within or outside 100-year flood zones. Based completely on open-source geospatial data, the proposed approach first identifies potential flood inundation areas independently from historical inundation occurrences, and geomorphic landscape features including the height above nearest drainage, distance from stream, and curve number at 10-m spatial resolution. Next, a multi-criteria optimization process produces corresponding weighting factors to integrate these variables into a quantifiable index. The value of this index ranges between 0 and 1, measuring the relative magnitude of flood susceptibility across all CI (1 denoting the most susceptible CI) within the geographical extent of analyses. Initial validations with respect to remotely sensed inundation extents show good accuracy of the new flood susceptibility index. The results from a preliminary study on Houston, Texas, suggest that (1) more than 50% of highly flood-susceptible CI (index value greater than 0.5) are outside the known 100-year flood zone, and (2) flood susceptibility of a CI is not necessarily correlated with its proximity to a river. The approach and results presented here will pave a new way for fast, accurate, and economic policy decisions to effectively materialize the perception of resilient cities across the nation.

Many studies pointed out that applying wetlands to detain part of peak runoff would be a practical approach to mitigate floods. Since wetlands have a significant impact on flood mitigation, it is necessary to understand spatial distribution and maximum storage capacity of wetlands in a watershed. With the advance of earth observation technologies, high-resolution LiDAR-derived bare-ground digital elevation models (DEM) obtained from airborne platforms provide a great opportunity for researchers and engineers to understand the three-dimensional topographic condition at the watershed scale. As wetlands are a topographic feature, the three-dimensional LiDAR-derived DEM also can be helpful for identifying the locations of wetlands and further estimate their storage capacity. This paper presents a LiDAR-derived method for identifying the locations of existing wetlands and modeling their potential maximum storage capacity at the watershed scale. A rapid and accurate approach called deterministic topographic wetland index was used to identify the locations of existing wetlands. And the “filling-and-spilling” method was used to delineate potential maximum inundation areas at the locations of the existing wetlands. The potential maximum storage capacity of a wetland was determined by the estimated water storage capacity beneath the water surface plus the calculated volume above the water surface. The findings of this paper aim to demonstrate an efficient and accurate approach for potential maximum wetlands’ storage capacity estimation at the watershed scale, which further provides important information for flood mitigation.

In the last two decades, artificial neural networks (ANNs) have offered a valid alternative to physical modeling for river flow forecasting based on rainfall input, as testified by the numerous successful models in the literature. While there is noticeable heterogeneity in the range of applications, e.g., basin size, temporal resolution of the data, and neural network architecture, little effort has been made so far to systematically compare alternative modeling procedures on the same hydrological system, and among basins of different characteristics. The former could be helpful to establish a list of “best practices” when building data-driven ANN models for river flow forecasting; the latter could allow for a deeper understanding of the underlying hydrological phenomena, by detecting which information most improves model performance in forecasting flows and, therefore, is most relevant in the rainfall-runoff conversion process. By training and testing multiple ANN models for a range of basins in the state of Georgia (USA), with surface areas from tens to a few thousands of square miles, we systematically study the effects of (1) the spatial heterogeneity of past precipitation; (2) the length of the time-window of predictors and lead time for the forecasts; and (3) the basin size.

Recent research in climate science has highlighted the need to abandon stationarity, the use of past observations to predict future rainfall, for a new paradigm that is based on the concept of nonstationarity. This work used downscaled climate model results, including coordinated regional downscaling experiment, localized constructed analogues, and multivariate adaptive constructed analogs. Best models were selected using the interannual variability of climate extreme metrics by comparing model outputs to a historical data set. Using the peaks-over-threshold approach, depth-duration-frequency (DDF) curves were generated for five Florida climate divisions with rainfall durations of 1, 3, 7, and 10 days for two future periods of analysis at return periods of 5, 10, 25, 100, and 200 years. Change factors (CFs) were calculated by comparing the DDF estimates to Atlas 14 DDF data sets at 242 locations across Florida. CFs ranged from 1 to 1.6 indicating that extreme rainfall is predicted to be larger than what is currently provided by Atlas 14 stations.

Errata identify incorrectly published items and technical errors. This file contains errata that shall be used from their effective dates; the most recent effective date is 07 14 2022.