World Environmental and Water Resources Congress 2021: Planning a Resilient Future along America's Freshwaters

This paper presents the effect of hybridization of nanofiltration and reverse osmosis membrane on inorganic fouling potential of groundwater. A comparative assessment of three RO plants (using brackish groundwater) located in Delhi region (India) having permeate water flow rates as 12,000 L/h (RO-I), 3,000 L/h (RO-II), and 3,000 L/h (RO-III), respectively. The comparative assessment was performed on the basis of trans-membrane pressure (TMP), water recovery, pure water flux, salt rejection, and specific energy consumption (SEC). Samples were characterized as per Indian Standards for drinking water. RO-I showed overall better performance in comparison to other membranes. Inorganic fouling tendency of feed water of all the three RO plants was examined after employing ROIFA (RO inorganic fouling assessment) software. The results predicted by the software showed that the chemical nature of feed water causing scaling in all the three RO plants is sulphate type (with lesser amounts of silicates and phosphates). Lab scale experiments were performed to investigate the effect of hybridization of nanofiltration (NF) and RO membrane in different permeate and concentrate configuration on inorganic fouling potential of the feed water. Based on these experiments, it was suggested that hybrid membrane configuration will help to minimize the effect of inorganic fouling and improve the performance of the membrane system.

The study aimed to analyze desalination and water purification using modified double-slope passive solar still (MDSPSS). The MDSPSS technique promotes sustainability and minimizes energy consumption, chemical additives, and environmental impacts as compared to other conventional desalination processes. The performance of MDSPSS was evaluated experimentally and theoretically in terms of physicochemical parameters of water quality and productivity. An economic analysis was performed to assess the viability of the process. The experiments were conducted on typical days of June and December in 2017 to account for summer as well as winter conditions. The cumulative distillate productivity was about 8.21 L/day and 6.01 L/day at 1.0 cm water depth during the summer and winter seasons, respectively. The experimental results were compared with standard (water quality) values recommended by the U.S. Environmental Protection Agency and World Health Organization. The cost of the distilled water, as per the economic analysis over 15 years of use, is $0.009 and $0.027 per liter per kWh, respectively, with a currency conversion rate of ₹73.25 for every $, with a payback period of 99 days. The maximum (instantaneous) energy efficiency and overall energy efficiency of MDSPSS in this study are 26.18% and 10.12%, respectively.

In Indian industries, the wastewater reclaim-reuse-recycle practice has been prevalent since the last two decades due to acute water shortage as well as high cost of freshwater supply. This paper presents case studies of water reclamation projects in the textiles processing, automobiles, chemicals, and fertilizers industries, and the municipal sector where the author was involved. Reclamation requires affordable wastewater treatment and its hazard free sustained reuse. The Indian Reuse and Discharge Standards were revised upwards in April/May 2018 by the National Green Tribunal for the whole country with wide implications on the choice of treatment strategies, processes, and technology. This paper showcases the water reclamation plants in India. A 15 MLD textile processing ETP of Trident Group reclaims 10 MLD water, a 23 MLD STP of RCF Trombay recycles 16 MLD water; another 1.5 MLD auto industry ETP of Mahindra & Mahindra at Nashik recycles the whole quantity for non-potable reuse. The process and design engineers had to develop robust, consistent, and cost-effective process regimes including advanced bio-oxidation and membrane based processes like ultrafiltration and reverse osmosis followed by UV for disinfection. The wastewater characterization, selection of technology, and design of process units and project realization for water reclamation was a very rewarding experience. A few water reclamation cases from India are presented to showcase the successful management of challenges of water scarcity.

Stream depletion is defined as the reduction in groundwater discharge flux to a stream resulting from extraction from an aquifer that is hydraulically connected to the stream. Many states regulate the maximum permitted amount of stream depletion, which is typically specified as a percentage of the pumping rate. To demonstrate that a proposed extraction well will not exceed the allowable amount of stream depletion, analytical or semi-analytical solutions are often used. These assume that the applied pumping rate is continuous; however, pumping rates typically vary throughout the year, following a cyclical pattern of high pumping rates in the summer and low pumping rates in the winter. In this work, a new semi-analytical expression was derived to calculate stream depletion resulting from a cyclical pumping pattern. The results of this method were compared to calculations based on a continuous pumping rate equal to the mean value of the cyclical pumping pattern.

Unsaturated zone flow modeling is now being used increasingly for groundwater recharge estimation. Groundwater recharge has an important role in groundwater systems management. However, accurate estimation of it still remains one of the most pressing issues in the field of hydrogeology. Moreover, since groundwater recharge is usually spatially distributed over a landscape, a regional-scale investigation seems to be necessary. In this study, a regional-scale non-stationarity-based framework is proposed, which with the help of inverse modeling against flow data from a large-scale soil moisture monitoring network models water flow through unsaturated zone using a multiple 1D soil column approach and by applying the numerical model HYDRUS-1D, to investigate the spatial distribution of groundwater recharge. In this framework, the study region is discretized into cells, and simulation is implemented at all cells using interpolated input data. This interpolation includes spatial non-stationarity investigation of the input data and their regionalization implementing a non-stationary kriging approach. The required input data are prepared and statistically analyzed for a case study. Furthermore, a simulation is performed through four focused stations. The study area is the state of Oklahoma, USA, where a unique extensive large-scale soil moisture monitoring network, namely the Oklahoma Mesonet, with 120 active automated stations covering the state (at least one in each of 77 counties) exists. The results show an existence of a spatial variability in input data, which stresses the importance of a regional-scale investigation. Moreover, according to the comparison of the observed flow data with the results of the simulations, incorporating inverse modeling into simulations seems to be essential. With the rapidly expanding large-scale soil moisture monitoring, this study can be used for other regions where such monitoring networks operate.

In coastal and estuarine environments, runoff from the inland merges with ocean waters. During tropical storms or heavy rainfall events, the combination of fresh and brackish water in these environments may lead to disastrous compound flooding. We must effectively anticipate the behavior of these complex events to improve short- and long-term decision making that will reduce loss of life and property, increase community resiliency, and improve policy implementation and infrastructure design. Combined inland and coastal modeling would provide this necessary knowledge. However, we are only beginning to understand how to most effectively couple inland and coastal models to produce the highest accuracy in our model outputs. This research presents an initial investigation into how to effectively couple inland and coastal models to better understand compound coastal flooding. We utilize a case study to explore the relative importance of various modeling components. This research will provide practitioners and researchers with an overview of the facets to consider when modeling the hydraulics of compound coastal flooding.

A general wave module is developed based on the third-generation theories; it is then coupled to the current model SRH-2D to produce a resultant wave-current interaction model named SRH-Coast. The new model is developed for applications in the coastal and estuary areas. Key features of SRH-Coast include (1) solution of the multi-frequency, multi-direction wave action balance equation; (2) adoption of the latest third-generation terms for the physical processes of the wave dynamics; (3) use of a single mesh for all modules; and (4) a tightly coupled approach. In this paper, governing equations, relevant theories, and numerical methods are presented. The focus is on the model verification and validations. Specifically, complex physical processes such as the wave-induced along-shore currents are simulated and discussed. Model verification is accomplished through comparison with analytical and laboratory data.

The velocity of flood flow in a river channel is a key hydraulic parameter for the engineering design of streambank stabilization. Two-dimensional (2D) numerical hydraulic modeling was performed to calculate flow velocities for a bank stabilization design in a study reach of the West Fork White River (White River) in Morgan County, Indiana. The 2D modeling results informed the engineering design by evaluating peak flow velocities under both existing and proposed conditions. Local peak velocities obtained from the 2D model were significantly higher than velocities obtained from a 1D model, which can significantly affect engineering design.

Aging infrastructure together with an increasing rate of extreme motivates many U.S. state departments of transportation to perform risk prediction and resource allocation analyses. However, such assessments are seldom validated with actual bridge collapse data. In this study, regional and peak flow conditions of 42 bridge collapse sites are derived and analyzed to assess the robustness of a risk assessment framework based on HYRISK, a model developed by the U.S. Federal Highway Administration to assess bridge collapse probability. HYRISK’s scour vulnerability and overtopping frequency risk factors are particularly assessed. Results suggest that risk assessment is not robust unless the analysis is specific to the (1) physiographic region’s intrinsic scour risk, and (2) hierarchy of flow data for a heavy-tail distribution. The findings can be included in asset management systems to help state departments of transportation prioritize resource allocation in maintenance and replacement to reduce hazard risk.

Scour processes downstream of hydraulic structures are challenging problems in hydraulic engineering. Many studies were carried out in the past, and others have been recently conducted to assess the effects of hydraulic and geometric parameters on the scour phenomena caused by plunging jets. However, to the best of the authors’ knowledge, there are no studies dealing with jet-driven scour processes under unsteady flow conditions. Therefore, the aim of this paper is to contribute to fill this gap of knowledge, presenting a preliminary analysis of the static equilibrium configuration (i.e., the equilibrium morphology when the jet action ceases). To this end, we conducted an experimental campaign varying jet discharge during each test. More specifically, for unsteady tests different hydrographs were simulated. In addition, reference tests were conducted under steady flow conditions. We found that static equilibrium configurations under unsteady flow conditions are significantly different from the reference counterpart (i.e., under steady conditions). Namely, both the water depth and the characteristics of the inflow hydrograph influence the static equilibrium morphology. In this regard, it is worth mentioning that under unsteady flow conditions and for low water depths, the scour hole is deeper than the reference tests. The opposite occurs for higher water depths. Overall, our preliminary analysis provides interesting insights on static scour features caused by plunging jets under both steady and unsteady conditions. Nevertheless, further analyses are required to assess the effect of jet characteristics on the dynamic equilibrium morphology.

There is a constant need or demand for U.S. Army Corp of Engineers (USACE) infrastructure to be more resilient and cost effective with respect to maintenance. USACE Engineering Research and Development Center (ERDC) has worked with Rijkswaterstaat from the Netherlands to build fiber reinforced polymer composite miter gates. ERDC can develop composite gates and other components on water control structures at locks and dams. Thus, the Jacksonville District Office of USACE performed a charrette to explore using composites and/or steel to repair and/or replace the 60-year-old sector gates at St. Lucie Lock. The results demonstrated that composite type sector gates were the best alternative to replace those sector gates due to their resiliency and lower costs over a 100-year period of life. This paper and the corresponding presentation will show some of the benefits of using composites and how it would eliminate some maintenance issues with respect to corrosion and cathodic protection, thermal expansion, and painting, etc.

Flooding causes the United States close to $8 billion a year. It can result in property damage, loss of life, and damage to the ecosystem. Oftentimes when houses and other infrastructure are built in places of high flooding potential, contractors need to follow specific building requirements in order to mitigate potential damage. Cherry Creek Dam is a man-made body of water located just southeast of Denver, Colorado. The dam was built in 1950 to prevent flooding from the South Platte River floodwaters, and since then it has not flooded. However, modeling has not been done to evaluate the effects of a probable maximum precipitation (PMP) storm, used to estimate a probable maximum flood (PMF). If such a storm would occur, it would be important to understand where the flooding would occur and to what extent. SRH-2D is a software program which can be used to model potential flooding. In this study, a research is designed to use SRH-2D to evaluate the flooding under PMF condition and subsequent breaching of the Cherry Creek Dam. Using the model results, future damage can be prevented through preparation and proper infrastructure standards.

Boulder placement is a common method to improve instream degraded habitats. Studies have shown that using boulders, if properly placed, can provide eco-friendly habitats for fish and other aquatic organisms by increasing spatial flow heterogeneity within a stream. This study assessed the effects of boulder placement on the ecological performance of a stream through evaluating habitat quality metrics. Experiments were performed in a gravel-bed flume with and without boulder placement at low and high flow rates. Metrics M₁ and M₂, representing spatial changes of kinetic energy, and M₄, as an indicator of flow recirculation in the horizontal plane, were calculated for each scenario, and their possible effects on habitat quality were discussed. High M₁ and M₂ values were observed around boulders, specifically in the wake of the boulders. Metric M₄ indicated that boulder placement at a low flow rate resulted in the most hydraulic complexity, which may be beneficial for fish and other aquatic organisms. The results can be used to improve stream restoration projects with boulder placement from a habitat quality point of view.

The world’s largest freshwater estuary, Green Bay, was a pristine habitat for centuries. The development of manufacturing industries in the area caused widespread pollution and natural habitat loss that resulted in the designation of the Lower Fox River and the Lower Green Bay system as an area of concern (AOC) by the International Joint Commission of Canada and the United States. The world’s largest polychlorinated biphenyls (PCB) cleanup and habitat restoration projects took place in the Lower Fox River. Lower Green Bay receives flows and sediment and nutrient loadings from five major tributaries: Fox River, Menominee River, Oconto River, Peshtigo River, and Duck Creek. Previous studies showed that most nutrient inputs to Green Bay are delivered by the Fox River—estimated to be approximately one-third of the total nutrient loading to Lake Michigan. The authors previously investigated loading impacts from the two largest tributaries to the bay, namely the Fox and Menominee Rivers, using the Finite-Volume Community Ocean Model (FVCOM), an unstructured-grid, free-surface, three-dimensional circulation model. This study investigates the impacts of the inclusion of the additional tributaries Oconto River, Peshtigo River, and Duck Creek on the Green Bay circulation and thermal regimes.

Siphons are often used to release excess water from impoundments such as lakes. They eliminate the use of pumps, which save energy and provide consistent water level control. However, it is often difficult to determine the actual flow rate at different stages of a siphon cycle. Field condition, storm type, and design criteria play critical roles in major and minor loss components of an active siphon system. A calibrated model thus can be useful to evaluate the performance of a siphon. Therefore, the objective of this study is to estimate the flow rate through a lake siphon system via three-dimensional modeling. Spencer Creek Lake in West Tennessee is chosen for this study, which is monitored by a water level sensor at the lake and another near the siphon outlet. The lake level data are simulated in the Ansys-Fluent package for steady flow conditions at various stages of the siphon operation. It reveals the associated flow physics of the siphon operation. Therefore, sources of loss at different sections of the siphon system can be identified to correlate with the discharge. Finally, the predicted outlet discharge is compared to the flow rate at the outlet channel. The successful calibration of the siphon system would allow the lake operators to estimate siphon release at different stages of an active siphon cycle and provide the knowledge to design more effective siphons for other lakes in West Tennessee.

Climate change and urban growth have resulted in unpredictable flood events throughout the world in recent years. The impact of the flood has physical and social consequences that include loss of life, property, destruction of agriculture, and infrastructure. A flood event in New Mexico in September 2014 had severe damages and deaths due to the fragments of Hurricane Norbert and Odile. To assess and map such disastrous flooding events, HEC-RAS, with the ability to simulate open channel hydraulics and other hydraulic structures, was utilized in this study. HEC-RAS provides 1D and 2D steady and unsteady simulations to develop a robust model, which mimics the actual flood event. In the current study, HEC-RAS 1D steady model as well as HEC-RAS 2D unsteady model was developed to perform flood simulation of the 2014 flood event in Pecos River near Malaga in New Mexico. The comparison of steady and unsteady flood models showed that the unsteady model could be more realistic, as it is time-dependent, which needs a flow or stage hydrograph as an input. The steady flow model is best to use when the hydrologic streamflow routing is accurate and gives reliable flow data. Furthermore, comparing 1D and 2D flood models, the 1D model just recognizes the geometry of the floodplain at some isolated places throughout the main channel, while the 2D model takes the landscape as a constant surface. Therefore, the 1D flood model performs better if the flow is mainly longitudinal, laminar, and the elevation data is limited.

Extreme flood events have become increasingly common and unpredictable throughout the world in recent times. Mississippi River, located in the Upper Mississippi River Basin, has instigated many historic floods in the Mid-West, of which the flooding of Davenport, Iowa, in 2019 is a major one. Due to the disastrous flooding events, the loss of the economy is increasing in the city of Davenport. This study focused on flood frequency analysis and floodplain inundation mapping of different flood events of Duck Creek in Davenport. Gumbel distribution, generalized extreme value (GEV), and Log Pearson III were utilized for the frequency analysis, and the distribution with the best fit was evaluated by utilizing the Kolmogorov–Smirnov (KS) test. Using the Civil Geo-HECRAS created by the CivilGeo team, flood plain inundation mapping was prepared for the 2019 flooding event at different recurrence intervals. For the analysis, the terrain data and historical flow data were extracted from the United States Department of Agriculture and the United States Geological Survey website, respectively, available in the Civil Geo-HECRAS interface. The model was calibrated and validated using different flooding events. Then, the results were compared with the Federal Emergency Management Agency flood extent map. The developed flood inundation maps suggest that the residential areas located along the banks of the Duck Creek are certainly at the flood risk zones and thus require flood management measures. This study will be helpful for effective floodplain management of extreme events and would be beneficial for sustainable urban planning.

Small dams provide water storage, flood protection, and ground water recharge for water scarce countries like Pakistan. However, damming up water may pose some risks to population dwelling downstream the dam. Hence, it is vital to study the impact of dam failure beforehand. Different types of physical and numerical modeling are used for it. The availability of high end computers, digital elevation models, topographic survey data, and multi-dimensional (1D, 2D, and 3D) numerical solvers have enabled water resource professionals to perform hydrological and hydraulic modeling efficiently and accurately. In this study, a two-dimensional unsteady flow modeling was performed using HEC-RAS for Aripir Dam, a small recharge dam to be constructed in Lower Kohistan, arid region of Sindh. Hydrograph of 100-year return flood period was produced through hydrological modeling using HEC-HMS. Dam overtopping and piping breach were modeled. Four cases (i) no breach (flood peak routing spillway operational); (ii) dam break with piping breach; (iii) rainy day dam break; and (iv) sunny day dam break were modeled. In overtopping cases, breach parameters were calculated using MacDonald method. Piping breach modeled in Case (ii) triggers as reservoir level reaches HFL of Case (iv). Flood propagation transects were digitized after analyzing 1-h flood extents of Case (i) and Case (iii). Different results including maximum flood inundation maps, flood propagation maps, population at risk maps, and depth × velocity map to identify hazardous and life-threatening zones were produced. Model also predicted breach hydrograph for each case: (i) 11,665 cfs; (ii) 18,536 cfs; (iii) 24,154 cfs; and (iv) 17,642 cfs. Rainy day breach Case (iii) is predicted to be the most disastrous event.

The Isleta Reach of the Middle Rio Grande spans about 42 miles from Isleta Diversion Dam to the confluence with the Rio Puerco. Analysis of spatial and temporal trends in channel geometry and morphology are reported. Hydrologic and hydraulics have been dynamic over the past century. The mean annual discharge has decreased since the 2000s, and the suspended sediment discharge has been declining since the 1970s, resulting in channel degradation. GIS analysis of aerial photographs and maps dates as far back as 1918 showing geomorphic changes; the current channel is less than one-fifth of what it was in 1918. There is also a slight increase in depth, velocity, median bed grain size, and sinuosity (channel length/valley length), while the slope decreased from 1972 to 2012.

This paper presents the hydrologic responses under climate change scenarios over a large river basin, Upper Narmada River Basin (UNB), India. Narmada is one of the longest western flowing rivers of India that fulfills the water requirement of Central India. In this paper, a semi-distributed hydrologic model soil and water assessment tool (SWAT) is used for estimating the future hydrological components under changing climate. Model is fine-tuned and validated by observed discharge data. In order to assess the impact of climate change, regional climate models (RCMs) from Coordinated Regional climate Downscaling Experiment (CORDEX)–MIROC5 and MPI-ESM-LR are used to simulate the water balance components. The hydrological responses of the basin were simulated under historical (1971–2000) and future climate (2071–2100) scenarios, considering the Representative Concentration Pathways (RCP) 4.5 and 8.5. Climate data were bias corrected before coupling with hydrological model.

Regional flood frequency analysis (RFA) is widely used for reliable estimation of extreme hydrological quantiles and for flood prediction at ungauged locations. The index-flood method, one of the most popular approaches for RFA, is based on the assumption that flood records are identically distributed in a homogeneous region. However, climate and land-use changes can alter flood characteristics, thereby questioning the assumption of stationarity in RFA. In this study, we employ non-stationary index-flood-based RFA technique considering a mathematical formulation for flood estimation in Maharashtra, India. We first choose sites with sufficient flow data thereafter; sites with trends are detected by Mann-Kendall test, followed by employment of region of influence (ROI) approach to identify homogeneous regions. Time varying quantiles are obtained, which reveal that considering a stationary over non-stationary analysis can lead to over(under) estimation of flood quantile for sites marked with decreasing(increasing) trends in the magnitude of floods.

Improving the resilience of stormwater conveyance networks to handle not only normal conditions but extreme ones is a vital step towards a sustainable urban water infrastructure. Although various reliability and resilience boosting paradigms have been broadly introduced and described, few attempts have been made so far to systematically investigate how different pipe-sizing intervention strategies affect the resilience of stormwater networks. To address this gap, two hydrodynamic modelling-based automatic designs alongside a steady-state one (i.e., rational method) are implemented using six storm design events. Further, a novel network graph-based approach is employed in this study to determine rational formula’s components. The proposed framework is applied to a real-world stormwater network. The results indicate that pipe sizing the stormwater network with the rarer events (e.g., over 20 years) under surcharge allowance reveals remarkable cost savings while leading to marginal differences in resilience in comparison with the other design methods. This study can be served as a generic framework for decision-makers to evaluate the trade-off between resilience and different design techniques.

Extreme rainfalls of short time scales are usually required for the design of urban infrastructure. These data, however, are often limited or unavailable at the location of interest, while those for the daily scale are widely available. Hence, an improved method for modeling of extreme rainfall processes over a wide range of time scales is necessary so that short-duration rainfalls can be estimated from those of longer durations. Scaling models such as the scaling Gumbel (GUM) and generalized extreme value (GEV) models have been proposed for addressing this issue. These models are based on the scale-invariance properties of the ordinary moments or non-central moments (NCMs) of the observed extreme rainfalls. However, the probability weighted moments (PWMs) have been known to provide more robust estimates of random variables for small sample sizes. The present study introduces therefore a PWM-based scaling GEV distribution (GEV/PWM) model. Results of a numerical application using historical rainfall records from a network of 74 raingauges located across Canada have indicated that the extreme rainfall estimates given by the GEV/PWM model are the most accurate as compared to those given by existing scaling models such as GEV/NCM, GUM/NCM, and GUM/PWM.

The smart rain barrel (SRB) represents a micro storage developed as an IoT-based solution for advanced rainwater harvesting, consisting of a conventional rain barrel and a remote controllable discharge valve which enables novel ways of operation. To overcome the limitations of small storage volumes, high-resolution weather forecasts are used to increase detention volume, whereas ensuring a sufficient collection of rainwater for irrigation purposes. The aim of this work is a model-based upscaling to investigate the effects of a hypothetical retrofitting of SRBs on an existing urban water infrastructure (drainage and water supply system) of an Alpine municipality with 2,900 inhabitants. Therefore, the open source software “Smartin” was developed integrating Python packages for SWMM5 and EPANET2 into a coupled model. The results show that already a simple control strategy can clearly improve the integrated system performance (e.g., reduced combined sewer overflows and drinking water demand) compared to uncontrolled rain barrels.

Citrus production is one of the most important agricultural activities in Sicily. Consequently, it also implies significant water consumption. Considering semi-arid climate of the island, it is also prone to droughts, and some areas suffer water scarcity problems. Climate change may also exacerbate the frequency of water shortages; hence, for adaptation, it is fundamental to improve irrigation efficiency. Various technologies are emerging to this aim: installation of tensiometers and flowmeters to compare water needs and consumption so as to suggest a correction of irrigation amounts. Unmanned aerial vehicles (UAVs) mounting thermal or multi-spectral cameras may allow also a rapid assessment of the plants’ stress potentially due to the need for irrigation. In this paper, we illustrate the results of preliminary research aimed at understanding whether multi-spectral images can be useful for monitoring plants’ stress in citrus orchards. In particular, images were acquired through a commercial drone, the Parrot Bluegrass, mounting the Sequoia multi-spectral camera. The four-band images have been combined to obtain several vegetation indexes (VIs): the normalized difference vegetation index (NDVI), the Green NDVI (GNDVI), the leaf chlorophyll index (LCI), the normalized difference red edge (NDRE), the structure intensive pigment index (SIPI2), and the modified chlorophyll absorption in reflectance (MCARI). The maps of the indices were pre-processed in GIS to obtain single averaged values per tree. Results show that the following indices are more suitable for identifying differences in the health of orchards: NDVI, GNDVI, and SIPI2. These three indices may help identifying areas of the orchard that received a surplus or a deficit of irrigation water, or other causes of stress, finally improving orchard management and, possibly, irrigation efficiency.

Numerical techniques offer various tools that can be used to observe the relationships between crop water requirements and the variables that contribute to the plant intakes. These variables range from meteorological to field level physical conditions. Field conditions, specifically soil type and soil moisture level in the root zone, are important to consider for quantifying crop water requirements. If total soil moisture (TSM) curve over a period of time can be constructed, the curve can be used to calculate the rate of change of moisture level in the root zone. This rate of change of soil moisture in the root zone offers the basis to calculate the plant water intake (PWI) if the water percolation rate is known or estimated. The calculated PWI can then be correlated with the meteorological variables including evapotranspiration (ET), air and soil temperatures, solar radiation, wind speed, and relative humidity to observe the relationships. Multilinear (MLR) and nonlinear (NLR) regression models have been developed in this study to observe the correlation between PWI and the weather variables. A brute force method was applied to identify the number of combinations to observe the lag and cumulative effects of weather variabilities. Total 1,211,040 combinations for MLR and NLR models were run to observe different impacts on PWI. Results show that some of the weather variables are highly correlated with the PWI at lower lag days. As the lag day increases, the correlation decreases; and after a certain number of lag days, the correlation does not change. Results also show that the correlation increases with the increase of number of independent variables in a combination to predict the PWI. The approach was applied to an olive field at the University Agricultural Lab (UAL) located at California State University, Fresno.

Flow measurement is an essential component of modern irrigation delivery systems. As irrigation districts undergo modernization efforts, it can become necessary to install flow measurement devices in non-traditional applications. Some applications feature a combination of characteristics that make traditional flow measurement structures unsuitable. Furthermore, as new regulations obligate many districts to report real-time diversions, installing redundant flow measurement devices that use different methods or technologies has become necessary to reduce the potential for temporary gaps in diversion data. In these cases, non-contact type flow measurement devices may be of interest. Two non-contact flow meters were installed at different irrigation district canals. Data were collected from the non-contact meters as well as pre-existing flow measurement devices operating in parallel. In addition, intermittent current metering was conducted at each site and used as the standard for calibration purposes. This paper presents an analysis of the flow measurement data collected and a discussion of the non-contact meter performance in open channel irrigation system applications.

ITRC tested a range of flow meters installed in various pipeline conditions replicating realistic installations to provide flow measurement accuracy data. All testing was performed at the ITRC Water Resources Facility. The devices tested were from various manufacturers and included portable saddle-style insertion magnetic flow meters, adjustable depth insertion magnetic meters, spool-type full bore magnetic flow meters, and saddle-type insertion propeller flow meters. Each testing condition was designed to replicate a realistic flow meter installation, providing accuracy values that could be expected from actual installations. Most of the tests performed had device accuracies within ±6%, including many within ±3%.

Stormwater management practice (SMP) effectiveness was investigated under future climate scenarios in Sandy Run, an intermittent stream near Roychester Park, Abington Township, PA. Precipitation and temperature were adjusted using EPA’s SWMM-CAT to reflect hot/dry, median, and warm/wet scenarios in the near (2020–2049) and far (2045–2074) future. Parcel-scale SMPs (rain gardens, rain barrels, and disconnected impervious surfaces) and neighborhood-scale SMPs (infiltration basins and vegetative swales) were modeled using CHI’s PCSWMM. Results suggest future precipitation rates and total volumes will increase up to 10.0% and 11.2%, respectively. However, future evaporation rates are predicted to increase up to 18.7%. This combination results in little change in predicted SMP performance. Future median peak runoff rates vary with climate scenario and are predicted to be 0.75% lower (hot/dry) to 0.65% higher (warm/wet) than predicted under historic climate. Future median total runoff volumes are predicted to be between 2.5% lower (hot/dry) and 0.6% higher (warm/wet) than predicted under historic climate.

Low impact development (LID) or green infrastructure (GI) systems are stormwater control measures (SCM) designed to mitigate the adverse impacts of urbanization by mimicking the pre-development hydrology, restoring the natural flow regime, and enhancing the water quality. The performance of these systems is highly variable and dependent of the design parameters and local conditions. A full-scale LID testbed was implemented at the University of Texas at San Antonio (UTSA) to conduct a comparative evaluation of three different LID designs operating under same conditions. The LID testbed is composed of six parallel cells including a sand filter basin and two rain gardens with two different biofiltration media: (1) the regional standard biofiltration media, and (2) an innovative custom blend with use of limestone sand in the mixture. The LID designs are tested in duplicates—with and without impermeable liner—to investigate the potential impacts of the direct infiltration on water quality and aquifer recharge. To simulate the hydraulic and treatment performance of the LID testbed, a stormwater management model (SWMM) was developed, calibrated, and validated using the field monitoring data. The model was used to assess effectiveness and sensitivity of each LID control under changing climate. Specifically, this study evaluated the ability of each LID control to mitigate the alternations brought by climate change in hydrologic terms and the treatment of total suspended solids (TSS). Design recommendations were elaborated in order to better mitigate the impacts of urbanization and future climatic changes accordingly.

Microplastics (MPs) are considered emerging contaminants of concern in surface waters. To date, several monitoring studies have reported the presence of MPs in surface water systems, including beaches, waters, and sediments. The harmful impact of MPs on aquatic and marine life has been well documented. Several studies suggested that inland litter transported via stormwater runoff is one of the primary sources of plastics in surface water. Recent studies to quantify the number of MPs in urban stormwater have applied traditional stormwater sampling methods and NOAA methods for analysis. In this paper, we present a critical review of applying existing sampling and extraction methods for MPs in stormwater and present our experience with adapting and revising methods intended to accurately quantify MPs and optimize the separation process. Three designs of metal strainers were built and tested, and the best design was placed in storm drains to collect stormwater samples. Existing methods for soil and sediment analysis suggest wet oxidation prior to density separation; this results in using large volumes of hydrogen peroxide. In addition, stormwater samples could be rich in grass and other organics that are not readily decomposable. A step was added at the beginning to separate floatables and reduce the sample amount for oxidation. This paper tested the efficacy of using a semi-automated mixing to fasten the extraction process and reduce the possibility of losing bio-fouled plastic particles. The paper will also discuss the challenges of laboratory analysis and separation.

651 flooding tweet locations along with dates and times were extracted using publicly available data on Twitter for Allegheny County, Pennsylvania. The flooding tweet locations were then used to perform statistical analysis of the data. Results indicated that approximately 70% of the flood tweets were spatially located in the southern half of the county. The locations were compared to existing FEMA flood zones, and it was determined that 55% of the flood tweet locations were outside designated flood zone areas. The majority of the flood tweets occurred between the months of May and September, indicating flash flooding by heat-induced thunderstorms is likely. This hypothesis was tested and confirmed for flood tweet locations within the Saw Mill Run watershed in Allegheny County with 15-min high-resolution radar rainfall data. Rainfall distribution patterns were calculated for the flood events in Saw Mill Run, which can be used for future planning and design efforts.

Although there are different types of flood risk assessments, methodologies, and goals, the framework behind them follows a similar standard, from defining a scenario and acquiring specific basic data to obtaining key flood hazard parameters. Ground measurements, remote sensing analyses, and hydrological modeling are the current tools applied in flood hazard assessment. These classical tools present some specific constraints related to their intrinsic characteristics of the context of the application. For ground data acquired by different instruments, spatial and temporal coverage is a great challenge, both in terms of data processing costs and a representative’s maintenance. As for hydrological modeling, it is very sensitive to the quality and quantity of input data, affecting the results’ acceptability and accuracy. Moreover, the absence of comprehensive watershed data such as details of drainage systems can complicate the watershed modeling process, especially when trying to simulate or predict extreme events in unique locations. In this study, we modeled an urban watershed response to 2- and 5-year return period rainfall events by using basic, existing data and applying a physically based, spatially distributed urban watershed model, PCSWMM. To pursue these questions, participatory research was applied in a low-resourced community in the City of Paternò, in Sicily, Italy. We collected as unbiased as possible information about pluvial flooding events through 207 surveys. The locally gathered data were compared to the advanced hydrodynamic model results to explore this type of model’s challenges and shortcomings at a large city-scale. Finally, we discuss the opportunities to improve urban pluvial flood modeling at the small-scale through community engagement in data collection and characterization of urban watersheds. Instead of handling the modeling at a large scale, we can identify priority areas and, consequently, have better modeling by focusing on small scale watershed modeling and capture related details.

The availability of clean water in the Middle East for sustaining environmental, economic, and society demand is drastically reducing, due to the escalating growth of population, developing economies, and consequence of climate change. Iraq (Mesopotamia) is one of the main countries which are currently witnessing a dramatic change in the quantity and quality of the rivers’ waters. The Tigris and Euphrates are the two main rivers in this area; they are the source of life for this land to develop agriculture, industry, and human life. This research aims to identify the impact of the regulator dam (Kut Dam) on the water quality of the Tigris River. These techniques based on long term data for the flow and water quality measurements are available in stakeholders’ database. The results showed that these types of barriers have a low effect on changing the water quality of the river downstream.

The rate of salt transport from an unstable source into the underlying porous media containing fresh or brackish water was determined by experiments and then verified through numerical solutions. The rate of mass transport was determined through four experiments, conducted over 9.0–14 days, using a rectangular plexiglass model (1.82, 0.61, and 0.61 m). A finite mass of “source” solution with a saltwater concentration of 36 kg/m³ was placed over a saturated porous media containing freshwater or brackish water with salt concentrations of 9.0, 18, and 27 kg/m³. A three-dimensional numerical model SEAWAT was used to determine the rate of mass transport under the experimental conditions. The numerical solutions showed a good match with the experimentally determined rates of salt mass transfer. The apparent dispersion coefficient values used in the numerical model ranged from 4.05 × 10^-09 to 1.26 × 10^-08 m²/s. The analysis showed that there is a direct linear correlation between the apparent dispersion coefficient and the difference between the initial source concentration and porous media concentration. The percentage salt mass transported from the source into the porous media after 1 day was found to be 42.9% when the porous media contained freshwater, and 27.0%, 13.6%, and 3.9% when the porous media saltwater concentrations were 9.0, 18, and 27 g/L, respectively. These results show that a significant amount of salt may transfer from the finite unstable source, such as an estuary, into the underlying aquifer under some conditions, and this knowledge could be important in maintaining the estuary salt balance.

In the recent past, Pakistan’s economy has suffered due to a shortage of electric power. To shorten the production and demand gap, coal reserves in the Thar region of Pakistan are being utilized. During the process of mining, a huge quantity of saline water is being pumped from the mining site to a natural depression called Gorano Dam. This study examines the impact of saline water on land cover in the area. Two scenarios including pre-disposal conditions (February 2017) and existing conditions (February 2020) were compared. Sentinel-II images with a spatial resolution of 10 m were classified using the maximum likelihood supervised classification method. This study also determines the spatial and temporal variation of total dissolved solids (TDS) in the Gorano Dam. Water quality samples were collected to measure TDS. Landsat 8 OLI images were used to develop a linear regression equation between Band 5 reflectance and TDS measurements. Using the regression model, spatiotemporal maps of TDS were developed. The results revealed that the area covered by water in February 2020 was 1,233,100 m². After the creation of the dam, the area covered by barren land has decreased from 4,592,100 to 4,134,900 m² (9.96% decrease), and the area covered by vegetation has decreased from 3,682,400 to 1,906,500 m² (48.23% decrease). The coefficient of determination (R²) for the multiple regression equation was 0.846. The study will help to understand the impacts of Gorano Dam on the land cover of the area and temporal change in TDS of the dam.

Modeling high-resolution spatial distribution of overland flow and total suspended solids concentration (TSS) is becoming more feasible due to parallel computing and gridded physiographic and rainfall data available. In this article, we developed a fully distributed model based on the methods of Green-Ampt for infiltration loss, non-linear reservoir for flow routing, and build-up and wash-off approach for TSS accumulation. The model was applied in a parking lot catchment (7.85 ha) at the University of Texas at San Antonio. Calibration results indicate that the model can predict overland flow (NSE = 0.89, R² = 0.95) and TSS concentration (NSE = 0.91, R² = 0.96) at the outlet of the catchment. Moreover, 54% of the normalized TSS accumulated mass were carried out in the first 30% of normalized accumulated volume, characterizing the first flush at the outlet by the m(v) curve. The first flush spatial analysis, however, showed that other hotspots had more intense m(v) rates for 30% of the normalized accumulated volume, indicating possible areas to allocate low impact development techniques to treat first flush. A topographic influence analysis was performed assessing the role of topographic slope, total volume, total pollutant mass, and event mean concentration (EMC) for all cells in the grid by a descriptive statistical analysis via Pearson and Spearman correlations. Only the total pollutant mass and total volume had a strong Pearson correlation, and EMC, total mass, and total volume had a strong Spearman correlation compared to each other. These results suggest that these variables follow a non-linear monotonic relationship.

The value engineering (VE) study was performed on a real pilot project in the disciplines of roads and civil works, earthworks, bridges, marine works including beach well construction, hydrology and flood mitigation measures, infrastructure and utility networks such as potable water, sewage, storm water, irrigation, power, communications, etc. The primary objective was to reach an estimate for a reduction of the project’s infrastructure total cost by identifying areas of capital cost where alternative methodologies can reduce those costs and, where appropriate, make recommendations including the order of magnitude of the cost savings. The value study identified some 120 ideas for value enhancement. Of these, 26 ideas were selected for development into recommendations for improving the performance and/or lowering the initial and life cycle cost of the project. The use of VE has proven to be successful in saving about 34.4% of maximum initial cost savings identified by the VE study.

K_La, also known as the oxygen mass transfer coefficient, describes the efficiency at which oxygen is transferred into a bioreactor. The goal of this study is to evaluate the impact of geometry of the tank on K_La by testing three different shapes—inverted truncated cone, cylindrical, and rectangular reactors—while using an equal volume of water. Dissolved oxygen concentrations (DO) were chemically lowered by adding sodium sulfite and cobalt chloride to tap water and monitored as the water was reoxygenated with an air pump. The K_La and C_∞ values were calculated using a non-linear regression program developed by Naik and Stenstrom. Observationally, the inverted truncated cone had the highest K_La values with an average of 2.62 h⁻¹, while the rectangular tank had the lowest values at an average of 2.01 h⁻¹. A least significant difference (LSD) analysis showed significant differences between all containers’ K_La values (at α = 0.05). However, a Tukey’s test showed significant differences only between the inverted truncated cone and rectangular tank.

Hyperion Water Reclamation Plant (HWRP), operating since 1892, and LA Sanitation & Environment’s (LASAN) core mission has championed the protection of public health and environment as a department within the City of Los Angeles (City). Our environmental charge has evolved through the years garnering our organization a strong standing as a world-class environmental leader. HWRP is one of the largest treatment plants in the world with an average dry weather capacity of 450 mgd. The Hyperion BioEnergy Facility (HBEF) was commissioned in early 2017 at cost of $170M and uses biogas to power two gas turbine electrical generators for the production of electricity on site. Hot exhaust from the gas turbines is used to create steam, powering a steam turbine and providing heating steam for Hyperion’s solids digestion process. HBEF provides renewable source of energy for HWRP, amounting up to 27 megawatts (MW) of power generation and 70,000 pounds of steam per hour. The construction and installation took approximately 28 months. Two Solar Mars 100 engines were installed, each rated at 11,347 kW of electrical power with a heat rate of 10,365 Btu/kW·h. Both turbines are dual fuel (biogas and natural gas). Natural gas is used/mixed as needed when biogas volumes are low. Biogas is treated with vessels containing a special adsorption media that removes siloxanes, volatile organic compounds, and other impurities in the gas. HBEF incorporates catalytic oxidation (CO) and selective catalytic reduction (SCR) systems for carbon monoxides and oxides of nitrogen emissions control, respectively. Three and a half (3.5) years of performance data, air emissions numbers of the two turbines, and operations and maintenance (O&M) challenges will be presented for LASAN renewable energy source.

Mixing is among the most important applications used by wastewater treatment facilities to achieve blending, solids suspension, and prevention of sludge accumulation. Jet mixing is a widely adopted mixing technology used in equalization tanks, anoxic basins, sludge storage tanks, and digester tanks. With increasing energy costs in recent years, it is very important to study and optimize the mixer design to improve mixing performance and minimize energy expense. This paper compares the mixing performance of two commonly used jet mixing technologies in wastewater tanks using a computational fluid dynamics (CFD) tool. Accordingly, three-dimensional CFD models are developed for these mixers and solved based on the Reynolds-averaged Navier-Stokes equations using the standard k-ε turbulence model. The simulation results are used to determine the mixing flow patterns, length of jet plume, dead volume, and mixing velocities achieved for each mixer. The results are also interpreted to determine the effect of total solids concentration on the mixing performance.

The purposes of this paper are to identify and discuss best available technology measures to limit soil erosion and to provide sediment control measures for a large construction site in U.K. Construction sites are required to meet pre-development water quantity and quality conditions to minimize their environmental impacts. A major challenge for all construction sites is to limit erosion of disturbed land and control downstream transfer of sediment. Because erosion and deposition processes in nature are highly uncertain and depend on many site and environmental factors, adequate sediment characterization and quantification are technically challenging but are crucial to demonstrate compliance with permitting limits at all stages of a project. The paper provides an approach to estimate the amount of erosion and a framework for the selection, design, and optimal integration of best available technology measures to achieve a sustainable plan for the management of erosion and sediment carryover for a large, complex, construction project. Specifically, the paper documents the evaluation and engineering processes for erosion and sediment control including proper interpretation and dissemination of construction phase water discharge requirements; site meteorological, hydrological, and soils conditions; estimation of influx and efflux of total suspended solids concentration; and selection and design of sustainable treatment trains for erosion and sediment control.

Sustainability has become a trend in recent years in stormwater infrastructure management and will need to be practiced in perpetuity. Trenchless rehabilitation technologies are sustainable and innovative techniques for the renewal of stormwater drainages. Cured-in-place pipe (CIPP) is a trenchless technology solution for rehabilitation of large diameter stormwater drainages that prevent further deterioration and can provide structural support for severely damaged host pipes. Trenchless CIPP method involves a liquid thermoset resin-saturated material that is inserted into the existing pipeline. Life-cycle assessment (LCA) is a tool for quantifying the environmental performance associated with the rehabilitation of stormwater drainages considering the complete life cycle, starting from the production of raw materials to the final disposal of the products. The available information of the materials, manufacturing, processes, transportation, and disposal are used to analyze the emissions and other ecological impacts associated with a trenchless CIPP renewal project. The objective of this paper is to conduct the LCA of CIPP liners using styrene based unsaturated polyester resins for stormwater drainages and to identify influencing factors impacting the environment. The LCA was carried in SimaPro using TRACI method. Results show that carbon dioxide and ozone are the major emissions in CIPP renewal process that can lead to global warming and smog, respectively. It can be concluded that the LCA of CIPP is an important component when considering sustainable stormwater infrastructure management. This study can be useful for analyzing the LCA and associated costs of CIPP renewal for large diameter culverts with different project conditions.

According to the U.S. Environmental Protection Agency (U.S. EPA), nutrient pollution is one of America’s most widespread, costly, and challenging environmental problems impacting water quality. Discharge of these nutrients in excess to our waters leads to a variety of problems including eutrophication, with impacts on drinking water, recreation, and aquatic life. Therefore, more stringent effluent nutrient limits have been imposed on most of the wastewater treatment facilities (WWTF) and are coming to others. WWTFs have added or adding intensive treatment processes for extensive nutrient removal, but these upgrades are not affordable especially for smaller treatment facilities. WWTFs have significant economic and environmental benefits associated with their construction and operation; however, like other similar infrastructure, the economic and environmental impacts of their construction and operation need to be minimized to make affordable to the smaller facilities. Worldwide, it has been acknowledged that small-scale WWTFs can be resource intensive when compared with larger plants. WWTFs have reduced their nutrient discharges by optimizing operation and maintenance practices without incurring large capital expenses. This paper presents economical ways the existing small utilities can retrofit/upgrade, optimize, and/or operate their facilities to meet nutrient effluent limits.

One-dimensional mathematical models have been developed in order to predict pressure transients for pipes containing entrapped air undergoing rapid filling. A common hypothesis was adopted in these models, as there exists a distinct vertical air-water interface throughout the filling process. The limitation on the assumption becomes significant for pipes with large diameter, where the filling front undergoes notable deformation due to density difference and gravity effects. This study modeled air-water interactions in a horizontal pipe over rapid filling processes, by using the compressibleInterFoam solver of OpenFOAM. Both empty and partially filled pipe filling cases were simulated and compared with rigid-column models. Comprehensive analyses are presented, including detailed velocity profile, pressure distribution, temperature variation of entrapped air, and interface evolution. The results indicate that the transient water flow is analogous to water hammer flow and that the contribution of air-water mixing on the pressure oscillation damping is considerable. The findings are helpful to better understand the physics of the flow and to improve numerical models.

Storm geysers increasingly occur in sewer systems under climate change and rapid urbanization. The geyser mechanism in a single-inlet system has been extensively studied, while the geyser mechanism in multi-inlet systems has yet to be discovered. In this study, three-dimensional computational fluid dynamics models with multi-inlets at laboratory and prototype scale were established to investigate geysering induced by rapid filling. The numerical results at laboratory scale indicate that compared to the single-inlet model under identical inflow conditions (rapid increase the same total flow in the same time), the geyser pressure generated in the multi-inlet model is less than that of a single-inlet model, but more water is ejected out, and the geyser process is closer to the actual geyser event. The numerical results of the prototype model show that the equivalent density of the water-air mixture during geysering in the prototype scale model is about 212 kg/m³, which is less than the equivalent density in the laboratory scale model.

With rare exceptions, domestic wastewater treatment plants are constructed outdoors and exposed to the elements. This paper presents the critical design requirements for six fully enclosed domestic wastewater treatment facilities, the differences between inside and outside design elements, the shifts in priorities leading to the decisions to construct indoor systems, and the differing cost benefit–life cycle cost values. Following the session, conference participants will be able to clearly identify unique engineering design requirements and building code compliance criteria, which differ between treatment facilities designed, constructed, and operated inside buildings and typical outdoor wastewater treatment plants. The benefits of increased resilience to degradation from the elements and enhanced security will be contrasted to the increased costs of design, construction, and operations. The planning, design, permitting, construction, and operation for six fully enclosed wastewater treatment facilities will be presented, compared, and discussed in detail. They are the Silver Creek Ski Resort Wastewater Treatment Plant, the Warrenton Chase Wastewater Treatment Plant, the Pocahontas County Snowshoe Regional Wastewater Treatment Plant, the FEMA Mount Weather Wastewater Treatment Plant, the Lucketts Elementary School Rotary Sand Filter Plant, and the Lucketts Elementary School Wastewater Treatment Plant. Specific topics include the need to involve architects in the design process and the understanding of heightened life safety concerns and design requirements. The topics also discuss how to address the high humidity issues for HVAC systems and building finishes and the coordination between tank depths and building heights. It is necessary to provide accessibility to submerged equipment by including both portable and overhead gantry cranes, and it is necessary to provide enhanced noise and odor management systems. Electrical code requirements include explosion-proof fixture, and it is necessary to provide enhanced indoor lighting for both above-grade and below-grade structures. And the limiting nature of an enclosed facility affects future plant modifications and expansions.

In many cases, estimation of peak discharge is the primary goal of hydrologic modeling. According to the natural resources conservation service (NRCS) unit hydrograph method, the peak flow depends on the watershed drainage area, the peak-flow time, and a peak rate factor (PRF), which is recommended to be 484. However, this recommendation does not always apply because the PRF value depends on the shape of the unit hydrograph and the watershed parameters. In this paper, we employ a data set of 186 rainfall-runoff events in 23 small watersheds in Houston, Texas, to explore this assumption. For each event, a unit hydrograph was determined by deconvolving the direct runoff hydrograph with the excess rainfall hyetograph. To simplify the process of determining the unit hydrographs, a gamma distribution shape was assumed (i.e., skewed bell shape). PRFs were then computed for each of the calculated unit hydrographs. Results showed that PRF values vary between 8 and 412 in Houston watersheds, with a median of 152. The fact that the PRF values of the watersheds studied here are, in general, lower than that recommended by NRCS, implies that the unit hydrographs in Houston, Texas, are more front-loaded than the recommended NRCS unit hydrograph.

Long periods of snow-covered frozen ground affect the generation of surface runoff by altering the infiltration process. Physically based approaches to identify frozen ground are relatively data-intensive, since they incorporate heat transfer procedure for computing the energy flux of the soil. In order to simplify the identification of frozen ground, the majority of the macro-scale hydrologic models utilize empirical frost indices to estimate the frozen ground condition. The main objectives of this study are to provide statistical analyses of the frozen ground condition and to evaluate the performance of a continuous frozen ground index (CFGI) methodology by using measured soil temperature data in North Dakota. The observed average daily air temperatures and snow depth data from the snow data assimilation system (SNODAS) were used to estimate the frozen ground condition for different stations. The analysis of the soil temperature data and results from the CFGI method accentuate the presence of long periods of frozen ground conditions at different stations. Results from this study can be used by macro-scale hydrologic models to provide better simulations of generated surface runoff in cold climate regions.

The development of operational, region-wide hydrologic forecasting systems requires a large-scale modeling approach that includes various physical components and a representation of their interactions. Such modeling systems rely on a significant amount of pre-processing efforts in terms of model parameterization. The NOAA National Water Model (NWM) is a recent example of a large-scale hydrologic modeling system with the primary goal of forecasting streamflow and other hydrologic states across the river basins of the Contiguous United States (CONUS). The NWM version 2.1 includes 5,781 lakes/reservoirs (hereafter, waterbodies), which represent a variety of geophysical attributes and outflow conditions (managed versus unmanaged). Major data sets that currently support features of the NWM rivers and waterbodies are based on the National Hydrography Dataset Plus (NHD+), and from data sets managed by the United States Army Corps of Engineers (USACE) and the U.S. River Forecast Centers (RFC). However, the assessment of the NWM’s performance of discharge below managed reservoirs underscores the need to revise the waterbody geometry and discharge characteristics. In this study, we investigate the sensitivity of waterbody outflows and the water balance to different geometric assumptions such as shape attributes and head-area-volume (h-A-V) relationships. We also investigate the sensitivity of discharge characteristics of these waterbodies (e.g., weir and orifice parameters) and their impact on the streamflow prediction in the NWM. We evaluate various aforementioned model parameters and configurations on waterbody discharge against streamflow observations from a set of USGS stations.

Sensitivity analysis is an important assessment usually performed to gain a better understanding of the hydrological processes impacting model outcomes as well as to identify most dominant parameters for model optimization and calibration. In this study, a watershed model developed using the Hydrologic Simulation Program–Fortran (HSPF) for South Chickamauga Creek watershed was evaluated for parameter sensitivity. Critical HSPF model parameters, i.e., lower zone evapotranspiration (LZETP), index to infiltration capacity (INFILT), base groundwater recession (AGWRC), interflow inflow (INTFW), fraction of groundwater inflow to deep losses (DEEPFR), etc., were investigated for the sensitivity analysis. This paper presents the sensitivity analysis results using sensitivity factor, which is expressed as a ratio of the percentage change in model output (i.e., runoff, peak flow) to percentage change in model input parameter (expressed as percentage) and explains the variability of model outcomes from the selected perturbations of input parameters. Low flow conditions were mostly influenced by AGWRC, DEEPFR, LZETP, and INFILT, whereas INFILT and INTFW had most influence on the peak flows. Annual runoff volume and high flow conditions were highly sensitive to LZETP. However, AGWRC was found to be the most influential parameter in all hydrologic responses in this watershed. Overall, this study helps watershed management by providing insight into model structure and adjustment. Besides, it will work as a basis for future multisite sensitivity and uncertainty analysis.

The Public Health Security and Bioterrorism Preparedness and Response Act of 2002 (Bioterrorism Act) required water utilities to perform vulnerability assessments (VA). Later, it became clear that the security focus of the VAs needed to be expanded to an “all-hazards” approach. Utility managers have expanded their thinking from looking only at the vulnerability of their systems to malevolent attacks to a more robust understanding of the risks their systems face from natural hazards, and “dependencies,” such as utility power or key vendors and supply chains. America’s Water Infrastructure Act (AWIA) of 2018 requires that all community water systems serving at least 3,300 people assess the risks to, and the resilience of, their drinking water systems. The AWIA requires that a risk and resilience assessment (RRA) must be conducted and aligned with an emergency response plan that incorporates the RRA findings. Water utility managers have long understood the concept of managing risk. While the concept of “resilience” has gained traction more recently, water utilities regularly take measures to anticipate interruption of water service, as well as providing solutions and pragmatic “workarounds” to restore service quickly. These are measures of resilience. The article details the authors’ insights gained over various analyses focused on RRA of urban water infrastructure and lessons learned from this process. In addition, it also provides specifics of an “all-hazards” approach that includes cyber vulnerability of municipal water infrastructure. These lessons are applicable to other similar projects and studies, opening the door to new and ongoing discussions on vulnerabilities of municipal water infrastructure and their potential risk mitigation needs, leading to more effective policies and procedures.

Recent developments have witnessed that remote operations attract considerable widespread interest due to their ability to work remotely, ease of access, and faster troubleshooting. This paper presents an architecture for the remote operation of global and local connections to release water from storage units. This approach could be adapted for a wide array of applications to control flooding, perform maintenance operations, and release water for ecological purposes. An inverted u-tube structure known as a siphon and the widely used conventional drainage pipe, both provided with actuated gates, facilitate water release from storage units. They are operated remotely using the 4G/5G cellular network. A graphical user interface (GUI) has been developed to monitor and control hardware and software components. Sensors were deployed in the field to collect information about the water depth of the storage units. All the components are powered using solar energy. Several experiments have been performed and tested in our laboratory to verify system reliability to get a stable and consistent connection. This methodology may open new avenues for the application of remote operations, particularly in civil and environmental engineering.

The significant growth in many developing regions has led to increasing water use in the industrial sector. Water as a source required for industrial and cooling processes is directly related to energy production and carbon dioxide emissions. In this study, the water-energy-carbon (WEC) nexus has been investigated about industrial water demand. The dynamics of the WEC nexus are investigated through the use of a system dynamics (SD) approach. The interaction between the components is mainly calculated from the mass and energy balance. The proposed framework has been applied to the water use information of the industry sectors in the Netherlands. The functional relationships of the energy and carbon production are investigated using exponential and logistic growth functions, and the impact is measured using the Kaya identity framework. A range of exchange in water use to energy and carbon production for cooling purposes is estimated. The results show the significant value of combining mass and energy balance of WEC in an SD framework.

This paper presents the operational reliability assessment of a remotely controlled siphon system. The siphon system mostly consists of water level switches, air vents, bilge pumps, and an actuated butterfly valve. In this study, the reliability block diagram (RBD) model based on the ExtendSim software is employed to assess a remotely controlled siphon system’s operational reliability. The Monte Carlo simulation results from the RBD model demonstrate that the non-repairable siphon system’s operational availability can be enhanced from 0.683 to 0.855 within a 1-year life cycle by increasing the safety factor to 2 for the vulnerable components, such as the water level switch and the air vent. The value can increase to 0.999 when adopting an on-site maintenance strategy. Based on the analysis of multiple scenarios and maintenance strategies, a suitable architecture of the siphon system is proposed herein.

Over the last decade, gap between available fresh water and demand is widening due to exploding population growth, the existing available water/wastewater treatment-technologies are challenged to treat tougher waters and meet more stringent water quality goals at reasonable costs. There has been increasing interest in development and implementation of low energy/low carbon, advanced nutrient removal processes coupled with intensification technologies, and advanced controls at water resource recovery facilities (WRRFs). WRRFs have been facing ever increasing energy demand and energy costs, trends that are expected to continue in the future. Thus, WRRFs utilities are increasingly looking for innovative, cost effective, and sustainable ways of reducing energy costs and energy consumption. The paper will focus on the state-of-the-art of the recent advances in process intensification technologies that facilitate lower costs and improve efficiency within smaller footprint for nutrient removal.

BRICS countries represent some of the fastest-growing world’s economies and populations. At the same time, the five nations face the challenge of poor health-hygiene and water quality crisis. The rapid industrialization and reforms to provide substantial health systems have resulted in the ubiquitous presence of emerging contaminants, mostly pharmaceutical and personal care products (PPCPs), in the different ecosystem matrices. Furthermore, antimicrobial resistance (AMR) is advancing global health concerns. Thus, evaluating the ecological, human health, and microbial risks associated with PPCPs is necessary. With this aim, the study was designed to assess the risk of PPCPs and AMR in the surface water. The application of point of use (POU) technologies as a plausible option to reduce the risk associated was determined. The most frequently detected PPCPs in five regions from the secondary data included ibuprofen (IBP), diclofenac (DCF), carbamazepine (CBZ), caffeine (CAF), ciprofloxacin (CIP), trimethoprim (TMP), sulfamethoxazole (SMX), and methylparaben (MPB). However, the risk associated with the above-mentioned PPCPs was not estimated in any case. The widespread presence of CAF enabled the detection of anthropogenic pollution. Similarly, the dominance of antibiotics was attributed to the overuse of antibiotics or non-astringent regulation. In terms of spatial variation, the PPCP concentration was in the order: India > China > Brazil > South Africa. We determined the ecological risk for surface water samples, and high risk (RQ > 1) was found for algae, daphnia, and fish for almost all PPCPs. For chronic human health risk, high carcinogenic (5×10^-6–1.8×10^-1) and non-carcinogenic risk coefficients (HQ = 2.5×10^-4–11.5) were determined for various age groups. The age groups 16–21 years and 21–50 years depicted the least overall risk between 0.9 and 10. The probability of AMR risk was carried out using the quantitative microbial risk assessment (QMRA) method. Human exposure via accidental and incidental ingestion was obtained in the range of 50–10⁶ CFU/100 mL E. coli, with the variation in the probability of illness greater than 0.9. On evaluating the POU technologies for microbial reduction, maximum risk drop was obtained for carbon filter combined with UV with a reduction of probability of illness by 0.007. Overall, the study aids in fulfilling the large gap in PPCPs’ monitoring and risk in the emerging countries (BRICS) compared with North American and European countries.

Disinfection is an essential process for both potable water and wastewater treatment plants. However, disinfection byproducts (DBPs) like trihalomethanes (THMs), haloacetonitriles (HANs), and nitrosamines (NOAs) are formed when organic matter precursors react with disinfectants such as chlorine, chloramine, and ozone. Formation of DBPs is strongly associated with the type of water source, type of disinfectant, and organic matter concentration, which can have seasonal variation. In this study, water samples were collected from 20 different intra-watershed locations, which included urban runoff (with and without the influence of unsheltered homeless populations), wastewater effluent discharges, and a large, terminal reservoir that serves as the local drinking water source. Samples were collected on dry and rainy days, which represent seasonal samples. DBP formation potential (FP) tests were conducted at consistent pH, contact time, and temperature. THMs, NOAs, and HANs were analyzed by gas chromatography-mass spectrometry (GC-MS). The FP tests performed on these water samples revealed that chlorine formed the highest THM concentrations, while THM concentrations were low for the ozone FP test as expected. Chloramine produced the greatest HAN concentrations, with dichloroacetonitrile representing the highest concentration. With respect to sample type, more DBPs were formed at the non-wastewater-impacted runoff sites as compared to the wastewater effluent discharge sites. With respect to TOC levels, rain event samples for all locations had higher TOC concentrations compared to dry sampling days. Similarly, rain event samples showed increased DBP formation; a significant amount of precursors for THMs was found in runoff waters that were influenced by wastewater effluent discharges and unsheltered homeless locations (concentration of total THMs for chlorine FP test was >200 μg/L). Therefore, urban runoff waters should be considered as potential sources of DBP precursors to drinking water source waters, and runoff water is prone to seasonal variation.

The small, medium, and large municipal water and wastewater systems serve the populations from less than 1,000 to more than 1,000,000 in the U.S. (and worldwide), where the municipalities operate with stringent financial resource(s) to conduct water systems. The One Water concept of an integrated water management (IWM) at municipal operations would include resource water (surface water and/or groundwater); drinking water treatment; metered, potable water distribution; wastewater (sewage, I/I, stormwater, pre-treated industrial, and the leachate-wastewater and septage, as locally applicable) collection; wastewater treatment and resource recovery; water-reuse; and the permitted disposal of treated effluents back to watershed. The total energy use for effective operation of municipal water infrastructure (MWI) is significant; an estimated U.S.-wide average of (approximately) 4.75E+06 J/m³ (5,000 kWh per a million-gallon) water-processed is expended. This energy use can be reduced or conserved via an effective design (or a rehabilitation) of various water-systems including the application(s) of renewable energy-systems; thus, the water-systems can be made operating with net-zero-to-net-positive-energy into the future. Author has accomplished energy resilient water-systems at various municipal water operations. This paper includes identification and explanation of various elements of municipal water infrastructure; energy-use by the components of water systems; energy efficient and environmentally compliant design of unit and process operations; recommendation on effective application(s) of renewable energy systems; the net-zero-energy design and making the water systems net-positive-energy into the future; discussion of a few case studies; and resulting cost-effective and environmentally sound operation of a Municipal One Water System (MOWS) into the circular-economy.

In this study, we demonstrate how a Bayesian belief network (BN) model can be used to quantify hypothesis-based weight-of-evidence (HBWoE) evaluation for the particulate matter (PM) exposure network risk factors. Most studies of particulate matter exposure and adverse health outcomes have been performed for PM_2.5 (aerodynamic diameter ≤ 2.5 μm) and PM₁₀ (aerodynamic diameter ≤ 10 μm). However, the lack of direct measurement of coarse PM (PM_2.5-10, aerodynamic diameter from 2.5 to 10 μm) causes inconsistent results. There are limited studies on exposure to PM_2.5-10 during gestation and low birth weight. It is important to investigate the impacts of PM_2.5-10 on birth weight by weighing all of the evidence that can help to understand and predict the potential risks. The results of the designed model indicate that maternal exposure to ambient coarse PM pollution (>16 μg/m³) provides high correlation between low birth weight and coarse PM concentration with false negative rate (FNR) of 15%. The results show an effective way of evaluating the cumulative results of studies to measure how much the evidence supports the hypothesis. The proposed framework can be implemented in several other environmental contaminant exposure health-risk problems to understand the value of information in each study and overall cumulative information.

The purpose of this preliminary investigation is to find the effect of the COVID-19 pandemic on water quality parameters in rivers, especially in the Great Lakes Basins. Several rivers and coastal areas in the Great Lakes region are highly polluted due to industrial and agricultural activities. The lockdown has caused industrial activities to shut down, people to work from home, and less waste to be introduced into natural bodies of water. Several studies show that air quality has improved during the lockdown in a variety of places, especially in big cities, but there are fewer studies on water quality parameters. Recent studies, using satellite images, show there are improvements in the water quality of lakes and bays due to less traffic and industrial activities. In this study, with the collaboration of two high schoolers, we want to find rivers with dissolved oxygen data, in the Great Lakes region, and compare the period of lockdown with the same period of time in 2019. The outcome of this study will provide a better understanding of the role of human activities on water quality in natural systems and can be used for public education and awareness of environmental protection.

The quality of natural waters is of critical importance for public health, welfare, sustainable development, and ecological systems. Unfortunately, Lake Erie has been facing a persistent crisis of harmful algal blooms (HABs) since the 1960s. The most annual occurrence of HABs at Lake Erie predominately occurs at the western region between the months of May and August. HABs are exhibited by the excessive growth of cyanobacteria (i.e., blue-green algae), which often produce toxins such as microcystins. The goal of our research is to identify key factors affecting HABs in western Lake Erie from the perspective of machine learning, which is a powerful tool for predicting the output from the input features. Specifically, chlorophyll-a is usually a direct indicator of the severity of HABs and is applied as the output target in machine learning. We collected data from both on site and remote sensing. We found that several features of remote sensing were not reliable and thus applied only on-site data as input features in machine learning. After comparing 12 popular machine learning algorithms, we found that the random forests model had the best performance in predicting the value of chlorophyll-a, with a R² score of 0.84. Moreover, with the help from machine learning, we could identify the quantitative importance among input features and find that particulate organic carbon is the most correlated factor to chlorophyll-a. Furthermore, we showed that the machine learning model was location dependent and that different structures of a machine learning model should be applied to different locations to predict HABs.

The excessive burning of the biomass materials and hydrocarbons produces more carbon dioxide than the nature can absorb. The increase in the CO₂ concentration in the atmosphere is also due to the excessive deforestation and increased industrialization. The extra CO₂ in the atmosphere will contribute to the global warming by absorbing and re-emitting the infrared radiations from the sun. Carbon dioxide storage in underground sedimentary reservoirs is one of the possible options that can help in mitigating the effect of global warming. During the geological carbon dioxide storage process, CO₂ is injected at higher injection pressure to the underground sedimentary reservoir, which causes the base pore pressure of the reservoir to increase excessively. Any possible injection of CO₂ near to the already existing fault can activate the fault and can cause the leakage of the stored carbon dioxide to the overburdened potable water layers and to the atmosphere. In this paper, an integrated geomechanical and fault activation modeling study is performed for the Wasia reservoir in Saudi Arabia. During the geomechanical modeling process, a fault passing through the Wasia and Aruma geological layers is also considered. The pore pressure buildup and ground uplift were calculated during carbon dioxide injection into the reservoir for the case of absence of a fault across the reservoir, as well as the case with a fault. The Mohr-Coulomb failure criterion was utilized to perform the stability analysis of the reservoir for the case of absence of a fault across the reservoir, as well as the case with a fault. The integrated geomechanical and fault activation modeling performed in the current study has provided estimates for the safe injection parameters of CO₂ based on the magnitudes of the reservoir pore pressure and stresses in the reservoir.

Coastal cities increasingly experience tidal flooding and as a result may find excess salt concentrations, potentially affecting the health of urban vegetation in parks. However, the transport, buildup, and potential persistence of elevated salt levels in coastal urban soils are poorly quantified. The objective of this study was to quantify the risk of tidal salt damage to urban vegetation and soils in coastal cities. To do this, we measured soil electrical conductivity by probe at 15–20 locations within 11 parks located in downtown Charleston, South Carolina, over a one-week period in July 2020. Despite all of the parks being located within 1 mile of the coast, we found that salt levels were generally low, with an average concentration of 0.15 mS/cm, a level harmless to vegetation. Notably, the park located closest to the coast had the highest average salt concentration, 1.0 mS/cm, a level damaging to vegetation, soil microbes, and soil structure. Our findings indicate that while urban park soils that occasionally experience flooding may be resilient to salt damage, there may be a level of flooding above which dangerous salt levels may persist. These findings also indicate that salt-tolerant vegetation may not be necessary for all coastal park designs, but only for parks located directly along the coast.

The impervious nature of modern cities promotes heat islands, elevated local air pollution, excess stormwater, flooding, and lack of habitat for wildlife. While these negative effects are mitigated by especially large trees, the growth rate of urban street trees is poorly quantified. To better quantify these rates, we measured the growth rate of 94 street trees in Charleston five years after their previous measurements. We did this by recording physical aspects of the tree and the diameter at breast height (DBH). We found that the trees that were smaller at the beginning of the study, between 2 and 6 in. DBH, grew at 0.22 in./year, while those that were larger, between 6 in. and up DBH, grew at 0.92 in./year. This result may be due to transplant shock for recently planted trees and increased resilience to stress for larger trees. We also found that oaks had statistically greater growth rates (0.47 in./year) than crape myrtles (0.19 in./year) (p = 0.001). Surprisingly, both the presence of obstructions (overhead wires, signage, trees, and buildings), as well as the perpendicular distance to the street, did not produce statistically significant effects on growth rates. Similarly, unexpectedly, despite prior research suggesting that south-facing trees experience the greatest water stress, we found that south-facing trees had greater growth rates (3.5 in./year) than east, west, or south-facing trees. Our findings can help quantify the rate at which ecosystem services improve as urban street trees age.

A good understanding and observation of ethics has now been more than ever critical in all professions toward a sustainable and continuation of world affairs. Various scientific, engineering, social institutions, and organizations have been putting a heightened emphasis on observation of the ethical approach in all fronts during this CoVid19 time and moving into the future. To date, the elements of ethics have been developed and observed by various and the said entities and professions; however, at times, professionals working with various entities in accomplishing projects (including, the research) may and do see (a significant) subtleness in the way elements of ethics are included and a level of difficulty in observation(s). Some of the noted entities, revisiting the requirement of ethics to make sure are good for application in a broad manner (i.e., across applicable entities). In this work, authors, with a significant work experience in academia, government, and private industry, made an attempt compiling (as selected) those elements of ethics residing with various critical scientific, engineering, and social institutions. For example, professionals accomplishing on environmental compliance would need to observe ethics at a level with no room to failure at any step of the project(s). A few selected and field observed ethical situations will be detailed in presentation. Thus, this effort on a comprehensive review (and verification) of ethics and requirements would be helpful to various certified and registered professionals and provides good guidance.

The increase in anthropogenic activities across the globe is rising the water scarcity problem at an alarming rate. The non-compliance of discharge standards in most of the conventional centralized treatment systems calls the need for source separation and state-of-the-art treatment practices. 60%–75% of domestic wastewater is contributed by greywater, and the reuse of greywater emerging from the bathing, kitchen, and washing sources is a recommended paradigm shift to counter the above-mentioned water crises. From the past few decades, bacterial degradation of greywater is on moot due to the meager of nutrients and organic matter in comparison to domestic wastewater. In the present work, the biological degradation of greywater using the algae Chlorella vulgaris is carried out. Greywater samples were collected from three different places of the metropolitan city Chennai and analyzed for basic quality parameters. All the samples were inoculated with C. vulgaris in a controlled environment of 680 nm for a duration of 12 h per day and 12 h in no light. Growth analysis, total nitrogen (TN) removal, total phosphorous (TP) removal, and total organic carbon (TOC) removal were monitored for the inoculated batch samples. In all the samples, the algal growth reached the stationary phase after 6–7 days of inoculation. From the observed initial values ranging between 12.93 and 17.8, 7.42 and 13.42, and 31.6 and 73.85 mg/L, respectively, for TN, TP, and TOC, complete removal of TP is observed in all the samples. TN removal in the samples varied from 80.1% to 88.8%, and an average removal of 60% TOC is observed. Even though the results of the study are on par with other treatment technologies, efforts should be made to increase the productivity of algal biomass.

Urban water system managers face a set of interrelated water security challenges as they pursue the goals of sustainable sources of water, mitigating flood hazards, and improving water quality. These challenges are often subject to change (and hence highly uncertain) due to the coupled effects of hydro-climatic variability, socio-economic trends, and regulatory reforms. To meet these intersecting goals, we present a mechanistic framework with illustrative examples that evaluates an urban water system’s resilience under future uncertainty. By employing principles from engineering design, ecosystem science, and social equity studies, our resilient urban water systems (ReUWS) framework explores the potential of effectively combining green and gray infrastructure (GGI) in an urban watershed while prioritizing stakeholder and community engagement throughout the lifecycle of water system projects. A nested set of hydrology, ecosystem, and hydraulic models are developed with data flow among them defining the boundary and initial conditions for each other. An example is shown with the Baltimore water system on an approach to evaluate the effects of GGI hybrids on major water security metrics. The corresponding engineering designs, ecosystem service potentials, and measures of equitable access to services are also analyzed using the framework. The results evaluate performance of the existing systems under future conditions and also compare different GGI-based strategies for improving resilience in urban water systems. The findings of the study help to evaluate the potential for using GGI strategies to cope with changing climate extremes and other environmental factors as well as social change. Trade-offs derived from the case studies also can be used to adjust local/regional policies and regulations.

The effective management of suspended solids and their accompanying contaminants in water bodies requires information on the sources of sediments. Clear water reflects small amounts of solar irradiance, while water loaded with suspended materials (SM) has the potential of reflecting large amounts of sunlight. This study focused on the analysis of SM in Lake Mead, which lies on the Colorado River, using remote sensing spectral indices. Landsat 7 Enhanced Thematic Mapper (ETM+) satellite images were used to determine the spectral indices such as normalized suspended material index (NSMI), normalized difference suspended sediment index (NDSSI), and band ratio (BR). This paper established relationship between the satellite image and ground truth data obtained from United States Geological Survey (USGS) data. A map of spatial distribution of suspended sediments in Lake Mead was produced. The map showed that high suspended sediments were generally identified at the entry points of Lake Mead, with lower suspended sediments being concentrated at the basins of the lake. Results also showed that an increase in suspended sediment concentration (SSC) produces a corresponding increase in NSMI values. An exponential relationship between SSC and NSMI values, with coefficient of determination (R²) of approximately 0.96, was developed in this study.

The Salton Sea is one of the largest inland man-made water bodies in California and supports vital habitat for birds and wildlife. However, the lake has been in a critical situation in the past few years due to decreasing water levels, receding shorelines, and increasing salinity. In this study, we quantify and analyze the long-term changes in the surface area and volume of the Salton Sea utilizing remote sensing-based spectral water indices and GIS. Landsat TM images of every five years during the period of 1995–2015 were used. Normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) were computed to delineate open water features. These spectral indexes were calculated, analyzed, and classified independently to extract the lake surface area for each year in GIS. The index threshold for water was adjusted using aerial imagery from Google Earth as reference. The index that provided clear demarcation of water-non water boundary was chosen from visual analysis at lake-river confluence. The Database for Hydrological Time Series of Inland Waters (DAHITI) was used for surface area validation. The lake surface maps were generated from all remote sensing images and overlaid to produce lake surface area change maps over the study period. The volume calculation utilized one-foot bathymetric contour data, water surface elevation, and water maps. The calculated area agreed well with the validation data set with the difference of less than 0.5%. The assessment of the area and volume over the study period demonstrated significant variations. The reduction of surface area by 7.5% and volume by 19% was observed. Volume of the lake showed the potential of significant reduction in comparison to area and elevation. The proposed method can be used for the regular assessment of Salton Sea’s dynamics and can help planners for developing various mitigation, management, and restoration projects of the Salton Sea.

Milwaukee is located on the western shores of Lake Michigan and at the confluence of the Milwaukee, Menomonee, and the Kinnickinnic Rivers. The city attracted early European immigrants who brought beer brewing, meat production, leather tanning, and sausage making expertise, which promoted rapid industrialization. The consequence of this rapid domestic and industrial growth in the absence of proper waste treatment and potable water purification was extensive pollution of the rivers, ground-water, and Lake Michigan by sewage and industrial wastes and subsequent deaths from various intestinal diseases. The paper presents the 1926 Jones Island Plant, the demands of citizens for clean water, the limitation of local agencies to provide effective relief, and the creation of special purpose governmental entities to study and resolve these polluted industry problems. Early attempts of relief took the form of building sewers to discharge all wastes into the river system, followed by flushing the rivers to flow more effectively into Lake Michigan only to more seriously pollute the lake. After several years of difficult political and engineering deliberations, the conclusion reached were two serious problems—the need to properly treat/dispose of domestic and industrial wastes and to provide safe potable water to the citizenry. This realization as for waste treatment resulted in the construction and operation of the first large-scale state-of-the-art wastewater treatment facility (activated sludge process) in the U.S., the Jones Island Sewage Treatment Plant. The commission’s decision to proceed was bold, courageous, expensive, and correct. In evidence, this facility is recognized (1974) as a National Historic Civil Engineering Landmark by ASCE, the only sewage treatment facility so honored by ASCE, a National Historic Mechanical Engineering Landmark by ASME, and a place on the National Register of Historic Places by the U.S. Department of the Interior.

The waterways surrounding the City of Chicago have been a driving factor in its development. Initial development without modification of the Chicago River resulted in significant adverse impacts to the city’s residents due to contamination of their water supply by domestic and industrial effluent. The construction of the Chicago sanitary and ship canal, which both addressed the water supply issues plaguing the city and created a navigable connection between the Great Lakes and the Mississippi River, also resulted in the reversal of the Chicago River and the diversion of Lake Michigan water. This latter point resulted in litigation and several Supreme Court rulings and has remained a contentious issue for over a century.

The Canal du Midi (originally named: Royal Canal in Languedoc), connecting boat traffic from the Mediterranean to Atlantic or return, was constructed from 1666 to 1681 during the reign of Louis the XIV and was the largest European public works construction project since the Roman Empire. Constructed under tax collector Pierre Paul Riquet’s supervision, the 240 km (150 mi) canal had a navigable depth of 1.8 m (6 ft), an average bottom width of 13 m (42 ft), and overcame an elevation increase of 190 m (625 ft). The Canal du Midi is a summit canal, climbing from Toulouse over a distance of 52 km (32.3 mi) to the Seuil at Naurouze summit (189.43 m altitude) and continues 188 km (118 mi.) to the Mediterranean Sea. In addition to the manual excavation of the canal, the project required the construction of 328 separate structures, including 91 locks and more than 126 bridges, dams, diversion structures, and two tunnels. The main structures are presented: (1) St. Ferreol Dam and Reservoir [780 m or 2,560 ft long and 32 m or 105 ft high (the largest in the Western Hemisphere when built and second highest European dam then)], the stored water could be released in either direction through an ingenious two-gated basin near the summit to augment natural flows entering the canal; (2) the Malpas tunnel (165 m, 541.3 ft) through a mountain excavated by explosives (and the first canal passage ever built through a tunnel) and the Cammazes tunnel (constructed by the great French engineer Vauban more than 10 years after the canal was completed), which brings water from a diversion at Alzau into the St. Ferreol reservoir; (3) the three-gated circular lock which allows watercraft to continue on the canal or turn 90 degrees and exit to the existing Mediterranean port at Agde; and (4) the construction of the flight of eight original locks at Fonseranes (reduced to seven locks in a modernization) with 10,000 boat passages per year. Under the Act of 27 November 1897, the State of France owns the Canal du Midi, and its management is delegated to Voies Navigables de France, in the Ministry of Transport. Busier than the River Seine, the canal accounts for 1/5 of French river tourism and 80% of the passengers are Germans, Swiss, and British. The Canal du Midi was designated as a UNESCO World Heritage Site in 1996 and an ASCE International Historic Civil Engineering Landmark in 2016.

Denver’s City Ditch was the first attempt in Colorado Territory, and among the first in the arid West generally, to manipulate a natural water resource in such a way that an engineering skillset was required to do so. Between fall 1859 and spring 1861, the first iteration of the ditch was designed, and construction was overseen by two formally trained civil engineers, John M. Clark and Richard S. Little. Only about one-third of the ditch was built, though, before construction was stopped for reasons unexplained. Earl L. Mosley, in his History of the Denver Water System, speculated that some failure of the engineering might have been the cause, and subsequent authors have accepted his speculation as fact. To the contrary, by drawing on the previously uncited minutes book of the Capitol Hydraulic Company, an 1883 decree of water rights, and other resources, this article shows that there was likely nothing technically inadequate with the design and that the construction was suspended instead for financial reasons.

As huge modifications are underway in the lower Mekong basin (LMB) in Southeast Asia by building dams and expanding irrigation areas, biodiversity, environment, and livelihoods are impacted. Climate change and variability is another driver that stresses this system. This has tremendously caused damages to agriculture, fisheries, and the livelihoods of people in the region. Also, since the flows are regulated through the dams, flows are altered, and their effect on environmental flows (EFs) are not fully known. For maintaining the species, functions, and resilience of freshwater ecosystems and livelihoods of human communities that depend on healthy ecosystems, it is critical that quality, quantity, and duration of water flows are monitored. Environmental flow requirement (EFR) is one such metric, and we investigate using flow duration curves for each dam site by explicitly considering the spatio-temporal variability and quantify the cascading impacts in the lower Mekong. This study will integrate flow data from several gauge stations in the basin and simulate flows using the macroscale hydrology model for the period between 1950 and 2018. For selected locations, EFRs for both wet and dry seasons will be presented. In summary, EFR for very low flow locations varies between 16.1% for Class A and 6% for cCass F, while the mainstem location needs 13.2% MAF for Class A and 9% for Class F during the wet season. However, dry season EFR for Class A was highest for very flow low locations (4.8%) but lowest for Class F (1.1%). The results of EFR in % and mean annual flows for multiple locations will also be discussed. The difference in the MAF between Class A and Class F was more for the wet season (7%) as compared to the dry season (2.8%), suggesting that careful water management plans would be required during the low precipitation period.

The Mekong River Basin is among one of the largest transboundary basins in the world. It shares its boundaries with six countries, viz., China, Myanmar, Thailand, Lao People’s Democratic Republic, Cambodia, and Vietnam. Due to varied types of human activities carried out within and by adjacent countries associated with efforts to provide food and water demands for increased population, the hydrology, agriculture, ecosystem, and other watershed functions are continuously changing. We present a holistic view of how the external stressors such as climate change and variability, and land cover and land use change affect the spatial distribution of soil moisture, evapotranspiration, and streamflow. This is important to subsequently quantify the impacts on hydropower, water management, fisheries, and water supplies for domestic consumption, irrigation, and industries by integrating into a single system modeling framework. Rule curves developed using the simulated flows are used to calculate demand and outflow for each dam site, and the magnitude of flows in the dry season with irrigation expansion is integrated in the systems modeling. While the study is still ongoing, preliminary results suggest that hydropower production may be impacted if there is a shift in crop production during dry season when a third crop is cultivated. Also, crop water demand if not quantified correctly will impact the environmental flows as well. Results from this analysis will be extended to determine sustainable water supplies for various beneficial purposes and optimal reservoir operation strategies to develop a sustainable water resources development and management plan for this basin.

An inclusive international research experience for graduate students is being developed based on equitable, interdisciplinary opportunities in field research and training and proactive efforts in recruiting a diverse cohort. Michigan Technological University, the Consortium of Universities for the Advancement of Hydrologic Science, Inc., and Lutheran World Relief are collaborating to support local development interventions for agricultural and water-access challenges in the “Dry Corridor” of El Salvador. The three-year effort is supported by the National Science Foundation International Research Experiences for Students program. This project, titled “Agricultural Community Adaptations to Extreme Hydrometeorological Events,” recruited students for the summer 2020 experience before the COVID-19 interruption. Lessons from this past year pertaining to student recruitment, application selection, and preparatory training will enhance the processes for the coming year. Students were recruited through professional meetings, listservs, social media, and professional contacts. Proactive efforts were implemented to broaden student diversity. The selection process was systematically structured to evaluate applicant experience abroad, language abilities, and academic program relevance to the project goals. Pre-departure training content was developed to provide students with relevant tools and background for the travel, living, and research methods training in El Salvador. The project teams work with universities and governmental agencies in El Salvador. Agronomists, hydrologists, geologists, social scientists, and engineers are collaborating to explore new ways to couple participatory and hydrological research for informing adaptive strategies to water scarcity in agricultural communities. A planning visit in 2019 sought input from local farmers, representatives from governmental and non-governmental institutions, and project partners to help prioritize project research plans. This pre-planning approach fostered greater integration of the interdisciplinary project activities; planning to enhance local engagement in field work and continuous data collection; and development of insightful recruitment and promotional materials.

Flushing using fire hydrants is a very common way to get rid of contamination in any water distribution system. Unfortunately, this process directly exposes contaminated water to the environment. This contaminated water can end up in agricultural fields, natural water bodies, and even in treatment plants. One solution can be building a contaminant flushing pond to hold that water; however, the use of the pond also involves some environmental impact beginning from its construction phase. A life cycle assessment study has been performed using SimaPro software for both hydrant flushing and contaminant flushing pond processes, and the impacts have been assessed using the IMPACT 2002+ methodology. The results show that decontamination using flushing ponds can cause less environmental impact than decontamination using fire hydrants.

Data availability is a serious challenge for performing life cycle assessment (LCA) for water distribution networks (WDNs). In this context, data refer to two terms, including (a) inventory data in the LCA framework (i.e., primary and secondary) and (b) network data (i.e., lengths, diameters, and materials of pipes in networks). This paper investigated the possibility of performing a reliable environmental assessment for WDNs with incomplete inventory or unknown network data. For this purpose, a state-of-the-art inventory data set with uncertainty bandwidths was composed for the construction of WDNs. Applying LCA to two case studies and systematically overlooking data, the effects of data availability on results were evaluated. It was shown that by conducting LCA for WDNs with only the most essential data, the results are still meaningful. These findings and suggestions on the essential data make it feasible to conduct LCA for WDNs with unknown or incomplete data to explore potential aims for environmental improvements.

An increase in crop water requirement due to surge in population has urged the integration of groundwater with a canal for irrigation in Pakistan. As the cropping intensity grew from 102.8% in 1960 to 172% in early 2010 in certain areas, replenishment of groundwater has been challenged. This caused Lower Bari Doab Canal (LBDC) in Punjab to experience groundwater depletion in the last two decades. Literature reports the rate of depletion that ranges from 0.259 to 0.594 cm per year beyond 1990 in the observation wells in the canal division. This study proposes to analyze the correlation between population growth, crop coverage, and water table depletion rate in the districts irrigated by LBDC: Okara, Sahiwal, and Khanewal. It uses publicly available yearly statistical data published by the Bureau of Statistics, Pakistan. The data sets include population count and area irrigated under four dominant crops (wheat, rice, cotton, and sugarcane), precipitation, and temperature. The study period ranges from 1990 to 2010. There is an ever-growing population in all three districts. A non-parametric Mann-Kendall test revealed an increasing trend in the cultivation of total major crops in the command area. A simple correlation test is performed to relate various climatic, anthropogenic, and agricultural factors with varying depletion rates of groundwater in the districts. Overlaying the observation well locations over districts in GIS, three of them were allocated to Khanewal, two to Okara, and one to Sahiwal. The results show that the spatially variable depletion rates can be explained by the growth of population, cropped area, rainfall, temperature, and evapotranspiration. This emphasizes the need for flexible policies especially targeting the tail reach of the command area. Our study has also pointed out the most severe condition of groundwater lies in Khanewal. Therefore, restriction in the abstraction of water, artificial recharge, and other demand management techniques should be practiced in the region. The results of this study hope to bring awareness regarding the importance of conserving groundwater sources.

Coastal cities are increasingly vulnerable to flooding and shoreline erosion driven by sea-level rise and coastal storm events. Many communities face threats of environmental impacts associated with industrial development along the Texas coast, which places additional stress on residents, infrastructure, and natural resources. Such impacts are visible in the case-study for this project, Ingleside on the Bay (IOB), Texas, a small community located in close proximity to industrial sites in Corpus Christi Bay. In response to sea-level-rise and industrial growth in and around IOB, this interdisciplinary research project applies a participatory mixed-methods approach to (1) identify natural and built assets and challenges based on community input, (2) quantify current and future flood hazards, and (3) synthesize these into climate adaptation pathways. The resulting adaptation pathways highlight the importance of incorporating community input and considering both natural and human-caused drivers of vulnerability when evaluating potential adaptation strategies.

Water distribution networks (WDNs) are vital parts of the urban infrastructure, and their construction, operation, and maintenance incur major investments. Therefore, many different approaches for optimizing WDNs exist. However, when it comes to large real WDNs, computational time becomes a significant factor, as the possible number of potential solutions grows exponentially. This paper discusses a highly efficient approach for Pareto-optimal design of WDNs based on complex network analysis (CNA). A real WDN with about 4,000 pipes (decision variables) was optimized first using a straightforward evolutionary algorithm approach with two objectives being cost minimization and resilience maximization. By systematically investigating topological features of the obtained Pareto-optimal solutions, insights into optimal networks are generated and a new design approach based on CNA is developed, which outperforms the results of the evolutionary algorithm. The proposed CNA approach is then successfully used to optimize a WDN with the same objectives where the evolutionary algorithm approach is computationally infeasible (semi-real case study with 157,040 decision variables).

Different researchers have comprehensively addressed the water distribution network (WDN) optimization design problem in the past years. However, in the analysis of the optimized WDN, the relationship between the geometric parameters of the network and the hydraulic parameters obtained from the optimal design has been set aside. In this research, a robust geometric analysis of optimal WDN designs by pipe cost minimization is made in order to provide a response to the possible relationships between the geometry of the network and its optimized design. In addition, geometrical analysis is performed understanding that water distribution infrastructure, represented as a spatially organized graph, is a complex network of interconnected vertices (nodes) and edges (pipes) that belong to the emerging topic of complex network theory (CNT). Therefore, CNT metrics along with other geometric aspects (e.g., pipe diameter, pipe length, fractality, branch index, among others) of the network are measured for analyzing features of the physical domain where hydraulics and optimization occurs. As a result, it was determined how the effectiveness and efficiency of optimization methodologies are affected depending on the network topology.

Opportunistic premise plumbing pathogens (OPPPs) such as Pseudomonas aeruginosa and Legionella pneumophila, are microbial inhabitants of premise plumbing which can pose a serious risk to human health, and even cause death, mainly but not exclusively in elderly and immunocompromised individuals. Guidance on appropriate measures to control these OPPPs comes from many different scattered sources that are at times inconsistent and conditioned on various characteristics of the plumbing systems. Furthermore, such guidance is usually difficult to implement in practice because of the varying conditions that exist in buildings. Therefore, there is a need of developing a tool that can bring together knowledge from these different sources for building specific requirements and are free from inconsistencies. To address this problem, we have developed a web-based premise plumbing water quality management tool, herein called “plumbing information and performance evaluation (PIPE) decision support tool (DST).” The PIPE tool provides a free resource for water quality management in buildings that takes input from building facility managers and outputs guidance specific to their buildings. The PIPE requires simple user inputs related to the building and its plumbing system’s operational and design characteristics. In response, PIPE will help them assess if a water quality management plan is required for their building and identify those features that need the management most. The output recommendations of the PIPE tool are based on an inbuilt knowledge database on building water quality management guidelines. The database was developed based on summarizing the guidance from 15 important guidance documents that were systematically screened from a large pool of 54 guidance documents from worldwide organizations. The information summarized in the database included reconciling knowledge gaps/inconsistencies, management actions (e.g., use of chloramine rather than chlorine, temperature control, etc.), and water quality metrics with their appropriate levels that ensure water quality in building plumbing systems. Being at the early stage of development, the PIPE DST can be enhanced by beta-testing among the targeted users (i.e., building owners, engineers, facility managers) to identify management approaches customized for specific building types such as hospitals, hotels, and long-term care facilities.

This study adopts the concept of over-pressurizing pipelines to manage blockages and other disturbances in pipelines and expands it to a better, more advanced tool. The suggested approach introduces pressure transients into the system and manipulates it to better control the head pressure at a given point along the pipe. Through controlling pressure changes and patterns, we can imitate given pressure signatures, thus dramatically increasing the pressure oscillation and offering different assault patterns to eliminate disturbances along the pipe. Moreover, that is done while averting extreme devastating pressures that can damage the system’s components and introduce high pressure for a limited period of time. The suggested approach is simulated by the Lagrangian-based wave characteristic method transient analysis model and demonstrated in a case study for different pressure signatures.

This study presents a framework for pressure transient simulation as well as local wall shear stress analysis to manage biofilm growth in water distribution systems. The study aims to disrupt the growth of biofilm colonies attached to the inner walls of pipeline systems. In this approach, the examined systems are subjected to consecutive controlled pressure transient waves. The transient waves are originated by causing sudden changes via valves’ manipulation in the distribution system. It is vital to keep the head pressure confined between the allowed pressure range to ensure the integrity of the system. The transient simulation is done by the Lagrangian-based wave characteristic method transient analysis model; two example applications are explored demonstrating the potential of the suggested approach.

Contamination events in water distribution systems are emergencies which can cause distress in the population and require fast handling of the responsible utility manager. Various models have been built to explore the reactions of all relevant stakeholders during a contamination event or other emergencies and disasters utilizing agent-based modeling. None of them considers the social background and the possibly related psychological states of the affected population. This study proposes to use recent findings during the COVID-19 pandemic outbreak and draw analogies regarding response and reaction to a disaster on a major scale for implementing it in an agent-based model framework for reacting to a contamination event in a water network. A hydraulic simulation is coupled with an agent-based model which consists of consumer agents and a utility manager. Upon detection of anomalies in the water quality, the utility manager places mobile sensor equipment to emulate “contact tracing,” determine endangered areas in the water network, and warn the consumer agents in real time about the geographical spread of the event through, e.g., social media. The consumer agents’ actions are determined according to their social backgrounds, location in the water network, and possible symptoms from ingesting contaminated water by utilizing a fuzzy logic system. Results on an example application suggest that placing mobile equipment and warning consumers in real time is essential as a proper response to a contamination event. Furthermore, social background factors like age or employment status of the population can play a vital role in the response of consumer agents to a water quality contamination event in a water distribution system.

In this research, we investigated the influence of the heating of drinking water in the connection pipe under the influence of nearby district heating and the effect this has on water temperatures throughout the domestic drinking water system (DDWS) of a typical Dutch domestic property. We found that stagnant water in the connection pipe warms up fast, reaching the surrounding ground temperature in about 15 min, and these temperatures can be found throughout the house at taps such as the shower and the kitchen tap. Flowing water in the connection pipe is also, depending on the pipe length, heated up several degrees. The prevention of high temperatures in the soil around the connection pipe is the best measure to prevent high drinking water temperatures at the taps.

New York City (NYC) residents can report their drinking water quality complaints using NYC 311, a local government-sponsored call line and online portal that New Yorkers can use to report issues and request services. There were over 12,305 taste and odor (TO) drinking water quality complaints in NYC between 2010 and 2019. With the baseline data availability, along with annual increases, spatiotemporal analytics and machine learning can play a crucial part in understanding this water quality complaints trend. The objectives of this research are therefore to (1) perform spatiotemporal analysis of observed water quality complaints and identify continuous hotspots; (2) develop deep learning-based time series models to forecast water quality complaints data in NYC; and (3) compare the performance of the models in order to subsequently develop performance improvements. A long short-term memory (LSTM) network and a nonlinear autoregressive neural network (NAR-NN) model were used for the machine learning-based time series analysis. This study will provide an in-depth insight into the effective management of drinking water quality complaints throughout NYC, leading to bolstered strategies for enhanced sustainable drinking water infrastructure management and operations in large urban cities.

Ensuring the distribution of high-quality water from various sources to consumers via water distribution systems (WDS) is critical for guaranteeing public health. While standard water quality parameters are monitored at waterworks, it is still a challenge to monitor water quality in the WDS itself. A large body of research has investigated where to place online quality sensors in a WDS to detect deterioration in water quality. This study expands prior studies and aims to develop a methodology to determine the location of mobile sensor equipment to monitor water quality change in real-time at strategically important nodes in the water network. A graph-theory algorithm is utilized to determine possible paths from and to the node of the contamination detection. Considering the flow directions and patterns over time, the depth-first search (DFS) is used to explore the fate of the contaminant downstream, exclude possible sources, and to place mobile sensor equipment. By computing sub-graphs and clusters, possible source locations are identified for placing multiple grab samplings in strategically optimized locations, so the source can be detected quickly, and parts of the network can be identified as non-contaminated or as endangered of having deteriorating water quality. By utilizing the physical, topological, and hydraulic properties of the water network, a methodology is developed which enables water utilities to react to contamination events while collecting more information on the fate of the contamination downstream and the state of the water network in real time.

When a constituent such as chlorine, fluoride, bacteria, antibiotics, stimulants, depressants, or other pharmaceuticals enter a water distribution system, it spreads throughout the system in various ways. There are many constituents being discharged to water sources through the wastewater treatment plant that are not removed. These are termed “emerging contaminants.” The decay rates of many of these emerging contaminants are not yet known. Their behavior is complex, since a water system is composed of potentially thousands of pipes in various loops at different elevations, pipe sizes, and roughness values being pumped by multiple pumps and stored in multiple tanks. In addition, the rate of user demands at each junction or neighborhood varies throughout the day and night depending on water use habits. These vary in different ways depending on whether they are domestic or industrial use. To understand this better, a modeling study was performed in which the decay rate for various systems was varied and the time for the contaminant to reach locations throughout the system was documented. It was found that the decay rate did play an important part in the time for the constituent to spread. For one system, in particular, it was found that the time to reach a location did not change for decay rates varying from –0.00001 to –0.005 units per day, but values higher than that caused the travel times to decrease quite significantly. When the contaminant reached a storage tank, it took a long time for it to fill the tank and then exit.

For a model to have credibility, it needs to be calibrated against data from the distribution system. While this sounds simple, there are issues that can steer the calibration in the wrong direction. This paper discusses some common pitfalls and how to avoid them. The key to making adjustments to a model to achieve good calibration is understanding why the model and field data disagree. There are many reasons for this disagreement, and a good deal of detective work is usually necessary to find the cause. Once the cause is known, improving better calibration is usually easy.

Bursting and leaks in network components in water supply systems reduce the continuity and regularity of service provision, in addition to increasing water losses besides operating and maintenance costs. Therefore, an important approach is the management of water supply infrastructure by understanding contributing factors to the occurrence of bursting and leaks. Consequently, decisions could be supported by data to contribute to improving performance in water systems. Different approaches have been used to predict bursting and leaks in water distribution networks, such as statistical models, probabilistic models, and machine learning (ML). Thus, the objective of this study is to analyze and propose ML models to predict busting and leaks in water connections, since a significant portion of water leakage occurs in those connections. The following methods were used to predict and classify water connections vulnerability to ruptures and leaks: logistic regression, K-nears neighbors, support vector machine, decision tree classifier, naive Bayes, random forest, AdaBoost, gradient boosting, and XgBoost. The data used in this study were collected from water supply systems in Brasília, capital of Brazil. Altogether, the cadastral base investigated has 543,168 water service connections and has 5,700 km of water distribution network, consisting of materials such as high-density polyethylene, cast iron, and polyvinyl chloride. The infrastructure has been implemented since the 1960s. The historical database on ruptures and leaks in water connections/water service lines covers the period between January 2015 and April 2020. Data regarding possible factors were used such as material, diameter, network implantation year, water connection installation year, in addition to operational pressures of the water distribution network (minimum and maximum pressures, besides pressure range). The best model obtained a score of 0.61, indicating that database needs to be more investigated/improved to assist the distribution network management process, to be used to identify areas that can be assigned to leaks research campaigns or infrastructure rehabilitation. Possibly new features can be introduced to enhance models. The intervening factors were analyzed to comprehend the influence of each component in deterioration process on the case study. In addition, performance obtained by different ML models was compared.

Residential water consumption patterns are important data, and if well compiled, they can be important to establish a leak alerting and to establish detailed water balancing of district metering areas (DMAs). Thus, smart metering (SM) technologies using digital water meters can offer new and efficient processes to water utilities. One of them relates with the possible application of discriminative flow pattern analysis with the comparison of flow pattern distributions (CFPD) method. The CFPD method is a relatively simple procedure that consists in the comparison of the measurements for two different time periods and produces results that can be used to interpret two different types of change in the water consumption pattern: (1) consistent changes which could be related to variations in the population size and weather and (2) inconsistent changes which can be related to increased leakage. This study intended to use the CFPD method to evaluate and interpret the water consumption pattern changes in a smart metering scheme that was conceived in a residential block set located in the city of Brasília, Brazil. The DMA features 420 residential units, and the objective of the SM system was to provide an hour-based monitoring system for individual user-level water consumption. To register unit’s consumption, the water utility installed the infrastructure for radio transmission, data acquisition, and 424 telemetry-equipped water meters: one for each unit, three for the common areas, and one to register the total water inflow into the DMA. With the CFPD application, it was possible to understand changes in the water consumption patterns, relating then with the real losses level and other factors.

The leak repair process is one of the costliest operations for the water supply companies due to the amount of water lost, the customer inconvenience, and the further damages made to the infrastructure. To tackle this problem, a new approach is presented for detecting and prioritizing leaks at a district metered area (DMA) level. The performance of the algorithm is based on the extraction of the most meaningful features of the water flow daily, and the solution predicts the minimum night flow using neighbor DMA data to analyze and filter the noise for detecting and prioritizing leakages. The purposed solution has been validated with real historical data using a subset of 171 similar DMAs with data coming from January 2016 to July 2020. The algorithm was able to detect leakages successfully in nearly 72% of the cases, making around 18% of false positives. In conclusion, the presented approach consists of a full-fledged methodology able to predict the minimum night flow, detect leakages reliably, and prioritize them at a DMA level efficiently and reliably.

The primary goal of the project is to leverage recent developments in smart water technologies to detect and reduce water leakages in large water distribution networks with the aid of neural networks. A cost effective, non-invasive solution to detect leakages in transmission pipelines is needed by many water utilities, as it will lead to significant water savings and reduced pipe breakage frequencies, especially in older infrastructure systems. The eventual goal of the project is to test the ANN model on a real network using field measured pressure and pipe breakage data after tuning and developing the model with simulated data. In this project, we propose building a regression model, based on multi-layer perceptron (MLP) algorithm, which is a class of feedforward artificial neural networks (ANNs) to detect the leak locations within a proposed network. The model should be able to learn the structure, i.e., mapping of various leak nodes and sensor nodes in an area, such that it can detect the leak nodes based on the pressure values with significant accuracy.

As part of the present study, a tool was developed to automatically calculate the energy metrics of a water distribution system and map them, based on an input EPANET hydraulic model file. The tool was applied to a case study system of the Ontario Clean Water Agency (OCWA). Based on the inefficiencies identified with the new tool, an improved scenario was developed by adjusting pump controls and VFD speed settings. These changes led to an increase in energy efficiency and a 6.5% reduction in energy consumption, equating to about CAD$128,000 in annual electricity cost savings. Thus, this methodology can be a low cost solution for small-medium systems to identify electricity conservation opportunities, as opposed to more complex energy use optimizers.

Given the extent of a water distribution system (WDS) and its complexity and dependency on energy, it is important to observe, understand, and quantify the impact of WDS hydraulics on its energy consumption and energy flow. This observation will help to develop comprehensive knowledge in WDS energy management, which will eventually help WDS design and operation. This study observes the impacts of WDS model reduction on WDS hydraulics and hence on energy flow. Adding or removing a node can increase or decrease the number of pipes, and hence it changes the flow pattern and non-linear hydraulics of the system. This study ventures to answer the question how much change in system reduction can cause what amount of change in the system hydraulics and energy flow. The study developed a series of reduced models by removing nodes and observed the impacts of model reduction on system hydraulics and energy flow. Energy balance models have been set up for each of the reduced models separately to accomplish this goal. Results show that the total inflow energy and total outflow energy separately remain the same or fluctuate very minimally for all the reduced models. As the model reduces its size, the pumping energy also decreases but not significantly. However, as the model reduces its size, the pipe friction energy increases significantly compared to the pumping energy as the system average velocity increases even after the total length of the pipe is reduced. In this study, from the original model to the final reduced model, the system average velocity and friction loss increase by 54% and 95%, respectively.

How much water supply can come from a reservoir in Texas in 2030, 2040, 2050, 2060, 2070, and 2080? This is a key question that must be answered in the water planning process in Texas. Current regional water planning rules require regional water planning groups (RWPGs) to use reservoir firm yield, which is the maximum annual diversion from a reservoir at 100% reliability during a repeat of the drought-of-record. Firm yield is traditionally simulated using the Texas Commission on Environmental Quality (TCEQ) water availability model (WAM) Run 3 as an estimate of future water availability, while also considering the effect of future sedimentation within a reservoir. However, most of the TCEQ WAMs use hydrologic input extending from the 1940s to the 1990s, with only a few basins having records extended to recent years. Therefore, there is a need for longer simulations that can cover a range of possible hydrologic scenarios. In this study, we analyze long-term firm yield for Lake Meredith located in the Canadian River Basin. Using a reconstructed Palmer Drought Severity Index (PDSI) data set (extending from 1400 to 2003), we assessed critical drought periods and selected a 14-year drought (with a 600-year recurrence interval) as a potential new benchmark drought for the Lake Meredith watershed. We applied Markov chain Monte Carlo (MCMC) methods to generate a synthetic hydrologic data set (10,000 series) for the future period (from 2019 through 2080) using lag-1 annual drought transitional probabilities generated from, and incorporating the long-term trend in, the naturalized flows upstream of Lake Meredith for the period 1940 through 2018. Net annual reservoir evaporation that corresponds to the annual naturalized flow, projected reservoir capacity, and volume-area rating curves for each planning decade are input to the TCEQ’s Canadian River Basin WAM to simulate 10,000 series of future reservoir firm yield for each decade. Based on the 14-year benchmark drought-of-record, and a 90% exceedance probability, we find that future water availability from Lake Meredith decreases over the planning decades, with about 15 million cubic meters per year in 2030 reducing to about 0.9 million cubic meters per year in 2080. These results indicate an increase in drought risk exposure for the Lake Meredith watershed, given the occurrence of a drought worse than the observed 2010s drought-of-record. The findings could inform a water supply risk tolerance assessment by local water user groups and water planners in the Canadian River Basin.

The accelerating impacts of climate change pose significant threats to the agriculture sectors. On one hand, the rising summer temperature caused by climate change increases the agricultural water demand due to a higher rate of soil water evaporation and higher crop water demands. On the other hand, a decrease in precipitation amounts and timing threatens the availability of water for rainfed and irrigated agriculture. As such, the current patterns in water usage from existing water resources may soon be insufficient particularly during the warm seasons. Hard adaptation strategies involving infrastructure development and expansion, such as agricultural water systems for water transfers and surface water storage, have the potential to safeguard national and international food security. This study presents a conceptual model to simultaneous design, operation, and layout of an agricultural water distribution systems using robust optimization to deal with the uncertainties in the climate-change impacted agriculture water demand models while considering the impacts on crop yields. An integrated assessment model (IAM), involving climate change projections, a hydrologic model, and a crop production model, is used to determine the water demand at each crop field node. The water demands determined by the IAM can have significant uncertainties due to inherent uncertainties that exist in sub-models and input data. These water demand uncertainties are represented by deterministic variability in robust optimization. Meanwhile, continuous water supplies can incentivize the farmers to adapt to a new and higher yield crop rotation. Therefore, water demand at each node is also correlated to the potential yields, which is bounded above by the water rights assigned to each node. We will demonstrate the use and effectiveness of this approach in the agriculture communities of Umatilla River Basin, Oregon, USA, where water rights, environmental laws, Columbia River Treaty, and overused groundwater aquifers constrain water use and distribution for irrigated agriculture.

Water infrastructure, such as wastewater treatment plants (WWTPs), have significant roles in urban systems’ functioning. Their performance is directly related to how resilient they are to face and mitigate hazard/flood impacts. The governmental agencies such as NYCDEP, which are the primary decision-makers in allocating resources to various water infrastructure for improved resiliency, need to see how these infrastructure manage their assets to prioritize limited resources allocation. Therefore, any funding should be in the context of both physical and financial/asset management performances. One of the many methods for quantifying resiliency is in the context of four criteria known as 4Rs (Robustness, Rapidity, Resourcefulness, and Redundancy). This study’s scope is to consider asset management as one of the main attributes of robustness and resourcefulness in flood resiliency of water infrastructure. The proposed framework has the potential to be tested on 14 WWTPs in the coastal city of New York. The resilience improvement of these plants could be estimated and compared with different budgets. The initial results show that by including the asset management plans in the resiliency framework, compared to previous studies, the resource allocation program for each WWTPs could be done more effectively.

Hydropower has been the predominant source of electrical energy supply in Brazil, with significant increasing participation share of thermal and wind power plants. From 2000 to 2012, on average, 91% of Brazilian effective electric generation was provided by hydropower, while the reservoir system operated, on average, at 68% of the active storage. From 2013 to 2020, 73% was supplied by hydropower plants, with only 39% of active storage. Demand increase, delays in expanding the system, and a series of moderate to severe droughts occurred in Brazil over the last eight years have contributed to bringing the power system to its current state of low storage levels and intense dispatch of the thermal plants. The COVID-19 pandemic in 2020 hit the country hard and brought an abrupt reduction in energy demand, with persistent impacts expected for the coming years. On average, 7.5 GW or 9.7% reduction is expected for the next three years in power demand. To deal with the reduction in demand, a well-planned adaptation strategy is urgently needed. It is important to plan how to efficiently combine reduction of dispatching the most expensive thermal plants and recover water levels of reservoir storage and productivity in the complex hydrosystem with over 150 reservoirs. To determine the tradeoff and adaptation strategy, we use the HIDROTERM model, a nonlinear programming optimization model previously developed for planning the operation of the Brazilian hydrothermal system for analysis by comparing results with demand forecasts before and during the pandemic and under different hydrological scenarios.

Permeable pavements (PP) are one of the most flexible stormwater facilities to mimic pre-development flow conditions in urbanized areas. They provide multiple benefits as (1) runoff storage and slowly release, (2) pollutant treatment, and (3) reduce heat island effect due to evaporative cooling. Assessing PP long-term efficiency requires a continuous model to simulate flow routing, evaporation, clogging, and maintenance using high-frequency rainfall and temperature data. The purpose of this article is to develop a PP continuous model and assess the trade-offs among permeable asphalt (PA), permeable concrete (PC), and permeable interlocking concrete pavers (PICP) using the observed climate of San Antonio, Texas, for 1975–2000. The objective functions to assess the long-term effectiveness were the (1) month average treated volume, (2) month average evaporated volume, and (3) drainage layer cost. Solutions were assessed for different scenarios of diameter and number of underdrains and drainage layer depth (i.e., cost), as well as the type of the pavement. Results indicate that PA and PC have nearly the same long-term efficiency, and PICP typically provides less evaporation but can provide more treated volume for more expensive solutions. A PP design with a drainage layer of 30 cm and a 4-in. underdrain was assessed, and results indicate that it can provide, in average, 45 mm of treated volume in October. For this design, no significant difference in seasonality performance was found varying the type of the pavement, indicating that it may only provide marginal benefits for designs with relatively small drainage layer depths.

Rainwater collected from rooftops can be a safe, low-cost alternative source for non-potable water uses, thereby reducing tap water usage. In climates with adequate rainfall during cooling seasons, rainwater can compensate for evaporative water loss in cooling towers. Central chillers and cooling towers play an essential role in removing heat from large commercial, institutional, and industrial buildings. Water losses from evaporative cooling in the towers increase the concentration of minerals in the water system loop, and scaling occurs within the system, decreasing the heat exchange’s effectiveness and damaging equipment. Freshwater must be added to the cooling tower water system loop to make up for water losses. This paper presents a feasibility study on harvesting rainwater from solar panel canopies as an alternative water source for a cooling tower water makeup. A remotely controlled and automatically self-cleaning rain cistern is demonstrated in this study. In addition, a water quality analysis including the concentration of chemicals relevant to cooling tower operation was conducted on tap water and rainwater samples. The results show that the total dissolved solids concentration of the rainwater was significantly lower than tap water, indicating that an increase in the number of cycles of concentration (COC) could be achieved by using rainwater as part of the water makeup source. The predicated COC values for the rainwater/tap water blends were calculated, and the tap water reductions, financial benefits of using rainwater, and the pay-back period of the application of the remote control technology are analyzed in this study.