World Environmental and Water Resources Congress 2019: Groundwater, Sustainability, Hydro-Climate/Climate Change, and Environmental Engineering

The wetlands are unique ecological sites which play a substantial role in the environment relating to its unique characteristics of biology, hydrology, and ecology. Wetlands provide a transition between the aquatic and terrestrial life forms, hence providing huge carrying capacity for all kinds of organisms. Soil plays an important role in any water body right from storage of the pollutant to the release of those pollutants. There are many characteristics of the soil which governs the behaviour of pollutants among them are micro-organisms. The wetland soil is highly saturated with low oxygen content hence it becomes a perfect habitat for diverse bacterial communities. The rhizobacteria are mainly responsible for the leaching of heavy metals from the soil. The low molecular organic acids which were released by the rhizobacteria in the soil helps in leaching the heavy metals, and this leads to one of the characters of bioavailability to the plants. In this study, the soil bacteria have been classified for the wetland in south Chennai, India, regarding its abilities to enhance the phytoremediation process. DNA extraction technique was adopted followed by 16srna in identifying the bacteria. The results yielded eight different bacterial species of Proteobacteria, Firmicutes, and Actinobacteria phylum. The bacterial diversity helps to understand the bioavailability phenomena to the plants and also in finding out the best effective bacteria to use in the bacterial assisted phytoremediation studies.

Assessment of the impact of unconventional gas operations on household drinking water quality is necessary to help minimize community exposure to contaminants from this industry. Household water samples (n=265) were collected from 154 houses in Washington County, Pennsylvania, between 2012 and 2014. Water quality analytes (also found in formation brines) in southwestern Pennsylvania and physical parameters were compared to the density of active unconventional gas wells relative to each household. Approximately 12% of samples were outside the acceptable range of pH for drinking water, but these variances are common in that region due to historic coal mining activities throughout the county. Median lithium values (7.7 ppb) were nearly three times higher than the national median (2.8 ppb). Two analytes (Fe and Na) showed significant (p < 0.05) negative relationships and three analytes (Ba, Li, Sr) showed significant (p < 0.1) positive relationships between sample concentration and the density of gas wells. Correlations may be explained by natural or anthropogenic causes. Overall, the groundwater in Washington County is of good quality, and, based on the results of this study, there was no evidence for systematic deterioration due to the density of gas wells. Further characterization of causal pathways is needed to clarify these relationships.

Effect of daily traffic conditions on air quality in a local neighborhood was investigated. An air quality monitoring apparatus consisting of an on-site air/gas monitor, traffic recorder, and weather station were set up near US-11 Highway to measure the extent to which key air pollutants (CO, CO₂, O₂, and NOx) were affected by vehicular traffic. Over a span of a month, two hundred hours of data, at 10 minute intervals, were collected and included concentrations of key air pollutants, traffic volume, speed, and type, and weather data. Using the traffic and weather information in a dispersion model, concentration of CO₂ were modeled. The modeled results compared well with on-site measured concentrations. This paper evaluated the transportation and environmental factors that contribute to increases in pollutant concentrations. Findings from this study will increase understanding of traffic and weathering effects on neighborhood exposure to harmful emissions throughout the day.

The advantages of natural adsorbents in adsorption of toxic ions from aqueous solution, comprises their low cost, easy handling, abundancy, and environmental-friendly characteristics, cause their expanding application in decontamination processes. In this study, natural calcium sulfate hemihydrate, which is termed as bassanite mineral, has been proposed as a novel suitable adsorbent for iron (Fe³⁺) removal from aqueous solution. The properties of bassanite from Saveh region, located in north-western Iran, was characterized by XRD, XRF, and FTIR. The adsorption capacity of iron onto raw bassanite was investigated as a function of contact time, iron initial concentrations, ionic strength, bassanite dosage, and additive electrolyte (HCl, NaCl, and CH3COONa); so, the optimum condition was determined as using 5 g bassanite, particle size -150 μm at room temperature with iron initial concentration of 1000 mg/L, solid to liquid ratio of 50 g/L, contact time of 60 min, and stirrer speed 600 rpm. Afterwards, in order to enhance adsorption capacity, the bassanite was treated with sodium acetate as a modifier electrolyte. This modification was so appropriate and cause to increase adsorption to more than 95 percent of iron from 1 g/L iron solution. The equilibrium studies have been carried out by the consideration of Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich isotherm models, which displayed that iron adsorption onto raw and modified bassanite were performed favorably and chemically by the homogenous process. Based on Langmuir model maximum adsorption capacity of raw and modified bassanite are 12.66 mg/g and 117.67 mg/g respectively.

This study evaluated the trends and shifts of the ambient air quality standards of the most polluted states and cities of India with respect to air quality parameters, e.g., nitrogen dioxide (NO₂), sulfur dioxide (SO₂), suspended particulate matter (SPM), and respirable suspended particulate matter (RSPM). The choice of air quality parameters was based on the guidelines of the National Air Quality Monitoring Programme of India. Besides evaluating the long-term trends and the major shift points along the last few decades, the study also analyzed the variation in air quality parameters across the seasons since burning of crop residue during certain seasons plays a significant role as a primary source of particulate pollution. Multiple cities within each state were analyzed separately to evaluate their spatial pattern, while each city was also analyzed based on residential and industrial locations. The obtained results were compared against the National Ambient Air Quality Standards of India to determine the air quality status quo. The results suggested considerable variation across the states and among the adjacent cities within the same state. The difference in slope (rate) of the detected trends between the residential and industrial locations was also noteworthy. Post-monsoon and winter seasons showed the higher presence of SPM and RSPM. The obtained results may be helpful for a country like India, which is currently the third largest emitter of greenhouse gases. The increasing rate of diseases related to poor lung functionality across many cities in India can also be correlated with the increasing trends of particulate pollutants. Such analyses, as presented in this study, may also be helpful in the stringent implementation of the Air (Prevention and Control of Pollution) Act of India as well as the air quality monitoring programs.

Stream health can be significantly affected by the type and characteristics of riparian zones along stream corridors. Research is advanced focused on the identification and assessment of habitat, water quality, and flood hazards processes along the main channel and tributaries of Catalpa Creek. Research results would be used to support the implementation of the management plan for this watershed. A study is in progress to compare forested and grassed riparian zones on tributaries within the Catalpa Creek watershed, in order to better understand their effects on stream water quality and health. Water quality is monitored weekly for parameters such as temperature, dissolved oxygen (DO), pH, total dissolved solids (TDS), and turbidity. Temporal and spatial differences in water quality, including changes in temperature, dissolved oxygen levels, and suspended solids will be assessed to determine how they are affected by seasonal changes (i.e. fall and winter) and the riparian zone characteristics (i.e. forested and grassed). Overall, results would help to validate the need for properly maintaining and improving forested riparian zones to provide benefits in water quality and stream health in the Catalpa Creek.

The many advantages to using benthic macroinvertebrates in freshwater biomonitoring are now well known and utilizing them in water quality monitoring has become a common practice around the world. Their ubiquity, diversity, and sensitivity to water quality make them excellent indicators of stream health. A study has been performed to identify associations between macroinvertebrate communities and environmental factors such as water quality along tributaries of Catalpa Creek, Mississippi. The macroinvertebrate demographics of two tributaries of Catalpa Creek were assessed. The pollution tolerance index (PTI) of the sampled stream reaches reported, almost exclusively, an “excellent” rating. However, community abundances showed that many samples were dominated tolerant taxa while the most intolerant taxa (indicators of good water quality) were represented by 1 or 2 individuals. Community analysis also showed that stream reaches were vacant, or nearly so, of scrapers and predators, likely due, in part, to the absence of adequate habitat and other resources. Results of this study highlight the importance of ecological metrics and community demographics in the evaluation of stream health.

The Indian River Lagoon (IRL) is located on the east coast of Florida and is protected from the Atlantic Ocean by coastal islands known as the “barrier-island chain”. The IRL is an estuary that is approximately 250 km long and stretches from Volusia County in the north to Palm Beach County in the south. Its width varies of 0.8 km to 8 km. The IRL watershed has been modified by urban and agricultural development. The main concern is that the IRL system is becoming more eutrophic, particularly in the northern reaches where major algae blooms of long duration (months) are becoming more frequent. A study was conducted to determine the groundwater seepage and the associated nutrient (dissolved nitrogen and phosphorus) loads transported into the lagoon via groundwater at River Walk, Florida, from June 2014 to September 2015. The width of the lagoon at River Walk is approximately 1.56 km. The nutrient loads were determined using the finite difference model SEAWAT which was calibrated by comparing model predicted hydraulic heads with measured hydraulic heads. During the fifteen-month period from June 2014 to September 2015, the groundwater seepages, per unit length of shoreline, ranged between 0.67 m³/day and 0.85 m³/day. The total nitrogen loads, per linear meter of shoreline, ranged from 562 mg/day to 1866 mg/day or 205.1 kg/year per km of shoreline to 681 kg/year per km of shoreline whereas, the total phosphorus loads ranged from 177 mg/day to 248.3 mg/day per meter of shoreline or 64.6 to 90.6 kg/year per km of shoreline. The assessed TN and TP loads due to groundwater showed a high level of temporal and spatial variation, and can be a significant contributor to the eutrophication within the IRL.

As in many of China’s freshwater lakes, Lake Erhai’s water level and surface area have been seriously affected by human activity in recent decades. Eutrophication is a major long-term water quality problem and it is thus essential to understand the underlying mechanisms, identify pollution sources, and analyze the factors governing the nutrient levels and the formation of the algal contaminants. This study investigated various factors affecting the fate and transport of chlorophyll-a and nitrogen and phosphorous related species, focusing on the correlations between these factors and variations in the contaminant levels. Total phosphorus was found to be the determining factor, with non-point sources being responsible for the majority of the total phosphorus in the lake. These findings indicate that establishing artificial wetlands, which are known to be an effective way to remove phosphorus nutrients from non-point sources, around the lake’s periphery could improve the lake’s water quality considerably.

Rapid assessment of water quality at a regular interval is important to monitor changes in water quality caused by manmade and natural interventions. However, large expanse of water bodies cannot be frequently monitored by sample collection and analysed due to economical and practical reasons. In the present study, water samples were collected during Sept 2017–May 2018 from inland water bodies: Narmada River and Reserviors (Bargi, Ukai, and Ujjani), and analysed for various water quality parameters. Two optically active water quality parameters viz., Chl-a and turbidity were correlated with Landsat 8 remote sensing data (LASRC). Surface reflectance values obtained from Band 1(0.435-0.451 μm), Band 2 (0.452-0.512 μm), Band 3 (0.533-0.590 μm), Band 4 (0.636-0.673 μm), Band 5 (0.851-0.879 μm) were used to derive various single and multiple band algorithms to predict these two parameters. Multiple linear regression using B3, B4, and B5 provided good correlation between predicted and actual turbidity data (R²=0.62) with root mean squared error (RMSE) 27.85%. In case of Chl-a, ratio of B1/B3; and B2/B3 correlated well with actual Chl-a data with R²=0.62 and RMSE=34.70% and R²=0.72 and RMSE=23.69% for Chl-a values between 1 and 7 mg/m³, and 5 and 25 mg/m³, respectively. The study revealed that remote sensing data can be used to predict fairly accurate values of turbidity and Chl-a temporally in inland water bodies. Values derived using remote sensing data can be confirmed by sporadic collection and analysis of water samples enabling rapid and economical monitoring of vast water bodies.

The Sustainable Water Initiative for Tomorrow (SWIFT) program is an initiative to replenish the Potomac aquifer system (PAS) using managed aquifer recharge (MAR). The SWIFT Research Center is a 1 MGD advanced water treatment facility producing reuse water suitable for MAR. In order to characterize flow distribution through a multiscreen recharge well and solute travel time, we analyzed tracer breakthrough curves using solute transport models modified using the method of superposition. Distinct breakthrough was observed in the upper and middle Potomac aquifers with travel time varying from approximately 2–37 days over a 50-ft radial distance. Approximately 73% of the recharge was delivered to 3 of the 11 well screens. Recharge flow to the lower Potomac aquifer was negligible as indicated by relatively slow breakthrough. Breakthrough curves were affected by recharge stoppages during the initial evaluation period with some screening locations exhibiting abrupt changes in specific conductivity during stoppages. Results of the initial groundwater recharge efforts are presented, including implications for full-scale implementation of SWIFT.

This paper presents an assessment of two-layer, depth-averaged Richards equation model (DARE) under various soil texture and boundary conditions by comparison with HYDRUS predicted depth-averaged volumetric moisture content. DARE was assessed for three soil textures for two layered soil profiles subject to different fluxes and prescribed pressure conditions at the soil surface combined with zero-pressure head and free drainage bottom boundary conditions. The results showed that DARE had good response with prescribed upper boundary condition. It predicted average soil moisture contents under free drainage bottom boundary condition matched well with HYDRUS predicted results. With zero-pressure head bottom boundary condition, DARE matched well with HYDRUS for shallow soil depth. However, the discrepancies increased with deeper second layer depth. Considering its efficiency and reliability, DARE can be a robust methodology for large scale applications where only average moisture content of few soil layers are needed.

In the United States, the population density of coastal shoreline counties is over six times greater than the corresponding inland counties. In 2010, 123.3 million people, or 39% of the nation's population, lived in counties directly on the shoreline. This population is expected to increase 8% from 2010 to 2020. The quality of the water in rivers that brings runoff water to coastal areas often does not reach the required standards to be used as a source for drinking water treatment plants due to technical and economic reasons. Therefore, groundwater is the preferred source to meet ever increasing water demand by growing populations in coastal areas. Higher groundwater withdrawal in coastal areas results in higher saltwater intrusion. This project explored electrokinetic barriers against saltwater intrusion at a lab-scale. Specific experimental procedures were adopted to have a uniform background among all experiments in order to focus on measurement of experimental variables. Efficacy of applied voltages, pH levels, and types of electrode materials were studied in creating a barrier that allows water and selected ions to pass through, but blocks certain ions in a way that reduces the salt intrusion and protects ground water. Porosity of sand, salt concentration, separation of electrodes, and water content of sand in experimental setup are some of variables that influenced the way experiments were conducted as a part of this study. The poster provides a graphic summary of experimental methods and results of this study.

Inland precipitation and sea level rise (SLR) are stressors that may affect coastal regions worldwide. Flooding is the main consequence of inland precipitation and SLR, and therefore, local and regional governments seek solutions for adaptation through effective storm and tidal water management. Challenges in coastal environments include topography, extreme hydrologic events, tides, subsurface geology, and surface-ground water interactions. The goal of this study was to support a larger research goal that pursues a fundamental understanding, including coupled-groundwater-surface mathematical models, of the potential of dike-like subsurface barrier systems as adaptation strategies in coastal urban areas of different subsurface characteristics. This paper presents preliminary results from experiments using a laboratory-scale physical model and their analysis and verification with the numerical flow-net model SEEP/W (from GeoStudio) that simulates seepage flow under subsurface barriers; results were then used to forecast flow conditions at realistic prototype scale conditions. Experiments and computational simulations, herein reported, focused on the subsurface of the barrier island sandy formation of the city of Miami Beach, FL. The specific objective of the study was to assess the effect of the depth of subsurface barriers on the Darcy’s velocity and seepage flow. At pseudo-state state seepage conditions, various hydraulic head drops across the barrier headwater were tested to represent selected ponded conditions at the city of Miami Beach, including sea level rise. Seepage and Darcy’s velocity were determined in the area of flow between the toe of the barrier and the bottom of the tank, along an averaged pathline of the seepage flow, and used to observe the effect of deeper depths of the barrier.

The injection of heated water into an aquifer produces a thermal plume that travels through the aquifer. If the aquifer contains temperature-sensitive receptors, such as an extraction well for drinking water or cooling water, or a discharge point that feeds a temperature-sensitive ecosystem, the location of the injection point should be chosen to ensure that the groundwater temperature at the receptor does not increase by more than an allowable threshold. The adjoint method is an efficient tool for identifying allowable injection points. In the adjoint method, information is propagated upgradient, against groundwater flow, from the receptor to all possible injection locations. Thus, the results of one adjoint simulation can identify all possible injection locations for which the temperature change at the receptor would remain below the threshold. This work demonstrates the use of the adjoint method for identifying allowable injection points of heated water.

An aquifer pumping test in a hypothetical groundwater system is evaluated by calibrating a three-dimensional groundwater model using drawdown data from a 72-hour pumping test followed by a recovery period. Two different approaches are undertaken in estimating hydrogeological parameters (hydraulic conductivity and specific storage): 1) a zonation approach where there is prior knowledge of the spatial distribution of hydraulic conductivity; and 2) there is no knowledge of how hydraulic conductivity varies spatially. Both approaches use an inverse parameter estimation modeling code. In the first case, a limited number of parameters are estimated using zones delineated on the basis of spatial trends in lithology. The second case involves using pilot points, where pilot points are distributed evenly and at regular distances across the three layers of the groundwater system with each pilot point representing a hydraulic conductivity or specific storage value. A total of 14 parameters were estimated using the zonal approach by fitting the pumping test drawdown and recovery data against the simulated values and parameters compared against known values. Using the pilot point approach, a total of 506 pilot points was employed. In both cases, the simulated drawdowns closely followed the observed drawdowns in all 10 wells. The pilot point approach provided a heterogeneous distribution of parameters with more confidence of the estimates within the radius of influence of the aquifer pumping test. Overall, parameter values estimated using zonal approach were more accurate than those estimated using the pilot point approach, which indicates the value of even qualitative prior knowledge.

In Northwest Indiana, large number of septic systems are used in homes that are not connected to sanitary sewers. Septic system maintenance is very essential to avoid groundwater pollution. If the periodical maintenance is not properly done, it leads to the public health issue because poorly maintained septic systems results in groundwater contamination. As an education and outreach efforts, USEPA conducts awareness activities such as “Septic System Awareness Week”. In this research, as a user-friendly tool, a 3D septic system model was created. It will be a very useful tool in education and outreach activities. This model was developed in the Unity 3D game engine platform. Using the specifications provided in the Indiana State Department of Health document, this model was built. This tool also has a demonstrative groundwater contamination plume movement near the flow fields to show the users about the contamination progress with time. Users can move around the model and understand various components, maintenance efforts, sludge built up with time using this tool.

Las Vegas have undergone significant development in the past two decades in the form of pavements and buildings. Surface energy of the city has changed due to urbanization that plays crucial role in urban heat island effect and in altering the energy for evaporation and transpiration. It indirectly contributes to the urban hydrological cycle. Role of urbanization on the surface energy balance is an active area of research. The objective of this study is to relate surface energy fluxes (net radiation and soil heat flux) to urban land cover. The changes of buildup and vegetation land cover between pre-urbanized and urbanized conditions are analyzed for their impact on surface energy budget in the Las Vegas city. Changes from rural surface to four land use classes including residential, commercial, vegetative turf, and parking areas are considered. The surface energy balance algorithm (SEBAL) is used with Landsat data to estimate surface fluxes including net radiation and soil heat flux density. The land surface characteristics including normalized difference vegetation index (NDVI), land surface temperature (LST), and albedo are analyzed. The time frame of the study is 2002 to 2017 which coincides with implementation of water smart landscape (WSL) program in Las Vegas. WSL is a rebate program that has promoted xeriscaping thus reducing the vegetation turf and urban water demand. The results reveal increase in net radiation and reduction in soil heat flux due to land cover change from rural to urban. These are related to the surface albedo and potentially the cause of decrease in temperature.

Variations among the different precipitation intensities can be quite large. Analysis of annual precipitation data without the consideration of different precipitation intensities, especially the heavy precipitation events, may lead to misinterpretation of precipitation variation. In order to make clear the spatial-temporal behaviors of heavy precipitation events in recent years in Loess Plateau. Daily precipitation recorded at 161 precipitation stations between 1980 and 2017 were selected. Nonparametric Mann-Kendall test was employed to test the changing trend of precipitation. Results showed that the spatial distribution of heavy precipitation events can be quite different for the entire Loess Plateau. The contribution of heavy precipitation to the annual total precipitation is approximately 43~52%. The amount and days for the heavy precipitation both increased for the most areas of Loess Plateau in recent 38 years. Moreover, Mann-Kendall test shows a pronounced change toward more precipitation in the northern Loess Plateau, and higher intensity in southern Loess Plateau. Higher risk exhibited in areas of northern and southern Loess Plateau, which should raise concern. More soil and water conservation measures and practices could be implemented to reduce the negative impacts of flood or erosion events.

The impact of climate variability has raised itself as a very challenging issue to the present generation. For assessing this, it is needed to quantify the climatic changes in terms of different hydro-meteorological parameters like rainfall and temperature, as they are the key factors responsible for drought-like or intense flooding situations. In this study, the temporal variability in precipitation and average temperature over a period of 102 years (1901–2002) has been investigated over Bilaspur District, Chhattisgarh, India. The statistical non-parametric Mann-Kendall test has been utilized to detect the monotonic trend whereas, Theil-Sen estimator test was applied to quantify the rate of change at monthly, seasonal (winter, pre-monsoon, monsoon, and post-monsoon), and annual scales. The results reveal for the precipitation trends to be increasing for most of the months and seasons, although they are not significant except for March, May, and pre-monsoon season. The annual rainfall over the district has increased by 10.65% during the past 102 years. The average temperature was found to be significantly decreasing for monsoon season and increasing for non-monsoon seasons. The annual average temperature has increased by 1.44% from 1901 to 2002. This study will be helpful to the local stakeholders and policy makers to encompass the climatic variability aiding to effective decision making for proper water management.

Increasingly, engineers must make estimates of discharge associated with a particular risk (or set of risks) to design a hydraulic structure or stormwater management facility considering potential climate change. As part of a national cooperative highway research program (NCHRP) study “Applying Climate Change Information to Hydrologic and Hydraulic Design of Transportation Infrastructure,” the authors examined issues and proposed strategies for adapting downscaled global climate model (GCM) precipitation outputs as inputs to rainfall/runoff models used in hydrologic design. This paper describes the recommendations for estimating projected precipitation based on the downscaled outputs of GCMs. It provides actionable guidance for estimating projected daily precipitation data for use in rainfall/runoff modeling for many applications. It describes a 10-step procedure that includes selection of a portfolio of downscaled GCM outputs using alternative greenhouse gas scenarios. The procedure describes a method for using GCM-based information in conjunction with historical precipitation for estimating projected precipitation. The procedure generates estimates of mean values and confidence limits for each scenario. Finally, the paper illustrates derivation of sub-daily precipitation estimates and discusses the limitations of—and alternatives to—these methodologies.

The spatial distribution of alpine snow is largely governed by topographic complexity through shading of solar radiation and wind redistribution. While radiative shading is relatively consistent between years, wind redistribution is more variable, capable of producing anomalous areas of deeper snow that can persist into the late-summer and early-fall months. In a warmer future climate, we hypothesize that snow will become wetter and heavier than in the current climate, leading to less wind redistribution and a more homogeneous snowpack. This study seeks to investigate how the relative degree of snow redistribution will impact total streamflow generation in an alpine environment. A distributed hydrologic model is applied together with remotely sensed spatial estimates of snowpack in order to quantify the impact of spatial variability of snow water equivalent on streamflow. Preliminary findings for the Green Lakes Valley within the headwaters of the Boulder Creek watershed in Colorado, 2001–2014, show that more uniform snow distributions lead to earlier melt-out of 47 days on average and tend to produce less overall streamflow, with maximum decreases as large as 9.5% relative to the natural case. Overall, this analysis aims to provide insight into how warming-mediated changes in snow distribution will impact water resources in critical streamflow generating headwaters catchments.

The local relative sea level rise in Galveston Bay consists of global and local mean sea level rise due to global warming, local bedrock subsidence primarily due to tectonic plate motion, primary consolidation subsidence due to groundwater withdrawal from uncemented or semi-cemented aquifer systems, and secondary consolidation subsidence due to geo-historical overburden pressure of the aquifer systems. The global and local mean sea level rises are 1.70 and -0.27 mm/yr., respectively. The bedrock subsidence was estimated to be 2.41 mm/yr. based on GPS measurements. The primary consolidation subsidence at Galveston Pier 21 was considered to zero because groundwater level has been managed to be stable in trend since 2000. The local secondary consolidation subsidence was estimated to be 2.67 mm/yr. with time. The annual mean relative sea level in Galveston Bay was projected to rise to 0.66, 0.97, 1.67, and 2.48 m in 2100 for the lowest, intermediate low, intermediate high, and highest scenarios, respectively. Compared to the annual mean sea level of -0.04 m in 2000, the relative sea level was projected to rise 0.70, 1.01, 1.71, and 2.52 m in the 21^st century for the lowest, intermediate low, intermediate high, and highest scenarios, respectively. In the projected relative sea level rise values in the 21^st century, LS accounts for 72%, 50%, 30%, and 20% for the lowest, intermediate low, intermediate high, and highest scenarios, respectively.

Intensity-duration-frequency (IDF) relations are essential for estimating extreme rainfalls for design of various hydraulic structures. The construction of these relations represents however a challenging and tedious task since it involves the uncertainty analysis of different probability models and the frequency analyses of a large amount of extreme rainfall data for different durations at a given site or over many different locations. This paper proposes hence a decision-support tool, herein referred to as SMExRain, that can readily be used to identify in an objective and systematic manner the most suitable distribution(s) for accurate and robust estimation of design rainfalls. In addition, in the context of a changing climate, the proposed tool include a statistical downscaling procedure for describing the linkage between climate predictors given by global climate models and the daily and sub-daily extreme rainfalls at a given site. Results of an illustrative application using climate simulations from different global climate models and extreme rainfall data for Ontario region, Canada, has demonstrated the accuracy and practical usefulness of the SMExRain for establishing reliable IDF relations at a given site for present and future climates.

Climate change impact analysis applies dynamic and statistical downscaling of meteorologic data which can be highly uncertain due to both hydrologic model and climate model uncertainty. It is crucial to assess model performance such simulations over an historical period and uncertainty for projections of future stream flows under climate change. Calibrated precpitation-runoff modeling system (PRMS) models for two watersheds in New Jersey were used. The objectives were to generate FDCs for the period for water years 1956–2005 and assess model performance for observed stream flow, simulated stream flows driven by observed data, and GCM driven simulations. The projected impact of climate change on FDCs for the period 2069–2099 was also analyzed. PRMS simulations were able to simulate the FDC and the annual variation of FDCs within each basin. Annual FDCs for dynamically downscaled simulations over the historical period fell within the range of observed annual FDCs. Analysis of the FDCs for dynamically downscaled simulations indicated that these hydrologic simulations can be used with some confidence to assess potential changes in FDCs under climate change.

A new methodology is implemented to obtain the probability density function of the water table height in the subsurface stormflow process, while considering the hydraulic conductivity as a random function. The methodology incorporates the Boussinesq equation that describes the subsurface stormflow process into a Fokker-Plank equation, which estimates the evolution of the probability density function of the water table height through time in a single realization. The results show that the new methodology performs quite well comparing the ensemble average behavior against the Monte Carlo approach.

Surface currents in large lakes are important for water quality and ecosystem processes since they drive nutrient transport. In this study, the individual effects of wind and stratification on surface currents are analyzed in a large lake, Lake Ontario. A state-of-the-art numerical model is applied to explore effects of a common wind scenario (6 m/s eastward) and stratification on surface currents, and their interactions with tributary plumes. For a non-stratified lake, eastward wind accelerates the surface velocities by maximum 23.5 cm/s in nearshore areas, while its effects on current direction are not obvious in the nearshore areas. In mid-lake regions, wind could change the current directions by about 100 degrees counter-clockwise. This eastward wind accelerates the propagation of the Niagara River plume, but decreases its width and bulge area at the river mouth. Lake stratification increases surface velocities in offshore regions and decreases velocities in nearshore regions. The changes of surface current direction by stratification are within 68 degrees in most areas. Tributary plumes are strongly affected by surface currents and the unusual westward Niagara River plume observations could be explained by currents caused by unusual westward wind conditions. Predicting changes in surface currents caused by wind and stratification is important for understanding nutrient dynamics and shedding light on ecological problems such as algal bloom occurrences.

Precipitation intensity-duration-frequency (PREC-IDF) curves are a standard tool to derive design floods for hydraulic infrastructure. In snow-dominated regions, where a large percentage of flood events are caused by snowmelt and rain-on-snow, precipitation alone can be a poor predictor of flood risk. Meanwhile, anthropogenic climate change is expected to intensify the hydrological cycle and alter hydrologic extremes, potentially increasing the likelihood of infrastructure failure in their design life period. To enhance future hydrologic design, we propose next-generation IDF (NG-IDF) curves with consideration of both snow process and climate nonstationarity. The NG-IDF curves, which characterize the actual water reaching the land surface (melt+rain), use of the concept of “water available for runoff” rather than “rainfall” for hydrologic design. This paper demonstrates that in the mountainous regions of the western United States, the standard PREC-IDF curves without considering snow process can substantially underestimate the input water intensities and the consequent peak design floods (i.e., the PREC-IDF curves may lead to underestimation of peak design flood by as much as 324%). Under a warming climate, we also observe statistically significant declining trends in both snowpack mass and extreme water available for runoff across the mountainous regions of the western United States from 1979 to 2017, supporting the proclamation that “stationarity is dead” and demonstrating the need to develop nonstationary NG-IDF curves for future hydrologic design.

In the western United States, understanding the spatial distribution and magnitude of alpine snowpack is crucial for the prediction of water resources. However, ground observation networks are sparse, and snowpack models are often poorly-constrained by these observations. Spatially-continuous satellite data are available, yet only snow covered area (SCA) is easily monitored through this approach, despite the need for volumetric water content of the snow, or snow water equivalent. In this study, we investigate the potential to create spatially-continuous, computationally-efficient SWE maps that leverages in situ and remotely sensed snow information to improve understanding of spatial snowpack distribution across the West. A statistical model that integrates in situ and remotely-sensed snow disappearance observations for bias-corrected, spatially-continuous estimates of date of snow disappearance (DSD), with in situ peak SWE, distributed meteorology, and terrain data to produce a topographically-aware, annual estimate of peak SWE at a 500-m horizontal resolution. This lightweight, observationally-based snowpack model can be used to generate a high-resolution SWE dataset over large spatial areas useful for the development and validation of large-scale hydrologic models across the snow-dominated western U.S.

Historically, water quality analysis and water management planning have been dependent on accurate assessment of baseflows. Understanding the relationship between oceanic-atmospheric variability and baseflow changes in the continental United States that is beneficial for water resources management is the focus of this study. Baseflows obtained from unimpaired daily streamflows at 574 stations in the United States for a 44-year period from 1970 through 2013 are used in this study. Temporal windows that coincide with the phases of North Atlantic oscillation (NAO) and El Niño-Southern Oscillation (ENSO), are used to evaluated changes in the baseflow extremes and characteristics. Statistically significant changes are evaluated using a non-parametric rank-sum test. Based on a preliminary analysis of results obtained nonparametric tests indicate the spatially varying influence of ENSO and NAO on baseflow in the United States. The warm phase of the NAO has contributed to higher median baseflow in the Souris Red Rainy, Upper Mississippi, Arkansas-White-Red, and Missouri Basin, but the cold phase of ENSO isconnected with higher median baseflow in these regions. The warm phase of the NAO and the cold phase of the ENSO are associated with higher median baseflow in the northwest region of the United States. Improved knowledge of oceanic-atmospheric variables with regional baseflow variability may help in baseflow prediction studies and regional water quality management.

Snow surveys have been conducted by the U.S. Army Corps of Engineers New England District flood risk mitigation projects since the 1960s. Currently there are 93 snow courses for the 31 projects across the district’s five major river basins: the Connecticut, Merrimack, Housatonic, Thames, and Blackstone. These snow courses were established with the purpose of monitoring the snowpack for flood potential. Snow courses in eastern Vermont, southwestern New Hampshire, and south-central Massachusetts were compared for snow water equivalent (SWE) and analyzed for temporal trends. Generally speaking, the yearly peak snow water equivalent values range from zero to 31.7 cm (12.5 inches). Characteristic of the region is the possibility of a single rain-on-snow event melting the entire snowpack, causing flooding in vulnerable areas and impacting life and property. The characteristics of SWE within each basin are presented as well as the evidence for temporal trends.

In a country India, in the most of the regions, almost 80% of the annual precipitation is concentrated during monsoon months. As a result, the inflows in the river for the water resources projects are also concentrated in the monsoon season (i.e. June to October). So, analysis of the climate change causing impact on rainfall pattern bears importance for the safe operation of the hydraulic structures and also, for water and food security. The impacts and extent of changing climate varies region to region. In this study, the climate change is assessed by the analyzing the meteorological parameter, rainfall in Watrak and Mazam river watersheds in Sabarmati River basin of India. It is analyzed through Mann-Kendall test that there is an increasing trend in the annual rainfall in watersheds of Mazam and Watrak River, and monthly trend for the month of July and August shows increasing trend. Also, analysis indicate increase of intense rainfall in the month of July and August, and shifting of the monsoon season to start and finish late.

In a country India, in the most of the regions, almost 80% of the annual precipitation is concentrated during monsoon months. As a result, the inflows in the river and inflows available for the water resources projects are also concentrated in the monsoon season (i.e. June to October). In view of the changing climate, analysis of changing rainfall pattern bears importance for the safe operation of the hydraulic structures and also, for water and food security. In this study, monthly time period of the monsoon season and annual rainfall trends have been studied to assess the impact of climate change in the region. The monthly rainfall data series from 1970 to 2016 (47 years) have been made available for the raingauge sites in the Unch watershed of Orsang River. The Orsang River is a tributary of the Narmada River in the Gujarat State of India. The monthly and annual rainfall data series trend analysis has been carried out for these raingauges installed in a Orsang River basin. Four raingauge stations namely, Kalarani, Sanjuli, Vora, and Dhandhoda are installed in the Unch watershed of the Orsang River basin. Sanjuli and Dhandhoda are located in the Chhota Udepur Tehsil of Vadodara District, while Kalarani and Vora are located in a Sankheda and Tilakwada Tehsil of the Vadodara District respectively. It is summarized that the climate change impacts on the small-regional scale study area confirms the increase in the annual rainfall magnitude, decreasing June month rainfall, increasing July month rainfall, decreasing in the August month rainfall magnitude, decreasing in the intense rainfall in the month of August, and shifting of the monsoon season to start and finish late.

Sabine Pass is a small coastal city along the coast of Mexico Gulf in Texas. It is located about 70 miles northeast from Houston where the maximum land subsidence is about 10 ft. due to groundwater withdrawals. No significant groundwater was developed in the shallow unconsolidated aquifers in the Sabine Pass area. The monitored and simulated groundwater level was not changed in this area. Thus it was assumed that there is no significance land subsidence due to groundwater withdrawals in this area. The NOAA sea level monitoring data at Sabine Pass was employed to analyze historical sea level rise (SLR) and project future SLR for verifying the SLR projection in the Galveston-Houston region. The relative SLR trend of the station is 5.80+/-0.77 mm/year based on monthly mean sea level data from 1958 to 2017, which is the sum of global mean SLR 1.70 mm/year, local mean SLR -0.04 mm/year, bedrock subsidence 2.41 mm/year, and secondary consolidation subsidence 1.73 mm/year. Relative SLR at Sabine Pass was projected for four different IPCC scenarios by the year 2100, of which, the lowest SLR is 1.90 feet (0.58 m), the intermediate low is 2.95 feet (0.9 m), the intermediate high is 5.25 feet (1.60m), and the highest is 7.87 feet (2.40m) based on the values of global SLR acceleration for the four scenarios from IPCC. This preliminary result can verify a projected relative SLR in a range of 0.66 to 2.48 m for the four scenarios in the Galveston-Houston region.

Effect of the climate change on rainfall characteristics varies spatially and must be quantified locally for optimal natural resources management. An attempt has been made to analyse the dependability in annual and monsoonal rainfall data over Eastern Ganga Canal (EGC) command area, India, for entire century, i.e. 1901–2012. The daily gridded (0.25°×0.25°) rainfall data prepared by the India Meteorological Department (IMD), Pune, are used. Long term data series are scaled to annual and monthly level. Total 12 grids of IMD rainfall data covering entire command area were selected in this study. Analysis for dry and wet year on annual scale along with five year moving average was carried out for all the grids as well as for entire command area. The analysis revealed that the chances of occurrence of wet year are more over chances of occurrence of dry year in the entire command area by the ratio of 14:13. However, data of last one and half decade has contradictory trend with higher changes of occurrence of dry year to very minimal chances of occurrence wet year over the command area. Dependable rainfall at various probability level has been estimated by employing gamma distribution analysis over the annual and monsoonal rainfall data. It was observed that mean annual and monsoonal weighted rainfall over entire command (1,165.93 mm and 901.95 mm, respectively) is much different than the 75% dependable rainfall values (985.48 mm and 727.54 mm, respectively), which generally must be used in any planning activity.

Climatic variability of a region depends on various hydrological parameters like precipitation, evaporation, temperature, etc. In addition to this, the changes in land use-land cover (LULC) patterns can also have an impact on the climate over an area. The present study aims to observe the effect LULC changes in the runoff yield (calculated using soil and water assessment tool), from Wainganga Basin situated in Maharashtra State of Central India. The potential impact of rainfall in the near future of study area has been carried out using rainfall trend analysis along with flood frequency analysis. LULC data was obtained from Goddard Earth Sciences Data and Information Services Center (GES DISC) and rainfall data, during a period of 1913–2013 (101) years was procured from India Meteorological Department (IMD). The transition of land cover to land use is dominating in the recent past as there is considerable reduction in area of surface water resources and increase in fallow land. A separate study was conducted to analyze groundwater stability of the study area using inverse distance weighting interpolation (IDW). The study reveals that, the impact of LULC changes should not be pretermitted as it has a control over the hydrologic responses of an area.

The aim of this study is to examine uncertainty in projections of streamflow and water quality (TSS load) under the impact of changing climate in the Dong Nai River Basin, which is one of most vulnerable areas to climate change in Vietnam. Uncertainty associated with different general circulation models (CanESM2, CNRM-CM5, HadGEM2-AO, ISPL-CM5A-LR, and MPI-ESM-MR), emission scenarios (RCP4.5 and RCP8.5), statistical downscaling techniques (delta change method, SDSM, and LARS-WG), and hydrological models (SWAT and HSPF) was considered. The results indicate that the largest uncertainty source is come from GCMs simulations, followed by the emission scenarios, statistical downscaling methods, and hydrological models. Consequently, it should pay more attention to apply different GCMs when implementing studies on the hydrological impact of changing climate.

The river Gorai is the largest perennial distributary of Ganges and only major source of fresh water for south western part of Bangladesh. Diversion of water from Farakka barrage has resulted in low flow in Gorai which ultimately led to severe increase in salinity in the whole southwestern region. This research work aims at developing a salinity model and the statistical analysis of trend of variables (discharge, water level, and cross section) for over past 40 years. Afterwards a model of salinity condition forecasting is developed focusing on 1D computer flow and salinity modeling of the Gorai River by HECRAS and calibrated with best possible value of Manning's 'n' and dispersion coefficient ‘D’. Results show decrease of flow and increase of salinity over time. Projects taken up so far are unable to deliver a long term solution.

Communities across the globe are grappling with identifying pathways to increase resilience to natural hazards due to increased frequency and intensity of hazards caused by climatic change. Regional collaboration among communities can be challenging but when successful, can leverage limited resources to achieve maximum benefit. The coastal area of the state of Connecticut, USA, encompasses 24 towns (approx. 45% of state’s population) and was hard-hit during both Tropical Storm Irene (approx. $200M damages) and Sandy (approx. $360M damages). To envision and advance a resilient path forward, The Nature Conservancy engaged with core regional partners to develop regional frameworks for resilience. An essential component of these frameworks included a geospatial database populated with resilience-building projects, hosted on a public-facing website. This resource allows communities and individuals to visualize a suite of resilience-based projects across the entire region and promotes multi-jurisdictional and cross-organization collaboration and partnership, with implications for regional planning, environmental efforts, and funding opportunities. The geospatial database development identified numerous natural infrastructure projects that reduced risk to infrastructure, strengthened ecosystems, and enhanced a public amenity (i.e. “resilient triple bottom line”); however, many of these projects employed approaches that are still unfamiliar to the public, municipal officials, regulators, and practitioners. Conceptual designs were developed to both provide visualization of nonconventional alternatives and assist with obtaining funding for full design and construction of high-priority projects. This regional resilience framework approach has been implemented across the Connecticut coast, and the process can be readily adapted in other communities and scaled to the resources available to advance resilience both locally and regionally, in the USA, and internationally.

The urban area of Las Vegas expanded rapidly between 1990 and 2010 covering large areas of native desert landscape with urban materials. These alterations to the surfaces change the thermal processes in the immediate region. In this research, we study the relation between air temperature and surface temperature in Las Vegas by comparing ground weather station temperature data to land surface temperature images from the Landsat thematic mapper. Urban heat island intensity (UHII) is estimated based on noon and midnight air temperature. The thermometric air and remotely sensed surface temperature are related and used to interpolate UHII for Las Vegas. The resultant UHII map was compared with Landsat 5 true color composite images and a 2006 tree canopy coverage created by the Southern Nevada Water Authority. We find that places with strong UHII typically have less urban development and sparse vegetation. New residential developments in an arid region with high surface vegetation have a cooling effect on the temperature. Averaging the UHII values in areas with similar land use zones show that industrial and commercial areas average a UHI index value that is 0.3 greater than residential land use zone.

Drinking water treatment, integral for ensuring public health is an energy-intensive process. Increasing population and pollution levels compel water sector to incorporate design practices that help achieve sustainability of water operations. Incorporating renewables such as wind and solar energy into a drinking water treatment plant (DWTP) operations can help offset the energy consumption of the treatment process and lead to reduced carbon emissions into the atmosphere. The southwestern U.S. possess tremendous solar and wind resources. The purpose of the current study was to conduct a techno-economic assessment of using solar photovoltaics (PV) and wind energy for a DWTP to reduce its dependence on the traditional thermoelectric power generation. A DWTP, treating 0.34 Mm³day^-1 of river water using conventional filtration, located in southwestern U.S. was selected. System advisor model (SAM) was used to conduct the techno-economic assessment of using solar PV and wind energy in standalone and grid-connected mode for the location of Pheonix, Arizona. Results showed that using PV (570 kW capacity, battery storage 76.5 MWh) and wind energy (600 kW) can successfully offset the energy consumption of the selected plant. Available acreage of the plant was found to be sufficient for PV and wind development. Net present value was found to be positive. The methodology used in this study can be applied to other treatment plants in the region, to incorporate renewables and attain energy sufficiency.

In an effort to prevent global food waste and create a renewable energy source, the goal of this project was to design a residential, batch-scale, anaerobic digester for the purpose of converting food scraps to methane to be used as biofuel. A senior design team at Mercer University designed and constructed an 18.9-L anaerobic digester that could be built by the average homeowner. The anaerobic digester was monitored over 5 weeks. Plant-based food scraps were blended with anaerobic sludge obtained from a local wastewater treatment facility at a 7:1 ratio to create the feedstock to the digester. An automated mixer was used for mixing the digester. The temperature was held at between 35–38°C using aquarium heaters and heating tape. The substrate within the digesters was monitored biweekly for changes in BOD, COD, and TVS. Gas production and composition was analyzed weekly using a GEM 2000 landfill gas analyzer. Methane production eventually ceased as the pH within the digester dropped below 6.8 creating an uninhabitable environment for methanogenic bacteria.

This paper presents a new water infrastructure performance index (WIPI) for the United States for the period 1990 to 2016. The ultimate goal is to provide a useful tool for the development of water infrastructure investment strategies and policies that support and encourage economic growth/competitiveness based on performance. The proposed WIPI utilizes publicly available data for the supply, quality of service, and utilization of the nation’s water infrastructure. A range of attributes were considered, including the availability of drinking water, sewer overflows, and boil orders for drinking water, and appropriate weights assigned based on stakeholder surveys. The outcomes are intended to capture and track the overall performance of U.S. water infrastructure systems over time, as well as demonstrate the relative contributions/connections within each criterion. The results for the study period revealed far from ideal conditions, albeit accompanied by a gradual improvement, but more attention is required if the U.S. water infrastructure is to deliver a solid performance that supports both economic competitiveness and public well-being.

In this study, the environmental benefits and the feasibility of utilizing landfill gas as an alternative source of energy from two landfill sites of Bangalore and Mysore are evaluated. Bangalore generates around 4,500 tons of municipal solid waste (MSW) per day and the majority of this is collected and disposed in landfills. About 2.1 million tons of MSW is estimated to be dumped in one of the prominent dumpsites in Bangalore during its active phase (between 2008 to 2014). The landfill in Mysore has a waste intake capacity of 32.8 kilo tons per year and is in operation since 2012. The landfill gas emissions from the above landfill sites are estimated by using LandGEM-3.02 version. The methane generation rate constant (k) and the potential methane generation capacity (L₀) are determined by using theoretical methods. The estimated maximum landfill gas flow rates were 2.49 and 19.85 m³/min for Mysore and Bangalore sites respectively over a period of 20 years. U.S. EPA’s landfill gas energy cost model, LFGcost-Web (version 3.2), was used to conduct the economic analysis of various landfill gas energy recovery projects. Out of the twelve LFG energy recovery options evaluated, only the onsite CNG production and fueling station and CHP Micro-turbine were found to be economically feasible for Bangalore landfill site. In the case of Mysore landfill, none of the LFG energy projects evaluated were economically viable.

There is growing interest in enhancing the energy sustainability of seawater desalination processes given the increasing reliance on this technology in water-stressed regions. In this paper, we present the design and modelling of an energy-efficient thermal desalination plant (using low-pressure multi-effect distillation) powered by a solar linear Fresnel collector. A steady-state computer model was developed in engineering equation solver (EES) using energy, mass, and salt balance equations. The EES model was used to evaluate the annual performance of the plant and to calculate its equivalent mechanical energy consumption. We also assessed environmental impacts using the life-cycle assessment (LCA) methodology. The equivalent mechanical energy of the optimized desalination plant was 8 kWh/m³, which is 59% lower than that of conventional thermal desalination plants. This significant reduction in equivalent energy consumption reduces the required solar field size by 25%. The environmental assessment showed that the operation phase accounted for approximately 80% of the plant’s climate change impact. Our integrated solar desalination plant can potentially reduce CO₂ emissions by 10 kg per 1 m³ of freshwater produced, and can reduce human toxicity impacts three fold. Chemical usage in the desalination process has a significant impact on ozone depletion based on the consumption of antifoaming agents that contain many ozone-depleting substances.

A shortage of freshwater is one of the leading factors restricting sustainable global development. Desalination has evolved to overcome water shortages in many regions since the mid-20th century, especially in North Africa, the Middle East, some states of the United States, and Mediterranean countries. In particular, Middle Eastern countries have established desalination facilities that produce approximately half of the globally desalinated water to secure the future of humanity, and a large percentage of this water comes from thermal desalination. The energy intensive nature of thermal desalination creates significant negative impacts on the environment, which has been poorly understood in many of these countries. Therefore, to quantify the environmental impact in a case study, we selected a small country of the Arabian Gulf, Qatar, which has a total annual desalination capacity of approximately 500 million m³ of which 68% is being produced by multi-stage flash (MSF) thermal desalination. Life cycle assessment (LCA) was employed to quantify the impacts of two different MSF configurations with varying gained output ratios (GORs). Environmental load analysis showed that the plant with the low GOR released a higher amount of CO₂ (12. 6 kg) to produce 1 m³ of water while the modified plant with the high GOR released less CO₂ (7. 32 kg) per m³ of water. This comprehensive quantitative analysis has a significant regional impact because it has the potential to act as baseline for more sustainable water systems in areas that are highly dependent on MSF desalination for water security.

Green infrastructure (GI) projects provide new and sustainable solutions for managing stormwater by reducing impervious cover, capturing and conveying localized flood waters, promoting infiltration, replenishing depleting groundwater supplies, improving runoff quality, and increasing flood risk and drought resiliency. Green infrastructure projects have been implemented within southern California, including in the highly urbanized Los Angeles metropolitan area. However, despite the growing use of GI, there is a need to better understand the existing inventory of projects. This paper presents the review of the current portfolio of GI in the counties of Orange and Los Angeles, including the city of Los Angeles, through the development of a geographic information systems (GIS) database and the evaluation of pertinent project data from over 2,400 GI projects such as project types, locations, design volumes, and monitoring information. This review will improve understanding of the existing infrastructure for future planning, detailed design, and performance analyses to ensure optimal use of available resources.