Geology topics

Mantha S. Phanikumar

Publications and source records attributed to Mantha S. Phanikumar.

12 recordsLinked to original sources

USGS2022

Microbial source tracking and evaluation of best management practices for restoring degraded beaches of Lake Michigan

Attempts to mitigate shoreline microbial contamination require a thorough understanding of pollutant sources, which often requires multiple years of data collection (e.g., point/nonpoint) and the interacting factors that influence water quality. Because restoration efforts can alter shoreline or beach morphology, revisiting source inputs is often necessary. Microbial source tracking (MST) using source-specific molecular markers, genomic community analyses, and physical modeling was used to identify contamination sources along three Lake Michigan beaches of the Laurentian Great Lakes with historically high fecal indicator bacteria (FIB, E. coli ) concentrations. Genetic markers for human (Bacteroides HF183) and mixed gull species ( Catellicoccus marimammalium ) fecal sources were tested from water and sediment. Gene sequencing (16S rRNA) was used to identify similarities in bacterial communities in nearshore water, river inputs, sand, sediment, and groundwater. Synoptic surveys of water exchange were conducted to determine nearshore-offshore interactions of FIB. In addition to these MST studies, best management practices to mitigate FIB, including gull deterrence, slope grading, wetland establishment, and shoreline plantings, were reviewed for their effectiveness at reducing FIB concentrations over time. Using multiple tools for MST helped identify primary and secondary sources of FIB (gulls, stormwater inputs) and the physical processes that exacerbate FIB concentrations (onshore currents, limited circulation). Management actions were successful in the short-term at reducing FIB, but scope of success was temporally limited, with FIB concentrations often rebounding. Results highlight the usefulness of MST to inform best management practices and the need for a sustained adaptive approach that adjusts for changes in the coastal system.

Illinois, Wisconsin↗

USGS2021

Influence of filter pore size on composition and relative abundance of bacterial communities and select host-specific MST markers in coastal waters of southern Lake Michigan

Water clarity is often the primary guiding factor in determining whether a prefiltration step is needed to increase volumes processed for a range of microbial endpoints. In this study, we evaluate the effect of filter pore size on the bacterial communities detected by 16S rRNA gene sequencing and incidence of two host-specific microbial source tracking (MST) markers in a range of coastal waters from southern Lake Michigan, using two independent data sets collected in 2015 (bacterial communities) and 2016–2017 (MST markers). Water samples were collected from river, shoreline, and offshore areas. For bacterial communities, each sample was filtered through a 5.0-μm filter, followed by filtration through a 0.22-μm filter, resulting in 70 and 143 filter pairs for bacterial communities and MST markers, respectively. Following DNA extraction, the bacterial communities were compared using 16S rRNA gene amplicons of the V3–V4 region sequenced on a MiSeq Illumina platform. Presence of human ( Bacteroides HF183) and gull (Gull2, Catellicoccus marimammalium ) host-specific MST markers were detected by qPCR. Actinobacteriota, Bacteroidota, and Proteobacteria, collectively represented 96.9% and 93.9% of the relative proportion of all phyla in the 0.22- and 5.0-μm pore size filters, respectively. There were more families detected in the 5.0-μm pore size filter (368) than the 0.22-μm (228). There were significant differences in the number of taxa between the two filter sizes at all levels of taxonomic classification according to linear discriminant analysis (LDA) effect size (LEfSe) with as many as 986 taxa from both filter sizes at LDA effect sizes greater than 2.0. Overall, the Gull2 marker was found in higher abundance on the 5.0-μm filter than 0.22 μm with the reverse pattern for the HF183 marker. This discrepancy could lead to problems with identifying microbial sources of contamination. Collectively, these results highlight the importance of analyzing pre- and final filters for a wide range of microbial endpoints, including host-specific MST markers routinely used in water quality monitoring programs. Analysis of both filters may increase costs but provides more complete genomic data via increased sample volume for characterizing microbial communities in coastal waters.

Illinois, Indiana, Wisconsin↗

USGS2020

Interaction of bacterial communities and indicators of water quality in shoreline sand, sediment, and water of Lake Michigan

Shoreline sand harbors high concentrations of fecal indicator bacteria (FIB) that may be resuspended into the water column through washing and resuspension. Studies have explored coastal processes that influence this sand-water flux for FIB, but little is known about how microbial markers of contamination or the bacterial community interact in the sand-water interface. In this study, we take a three-tiered approach to explore the relationship between bacteria in sand, sediment, and overlying water at three shoreline sites and two associated rivers along an extended freshwater shoreline. Samples were collected over two years and analyzed for FIB, two microbial source tracking (MST) markers ( Catellicoccus marimammalium, Gull2; Bacteroides HF183), and targeted metagenomic 16S rRNA gene analysis. FIB was much higher in sand than in water at all three sites. Gull2 marker was abundant in shoreline sand and water while HF183 marker was mostly present in rivers. Overall bacterial communities were dissimilar between sand/sediment and water, indicating little interaction. Sediment composition was generally unfavorable to bacterial resuspension. Results show that FIB and MST markers were effective estimates of short-term conditions at these locations, and bacterial communities in sand and sediment reflected longer-term conditions. Findings are useful for locating contamination sources and targeting restoration by evaluating scope of shoreline degradation.

Lake Michigan↗

USGS2020

Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach

Beaches along the Great Lakes shorelines are important recreational and economic resources. However, contamination at the beaches can threaten their usage during the swimming season, potentially resulting in beach closures and/or advisories. Thus, understanding the dynamics that control nearshore water quality is integral to effective beach management. There have been significant improvements in this effort, including incorporating modeling (empirical, mechanistic) in recent years. Mechanistic modeling frameworks can contribute to this understanding of dynamics by determining sources and interactions that substantially impact fecal indicator bacteria concentrations, an index routinely used in water quality monitoring programs. To simulate E. coli concentrations at Jeorse Park beaches in southwest Lake Michigan, a coupled hydrodynamic and wave–current interaction model was developed that progressively added contaminant sources from river inputs, avian presence, bacteria–sediment interactions, and bacteria–sand–sediment interactions. Results indicated that riverine inputs affected E. coli concentrations at Jeorse Park beaches only marginally, while avian, shoreline sand, and sediment sources were much more substantial drivers of E. coli contamination at the beach. By including avian and riverine inputs, as well as bacteria–sand–sediment interactions at the beach, models can reasonably capture the variability in observed E. coli concentrations in nearshore water and bed sediments at Jeorse Park beaches. Consequently, it will be crucial to consider avian contamination sources and water-sand-sediment interactions in effective management of the beach for public health and as a recreational resource and to extend these findings to similar beaches affected by shoreline embayment.

Illlinois↗

USGS2018

Real-time nowcasting of microbiological water quality at recreational beaches: A wavelet and artificial neural network-based hybrid modeling approach

The number of beach closings caused by bacterial contamination has continued to rise in recent years, putting beachgoers at risk of exposure to contaminated water. Current approaches predict levels of indicator bacteria using regression models containing a number of explanatory variables. Data-based modeling approaches can supplement routine monitoring data and provide highly accurate short-term forecasts of beach water quality. In this paper, we apply the nonlinear autoregressive network with exogenous inputs (NARX) method with explanatory variables to predict Escherichia coli concentrations at four Lake Michigan beach sites. We also apply the nonlinear input–output network (NIO) and nonlinear autoregressive neural network (NAR) methods in addition to a hybrid wavelet-NAR (WA-NAR) model and demonstrate their application. All models were tested using 3 months of observed data. Results revealed that the NARX models provided the best performance and that the WA-NAR model, which requires no explanatory variables, outperformed the NIO and NAR models; therefore, the WA-NAR model is suitable for application to data scarce regions. The models proposed in this paper were evaluated using multiple performance metrics, including sensitivity and specificity measures, and produced results comparable or superior to those of previous mechanistic and statistical models developed for the same beach sites. The relatively high R 2 values between data and the NARX models ( R 2 values of ∼0.8 for the beach sites and ∼0.9 for the river site) indicate that the new class of models shows promise for beach management.

Environmental Science & Technology↗

USGS2018

Identifying and eliminating sources of recreational water quality degradation along an urban coast

Restoration of highly degraded urban coastal waters often requires large-scale, complex projects, but in the interim, smaller-scale efforts can provide immediate improvements to water quality conditions for visitor use. We examined short-term efforts to improve recreational water quality near the Grand Calumet River (GC) in the Laurentian Great Lakes. Identified as an Area of Concern (AOC) by the International Joint Commission, the GC has experienced years of industrial and municipal waste discharges, and as a result, coastal beaches have some of the highest rates of beach closings (>70%) in the United States. Project objectives were to identify sources of microbial contamination and to evaluate a short-term management solution to decrease beach closings: during 2015 (partial) and 2016 (season-long), canines were used to deter gull presence. Water samples were analyzed for Escherichia coli in 2015 and 2016, and fecal sources were evaluated using microbial source tracking markers (2015): human ( Bacteroides HF183, Methanobrevibacter nifH ), gull (Gull2), and dog (DogBact). Hydrometeorological conditions were simultaneously measured. Results indicated that human, gull, and canine fecal sources were present, with gulls being the dominant source. Escherichia coli densities were highly correlated with number of gulls present, Gull2 marker, and turbidity. Gull deterrence decreased E. coli and Gull2 marker detection during 2015, but numbers rebounded after program completion. The full-season program in 2016 resulted in lower E. coli densities and fewer beach closings. Large-scale restoration efforts are underway at this location, but short-term, small-scale projects can be useful for reducing beach closings and restoring ecosystem services.

Indiana↗

USGS2016

Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan

Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models are developed, tested, and used. We describe a cooperative modeling approach for freshwater beaches impacted by point sources in which insights derived from mechanistic modeling were used to further improve the statistical models and vice versa. The statistical models provided a basis for assessing the mechanistic models which were further improved using probability distributions to generate high-resolution time series data at the source, long-term “tracer” transport modeling based on observed electrical conductivity, better assimilation of meteorological data, and the use of unstructured-grids to better resolve nearshore features. This approach resulted in improved models of comparable performance for both classes including a parsimonious statistical model suitable for real-time predictions based on an easily measurable environmental variable (turbidity). The modeling approach outlined here can be used at other sites impacted by point sources and has the potential to improve water quality predictions resulting in more accurate estimates of beach closures.

Lake Michigan, Ogden Dunes↗

USGS2016

Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches

Predictive empirical modeling is used in many locations worldwide as a rapid, alternative recreational water quality management tool to eliminate delayed notifications associated with traditional fecal indicator bacteria (FIB) culturing (referred to as the persistence model, PM) and to prevent errors in releasing swimming advisories. The goal of this study was to develop a fully automated water quality management system for multiple beaches using predictive empirical models (EM) and state-of-the-art technology. Many recent EMs rely on samples or data collected manually, which adds to analysis time and increases the burden to the beach manager. In this study, data from water quality buoys and weather stations were transmitted through cellular telemetry to a web hosting service. An executable program simultaneously retrieved and aggregated data for regression equations and calculated EM results each morning at 9:30 AM; results were transferred through RSS feed to a website, mapped to each beach, and received by the lifeguards to be posted at the beach. Models were initially developed for five beaches, but by the third year, 21 beaches were managed using refined and validated modeling systems. The adjusted R 2 of the regressions relating Escherichia coli to hydrometeorological variables for the EMs were greater than those for the PMs, and ranged from 0.220 to 0.390 (2011) and 0.103 to 0.381 (2012). Validation results in 2013 revealed reduced predictive capabilities; however, three of the originally modeled beaches showed improvement in 2013 compared to 2012. The EMs generally showed higher accuracy and specificity than those of the PMs, and sensitivity was low for both approaches. In 2012 EM accuracy was 70–97%; specificity, 71–100%; and sensitivity, 0–64% and in 2013 accuracy was 68–97%; specificity, 73–100%; and sensitivity 0–36%. Factors that may have affected model capabilities include instrument malfunction, non-point source inputs, and sparse calibration data. The modeling system developed is the most extensive, fully-automated system for recreational water quality developed to date. Key insights for refining and improving large-scale empirical models for beach management have been developed through this multi-year effort.

Illinois↗

USGS2015

Fecal indicator organism modeling and microbial source tracking in environmental waters: Chapter 3.4.6

Mathematical models have been widely applied to surface waters to estimate rates of settling, resuspension, flow, dispersion, and advection in order to calculate movement of particles that influence water quality. Of particular interest are the movement, survival, and persistence of microbial pathogens or their surrogates, which may contaminate recreational water, drinking water, or shellfish. Most models devoted to microbial water quality have been focused on fecal indicator organisms (FIO), which act as a surrogate for pathogens and viruses. Process-based modeling and statistical modeling have been used to track contamination events to source and to predict future events. The use of these two types of models require different levels of expertise and input; process-based models rely on theoretical physical constructs to explain present conditions and biological distribution while data-based, statistical models use extant paired data to do the same. The selection of the appropriate model and interpretation of results is critical to proper use of these tools in microbial source tracking. Integration of the modeling approaches could provide insight for tracking and predicting contamination events in real time. A review of modeling efforts reveals that process-based modeling has great promise for microbial source tracking efforts; further, combining the understanding of physical processes influencing FIO contamination developed with process-based models and molecular characterization of the population by gene-based (i.e., biological) or chemical markers may be an effective approach for locating sources and remediating contamination in order to protect human health better.

Book chapter↗

USGS2013

Quantifying wetland–aquifer interactions in a humid subtropical climate region: An integrated approach

Wetlands are widely recognized as sentinels of global climate change. Long-term monitoring data combined with process-based modeling has the potential to shed light on key processes and how they change over time. This paper reports the development and application of a simple water balance model based on long-term climate, soil, vegetation and hydrological dynamics to quantify groundwater–surface water (GW–SW) interactions at the Norman landfill research site in Oklahoma, USA. Our integrated approach involved model evaluation by means of the following independent measurements: (a) groundwater inflow calculation using stable isotopes of oxygen and hydrogen ( 16 O, 18 O, 1 H, 2 H); (b) seepage flux measurements in the wetland hyporheic sediment; and (c) pan evaporation measurements on land and in the wetland. The integrated approach was useful for identifying the dominant hydrological processes at the site, including recharge and subsurface flows. Simulated recharge compared well with estimates obtained using isotope methods from previous studies and allowed us to identify specific annual signatures of this important process during the period of study (1997–2007). Similarly, observations of groundwater inflow and outflow rates to and from the wetland using seepage meters and isotope methods were found to be in good agreement with simulation results. Results indicate that subsurface flow components in the system are seasonal and readily respond to rainfall events. The wetland water balance is dominated by local groundwater inputs and regional groundwater flow contributes little to the overall water balance.

Oklahoma↗

USGS2012

Wave-induced mass transport affects daily Escherichia coli fluctuations in nearshore water

Characterization of diel variability of fecal indicator bacteria concentration in nearshore waters is of particular importance for development of water sampling standards and protection of public health. Significant nighttime increase in Escherichia coli ( E. coli ) concentration in beach water, previously observed at marine sites, has also been identified in summer 2000 from fixed locations in waist- and knee-deep waters at Chicago 63rd Street Beach, an embayed, tideless, freshwater beach with low currents at night (approximately 0.015 m s –1 ). A theoretical model using wave-induced mass transport velocity for advection was developed to assess the contribution of surface waves to the observed nighttime E. coli replenishment in the nearshore water. Using average wave conditions for the summer season of year 2000, the model predicted an amount of E. coli transported from water of intermediate depth, where sediment resuspension occurred intermittently, that would be sufficient to have elevated E. coli concentration in the surf and swash zones as observed. The nighttime replenishment of E. coli in the surf and swash zones revealed here is an important phase in the cycle of diel variations of E. coli concentration in nearshore water. According to previous findings in Ge et al. (Environ. Sci. Technol. 2010, 44, 6731–6737), enhanced current circulation in the embayment during the day tends to displace and deposit material offshore, which partially sets up the system by the early evening for a new period of nighttime onshore movement. This wave-induced mass transport effect, although facilitating a significant base supply of material shoreward, can be perturbed or significantly influenced by high currents (orders of magnitude larger than a typical wave-induced mass transport velocity), current-induced turbulence, and tidal forcing.

Illinois↗

USGS2012

Nearshore hydrodynamics as loading and forcing factors for Escherichia coli contamination at an embayed beach

Numerical simulations of the transport and fate of Escherichia coli were conducted at Chicago's 63rd Street Beach, an embayed beach that had the highest mean E. coli concentration among 23 similar Lake Michigan beaches during summer months of 2000-2005, in order to find the cause for the high bacterial contamination. The numerical model was based on the transport of E. coli by current circulation patterns in the embayment driven by longshore main currents and the loss of E. coli in the water column, taking settling as well as bacterial dark- and solar-related decay into account. Two E. coli loading scenarios were considered: one from the open boundary north of the embayment and the other from the shallow water near the beachfront. Simulations showed that the embayed beach behaves as a sink for E. coli in that it generally receives E. coli more efficiently than it releases them. This is a result of the significantly different hydrodynamic forcing factors between the inside of the embayment and the main coastal flow outside. The settled E. coli inside the embayment can be a potential source of contamination during subsequent sediment resuspension events, suggesting that deposition-resuspension cycles of E. coli have resulted in excessive bacterial contamination of beach water. A further hypothetical case with a breakwater shortened to half its original length, which was anticipated to enhance the current circulation in the embayment, showed a reduction in E. coli concentrations of nearly 20%.

Illinois↗