Thomas D. Rockaway

Framing a new approach to critical infrastructure modelling and extreme events

This paper proposes a new framework to evaluate and improve the resiliency of communities as they face the risk of multiple hazards and cascading infrastructure failure. The central idea is to extend engineering-based fragility models of the effect of extreme events on physical infrastructure and to combine them with regional, economic and social impact models. The modelling framework would support analyses of the sensitivity of a community to varying events, signalling weak links in regional infrastructure systems and subsystems, and suggesting a more efficient allocation of federal, state, and local preparedness resources.

Temporal performance assessment of wastewater treatment plants by using multivariate statistical analysis

For most water treatment plants, a significant number of performance data variables are attained on a time series basis. Due to the interconnectedness of the variables, it is often difficult to assess over-arching trends and quantify operational performance. The objective of this study was to establish simple and reliable predictive models to correlate target variables with specific measured parameters. This study presents a multivariate analysis of the physicochemical parameters of municipal wastewater. Fifteen quality and quantity parameters were analyzed using data recorded from 2010 to 2016. To determine the overall quality condition of raw and treated wastewater, a Wastewater Quality Index (WWQI) was developed. The index summarizes a large amount of measured quality parameters into a single water quality term by considering pre-established quality limitation standards. To identify treatment process performance, the interdependencies between the variables were determined by using Principal Component Analysis (PCA). The five extracted components from the 15 variables accounted for 75.25% of total dataset information and adequately represented the organic, nutrient, oxygen demanding, and ion activity loadings of influent and effluent streams. The study also utilized the model to predict quality parameters such as Biological Oxygen Demand (BOD), Total Phosphorus (TP), and WWQI. High accuracies ranging from 71% to 97% were achieved for fitting the models with the training dataset and relative prediction percentage errors less than 9% were achieved for the testing dataset. The presented techniques and procedures in this paper provide an assessment framework for the wastewater treatment monitoring programs.

Assessment of Surface Infiltration Performance and Maintenance of Two Permeable Pavement Systems in Louisville, Kentucky

AbstractThis study presents the infiltration performance of two permeable pavement systems installed in the parking lanes of an urban neighborhood. Both systems were subject to large (12.9 and 9.8)...

Monitoring Hydrological Performance of Green Infrastructure Stormwater Controls

The Louisville Metropolitan Sewer District (MSD) has entered into a Consent Decree Agreement with U.S. EPA to reduce the number and volume of combined sewer overflows (CSOs) from the existing combined sewer system (CSS). As an aspect of this agreement MSD is using green infrastructure (GI) stormwater controls to reduce CSOs. The initial phase of the project is implementing GI controls in a small urbanized neighborhood (28 acres) in Louisville, KY in lieu of a planned concrete retention basin. In December 2011, two permeable interlocking concrete pavement (ICP) controls were constructed. To quantify surface infiltration and subsurface exfiltration performance each control was embedded with time domain reflectometers (TDRs), thermistors, and piezometers. To predict the hydrological performance of the GI controls, a spreadsheet model is developed by utilizing each control’s drainage area, hydraulic conductivity values for surrounding soil layers, and dimensions of each GI control. The model calculates the inflow and outflow volumes and predicts the water level inside the control for each rain event. Hydrological performance is defined as a GI control’s ability to capture the runoff volume (infiltration capacity) and then pass captured volume into the underlying soil layers (exfiltration performance). The model’s predicted water levels are compared to the recorded water levels by the embedded pressure transducers. The developed model predicts the ideal performance of the GI control and compares it to recorded data. This assessment technique works to quantify the progression of clogging at the surface and within the infiltration gallery. This model provides a method for monitoring the hydraulic performance of the GI controls over time.

Performance assessment of stormwater GI practices using artificial neural networks

This study evaluates the performance of a suite of stormwater green infrastructure (GI) practices at the Belknap Campus, University of Louisville. In lack of instrumentation within individual GIs, and detailed drainage and sewer information, data mining procedures and artificial neural networks (ANN) were used. Two separate Back Propagation Neural Network Models (BPNNMs) were developed to estimate the reductions of flow volume and peak flow rates within the combined sewer system. The results from developed BPNNMs showed that following the construction of stormwater GIs at the Belknap campus, downstream wet-weather related flow decreased. The developed BPNNMs showed that the flow volume reduction and the peak flow attenuation rates had averages of approximately 33% and 61% per storm event, respectively. The flow reduction rates generally were lower for larger storms. Similarly, the peak flow rates decreased by increase of maximum intensity values per storm. However, further analysis indicated that even for large storm events, with long durations, the GIs had a positive impact on mitigation of combined sewer flows. Additionally, using rainfall data and downstream sewer flow in conjunction with artificial neural network modeling, was determined to be an effective technique for evaluating the combined hydrological performance of a suite of stormwater GIs.

Integrated Approach to Treatment of High-Strength Organic Wastewater by Using Anaerobic Rotating Biological Contactor

AbstractThis research assesses the performance and methane production of a novel combined system for treatment of high-strength organic wastewater. The proposed system is composed of a rotating bio...

Emergency Communications with Your Local Government and Community

Recent events including the World Trade Center attack, the anthrax scare, Ohio River flooding and the Northeast power outage clearly demonstrate the need for improved systems of communicating emergency information to the public. To explore the arena of emergency communications, the research project analyzed current emergency communication practices utilized by water utilities though literature review, survey, interviews and case study. Through a combination of literature review, survey and interview data the research team constructed a preparedness guide from observable current best management practices (BMP) used in the industry. The preparedness guide document serves as the backbone for the emergency status information management system (eSIMs) toolkit. The eSIMs is a toolkit providing end users guidance in managing information during emergency events. This title belongs to WERF Research Report Series ISBN: 9781780403687 (eBook) ISBN: 9781843397786 (Print)