A Decision Support System for Indirect Potable Reuse Based on Integrated Modeling

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dc.contributor.authorLodhi, Adnan Ghaffaren
dc.contributor.committeechairGodrej, Adil N.en
dc.contributor.committeememberWang, Zhiwuen
dc.contributor.committeememberSen, Dipankaren
dc.contributor.committeememberLittle, John C.en
dc.contributor.departmentCivil and Environmental Engineeringen
dc.date.accessioned2020-12-23T07:00:22Zen
dc.date.available2020-12-23T07:00:22Zen
dc.date.issued2019-07-01en
dc.description.abstractOptimal operation of water reclamation facilities (WRFs) is critical for an indirect potable reuse (IPR) system, especially when the reclaimed water constitutes a major portion of the reservoir's safe yield. It requires timely and informed decision-making in response to the fluctuating operational conditions, e.g., weather patterns, plant performance, water demand, etc. Advanced integrated modeling techniques can be used to develop reliable operational strategies to mitigate future risks associated with water quality without needing high levels of financial investment. The Upper Occoquan Service Authority (UOSA) WRF, located in northern Virginia, discharges nitrified reclaimed water directly into a tributary of the Occoquan Reservoir, one of the major water supply sources for Fairfax County. Among the many operational challenges at UOSA, one is to regulate the nitrate concentration in its reclaimed water based on the denitrifying capacity of the reservoir. This study presents an integrated model that is used to predict future reservoir conditions based on the weather and streamflow forecasts obtained from the Climate Forecast System and the National Water Model. The application captures the dynamic transformations of the pollutant loadings in the streams, withdrawals by the water treatment plant, WRF effluent flows, and plant operations to manage the WRF performance. It provides plant operators with useful feedback for correctly targeting the effluent nitrates using an intelligent process simulator called IViewOps. The platform is powered by URUNME, a new software that fully automates the operation of the reservoir and process models integrating forecasting products, and data sources. URUNME was developed in C#.NET to provide out-of-the-box functionality for model coupling, data storage, analysis, visualization, scenario management, and decision support systems. The software automatically runs the entire integrated model and outputs data on user-friendly dashboards, displaying historical and forecasting trends, on a periodic basis. This decision support system can provide stakeholders with a holistic view for the design, planning, risk assessments, and potential improvements in various components of the water supply chain, not just for the Occoquan but for any reservoir augmentation type IPR system.en
dc.description.abstractgeneralIn an indirect potable reuse (IPR) system, reclaimed water from an advanced wastewater treatment facility is blended with a natural water source, such as a reservoir, to augment drinking water supply. Reliable operation of such a system is critical, especially when the reclaimed water constitutes a major portion of the withdrawals from the reservoir for treatment and distribution. One example of such an IPR system is the Upper Occoquan Service Authority (UOSA) water reclamation facility (WRF) which discharges its reclaimed water into the Occoquan Reservoir, a key water resource for Fairfax County. Integrated environmental modeling (IEM) provides a comprehensive approach towards the design and operation of water resource systems in which water supply, drainage, and sanitation are simulated as a single entity rather than independent units. In IEM, different standalone models, each representing a single subsystem, are linked together to analyze the complex interactions between various components of the system. This approach can be used for developing operational support tools for an IPR system to ensure timely and informed decision-making in response to the fluctuating conditions, e.g., weather patterns, plant performance, water demand, etc. The overarching goal of this research was to integrate different models and the data sources and develop a decision support system (DSS) to manage the UOSA-WRF performance. This resulting integrated model is used to predict future reservoir conditions based on the weather and streamflow forecasts obtained from the National Weather Service. The application runs various future scenarios to capture the possible variations of the pollutant loadings in the streams, withdrawals by the water treatment plant, WRF effluent flows, and plant operations and provide feedback to plant operators. The entire integrated model is operated periodically to output data on user-friendly dashboards, displaying historical and forecasting trends. The DSS provides stakeholders with a holistic view for the design, planning, risk assessments, and potential improvements in various components of the water supply chain, not just for the Occoquan but for any reservoir augmentation type IPR system.en
dc.description.degreeDoctor of Philosophyen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:20225en
dc.identifier.urihttp://hdl.handle.net/10919/101612en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectDecision Support Systemen
dc.subjectIntegrated Modelingen
dc.subjectIndirect Potable Reuseen
dc.subjectNational Water Modelen
dc.subjectWater and Wastewater Treatmenten
dc.subjectWeather Forecastingen
dc.titleA Decision Support System for Indirect Potable Reuse Based on Integrated Modelingen
dc.typeDissertationen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.nameDoctor of Philosophyen

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