{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/90540"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/90540","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Understanding sewer infiltration and inflow using impulse response functions derived from physics-based models","abstract":"Infiltration and inflow (I&I) are extraneous flow in a sanitary sewer system that originate from surface water and ground water. I&I can overload the sewer system and wastewater treatment plants, and cause sanitary sewer overflows (SSOs) or basement flooding. This flow can account for as much as ten times dry weather flow (DWF) but the estimation of the volume and peak of I&I involves a great deal of uncertainty. Temporal and spatial variability of the I&I processes make it difficult to understand the phenomena. Depending on the time scale of different I&I processes, some watershed properties may only affect specific I&I sources. For example, the configuration of sewer network and the geology of the watershed may affect fast and slow I&I processes differently. In this study, the physical process of three major I&I sources: roof downspout, sump pump, and leaky lateral, are investigated at the residential lot scale using physics-based models. The typical flow response of each I&I source is calculated and these flow responses, called Impulse Response Functions (IRFs), are evaluated. I&I estimation using the three IRFs, calibrated using a genetic algorithm (GA), was performed on a catchment in the Chicago area at the sewershed scale. Results are compared with one of the most widely used I&I estimation methods, the RTK method. The IRF method shows more stable solutions as the model is based on physical processes. The RTK method better predicts the monitoring data, however it is suspected that this is mainly because the RTK method is an empirical curve fitting method. Uncertainty related to rainfall induced infiltration (RII) is further investigated on six different input parameters: Antecedent moisture condition (AMC), pedotransfer functions (PTFs), soil hydraulic conductivities, initial conditions (IC), sewer pipe depths, and rainfall characteristics. The uncertainty analysis indicates that the model result is most sensitive to the soil hydraulic conductivity, which defines the maximum infiltration rate. Rainfall characteristics, including duration and hyetograph shape turn out to be the least influential factors affecting the infiltration response. Results from this study help understand the sewer I&I process in a complex urban system. In particular, using a small scale, detailed distributed model enables examination of the sensitivity of the I&I process to the different factors contributing to uncertainty. While the modeling results are site specific to Hickory Hills, IL, this study can provide insights to researchers and engineers about characteristic behaviors of different I&I sources and the uncertainty factors that affect sewer infiltration response including AMC.","abstract_html":"Infiltration and inflow (I&I) are extraneous flow in a sanitary sewer system that originate from surface water and ground water. I&I can overload the sewer system and wastewater treatment plants, and cause sanitary sewer overflows (SSOs) or basement flooding. This flow can account for as much as ten times dry weather flow (DWF) but the estimation of the volume and peak of I&I involves a great deal of uncertainty. Temporal and spatial variability of the I&I processes make it difficult to understand the phenomena. Depending on the time scale of different I&I processes, some watershed properties may only affect specific I&I sources. For example, the configuration of sewer network and the geology of the watershed may affect fast and slow I&I processes differently. In this study, the physical process of three major I&I sources: roof downspout, sump pump, and leaky lateral, are investigated at the residential lot scale using physics-based models. The typical flow response of each I&I source is calculated and these flow responses, called Impulse Response Functions (IRFs), are evaluated. I&I estimation using the three IRFs, calibrated using a genetic algorithm (GA), was performed on a catchment in the Chicago area at the sewershed scale. Results are compared with one of the most widely used I&I estimation methods, the RTK method. The IRF method shows more stable solutions as the model is based on physical processes. The RTK method better predicts the monitoring data, however it is suspected that this is mainly because the RTK method is an empirical curve fitting method. Uncertainty related to rainfall induced infiltration (RII) is further investigated on six different input parameters: Antecedent moisture condition (AMC), pedotransfer functions (PTFs), soil hydraulic conductivities, initial conditions (IC), sewer pipe depths, and rainfall characteristics. The uncertainty analysis indicates that the model result is most sensitive to the soil hydraulic conductivity, which defines the maximum infiltration rate. Rainfall characteristics, including duration and hyetograph shape turn out to be the least influential factors affecting the infiltration response. Results from this study help understand the sewer I&I process in a complex urban system. In particular, using a small scale, detailed distributed model enables examination of the sensitivity of the I&I process to the different factors contributing to uncertainty. While the modeling results are site specific to Hickory Hills, IL, this study can provide insights to researchers and engineers about characteristic behaviors of different I&I sources and the uncertainty factors that affect sewer infiltration response including AMC.","abstract_has_math":false,"creators":["Choi, Nam Jeong"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Schmidt, Arthur R.","Valocchi, Albert J.","Garcia, Marcelo H.","Cooke, Richard A.","Cantone, Joshua"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-07-07T19:53:54Z","date_published":"2016-07-07T19:53:54Z","updated_at":"2026-07-22T22:26:32Z","subjects":["Infiltration and Inflow (I&I)","Impulse Response Functions","Physics-based Models"],"languages":["en"],"rights":["Copyright 2016 Nam Jeong Choi"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/90540","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Schmidt, Arthur R.","Valocchi, Albert J.","Garcia, Marcelo H.","Cooke, Richard A.","Cantone, Joshua"]},{"key":"dc:creator","label":"Author","values":["Choi, Nam Jeong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-07-07T19:53:54Z","2016-04-19","2016-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Infiltration and Inflow (I&I)","Impulse Response Functions","Physics-based Models"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Nam Jeong Choi"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/90540"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Infiltration and inflow (I&I) are extraneous flow in a sanitary sewer system that originate from surface water and ground water. I&I can overload the sewer system and wastewater treatment plants, and cause sanitary sewer overflows (SSOs) or basement flooding. This flow can account for as much as ten times dry weather flow (DWF) but the estimation of the volume and peak of I&I involves a great deal of uncertainty. Temporal and spatial variability of the I&I processes make it difficult to understand the phenomena. Depending on the time scale of different I&I processes, some watershed properties may only affect specific I&I sources. For example, the configuration of sewer network and the geology of the watershed may affect fast and slow I&I processes differently. In this study, the physical process of three major I&I sources: roof downspout, sump pump, and leaky lateral, are investigated at the residential lot scale using physics-based models. The typical flow response of each I&I source is calculated and these flow responses, called Impulse Response Functions (IRFs), are evaluated. I&I estimation using the three IRFs, calibrated using a genetic algorithm (GA), was performed on a catchment in the Chicago area at the sewershed scale. Results are compared with one of the most widely used I&I estimation methods, the RTK method. The IRF method shows more stable solutions as the model is based on physical processes. The RTK method better predicts the monitoring data, however it is suspected that this is mainly because the RTK method is an empirical curve fitting method. Uncertainty related to rainfall induced infiltration (RII) is further investigated on six different input parameters: Antecedent moisture condition (AMC), pedotransfer functions (PTFs), soil hydraulic conductivities, initial conditions (IC), sewer pipe depths, and rainfall characteristics. The uncertainty analysis indicates that the model result is most sensitive to the soil hydraulic conductivity, which defines the maximum infiltration rate. Rainfall characteristics, including duration and hyetograph shape turn out to be the least influential factors affecting the infiltration response. Results from this study help understand the sewer I&I process in a complex urban system. In particular, using a small scale, detailed distributed model enables examination of the sensitivity of the I&I process to the different factors contributing to uncertainty. While the modeling results are site specific to Hickory Hills, IL, this study can provide insights to researchers and engineers about characteristic behaviors of different I&I sources and the uncertainty factors that affect sewer infiltration response including AMC.","Submission original under an indefinite embargo labeled 'Open Access'. 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I&I can overload the sewer system and wastewater treatment plants, and cause sanitary sewer overflows (SSOs) or basement flooding. This flow can account for as much as ten times dry weather flow (DWF) but the estimation of the volume and peak of I&I involves a great deal of uncertainty. Temporal and spatial variability of the I&I processes make it difficult to understand the phenomena. Depending on the time scale of different I&I processes, some watershed properties may only affect specific I&I sources. For example, the configuration of sewer network and the geology of the watershed may affect fast and slow I&I processes differently. In this study, the physical process of three major I&I sources: roof downspout, sump pump, and leaky lateral, are investigated at the residential lot scale using physics-based models. The typical flow response of each I&I source is calculated and these flow responses, called Impulse Response Functions (IRFs), are evaluated. I&I estimation using the three IRFs, calibrated using a genetic algorithm (GA), was performed on a catchment in the Chicago area at the sewershed scale. Results are compared with one of the most widely used I&I estimation methods, the RTK method. The IRF method shows more stable solutions as the model is based on physical processes. The RTK method better predicts the monitoring data, however it is suspected that this is mainly because the RTK method is an empirical curve fitting method. Uncertainty related to rainfall induced infiltration (RII) is further investigated on six different input parameters: Antecedent moisture condition (AMC), pedotransfer functions (PTFs), soil hydraulic conductivities, initial conditions (IC), sewer pipe depths, and rainfall characteristics. The uncertainty analysis indicates that the model result is most sensitive to the soil hydraulic conductivity, which defines the maximum infiltration rate. Rainfall characteristics, including duration and hyetograph shape turn out to be the least influential factors affecting the infiltration response. Results from this study help understand the sewer I&I process in a complex urban system. In particular, using a small scale, detailed distributed model enables examination of the sensitivity of the I&I process to the different factors contributing to uncertainty. While the modeling results are site specific to Hickory Hills, IL, this study can provide insights to researchers and engineers about characteristic behaviors of different I&I sources and the uncertainty factors that affect sewer infiltration response including AMC.","Submission original under an indefinite embargo labeled 'Open Access'. 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