Flow Data, Inflow/Infiltration Ratio, and Autoregressive Error ModelsSource: Journal of Environmental Engineering:;2005:;Volume ( 131 ):;issue: 003Author:Z. Zhang
DOI: 10.1061/(ASCE)0733-9372(2005)131:3(343)Publisher: American Society of Civil Engineers
Abstract: Sanitary sewer overflows (SSOs) are a major environmental issue. One of the major factors causing SSOs is the rain-derived inflow and infiltration (RDII) to a separate sanitary sewer system. If a wastewater collection system is not well maintained, cumulative system-wide RDII could easily cause the wastewater conveyance and treatment capacity to be overwhelmed, and thus lead to SSOs. Monitoring system condition is a key component in system management. The industry’s standard approaches to system monitoring include the practice of collecting and analyzing continuous rainfall and flow data at certain key locations in the system to estimate the level of RDII. However, the writer is of the opinion that the current standard analytical methodologies of the industry can be significantly improved. This paper introduces a basic regression approach with autoregressive errors to support statistical inferences with respect to the level of RDII.
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contributor author | Z. Zhang | |
date accessioned | 2017-05-08T21:48:19Z | |
date available | 2017-05-08T21:48:19Z | |
date copyright | March 2005 | |
date issued | 2005 | |
identifier other | %28asce%290733-9372%282005%29131%3A3%28343%29.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/62853 | |
description abstract | Sanitary sewer overflows (SSOs) are a major environmental issue. One of the major factors causing SSOs is the rain-derived inflow and infiltration (RDII) to a separate sanitary sewer system. If a wastewater collection system is not well maintained, cumulative system-wide RDII could easily cause the wastewater conveyance and treatment capacity to be overwhelmed, and thus lead to SSOs. Monitoring system condition is a key component in system management. The industry’s standard approaches to system monitoring include the practice of collecting and analyzing continuous rainfall and flow data at certain key locations in the system to estimate the level of RDII. However, the writer is of the opinion that the current standard analytical methodologies of the industry can be significantly improved. This paper introduces a basic regression approach with autoregressive errors to support statistical inferences with respect to the level of RDII. | |
publisher | American Society of Civil Engineers | |
title | Flow Data, Inflow/Infiltration Ratio, and Autoregressive Error Models | |
type | Journal Paper | |
journal volume | 131 | |
journal issue | 3 | |
journal title | Journal of Environmental Engineering | |
identifier doi | 10.1061/(ASCE)0733-9372(2005)131:3(343) | |
tree | Journal of Environmental Engineering:;2005:;Volume ( 131 ):;issue: 003 | |
contenttype | Fulltext |