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contributor authorZ. Zhang
date accessioned2017-05-08T21:48:19Z
date available2017-05-08T21:48:19Z
date copyrightMarch 2005
date issued2005
identifier other%28asce%290733-9372%282005%29131%3A3%28343%29.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/62853
description abstractSanitary 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.
publisherAmerican Society of Civil Engineers
titleFlow Data, Inflow/Infiltration Ratio, and Autoregressive Error Models
typeJournal Paper
journal volume131
journal issue3
journal titleJournal of Environmental Engineering
identifier doi10.1061/(ASCE)0733-9372(2005)131:3(343)
treeJournal of Environmental Engineering:;2005:;Volume ( 131 ):;issue: 003
contenttypeFulltext


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