A Study of Optimal-CSOs by Continuous Rainfall/Runoff Simulation Techniques

연속 강우-유출 모의기법을 이용한 최적 CSOs 산정에 관한 연구

  • Jo, Deok Jun (Department of Architecture and Civil System Engineering, Dongseo University) ;
  • Kim, Myoung Su (Department of Water Resource engineering, Namwonkeonseol Engineering Co., Ltd.) ;
  • Lee, Jung Ho (Department of Civil and Environmental System Engineering, Korea University) ;
  • Kim, Joong Hoon (Department of Civil and Environmental System Engineering, Korea University)
  • 조덕준 (동서대학교 건축토목시스템공학부) ;
  • 김명수 ((주)남원엔지니어링 수자원부) ;
  • 이정호 (고려대학교 사회환경시스템공학과) ;
  • 김중훈 (고려대학교 사회환경시스템공학과)
  • Received : 2006.08.14
  • Accepted : 2006.09.07
  • Published : 2006.11.30

Abstract

For receiving water quality protection a control systems of urban drainage for CSOs reduction is needed. Examples in combined sewer systems include downstream storage facilities that detain runoff during periods of high flow and allow the detained water to be conveyed by an interceptor sewer to a centralized treatment plant during periods of low flow. The design of such facilities as storm-water detention storage is highly dependant on the temporal variability of storage capacity available as well as the infiltration capacity of soil and recovery of depression storage. For the continuous long-term analysis of urban drainage system this study used analytical probabilistic model based on derived probability distribution theory. As an alternative to the modeling of urban drainage system for planning or screening level analysis of runoff control alternatives, this model has evolved that offers much ease and flexibility in terms of computation while considering long-term meteorology. This study presented rainfall and runoff characteristics of the subject area using analytical probabilistic model. Runoff characteristics manifested the unique characteristics of the subject area with the infiltration capacity of soil and recovery of depression storage and was examined appropriately by sensitivity analysis. This study presented the average annual CSOs, number of CSOs and event mean CSOs for the decision of storage volume.

Keywords

Acknowledgement

Supported by : 한국학술진흥재단

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