Journal
JOURNAL OF HYDROLOGY
Volume 558, Issue -, Pages 174-183Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jhydrol.2018.01.002
Keywords
Conductivity; Inflow; Infiltration; Sanitary sewer overflow; Sewer system
Funding
- National Natural Science Foundation of China [51678337]
- Major Science and Technology Program for Water Pollution Control and Treatment of China [2014ZX07305001]
- Tsinghua University Initiative Scientific Research Program [2014z21028]
- Australian Research Council [LP 160101040]
- City of Gold Coast
- Queensland Urban Utilities
- South Australian Water Corporation
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Quantifying rainfall-derived inflow and infiltration (RDII) in a sanitary sewer is difficult when RDII and overflow occur simultaneously. This study proposes a novel conductivity-based method for estimating RDII. The method separately decomposes rainfall-derived inflow (RDI) and rainfall-induced infiltration (RII) on the basis of conductivity data. Fast Fourier transform was adopted to analyze variations in the flow and water quality during dry weather. Nonlinear curve fitting based on the least squares algorithm was used to optimize parameters in the proposed RDII model. The method was successfully applied to real-life case studies, in which inflow and infiltration were successfully estimated for three typical rainfall events with total rainfall volumes of 6.25 mm (light), 28.15 mm (medium), and 178 mm (heavy). Uncertainties of model parameters were estimated using the generalized likelihood uncertainty estimation (GLUE) method and were found to be acceptable. Compared with traditional flow-based methods, the proposed approach exhibits distinct advantages in estimating RDII and overflow, particularly when the two processes happen simultaneously. (C) 2018 Elsevier B.V. All rights reserved.
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