Fuzzy Neural Network for Flow Estimation in Sewer Systems During Wet Weather

Authors: Shen, Jun; Shen, Wei; Chang, Jian; Gong, Ning

Source: Water Environment Research, Volume 78, Number 2, February 2006 , pp. 100-109(10)

Publisher: Water Environment Federation

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Abstract:

Estimation of the water flow from rainfall intensity during storm events is important in hydrology, sewer system control, and environmental protection. The runoff-producing behavior of a sewer system changes from one storm event to another because rainfall loss depends not only on rainfall intensities, but also on the state of the soil and vegetation, the general condition of the climate, and so on. As such, it would be difficult to obtain a precise flowrate estimation without sufficient a priori knowledge of these factors. To establish a model for flow estimation, one can also use statistical methods, such as the neural network STORMNET, software developed at Lyonnaise des Eaux, France, analyzing the relation between rainfall intensity and flowrate data of the known storm events registered in the past for a given sewer system. In this study, the authors propose a fuzzy neural network to estimate the flowrate from rainfall intensity. The fuzzy neural network combines four STORMNETs and fuzzy deduction to better estimate the flowrates. This study's system for flow estimation can be calibrated automatically by using known storm events; no data regarding the physical characteristics of the drainage basins are required. Compared with the neural network STORMNET, this method reduces the mean square error of the flow estimates by approximately 20%. Experimental results are reported herein.

Keywords: hydrological modeling; sewer system; environmental protection; storm; flow estimation; calibration; fuzzy deduction

Document Type: Research article

DOI: http://dx.doi.org/10.2175/106143005X89553

Publication date: 2006-02-01

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Water Environment Research� (WER�) publishes peer-reviewed research papers, research notes, state-of-the-art and critical reviews on original, fundamental and applied research in all scientific and technical areas related to water quality, pollution control, and management. An annual Literature Review provides a review of published books and articles on water quality topics from the previous year.

Published as: Sewage Works Journal, 1928 - 1949; Sewage and Industrial Wastes, 1950 - 1959; Journal Water Pollution Control Federation, 1959 - Oct 1989; Research Journal Water Pollution Control Federation, Nov 1989 - 1991; Water Environment Research, 1992 - present.
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Fuzzy Neural Network for Flow Estimation in Sewer Systems During Wet Weather

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