Scholarly Articles
Prediction of Minimum Night Flow for Enhancing LeakageDetection Capabilities in Water Distribution Networks
Journals
applied science
Author
이호현,이상수,이연정
Publication Date
20220523
In South Korea, a water supply enhancement project is being carried out to preemptively
respond to drought and water loss by reducing pipeline leakages and supplying stable tap water
through the maintenance of an aging water supply network. In order to reduce water leakage, a
District Metered Area (DMA) was established to monitor and predict the minimum night flow based
on flow data collected from IoT sensors. In this study, a model based on Multi-Layer Perceptron
(MLP) and Long Short-Term Memory (LSTM) was constructed to predict the MNF (minimum night
flow) of County Y. The prediction of MNF results was compared with the MLP networks and the
LSTM model. The outcome showed that the LSTM-MNF model proposed in this study performed
better than the MLP-MNF model. Therefore, the research methods of this study can contribute to
technical support for leakage reductions by preemptively responding to the expected increase in
leakage through the prediction of the minimum flow at night.
respond to drought and water loss by reducing pipeline leakages and supplying stable tap water
through the maintenance of an aging water supply network. In order to reduce water leakage, a
District Metered Area (DMA) was established to monitor and predict the minimum night flow based
on flow data collected from IoT sensors. In this study, a model based on Multi-Layer Perceptron
(MLP) and Long Short-Term Memory (LSTM) was constructed to predict the MNF (minimum night
flow) of County Y. The prediction of MNF results was compared with the MLP networks and the
LSTM model. The outcome showed that the LSTM-MNF model proposed in this study performed
better than the MLP-MNF model. Therefore, the research methods of this study can contribute to
technical support for leakage reductions by preemptively responding to the expected increase in
leakage through the prediction of the minimum flow at night.