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Advisor(s)
Abstract(s)
The current paper presents a comprehensive methodology for processing unevenly (and evenly)
spaced flowrate time series for subsequent use in engineering tools, such as the calibration of hydraulic models
or the detection and location of leaks and bursts. The methodology is a four-step procedure: (a) anomaly
identification and removal, (b) short-duration gap reconstruction, (c) time step normalization, and (d) long-
duration gap reconstruction. The time step normalization is carried out by a numerical procedure prior to the
reconstruction process. This reconstruction process uses a pattern model coupled with regression techniques
(i.e., autoregressive integrated moving average and exponential smoothing). The methodology is calibrated
using Monte Carlo simulations applied to a water utility flowrate time series and validated with two additional
time series from different water utilities. Obtained results demonstrate that the proposed methodology can
process flowrate time series from water supply systems with different characteristics (e.g., consumption pattern,
data acquisition system, transmission settings) both for normal operating conditions and during the occurrence
of abnormal events (e.g., pipe bursts). This methodology is a very useful tool for the daily management of water
utilities, preparing the time series to be used in different engineering tools, namely, hydraulic simulation, model
calibration or online burst detectio
Description
Keywords
Citation
Ferreira, B., Carriço, N., Barreira, R., Dias, T., & Covas, D. (2022). Flowrate time series processing in engineering tools for water distribution networks. Water Resources Research, 58, e2022WR032393