Flowrate time series processing in engineering tools for water distribution networks

• Autor(a) principal: Ferreira, Bruno
• Data de Publicação: 2022
• Outros Autores: Carriço, Nelson, Barreira, Raquel, Dias, Tiago, Covas, Dídia
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.26/49672

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