Methods to detect outliers in network flow measurements that may be due to pipe bursts or unusual consumptions are fundamental to improve water distribution system on-line operation and management, and to ensure reliable historical data for sustainable planning and design of these systems. To detect and classify anomalous events in flow data from district metering areas a four-step methodology was adopted, implemented and tested: i) data acquisition, ii) data validation and normalization, iii) anomalous observation detection, iv) anomalous event detection and characterization. This approach is based on the renewed concept of outlier regions and depends on a reduced number of configuration parameters: the number of past observations, the true positive rate and the false positive rate. Results indicate that this approach is flexible and applicable to the detection of different types of events (e.g., pipe burst, unusual consumption) and to different flow time series (e.g., instantaneous, minimum night flow).
Pluvial or surface flooding can cause significant damage and disruption as it often affects highly urbanised areas. Therefore it is essential to accurately identify consequences and assess the risks associated with such phenomena. The aim of this study is to present the results and investigate the applicability of a qualitative flood risk assessment methodology in urban areas. This methodology benefits from recent developments in urban flood modelling, such as the dual-drainage modelling concept, namely one-dimensional automatic overland flow network delineation tools (e.g. AOFD) and 1D/1D models incorporating both surface and sewer drainage systems. To assess flood risk, the consequences can be estimated using hydraulic model results, such as water velocities and water depth results; the likelihood was estimated based on the return period of historical rainfall events. To test the methodology two rainfall events with return periods of 350 and 2 years observed in Alcântara (Lisbon, Portugal) were used and three consequence dimensions were considered: affected public transportation services, affected properties and pedestrian safety. The most affected areas in terms of flooding were easily identified; the presented methodology was shown to be easy to implement and effective to assess flooding risk in urban areas, despite the common difficulties in obtaining data.
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