The BATtle of the Attack Detection ALgorithms (BATADAL) is the most recent competition on planning and management of water networks undertaken within the Water Distribution Systems Analysis Symposium. The goal of the battle was to compare the performance of algorithms for the detection of cyber-physical attacks, whose frequency has increased in the last few years along with the adoption of smart water technologies. The design challenge was set for the C-Town network, a real-world, medium-sized water distribution system operated through programmable logic controllers and a supervisory control and data acquisition (SCADA) system. Participants were provided with data sets containing (simulated) SCADA observations, and challenged to design an attack detection algorithm. The effectiveness of all submitted algorithms was evaluated in terms of time-to-detection and classification accuracy. Seven teams participated in the battle and proposed a variety of successful approaches leveraging data analysis, model-based detection mechanisms, and rule checking. Results were presented at the Water Distribution Systems Analysis Symposium (World Environmental and Water Resources Congress) in Sacramento, California on May 21–25, 2017. This paper summarizes the BATADAL problem, proposed algorithms, results, and future research directions.

This paper addresses the problem of leakage in water distribution systems through the use of ground penetrating radar (GPR) as a nondestructive method. Laboratory tests are performed to extract features of water leakage from the obtained GPR images. Moreover, a test in a real-world urban system under real conditions is performed. Feature extraction is performed by interpreting GPR images with the support of a pre-processing methodology based on an appropriate combination of statistical methods and multi-agent systems. The results of these tests are presented, interpreted, analyzed and discussed in this paper.

Digitalization in water networks is essential for the future planning of urban development processes in cities and is one of the great challenges faced by small cities regarding water management and the advancement of their infrastructures towards sustainable systems. The main objective of this study is to propose a methodology that allows water utilities with limited budgets to start the path toward the digitalization and construction of the hydraulic model of their water distribution networks. The small city of Pamplona in Colombia was used as a case study. The work explains in detail the challenges faced and the solutions proposed during the digitalization process. The methodology is developed in six phases: an analysis of the cadastre and existing information, the creation and conceptualization of the base hydraulic model, the development of the topography using drones with a limited budget, an analysis of water demand, the development of a digital hydraulic model, and a hydraulic analysis of the system. The product generated is a tool to assess the overall performance of the network and contributes to the advancement of SDG-6, SDG-9, and SDG-11. Finally, this document can be replicated by other cities and companies with similar characteristics (e.g., limited size and budget) and offers an intermediate position on the road to digitalization and the first steps towards the implementation of a digital twin.

Water distribution systems are critical infrastructures that can be the subject of various types of attacks. Concerns range from biological and chemical intrusions in pipelines to operational issues in water control assets. Cyber-attacks have also turned today into a crucial issue to consider. In highly automatized infrastructures, cyber-attacks can be considered as non-planned actions changing system operation to non-expected scenarios. They can potentially produce unavailability of enough water appropriated for public consumption or critical services such as firefighting. This work proposes to tackle the identification of cyber-attack scenarios through an early-alarm system able to recognize patterns corresponding to abnormal working conditions of the system. Firstly, an on-line forecasting model is developed that is based on the water system expected state regarding nodal pressures, tank water levels and control device flows. Then, an approach based on non-linear autoregressive networks with exogenous inputs (NARX) is proposed to take advantage of both their computational efficiency and the strong influence of the periodicity of the inputs under study. Finally, an analysis of abrupt change point, conducted in a time series composed by the differences between the observed measurements and the expected data, is built on top of the forecasting model.