Ariele Zanfei

AIAQUA

The ongoing transformation of the electricity market has reshaped the hydropower production paradigm for storage reservoir systems, with a shift from strategies oriented towards maximizing regional energy production to strategies aimed at the revenue maximization of individual systems. Indeed, hydropower producers bid their energy production schedu...

A reliable short-term forecasting model is fundamental to managing a water distribution system properly. This study addresses the problem of the efficient development of a deep neural network model for short-term forecasting of water consumption in small-scale water supply systems. These aqueducts experience significant fluctuations in their consum...

Short-term forecasting of water demand is a crucial process for managing efficiently water supply systems. This paper proposes to develop a novel graph convolutional recurrent neural network (GCRNN) to predict time series of water demand related to some water supply systems or district metering areas that belong to the same geographical area. The a...

Sustainable management of water resources is a key challenge for the well-being and security of current and future society worldwide. In this regard, water utilities have to ensure fresh water for all users in a demand scenario stressed by climate change along with the increase in the size of cities. Dealing with anomalies, such as leakages and pip...

Representing reality in a numerical model is complex. Conventionally, hydraulic models of water distribution networks are a tool for replicating water supply system behaviour through simulation by means of approximation of physical equations. A calibration process is mandatory to achieve plausible simulation results. However, calibration is affecte...

Sustainable use of water and energy sources is a crucial challenge for smart and resilient urban water infrastructure. At this aim, this study presents a methodology for implementing and selecting pumps-as-turbines (PaTs) in water distribution networks (WDNs) to minimise leakage losses and maximise energy recovery. A novel dynamic control algorithm...

The current water shortage and energy crises due to climate change, geopolitical problems, and the increasing demand for these resources require considerable efforts to develop new sustainable and efficient solutions. The sector with the most significant impact on water resources and consequently also suffers most from the water shortage is agricul...

In recent years, the sustainable management of urban water got increased attention from the scientific community. Indeed, a plethora of studies dealt with the creation of digital tools for improving and optimizing the use of water. Among the emerging trends in the field, it highlights the rise of complex networks and graph neural networks for infra...

The water industry is facing significant challenges due to the effects of climate change and energy crises. To address these issues, the water sector is undergoing a digital transformation, leveraging digital technologies and methods, such as artificial intelligence and smart sensors, to improve sustainable supply, distribution, and treatment of wa...

General Circulation Models (GCMs) simulations result on grids ranging from 50 km to 600 km, and, therefore, this coarse spatial resolution requires data processing, whereby the application of downscaling techniques has become a standard procedure. The main approaches employed are Statistical DownScaling (SDS) and Dynamic DownScaling (DDS). The form...

Drinking water demand modelling and forecasting is a crucial task for sustainable management and planning of water supply systems. Despite many short-term investigations, the medium-term problem needs better exploration, particularly the analysis and assessment of meteorological data for forecasting drinking water demand. This work proposes to anal...

Leakages in distribution networks reach more than 30% of the water supplied, entailing important risks for the water infrastructure with water contamination issues. Therefore, it is necessary to develop new methods to mitigate the amount of water wastes. This study proposes to seek new sources of information that can help for a more sustainable wat...

Water demand management is essential for water utilities, which have the critical task of supplying drinking water from water sources to end-users through the distribution network. Therefore, the water utilities have to make decisions for the current and future functioning of the water distribution system. In this context, the artificial intelligen...

Managing water distribution systems (WDS) in large metropolitan areas is a complex task. As highly connected, buried infrastructures, WDS are often exposed to failures and pose difficult control problems. To recover its capacity, various rehabilitation alternatives can be considered. Yet, specially in large, intermittent WDS, the wide spectrum of a...

A reliable short-term forecasting model is fundamental to manage a water distribution system properly. In the latest years, a plethora of methods have been proposed by the scientific community, ranging from classic naive methods to the more sophisticated statistical and machine learning models. Among several methods, neural networks gained particul...

Nowadays, drinking water demand forecasting has become fundamental to efficiently manage water distribution systems. With the growth of accessible data and the increase of available computational power, the scientific community has been tackling the forecasting problem, opting often for a data-driven approach with considerable results. However, the...

Sustainable management of water resources is a key challenge nowadays and in the future. Water distribution systems have to ensure fresh water for all users in an increasing demand scenario related to the long-term effects due to climate change. In this context, a reliable short-term water demand forecasting model is crucial for the optimal managem...

Water demand increases in urban zones, and water scarcity is associated with maintenance problems, such as leakage and pipe ageing, which inevitably lead to complex water distribution systems (WDS) management. In this scenario, intermittent operation emerges as an alternative for system operation. This is not the most desirable solution from a soci...

Water distribution system monitoring is currently carried out using advanced real-time control technologies to achieve a higher operational efficiency. Data analysis techniques can be implemented for condition estimation, which are crucial tools for managing, developing, and operating water networks using the monitored flow rate and pressure data a...

Short-term streamflow forecasting is crucial for many activities including flood risk mitigation, multi-use water management and production planning for hydropower plants. Several studies have shown that data-driven approaches are more suitable for operational forecasting than physics-based models due to the higher flexibility and reproducibility o...

The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparameters making the models’ tuning a tricky and crucial task. We hence propose an insightful analysis of...

Developing data-driven models for bursts detection is currently a demanding challenge for efficient and sustainable management of water supply systems. The main limit in the progress of these models lies in the large amount of accurate data required. The aim is to present a methodology for the generation of reliable data, which are fundamental to t...

Water leakages are one of the most significant uncertainties affecting water supply system (WSSs) modelling. Due to the dependence between water losses and pressure, the WSSs characterised by high values of pressure in the distribution network are strongly affected by this problem. High-pressure conditions are typical of WSSs in the mountain areas....

Proper hydraulic simulation models, which are fundamental to analyse a water distribution system, require a calibration procedure. This paper proposes a multi-objective procedure to calibrate water demands and pipe roughness distribution in the context of an ill-posed problem, where the number of measurements is smaller than the number of variables...

Many efforts have been made in recent decades to formulate strategies for improving the efficiency of water distribution systems (WDS), led by the socio-demographic evolution of modern society and the climate change scenario. The improvement of WDS management is a complex task that can be addressed by providing services to maximize revenues while e...