Related papers: Evaluating Time Series Models for Urban Wastewater…
Urban water distribution systems hold a critical and strategic position in preserving public health and industrial growth. Despite the ubiquity of these urban systems, aging infrastructure, and increased risk of terrorism, decision support…
Weather forecasting plays a crucial role in supporting strategic decisions across various sectors, including agriculture, renewable energy production, and disaster management. However, the inherently dynamic and chaotic behavior of the…
Data stream forecasts are essential inputs for decision making at digital platforms. Machine learning algorithms are appealing candidates to produce such forecasts. Yet, digital platforms require a large-scale forecast framework that can…
Accurate and efficient models for rainfall runoff (RR) simulations are crucial for flood risk management. Most rainfall models in use today are process-driven; i.e. they solve either simplified empirical formulas or some variation of the…
The electric grid is a key enabling infrastructure for the ambitious transition towards carbon neutrality as we grapple with climate change. With deepening penetration of renewable energy resources and electrified transportation, the…
In urban drainage systems (UDS), a proven method for reducing the combined sewer overflow (CSO) pollution is real-time control (RTC) based on model predictive control (MPC). MPC methodologies for RTC of UDSs in the literature rely on the…
Climate change results in altered air and water temperatures. Increases affect physicochemical properties, such as oxygen concentration, and can shift species distribution and survival, with consequences for ecosystem functioning and…
Industrial ecosystems are coupled with natural systems through utilization of feedstocks and waste disposal. To ensure resilience in production of industrial systems under the threat of climate change scenarios, it is necessary to evaluate…
Projecting climate change is a generalization problem: we extrapolate the recent past using physical models across past, present, and future climates. Current climate models require representations of processes that occur at scales smaller…
Underground water and wastewater pipelines are vital for city operations but plagued by anomalies like leaks and infiltrations, causing substantial water loss, environmental damage, and high repair costs. Conventional manual inspections…
Environmental disasters such as flash floods are becoming more and more prevalent and carry an increasing burden on human civilization. They are usually unpredictable, fast in development, and extend across large geographical areas. The…
Extreme streamflow is a key indicator of flood risk, and quantifying the changes in its distribution under non-stationary climate conditions is key to mitigating the impact of flooding events. We propose a non-stationary process mixture…
The Internet of Underwater Things (IoUT) is becoming a critical infrastructure for ocean observation, marine resource management, and climate science. Its development is hindered by severe acoustic attenuation, propagation delays far…
Cloud microphysics has important consequences for climate and weather phenomena, and inaccurate representations can limit forecast accuracy. While atmospheric models increasingly resolve storms and clouds, the accuracy of the underlying…
Sustainability and efficiency have become essential considerations in the development and deployment of Artificial Intelligence systems, but existing regulatory practices for Green AI still lack standardized, model-agnostic evaluation…
Smart cities transform urban landscapes with interconnected nodes and sensors. The search for seamless communication in time-critical scenarios has become evident during this evolution. With the escalating complexity of urban environments,…
A modern-day society demands resilient, reliable, and smart urban infrastructure for effective and in telligent operations and deployment. However, unexpected, high-impact, and low-probability events such as earthquakes, tsunamis,…
In an era of escalating climate change, urban flooding has emerged as a critical challenge for sustainable cities, threatening lives, infrastructure, and ecosystems. Traditional flood detection methods are constrained by their reliance on…
Modelling of precipitation and its extremes is important for urban and agriculture planning purposes. We present a method for producing spatial predictions and measures of uncertainty for spatio-temporal data that is heavy-tailed and…
Effective riverine flood forecasting at scale is hindered by a multitude of factors, most notably the need to rely on human calibration in current methodology, the limited amount of data for a specific location, and the computational…