The design, implementation and demonstration of a novel and generic computational forecast framework for multi-scale prediction of extreme sea levels and associated flooding is presented. Denoted Water Information Forecast Framework (WIFF), it integrates process-based models for waves, tides and surges from regional to local scales, predicting the flooding of coastal areas, and supporting the routine and emergency management of coastal resources. WIFF manages the simulations and the real-time monitoring data, archives the data and makes the information available through a WebGIS that targets users with distinct access privileges. Additionally, the web component of WIFF adapts automatically and transparently to any device. WIFF also provides ways to assess the model accuracy and generates tailored products based on model results and observations. WIFF is demonstrated in the prediction of extreme water levels in the Portuguese coast, simulating processes at different scales: at basin scales, waves are simulated in the North Atlantic and in the Portuguese shelf, and sea levels due to tides and atmospheric forcings are simulated in the Northeast Atlantic; at estuarine scales, high-resolution, fully coupled wave/circulation predictions are performed in the Tagus estuary to account for wave-current interactions. User-oriented georeferenced products are generated, including automatic model/ data comparisons, targeting the needs of civil protection agents and combining for the first time an agile, service-oriented platform with high-resolution, process-rich predictions of the Tagus dynamics.

Wireless sensor networks are being increasingly used in several application areas, particularly to collect data and monitor physical processes. Non-functional requirements, like reliability, security or availability, are often important and must be accounted for in the application development. For that purpose, there is a large body of knowledge on dependability techniques for distributed systems, which provide a good basis to understand how to satisfy these non-functional requirements of WSN-based monitoring applications. Given the data-centric nature of monitoring applications, it is of particular importance to ensure that data are reliable or, more generically, that they have the necessary quality. In this survey, we look into the problem of ensuring the desired quality of data for dependable monitoring using WSNs. We take a dependability-oriented perspective, reviewing the possible impairments to dependability and the prominent existing solutions to solve or mitigate these impairments. Despite the variety of components that may form a WSN-based monitoring system, we give particular attention to understanding which faults can affect sensors, how they can affect the quality of the information and how this quality can be improved and quantified.

A new oil risk management system is proposed herein. Risk is computed in a quantitative way, combining a detailed hazard maps generated with a process-based oil spill model over an unstructured computational grid, and a spatially detailed methodology for vulnerability analysis. The system has a web interface that serves as a single point of access to both emergency-driven and risk-management products. The system's products are made available to decision makers and emergency response agents through a WebGIS portal. The paper describes the methodological bases and application of a risk-assessment tool that provides hazard, vulnerability and risk assessment maps for oil spills in coastal areas. The system is demonstrated in the Aveiro lagoon. The hazard maps are obtained from the analysis of an oil spill scenarios database, generated for the climatological conditions most prone to the occurrence of an oil spill event in the study region. Several vulnerability indexes are considered (namely physical, socio-economical, biological and global vulnerability indexes) and adapted to consider the intertidal areas, instead of the commonly-used coastline representation of the vulnerability indexes usually found in the literature. This new feature was possible due to the capability of the oil spill model to represent the process of oil retention and re-suspension in the intertidal zones. The methodology and the risk management system and its WebGIS interface are of generic nature and can be applied to other hazards in coastal zones.

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Abstract-This paper presents an innovative real-time information system for enhanced support to flood risk emergency in urban and nearby coastal areas, targeting multiple users with distinct access privileges. The platform addresses several user requirements such as 1) fast, online access to relevant georeferenced information from wireless sensors, high-resolution forecasts and comprehensive risk analysis; and, 2) the ability for a two-way interaction with civil protection agents in the field. The platform adapts automatically and transparently to any device with data connection. Given its specific purpose, both data protection and tailored-to-purpose products are accounted for through user specific access roles. This paper presents the platform's overall architecture and the technologies adopted for server-side, focusing on communication with the front-end and with the wireless sensor network, and the user interface development, using state-of-the-art frameworks for cross-platform standardized development. The advantages of the adopted solution are demonstrated for the Tagus estuary inundation information system.