Environmental Decision Support Systems as a Service: Demonstration on CE-QUAL-W2 Model

An Environmental Decision Support System (EDSS) can be used as an important tool for rehabilitation and preservation of ecosystems. Nonetheless, high assimilation costs (both money and time) are one of the main reasons that these tools are not widely adapted in practice. This work presents a low-cost paradigm of "EDSS as a Service", this paradigm is demonstrated for developing Water Quality EDSS as a Service that utilizes the well-known CE-QUAL-W2 model as a kernel for deriving optimized decisions. The paradigm is leveraging new open-source technologies in software development (e.g. Docker, Kubernetes, and Helm) with cloud computing in order to significantly reduce assimilation costs of the EDSS for organizations and researchers working on rehabilitation and preservation of water bodies.

Survey of Process of Data Discovery and Environmental Decision Support Systems

The process of data discovery is an approach to extracting knowledge, valid, and usable information from large amounts of data, using automatic or semi-automatic methods. This article is an inventory of the different information extraction processes encountered in the literature for different fields of application and for the development of environmental informatics. Following an analysis between the different models, we can summarize the existing models with a proposal for a process that exploits the strengths of the different processes.

Integrating citizen science, open and big data into water and environmental decision support systems

<p>Water and environmental monitoring, observation and decision support systems (DSS) are being transformed by a wealth of open and big data that are increasingly available, accurate and timely. Consolidated technologies of earth observation, remote sensing, geospatial modelling and visualization systems are stimulating earth, hydrological and environmental sciences that are reacting not only with increasing scientific production, but with novel solutions-oriented methods, tools and algorithms. Procedures, methods and tools are more and more available for analysis, interpretation and mapping of river and basin coastal landscape features and hydro-environmental dynamics. Citizen science are further empowering the capabilities of DSS by gathering and sharing data on the human behaviour component to better understand the nature-human-urban interplay. Citizens, empowered by mobile devices, act as data and information producers, receivers and transmitters supporting the assessment of the effects of human-derived observations, feedbacks and actions sensing. Emerging hardware and software technologies (e.g. machine learning, artificial intelligence, IoT, etc.) are creating amazing opportunities for these DSS linked to the development of the human-machine interface and its use for promoting practical environmental and social actions to manage and mitigate natural hazard and climatic risks. The National System for Environmental Protection (SNPA) by the Italian Institute for Environmental Protection and Research (ISPRA) is supporting and implementing a wide and diverse range of research, applied research, learning and communication activities, both at the national and international level, in collaborating with leading academic, professional and international organizations, for integrating citizen science, open data and big data into next generation water and environmental decision support systems. This contribution, while depicting the overall SINA framework (Italian Environmental Information System) and ongoing and planned activities by ISPRA SNPA and SINA, presents recent outcomes of research initiatives developed within the Water JPI, UNEP INFORAC, National Plan for Climate Adaptation (PNACC), Marine pollution, Biodiversity, the Water, Food and Energy Nexus among others. Insights from joint research efforts and working groups are presented and shared while pursuing further synergies and stimulate the discussion on this crucial topic for national and international agencies, like ISPRA, that seek to transfer research data, models and tools into institutional and operational activities.</p>

Environmental Decision Support Systems for Monitoring Small Scale Oil Spills: Existing Solutions, Best Practices and Current Challenges

In recent years, large oil spills have received widespread media attention, while small and micro oil spills are usually only acknowledged by the authorities and local citizens who are directly or indirectly affected by these pollution events. However, small oil spills represent the vast majority of oil pollution events. In this paper, multiple oil spill typologies are introduced, and existing frameworks and methods used as best practices for facing them are reviewed and discussed. Specific tools based on information and communication technologies are then presented, considering in particular those which can be used as integrated frameworks for the specific challenges of the environmental monitoring of smaller oil spills. Finally, a prototype case study actually designed and implemented for the management of existing monitoring resources is reported. This case study helps improve the discussion over the actual challenges of early detection and support to the responsible parties and stakeholders in charge of intervention and remediation operations.