Aims & Scope
Hydroinformatics is a highly interdisciplinary subject that promotes the fundamental understanding and technology developments of the water cycle in natural system and the built environment in a digital era under uncertainty of global changes. It emphasizes the interactions between natural system from atmosphere to ocean and the built environment via artificial interventions in that cycle such as urban drainage, low impact development, flood and drought management, wastewater treatment, and water supply systems with the aid of sensing, monitoring, modeling, and control technologies. It also provides knowledge via decision science at all levels from governance and policy to management and operations, as well as strives to understand the social decision-making processes by which existing and emerging sensing, information, communication, automation, and control technologies are brought into practical use. While all synergistic applications of the above technologies are highly encouraged for use in addressing the increasingly serious water problems under global change impact, the traditional numerical simulation, optimization and forecasting of water flows and related hydrological and hydraulic processes remain a foundation of hydroinformatics. Topics of integrative informatics and hydrosystems covered by the journal include, but are not limited to, the following areas:
Theoretical Innovation in Process Modelling of Hydrosystems: Advancing hydrosystem modelling can help improve the understanding of many water-related processes with synergies in information, communication, automation, and control technologies. These hydrosystem models may include traditional models of computational hydrology and hydraulics or expanded models accounting for hydroenvironmental, hydrogeological, ecohydrological, ecohydraulic or cryospheric complexity. The following topics are of primary interest:
- Water-related natural hazard impacts (floods, droughts, mud flows, landslides etc.)
- Water quality variations in biogeochemical and/or biogeophysical cycle
- Compound effect driven by advanced physical, chemical, biological, and/or ecological processes
- Assessment of resilience and sustainable strategies
- Exploratory integration of emerging data, information, model, and knowledge
- Entropy theory and uncertainty assessment
- Order or disorder in models with chaotic and fractal implications
- Water infrastructure management and operation
- Interactions between surface and groundwater systems
- System analysis and system complexity
- Integration of simulation, optimization, forecasting and/or control models
- Predictions using extreme weather simulators or climate change patterns in hydrosystems
Computational Advancement of Hydrosystems Analysis via Data Science, Artificial Intelligence, Machine Learning and Informatics: Sensing, monitoring, modelling, and computing technology development in concert with advanced sensors, networks, platforms, communication, control, and data management strategies are essential for integrating informatics and hydrosystems. Exploration of advances in hydrosystem modelling with high-end computational intelligence techniques, machine learning tools, advanced computing methods, spatial analysis platforms, and data-driven approaches complement and enhance process modelling. The following topics are to be considered:
- Synergies between deductive and inductive approaches in hydrosystems analysis
- Computationally efficient emulators and digital twins
- Semantic knowledge engineering
- Spatiotemporal data analytics, forecasting, wavelets and geospatial analysis
- Computational intelligence and machine learning techniques (e.g., artificial neural networks, deep learning, support vector machine, ensemble learning, ant colony optimization, cellular automata etc.)
- Optimization techniques, including evolutionary computing and reinforcement learning
- Virtual reality, augmented reality and holography
- Edge computing, cloud computing, and distributed computing technologies
- Programming languages and data structure modelling
- Data-driven modelling and data science in simulation, forecasting, control and uncertainty assessment
- Advanced data harvesting methods, adaptive data analysis, and big data analytics techniques
- Data mining, fusion, assimilation, stochastic tools (copula) and statistical assessment (regression, classification, and clustering)
- Critical zone observatory, sensor networks and citizen observations
- Data centers, cloud solution and high-performance computational infrastructure
- Hydrosystems integrated with sensing, communication, networking and control technologies
- Internet of Things and advanced sensing in hydrosystems
Education, Training and Management via Hydroinformatics: The social, economic, and political processes and the consequences of such processes are critical in hydrosystems. Managerial need may lead to analyze the combined effects of these processes and identify options for governance and policies toward adaptation in a complex and uncertain hydroenvironment. Close interactions of education, training and management can help understand how the systems function socially to enable the managerial interventions in hydrosystems, such as:
- Socio-economic, policy and regulations studies via hydroinformatics
- Capacity building for education and training via hydroinformatics
- Interface with society via hydroinformatics
- Intelligent systems and decision making related to hydrosystems
- Intelligent decision support, negotiation and management related to hydrosystems
- Hydroinformatics libraries, ontology and holography
- Decision support systems and expert systems related to hydrosystems
- Governance structures and functions related to hydrosystems
- Risk assessment and policy analysis related to hydrosystems
- Gaming theory and decision making related to hydrosystems
- Socio-economic-environmental framework analysis in hydroinformatics
- Internet-based applications for education and training for hydroinformatics
Journal of Hydroinformatics is published monthly.