Tools and Technologies

This catalogue is a dataset of data models, AI technologies, simulation tools, intelligent systems, and digital twins for inland water management. The catalogue includes hydrological models for predicting flow and quality, social models for water usage, and hydraulic models for urban distribution. AI technologies, such as machine learning algorithms for processing hydrological data and analysing satellite images, are identified. Simulation tools are catalogued based on their ability to predict event outcomes. Intelligent systems integrating cyber-physical architectures, sensors, actuators, and software are analysed for their roles in monitoring, event detection, risk assessment, and decision support. Digital twins, which combine real data with models and simulations to create virtual system replicas, are also included.

ID â–² Name Technology Type Data used as input Produced datasets (openly available) Demo (video if available) Paper (if available) Paper DOI (if available) Project ID (if available) Project Acronym (if available) Service description
technologies-611 NaWaTech Community of Practice (CoP) Knowledge Sharing Platform Experiences and know-how from stakeholders Network of stakeholders from academia, industry, end-users, and decision-makers 308336 NAWATECH-EU PART Forum for exchange of knowledge and establishment of long-term partnerships.
technologies-612 NaWaKit Decision Support Online Platform Key results and information of the project Technical and business strategy tools for water practitioners 308336 NAWATECH-EU PART One-stop information tool for conceiving, launching, and growing a venture in the water and wastewater sector.
technologies-613 NaWaTech Video Dissemination Video Project overview, technologies, pilot projects Condensed overview of the project, including 3D animations and site footage https://www.youtube.com/watch?v=yfiiUT-WGws&feature=youtu.be 308336 NAWATECH-EU PART Provides a complete overview of the project.
technologies-614 Technical Notes Technology Implementation Guidance Documents Knowledge gained in WP1, WP2, and WP3 Ready source of information for practitioners 308336 NAWATECH-EU PART Ensuring the uptake practice of NaWaTech systems by practitioners.
technologies-615 NaWaTech Business Plan Guidelines SME Support Guidelines NaWaTech approach, market analysis, business model development Guidelines on how SMEs can integrate NaWaTech into their business plans 308336 NAWATECH-EU PART Supports SMEs in developing their business ideas based on the NaWaTech approach.
technologies-616 Decision Support System (DSS) for Na concentration control Hydroponics, Software Decision Support System Nutrient solution data Na concentration recommendations 245159 SIRRIMED Controls Na concentration in hydroponic nutrient solutions.
technologies-617 Benchmarking Tool (WAD - Web-based Analysis and Database tool) Web-based Software Data Analysis Tool District-scale irrigation data Irrigation performance indicators, Best Management Practices 245159 SIRRIMED Assesses irrigation performance and proposes best management practices.
technologies-618 District Information System (DIS) for Campo de Cartagena GIS-based modeling approach, Crop & Hydraulic Models, Remote Sensing Information System Groundwater data, Surface water data, Remote sensing data, Irrigation Water Applied data Irrigation bulletin at Farm-level 245159 SIRRIMED Quantifies water use and provides irrigation recommendations.
technologies-619 District Information System (DIS) for Plaine de Crau GIS-based modeling approach, Crop Model (STICS), Remote Sensing (EVASPA, BV-NNET) Information System Remote sensing data (Evapotranspiration - EVASPA, LAI and fraction cover - BV-NNET), Agricultural practices, Climate data Water balance sensitivity under climate change for hay production 245159 SIRRIMED Quantifies water balance sensitivity under climate change for hay production.
technologies-620 AquaData Software Data Management Tool Crop model (AquaCrop) input data Prepared input data for AquaCrop Lorite et al., 2013 245159 SIRRIMED Manages input data for AquaCrop model (Lorite, I.J. et al., 2013).