Work package 4

Models and software tools
Lead beneficiary : CUT

      Start Month    10              End Month    24

Participant numberShort name of participantPerson months per participant

• To identify, test, and evaluate the core technologies for GWS simulation and forecasting
• To deliver prototypes and integrated methodologies that will be applicable to the test sites’ data
• To enhance modelling tools by integrating artificial intelligence and deep learning algorithms
• To combine modelling tools to a joint approach covering a wide range of data availability and complexity

Description of work

This WP constitutes the research core of MEDSAL, as it will evaluate a cascade of existing and new techniques/methodologies to develop state-of-the-art simulation tools of GWS assessment and forecast. These tools will be applied in suitable demo sites (selected sites from case study areas) as stand-alone tools, to evaluate their individual performance and identify any limitations and/or specifics needed, to be appropriately applied in selected combinations at WP5. The tools/methods to be used include hydrogeological and hydrogeochemical models, advanced geostatistics, and machine learning techniques. The aforementioned tools/methods will be combined in the last task of the WP; thus, integrated the stand-alone tools into holistic methodological approaches, as part of the overall MEDSAL Framework.

WPsTasks LeadersPPs InvolvedDuration
T4.1Interoperability of Geo-DatabseCUTCUT, CERTH, UIZM16-M18
T4.2Advanced GeostatisticsCUTCUTM18-M22
T4.3Physical-based models for groundwater flow and salinization transportSWRISWRI, FSTM18-M22
T4.4Hydrogeochemical modelling of salinization in groundwater systemsMEUMEU, SWRI, THLM18-M22
T4.5Shallow and Deep Learning Methodologies CERTHCERTHM18-M22
T4.6Integration of MEDSAL Models and ToolsCUTCUT, CERTH, SWRI, THL, MEUM20-M24