Data management and storage

An open information infrastructure has been developed which offers free access to hydrological, environmental and geographical data. The framework provides free services of data validation, storage, visualization and retrieval. It is intended to be used both by data providers (e.g., scientific agencies, research institutes, etc.) and by data consumers (e.g., research institutes, educational institutions, practitioners, etc.). The hydrometric data of NOA IERSD are organized with this framework, and can be found here. 

Stochastic analysis

Machine learning models have been proven advantageous in Hurst–Kolmogorov stochastics. The preservation of the long-term persistence and the simultaneous statistical consistency at all time-scales (see climacogram) is important for the correct estimation of the frequency of dry spells and the sustainable water management  (see MLPS in Software).