which outlines the major risks and concurrently sets all necessary cost-effective measures to abate all anthropogenic impacts and sustain the good water status of both surface and groundwater [4]. As complementary legislation to the aforementioned WFD, Directive 2008/105/EC introduced Environmental Quality Standards (abbr. EQSs) in the water policy field [5]. Decision No 2455/2001/EC prioritized thirty-three (33) chemical substances in soft waters [6]. Directive 2013/39/EU amended the WFD and EQS requirements and adopted an updated, enlarged list of priority substances in published annexes [7]. Parameter monitoring and sampling is undertaken all year round. European water quality legislation is based on the United Nation's Integrated Methodological Framework and the deeper involvement of stakeholders is expected in the implementation of properly established river basin management plans towards water sustainability pathways. The former entails the issuing of Integrated Water Management Plans on a local and regional basis. Innovative ideas for the utilization of water resources are promoted through funded European programs as a priority area (Horizon 2020, Interreg, etc. ), based on legislation revision on the reuse of treated wastewater (industrial and domestic) for a variety of purposes, e.g., irrigation, peri-urban green and agriculture watering, water use for industrial needs, etc. [8; 9]. In EU countries, numerous agricultural activities are conducted, many of which are breeding farms, i.e., cattle farming, piggeries, poultries, etc., and certain administrative regions are covered with cultivated plots, mostly energy crops (i.e., sunflowers, sugar beets), cereals (i.e., wheat, maize, barley, oats), cotton, potatoes, and hydroponic green houses. All the aforementioned crops are irrigated by river waterbodies, with pumping stations abstracting water from local aquifers and water collection basins via a carefully engineered complicated irrigation network. Topsoil fertilization threatens soft water quality through increased salinity and nitrate pollution. Furthermore, agents rich in nitrogen (N), via their fate in the soil and inevitable propagation in rock beds, cause ion mobility, mineralization, etc. Aquifers' quality changes since, e.g., a new nitrogen pool enters the nitrogen cycle of the local ecosystem (Figure 1), unbalancing the water-soil-nutrient equilibrium. Yet, the humic part of the soil, microbiota, favors the formation of nitrous oxides, a strong greenhouse gas (GHG) with a great impact on climate change worldwide. Figure 1: Water, carbon/nitrogen carbon cycle, ambient pathways including corresponding pools in soil, surface, and atmosphere and brief mechanisms of transformation. Water/pollutant flow through porous media demonstrates a high complexity embodied via mathematical simulation models. Complexity increases explainability to the detriment of the processing difficulties to be encountered. Ontologies describe in full detail well-defined interrelated phenomena, suitably bound in conceptual structures of fluids flowing through porous media which are applied in artificial intelligence and affect new infiltration model generation [10]. Nutrient leachate prediction models estimate not only the residual nitrate part applied on the cropland but also all potential seeping losses of the nitrate pool into varied soil profile layers, combined with local weather characteristics and farming practices. Artificial intelligence (AI) and machine learning models are gaining an even higher importance [11] as an alternate reliable method for handling complicated nonlinear hydrological modeling with good countrywide-scale predictions. In numerous cases, a lack of sufficient and proper data, necessary to attain hydrological model calibration, combined with many parameter inputs for demanding, profound modeling, drastically increases the processing burden and undermines prediction accuracy and reliability.