Objectives

Groundwater is an important resource for water supply that is currently threatened by:

  • Saline intrusion
  • Pollution with pesticides and nutrients (agriculture), pharmaceuticals and antibiotic resistance genes from wastewater treatment plant effluents, hydrocarbons and heavy metals (runoff), and microplastics (both)
  • The effects of global and climate change

Although several initiatives have developed measures and tools for groundwater monitoring and protection, additional knowledge is needed to understand the synergistic effects and risks of multiple stressors and contaminants and to develop cost-effective groundwater monitoring strategies, pollution prevention and abatement technologies, and early warning systems.

NINFA will provide a novel strategy based on an early-warning DSS and knowledge base (the NINFA Plat-form) and a series of innovative and cost-effective monitoring, modelling and treatment solutions, considering diverse pollutants (nutrients, pesticides, salinity, CECs, ARG, and MP) and synergistic effects regarding stressors derived from climate and global changes, with the aim of preventing GW contamination, protecting its quality and enhancing its resilience.

Other sources of pollution, including wastewater treatment plant effluent and urban runoff infiltration (especially during storms), contaminate groundwater with contaminants of concern (CECs) such as pharmaceuticals, microplastics, and antibiotic resistance genes, as well as hydrocarbons and heavy metals. In addition, the exploitation of aquifers for water consumption results in increased pressure on groundwater resources, which may be exacerbated by climate change (lack of natural recharge to aquifers). In coastal aquifers, this problem is exacerbated by the intrusion of salts, mainly caused by water abstraction, which affects the quality of the groundwater.

NINFA’s innovative approach aims to facilitate the transition to a more effective groundwater management decision-making system by increasing knowledge of water flows, in situ mobility, and CEC transformation, and by developing predictive models to promote the treatment and reuse of water and its quality.

Groundwater is an important resource for water supply that is currently threatened by: i) saline intrusion; ii) pollution with pesticides and nutrients (agriculture), pharmaceuticals and antibiotic resistance genes from wastewater treatment plant effluents, hydrocarbons and heavy metals (runoff), and microplastics (both); iii) the effects of global and climate change. Although several initiatives have developed measures and tools for groundwater monitoring and protection, additional knowledge is needed to understand the synergistic effects and risks of multiple stressors and contaminants and to develop cost-effective groundwater monitoring strategies, pollution prevention and abatement technologies, and early warning systems.

NINFA will develop a novel strategy based on an early warning system and knowledge database (NINFA Platform) and innovaDiffuse pollution affects 35% of the area of groundwater bodies with pollutants such as pesticides, herbicides, and nutrients (leading to eutrophication and oxygen depletion).

Other sources of pollution, including wastewater treatment plant effluent and urban runoff infiltration (especially during storms), contaminate groundwater with contaminants of concern (CECs) such as pharmaceuticals, microplastics, and antibiotic resistance genes, as well as hydrocarbons and heavy metals. In addition, the exploitation of aquifers for water consumption results in increased pressure on groundwater resources, which may be exacerbated by climate change (lack of natural recharge to aquifers). In coastal aquifers, this problem is exacerbated by the intrusion of salts, mainly caused by water abstraction, which affects the quality of the groundwater.

NINFA’s innovative approach aims to facilitate the transition to a more effective groundwater management decision-making system by increasing knowledge of water flows, in situ mobility, and CEC transformation, and by developing predictive models to promote the treatment and reuse of water and its quality.