SOURCE-LINKED INTELLIGENCE
Offshore Freshened Groundwater Prospecting using Machine Learning
Offshore Freshened Groundwater Prospecting using Machine Learning Offshore freshened groundwater (OFG) refers to fluids stored in sediment pores and rock fractures below the seafloor, with a salinity lower than seawater. This phenomenon has been identified globally in continental margins and proposed as a resource that can potentially alleviate water stress in coastal regions. However, the scarcity of data to constrain the distribution and volumes of the reservoirs remains a challenge. OPTIMAL project aims to: (i) develop an interdisciplinary methodology to predict the occurrence and distribution of OFG resources built on Artificial Intelligence and (ii) apply the model globally to infer OFG occurrence and quantify the resource feasibility as a function of distribution characteristics such as offshore extent, depth below the seafloor and fresh to brackish water ratio. The proposed methodology uses a surrogate model to create a dataset
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 161411.52
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T02:21:08.944Z. This is not the publication date.