Numerically enhanced conceptual modelling (NECoM) applied to the Malta Mean Sea Level Aquifer

Conventional hydrogeological practice is to formulate a conceptual model, which is often the basis of a numerical model. The numerical model is then used to test groundwater management strategies. A workflow is proposed, employing the numerically enhanced conceptual model (NECoM) of the Mean Sea Level Aquifer (MSLA) on the island of Malta. The Malta MSLA is overexploited and under threat of salinization. Data (heads, chloride concentrations, electrical conductivity logs, tidal tests and qualitative analyses) were assimilated into a fast-running numerical model. Simultaneously, strategies for optimal acquisition of further data were examined through the modelling process. The model was delivered through the Energy and Water Agency, with suggestions for flexible model deployment. These workflows will, hopefully, spawn model improvements through further revision of the base concepts. The model allows the agency to make predictions, which have uncertainties that are quantified and reduced through data assimilation as new data become available. Contemplated management plans can therefore be properly assessed before implementation. The proposed NECoM approach can be generalized since it bases model usage on the premise that modelling should make maximum use of existing data by assimilating its information content, thereby highlighting the uncertainties of decision-critical predictions that remain because of data insufficiency. Thus, the presently disjointed process of modelling on the one hand, and data acquisition on the other, can be better aligned. Conceptual and numerical model development become parallel, rather than sequential, activities. Together, they enable predictions of future system behaviour for which bias is reduced and uncertainties quantified.