Artificial Intelligence and Resilient Water Governance: A Comparative Analysis of Data-Driven Models in Morocco, Israel, and Singapore

Abstract

Sustainable water resource management has become a major strategic challenge for countries facing structural water stress, particularly in a context where climate change intensifies precipitation variability and further weakens already strained systems. This article analyzes the transition from traditional water governance toward integrated models based on data and artificial intelligence (AI), through a comparative examination of three national trajectories: Morocco, Israel, and Singapore.

Drawing on a systematic literature review and a qualitative comparative multi-case methodology, the study highlights the institutional frameworks, technological architectures, and governance mechanisms specific to each context. The findings show that the performance of water systems largely depends on the level of digital maturity, the degree of decision-making coordination, and the capacity to integrate and leverage data effectively.

The analysis also reveals significant gaps in terms of interoperability, data governance, and the adoption of emerging technologies. Based on these insights, the article proposes a conceptual model of data-driven resilient water governance tailored to the Moroccan context, structured around three complementary dimensions: institutional, technological, and organizational.