Hydrocomplexity represents an area of hydrological science that seeks to unravel the multifaceted dynamics at play within water systems. Recent research has underscored the immense challenges presented by interacting hydrological, climatic, and anthropogenic factors, especially under a changing climate and considering the growing occurrences of extreme events such as floods, torrential rains and droughts. Recent progress in understanding these complexities has been driven by methodological innovations, yet persistent knowledge gaps remain regarding the accurate modeling and management of these systems. Notable advances include the expansion of data sources through remote sensing, the adoption of sophisticated numerical models, and the integration of data-driven analytics and artificial intelligence. However, the need for comprehensive, up-to-date syntheses of current achievements and remaining obstacles is urgent, particularly as societies seek to ensure the sustainability and resilience of water resources in an uncertain future.

This Research Topic aims to consolidate and critically review the latest developments shaping the frontier of hydrocomplexity. Authors are invited to synthesize emerging research, highlighting conceptual breakthroughs and methodological progress that enhance our understanding of, and response to, the interconnected challenges within water systems. The objective is to facilitate meaningful dialogue on innovative practices, inspire further research, and inform adaptive strategies that can improve water resource management and resilience to environmental stressors.

The scope of this Research Topic is limited to recent advances contributing to the understanding and resolution of hydrocomplexity in water systems, with a primary emphasis on new approaches and emerging technologies. We welcome review articles that address, but are not limited to, the following themes:

- Developments in numerical modeling and simulation of hydrological systems

- New data sources and innovations in remote sensing for hydrological research

- Advances in model-data fusion techniques and integration methodologies

- Data-driven and machine learning approaches for complex water system analysis

- Applications of artificial intelligence for water management decision support

- Prediction and management of extreme hydrological events (e.g., floods, droughts)

- Progress in ecohydrology and the interplay between ecological and hydrological processes

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Reviews in Hydrocomplexity