From Forest Canopy to Streamflow: Practice-Based and Data-Driven Insights for Adaptive Catchment Water Management

Forests and water are tightly coupled components of the Earth system, influencing hydrological processes from soil moisture dynamics to streamflow generation, groundwater recharge, and water quality regulation. Although forests are often promoted as natural regulators of water resources, growing scientific evidence shows that forest–water interactions are highly context-specific, scale-dependent, and governed by hydrological trade-offs rather than universal benefits. Recent advances in satellite remote sensing, in-situ monitoring networks, climate reanalysis datasets, and artificial intelligence–based analytics have significantly improved the capacity to observe and interpret forest–water processes across spatial and temporal scales. Building on these developments, this paper presents a practice-oriented, data-informed synthesis of forest–water interactions at the catchment scale, integrating classical hydrological understanding with recent global evidence (2020–2025) and field experience from monsoon-dominated environments such as India. Drawing on watershed observations and published studies, the analysis examines how forest type, structure, and condition influence key hydrological indicators including evapotranspiration, water yield, baseflow persistence, peak flow response, sediment transport, and water quality. The synthesis highlights the growing role of Earth observation and AI-enabled analysis in improving understanding of forest–water dynamics and provides practical insights for resilient, evidence-based catchment water management. Conceptual overview of forest–water interactions across scales, illustrating how forest structure and management influence hydrological processes and water outcomes, while satellite observation, sensor networks, and data-driven analytics support adaptive catchment water management