Environmental hydrology stands at the forefront of scientific efforts to address urgent global challenges such as climate change, shifting land-use patterns, and the intensifying impact of human activity on water systems. These forces increasingly drive complex issues, including agricultural non-point source pollution, ecosystem degradation, and rampant water scarcity across continental and regional scales. While traditional approaches in monitoring and modeling have provided foundational insights into hydrological processes and management, rapid advances in technology and data science now offer the potential to revolutionize how we understand, predict, and manage environmental water resources. However, knowledge gaps remain regarding the effective integration of emerging monitoring tools, advanced models, and decision-support frameworks—especially in translating scientific advances to scalable, actionable solutions.

Recent years have seen significant progress in environmental hydrology, spurred by breakthroughs in sensor networks, Internet-of-Things (IoT) platforms, and real-time remote sensing using UAVs and satellites. At the same time, hydrological modeling is evolving beyond process-based frameworks to leverage artificial intelligence, machine learning, Large Language Models (LLMs), and Digital Twin technologies. Integrated data streams and advanced analytical methods are generating unprecedented opportunities to support adaptive management, foster participatory stakeholder processes, and inform evidence-based policies. Despite these innovations, major challenges persist in closing the gap between technological capability, ecological insight, and practical implementation on the ground.

This Research Topic aims to catalyze and disseminate novel research that advances the full continuum of environmental hydrology, from next-generation monitoring to innovative modeling approaches and the development of decision-support systems for real-world application. By drawing on interdisciplinary advances, this initiative seeks to highlight how hydrological understanding can be harnessed to foster adaptive, resilient, and sustainable water management in the face of mounting environmental pressures.

Covering the full range of scales and settings, the scope of this Research Topic is limited to studies that demonstrate innovation in monitoring, modeling, and informed hydrological management with clear relevance to contemporary environmental challenges. We welcome articles that address, but are not limited to, the following themes:

• Breakthroughs in environmental hydrology and water system understanding

• Development and field application of advanced hydrological models

• Novel monitoring technologies, including IoT, UAVs, and real-time remote sensing

• Integration of AI, machine learning, and LLMs in hydrological science

• Digital Twins and data-driven approaches for water management

• Decision support systems for adaptive and participatory water management

• Impacts of climate change and land-use transitions on hydrology

• Management and mitigation of agricultural non-point source pollution

• Sustainable watershed and catchment management strategies

• Surface-groundwater interactions and ecosystem resilience

• Nature-based solutions for water resource sustainability

Appendix: We welcome submission types including original research articles, methodological advances, perspectives, reviews, and case studies.

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Addressing Grand Challenges in Environmental Hydrology: Innovations in Monitoring, Modeling, and Decision Making