Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management DOI Creative Commons
Dipankar Dwivedi, Ronald E. Poeppl, Ellen Wohl

et al.

Frontiers in Water, Journal Year: 2025, Volume and Issue: 7

Published: March 31, 2025

This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices address environmental challenges (e.g., climate change) sustainability. As a key driver of water movement nutrient cycling, connectivity influences flood mitigation, quality regulation, biodiversity conservation. However, traditional field-based dye tracing), indirect measurements runoff analysis), remote sensing techniques InSAR) often struggle capture the complexity catchment-scale interactions. Similarly, modeling approaches—including process-based percolation theory-based models, graph theory, entropy-based metrics—face limitations in fully representing these interconnected processes. Both measurement are constrained by inadequate spatial temporal coverage, high data demands, computational complexity, difficulties subsurface connectivity. Subsequently, we critique current management that prioritize isolated variables streamflow, sediment transport) over system-wide strategies emphasize need adaptive, connectivity-based approaches resource planning restoration. Moving forward, highlight importance interdisciplinary collaboration, technological innovations AI-driven real-time monitoring), integrated frameworks measurement, adaptive restore fragmented networks. approach sets stage transformative management, fostering proactive policy development stakeholder engagement.

Language: Английский

Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management DOI Creative Commons
Dipankar Dwivedi, Ronald E. Poeppl, Ellen Wohl

et al.

Frontiers in Water, Journal Year: 2025, Volume and Issue: 7

Published: March 31, 2025

This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices address environmental challenges (e.g., climate change) sustainability. As a key driver of water movement nutrient cycling, connectivity influences flood mitigation, quality regulation, biodiversity conservation. However, traditional field-based dye tracing), indirect measurements runoff analysis), remote sensing techniques InSAR) often struggle capture the complexity catchment-scale interactions. Similarly, modeling approaches—including process-based percolation theory-based models, graph theory, entropy-based metrics—face limitations in fully representing these interconnected processes. Both measurement are constrained by inadequate spatial temporal coverage, high data demands, computational complexity, difficulties subsurface connectivity. Subsequently, we critique current management that prioritize isolated variables streamflow, sediment transport) over system-wide strategies emphasize need adaptive, connectivity-based approaches resource planning restoration. Moving forward, highlight importance interdisciplinary collaboration, technological innovations AI-driven real-time monitoring), integrated frameworks measurement, adaptive restore fragmented networks. approach sets stage transformative management, fostering proactive policy development stakeholder engagement.

Language: Английский

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