Editorial: Advances in Hydrologic Connectivity -Linking Processes Across Scales

Dipankar Dwivedi^1*Ronald Erwin Pöppl²Ellen Wohl³

• ¹Berkeley Lab (DOE), Berkeley, United States
• ²Boku University vienne, Vienna, Vienna, Austria
• ³Colorado State University, Fort Collins, Colorado, United States

The studies presented here examine the conceptual framework of hydrologic connectivity by integrating interdisciplinary perspectives, refining models, and incorporating emerging technologies to enhance predictability and management strategies. Dwivedi et al. (2023) synthesized current knowledge from hydrology, ecology, biogeochemistry, and geomorphology, offering a more comprehensive framework for connectivity research. Their study categorized connectivity according to spatial domains (surface, subsurface, and surface-subsurface) and connectivity dimensions (longitudinal, lateral, and vertical). They argued that, although analyzing connectivity by spatial domains, connectivity dimensions, or temporal scale is practical, its full impact on catchment dynamics is best understood holistically, yet many resource management strategies fail to incorporate this integrated perspective. They further emphasized that incorporating emerging technologies such as artificial intelligence, graph theory, and entropy-based metrics into improved measurement and modeling approaches can address critical gaps in understanding connectivity dynamics, particularly the inadequate spatial and temporal coverage.These researchers proposed an integrated, system-based approach to hydrologic connectivity, linking key processes across disciplines. They suggested that simple analogies, such as the electric circuit analogy, can help interdisciplinary integration, illustrating how water flow, resistance, and storage interact within a system. In this analogy, gravitational potential drives water movement like voltage in an electrical circuit (Figure 1). At the same time, obstacles such as vegetation and rocks act as resistors; meanwhile, wetlands function as capacitors for temporary water storage, and groundwater flow represents inductance, highlighting subsurface interactions. Such simplified representations provide intuitive ways to bridge disciplinary perspectives and enhance integrated water management approaches. Table 1 expands on this analogy by contextualizing them within the effects of disturbances (e.g., wildfire, drought) and management practices (e.g., thinning, prescribed fire). While this analogy is intended to inspire a unified framework for understanding hydrologic connectivity, further research is necessary to enable its practical implementation in watershed management. Ultimately, the researchers recommended better interdisciplinary collaboration and adaptive management approaches to incorporate hydrologic connectivity into ecosystem restoration and resource management. Cho et al. (2023) expanded this conceptual foundation by introducing a sediment connectivity model that links hydrologic pathways and geomorphic processes. Their framework emphasized the role of spatialtemporal feedback between hydrologic processes (e.g., runoff, infiltration, return flow, percolation, and groundwater flow) and geomorphic drivers (e.g., runoff depth, soil conditions) in sediment transport, storage, and connectivity at multiple scales. Although to date their work remains theoretical and requires empirical validation for practical application, it demonstrated the value of incorporating geomorphic drivers into hydrologic connectivity studies to predict sediment flux and inform watershed management strategies. Considered together, the studies discussed in this section strengthen the conceptual foundation of hydrologic connectivity by integrating interdisciplinary perspectives, refining models, utilizing real-time data, and standardizing approaches to enhance predictability and inform sustainable water management in catchment systems.Several studies have explored key aspects of hydrologic connectivity-namely, topographic influence, wood accumulation, and tectonic impacts-that shape water movement, sediment transport, and landscape evolution across different timescales. Tull et al. (2024) investigated how topographic bluffs influence river-floodplain connectivity and residence times. According to their findings, bluff topography directs flow from the floodplain to the river. In contrast, levee-channels (i.e., the portion of a river confined between levees and engineered embankments) flow to the floodplain, with bluffs altering inundation patterns, creating exchange zones, and affecting residence times, nutrient transport, and sediment dynamics. Tull et al. ultimately emphasized the importance of integrating topographic features into floodplain restoration and management efforts, bolstering ecosystem functions such as solute sequestration and nutrient cycling. Marshall and Wohl (2023) focused on the role of wood accumulation in driving channel bifurcations and altering flow paths within river systems. Their study challenged traditional bifurcation classifications by proposing a continuum model that links the ratio of erosive force to erosional resistance (F/R) with bifurcation type. The authors demonstrated that higher F/R values lead to lateral bifurcations and increased channel avulsion whereas lower values result in more stable banks and longitudinal bifurcations. These findings have significant implications for river restoration and sediment transport modeling. fluxes and sustainable stream management. Joshi et al. (2023) investigated the dual role of suspended sediments as nitrogen exporters and reactors for denitrification and assimilatory nitrogen uptake during storms while quantifying the proportions of assimilatory nitrogen uptake and denitrification losses relative to the suspended-sediment-bound nitrogen load and examining how these vary across drainage areas, storm sizes, and the rising and falling limbs of the storm hydrograph. Their study demonstrated how storm-driven sediment transport enhances nitrogen connectivity by increasing denitrification rates and nutrient uptake, significantly altering watershed nutrient cycling. By linking sediment transport to nitrogen removal processes, the findings inform watershed management strategies to mitigate nitrogen pollution and improve water quality, particularly in response to extreme hydrological events.Fogel and Lininger (2023) examined how geomorphic complexity influences CPOM transport and storage in headwater streams. Their study revealed that stream reaches with more retentive features, such as wood and cobbles, store greater amounts of CPOM while valley geometry influences transport at broader spatial scales. These findings underscore the need to consider geomorphic complexity in stream management and habitat restoration, as both direct alterations (e.g., dam construction, water diversions, wood removal, logging) and indirect changes (e.g., shifts in precipitation patterns and snowpack conditions) can substantially modify peak flow magnitude and frequency, valley bottom geometry, lateral connectivity, and in-stream wood and woody CPOM loads. Taken together, these studies emphasize how hydrologic and geomorphic processes regulate nutrient and organic matter fluxes in stream ecosystems, with storm-driven sediment transport enhancing nitrogen removal and geomorphic complexity shaping nutrient and CPOM retention.Understanding key aspects of climate-driven river evolution-investigating drainage system changes over geological timescales, evaluating discrepancies between predicted and observed network development, and identifying additional geomorphic and hydrologic feedbacks-can inform the refinement of predictive models for river network evolution. Hunt et al. (2023) developed a predictive model for river network evolution under climatic influences, assessing drainage system changes over geological timescales.Although some rivers align with theoretical expectations, such as groundwater-river interactions following a non-linear spatio-temporal scaling relationship, others deviate, like the Rio Grande and Pecos, suggesting additional geomorphic and hydrologic feedbacks. Importantly, the findings from this study revealed that connectivity patterns within river networks critically influence these dynamics, underscoring the need to refine climate-driven river evolution models by incorporating a broader range of hydrologic, geomorphic, and climatic variables while addressing theoretical assumptions and limited long-term data through expanded geographic coverage and improved modeling approaches.analysis (e.g., Matheus Carnevali et al., 2021;Dwivedi and Mohanty, 2016;Arora et al., 2019;Dwivedi et al., 2022;Dewey et al., 2022;Arora et al., 2022;Wohl et al., 2019;Wohl, 2019;Pöppl et al., 2024) to enhance the analysis of connectivity dynamics and improve model precision. Concentration-discharge (C-Q) relationships also offer valuable insights into hydrologic connectivity by linking critical zone structure, biogeochemical processes, and landscape heterogeneity (Herndon et al., 2015;Ackerer et al., 2020;Arora et al., 2020). These metrics can be leveraged to infer various dimensions of hydrologic connectivity-including vertical, lateral, and horizontal linkages-and warrant further exploration to uncover additional spatial and temporal patterns across watershed systems. Furthermore, addressing data limitations, implementing modeling approaches, and integrating machine learning techniques will be critical for strengthening hydrologic connectivity applications in environmental management (e.g., Varadharajan et al., 2019;Faybishenko et al., 2022). Ultimately, interdisciplinary collaboration and adaptive management strategies are vital for effectively integrating hydrologic connectivity into ecosystem restoration and resource management.