Runoff Generation
Even though significant progress has been made in understanding flow generation mechanisms, there are still questions about the spatial distribution and variability of these processes in the landscape. Recent investigations have tackled these challenges from both empirical and modelling approaches. The use of water stable isotopes and other tracers in investigations of streamflow generation continues to expand across varied landscapes and land-uses. Modelling continues to refine the treatment of uncertainties and parameterization. Despite the combined effort, it is still immensely challenging to predict behavior in regions lacking data or outside the range of observed or modeled conditions
Synoptic campaigns to unveil spatial and temporal variability in water movement and biogeochemical processing: Synoptic campaigns in streams can reveal network-scale variability in water sources and flow paths. We have used synoptic campaigns in the H.J. Andrews Experimental Forest and the Marys River Basin to understand baseflow water sources, and network-scale patterns of nitrogen and phosphorus. Currently, our work aims at understanding the controlling effect of geomorphic history on water movement in headwater streams and the seasonal control of relative contributions of tributaries draining contrasting terrain NSF Award #1943574 and in the context of wildfire effects.
25. Segura, C., Noone, D., Warren, D., Jones, J. A., *Tenny, J., & Ganio, L. (2019). Climate, landforms, and geology affect baseflow sources in a mountain catchment. Water Resources Research, 55, 5238– 5254. https://doi.org/10.1029/2018WR023551
Groundwater-surface water interactions: Water stable isotopes from headwater streams, combined with a LiDAR-based analysis of landslide deposit depth, were used to assess how geomorphic landforms influence subsurface water storage and routing. Results indicate that landslide deposits facilitate complex storage and drainage processes that exert some control on headwater runoff generation.
Publications
55. *Perry, Z., C. Segura, J. R. Brooks, S. Takaoka, and F. J. Swanson. 2026. The Influence of Geomorphology on Storage and Surface Water–Groundwater Interactions in Mountainous Headwater Streams. Hydrological Processes 40, no. 1: e70361. https://doi.org/10.1002/hyp.70361.
Hydrological Responses Soil Moisture and Streamflow Across Catchment
Runoff generation is controlled not just by how much water enters a watershed, but by how and where it is stored. This project used soil moisture, streamflow, and climatic data across three watersheds with contrasting geomorphic histories to investigate how subsurface storage structure shapes the relationship between soil moisture dynamics and streamflow response. By comparing systems dominated by deep groundwater storage, weathered bedrock, and shallow flowpaths, we found that landscape form exerts a strong control on hydrological function, with geomorphic process domains driving distinct patterns of soil moisture dynamics and runoff generation.
61.*Perry, Z., C. Segura, D. Penna. Divergent Hydrological Responses to Storms: Soil Moisture and Streamflow Across Catchments. In preparation for Hydrological Processes.
Insights Into Heterogeneous Streamflow Generation Processes and Water Contribution in Forested Headwaters
Storage drives seasonal variation in the contributions from headwater catchments to a mountainous 5th-order catchment. During wet conditions (A), all headwater catchments are recharged by fall and winter storms and contribute to streamflow, but during dry summer conditions (B) two small tributaries (Cold and Longer Creeks) provide the majority of the streamflow. Network extents in A and B were approximated based on field observations.
53.*Ortega, J., Segura,C., Brooks, J.R., and Sullivan, P.L. . 2025. “ Insights Into Heterogeneous Streamflow Generation Processes and Water Contribution in Forested Headwaters.” Hydrological Processes 39, no. 8: e70241. https://doi.org/10.1002/hyp.70241.
Subsurface Storage Drives Hydrologic Connectivity and Spatial Variability in Stream Chemistry
We examine how subsurface storage and hydrologic connectivity shape stream chemistry variability in headwater systems in the western Cascades, Oregon. Using weekly synoptic sampling, we analysed concentration-discharge relationships, principal component analysis, and subcatchment synchrony across five subcatchments. Results show seasonal variation, with tributaries (marked by triangles, emphasised by subcatchment colouring) exhibiting higher solute concentrations (darker blue) and variable synchrony with the outlet. Catchments with high subsurface storage had greater synchrony, highlighting interactions between landscape features, hydrologic connectivity, and stream chemistry.
54.*Ortega, J., Bush, S., Segura, C. & Sullivan, P.L. Subsurface Storage Drives Hydrologic Connectivity and Spatial Variability in Stream Chemistry. Hydrological Processes. no. 8: e70228. https://doi.org/10.1002/hyp.70228.
Transit time modelling: Understanding the physics driving a watershed's hydrologic response to precipitation is essential for predicting water supply and its connection to biogeochemical cycles. Predicting water age is complex, influenced by water input, movement, mixing, and storage factors. This is crucial for headwater streams, where water quality and quantity depend on smaller stream inputs, and patterns of water storage and release are vital, especially with projected snowpack declines. Tracers like water isotope ratios, used to estimate water travel time via transit time distributions, provide insights into flow paths, storage, and water sources. NSF Awards #1943574 and # 2424997.
45. *Lazo, P.X., Mosquera, G.M., Cárdenas, I., Segura., C, Crespo, P. A simple mixing model using electrical conductivity yields robust hydrograph separation in a tropical montane catchment. Journal of Hydrology, 639, 131632. doi: https://doi.org/10.1016/j.jhydrol.2024.131632
38. *Lazo, P.X., Mosquera, G.M., Cárdenas, I., Segura., C, Crespo, P. Flow partitioning modelling using high-resolution electrical conductivity data during variable flow conditions in a tropical montane catchment, Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2022.128898
22. Mosquera G., Segura C, Crespo P. 2018.Flow Partitioning Modelling Using High-Resolution Water Stable Isotopes and Electrical Conductivity. Water 2018, 10 (7), 904; https://doi.org/10.3390/w10070904.
5. Segura C, James A, Lazzati D, Roulet NT. 2012. Scaling relationships for event water contributions and transit times in small-forested catchments in Eastern Quebec. Water Resources Research 48, W07502, doi:10.1029/2012WR011890.