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Abstract Understanding how mixed-species forests uptake subsurface water sources is critical to projecting future forest water use and stress. Variation in root water uptake (RWU) depths and volumes is common among trees but it is unclear how it is affected by species identity, local water availability or neighboring tree species compositions. We evaluated the hypothesis that RWU depths and the age of water (i.e., time since water entered soils as precipitation) taken up by red maples (Acer rubrum) varied significantly between two forested plots, both containing red maples, similar soils, topography and hydrologic conditions, but having different neighboring tree species. We measured soil moisture contents as well as stable isotopes (δ2H, δ18O) in plant xylem water and soil moisture across two years. These data were used to calibrate process-based stand-level ecohydrological models for each plot to estimate species-level RWU depths. Model calibration suggested significant differences in red maple tree RWU depths, transpiration rates and the ages of water taken up by maples across the two stands. Maple trees growing with ash and white spruce relied on significantly deeper and older water from the soil profile than maple trees growing with birch and oak. The drought risk profile experienced by maple trees differed between the plots as demonstrated by strong correlations between precipitation and model simulated transpiration on a weekly time scale for maples taking up shallow soil moisture and a monthly time scale for maples reliant on deeper soil moisture. These findings carry significant implications for our understanding of water competition in mixed-species forests and for the representation of forest rooting strategies in hydrologic and earth systems models. 

ABSTRACT Sampling of stable isotopes in plant xylem water (δ²H, δ¹⁸O) has become a ubiquitous technique to study spatiotemporal variations in the water taken up by plant roots; however, open questions remain concerning the most appropriate time of day to sample trees to obtain representative xylem water isotopic values (δ_XYLEM). We sampled the δ_XYLEMof oak and maple trees prior to solar midday (i.e., in a recommended sampling window) and then again after solar midday (i.e., outside of the recommended window) across 4 months. The paired root mean squared difference between AM and PM δ¹⁸O ranged from 1.00‰ to 1.16‰ for maples and 0.23‰ to 2.55‰ for oaks across all sampling dates. Xylem water seasonal origin index (SOI) values derived from AM and PM δ_XYLEMsamples were significantly different, though both SOI estimates supported the conclusion that maple and oak δ_XYLEMreflected summer precipitation on all sampling dates. We conclude that sampling time of day is a significant consideration in the design of δ_XYLEMsampling campaigns; however, our findings also support flexibility in the collection time of δ_XYLEMin field sites where sampling during the optimal time of day is challenging. 

Abstract Riverbank groundwater discharge faces are spatially extensive areas of preferential seepage that are exposed to air at low river flow. Some conceptual hydrologic models indicate discharge faces represent the spatial convergence of highly variable age and length groundwater flowpaths, while others indicate greater consistency in source groundwater characteristics. Our detailed field investigation of preferential discharge points nested across mainstem riverbank discharge faces was accomplished by: (1) leveraging new temperature‐based recursive estimation (extended Kalman Filter) modelling methodology to evaluate seasonal, diurnal, and event‐driven groundwater flux patterns, (2) developing a multi‐parameter toolkit based on readily measured attributes to classify the general source groundwater flowpath depth and flowpath length scale, and, (3) assessing whether preferential flow points across discharge faces tend to represent common or convergent groundwater sources. Five major groundwater discharge faces were mapped along the Farmington River, CT, United States using thermal infrared imagery. We then installed vertical temperature profilers directly into 39 preferential discharge points for 4.5 months to track vertical discharge flux patterns. Monthly water chemistry was also collected at the discharge points along with one spatial synoptic of stable isotopes of water and dissolved radon gas. We found pervasive evidence of shallow groundwater sources at the upstream discharge faces along a wide valley section with deep bedrock, as primarily evidenced by pronounced diurnal discharge flux patterns. Discharge flux seasonal trends and bank storage transitions during large river flow events provided further indication of shallow, local sources. In contrast, downstream discharge faces associated with near surface cross cutting bedrock exhibited deep and regional source flowpath characteristics such as more stable discharge patterns and temperatures. However, many neighbouring points across discharge faces had similar discharge flux patterns that differed in chloride and radon concentrations, indicating the additional effects of localized flowpath heterogeneity overprinting on larger scale flowpath characteristics. 

Flooding risk results from complex interactions between hydrological hazards (e.g., riverine inundation during periods of heavy rainfall), exposure, vulnerability (e.g., the potential for structural damage or loss of life), and resilience (how well we recover, learn from, and adapt to past floods). Building on recent coupled conceptualizations of these complex interactions, we characterize human–flood interactions (collective memory and risk-enduring attitude) at a more comprehensive scale than has been attempted to date across 50 US metropolitan statistical areas with a sociohydrologic (SH) model calibrated with accessible local data (historical records of annual peak streamflow, flood insurance loss claims, active insurance policy records, and population density). A cluster analysis on calibrated SH model parameter sets for metropolitan areas identified two dominant behaviors: 1) “risk-enduring” cities with lower flooding defenses and longer memory of past flood loss events and 2) “risk-averse” cities with higher flooding defenses and reduced memory of past flooding. These divergent behaviors correlated with differences in local stream flashiness indices (i.e., the frequency and rapidity of daily changes in streamflow), maximum dam heights, and the proportion of White to non-White residents in US metropolitan areas. Risk-averse cities tended to exist within regions characterized by flashier streamflow conditions, larger dams, and larger proportions of White residents. Our research supports the development of SH models in urban metropolitan areas and the design of risk management strategies that consider both demographically heterogeneous populations, changing flood defenses, and temporal changes in community risk perceptions and tolerance.