Quantifying floodplain flows is critical to multiple river management objectives, yet how vegetation within floodplains dissipates flow energy lacks comprehensive characterization. Utilizing over 3.4 million discharge measurements, in conjunction with aboveground biomass and canopy height measurements from NASA’s Global Ecosystem Dynamics Investigation (GEDI), this study characterizes the floodplain roughness coefficient Manning’s n and its determinates across the continental United States. Estimated values of n show that flow resistance in floodplains decreases as flow velocity increases but increases with the fraction of vegetation inundated. A new function (RMSE = 0.024, r2 = 0.74) is proposed for predicting n based on GEDI vegetation characteristics and flow velocity, with GEDI derived n values improving predictions of discharge relative to those based only on land cover. This analysis provides evidence of key hydraulic patterns of energy dissipation in floodplains, and integration of the proposed function into flood and habitat models may reduce uncertainty.

While yearly budgets of CO2 and evapotranspiration (ET) above forests can be readily obtained from eddy-covariance measurements, the quantification of their respective soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. To this end, methods capable of reliably partitioning the measured ET and F_c fluxes into their respective soil and plant sources and sinks are highly valuable. In this work, we investigate four partitioning methods (two new, and two existing) that are based on analysis of conventional high frequency eddy-covariance (EC) data. The physical validity of the assumptions of all four methods, as well as their performance under different scenarios, are tested with the aid of large eddy simulations, which are used to replicate eddy-covariance field experiments. Our results indicate that canopies with large, exposed soil patches increase the mixing and correlation of scalars; this negatively impacts the performance of the partitioning methods, all of which require some degree of uncorrelatedness between CO2 and water vapor. In addition, best performance for all partitioning methods were found when all four flux components are non-negligible, and measurements are collected close to the canopy top. Methods relying on the water-use efficiency (W) perform better when W is known a priori, but are shown to be very sensitive to uncertainties in this input variable especially when canopy fluxes dominate. We conclude by showing how the correlation coefficient between CO2 and water vapor can be used to infer the reliability of different W parameterizations.

The hydrologic community uses geochemical tracers to determine the age distribution of water exiting a catchment, with transit time distributions (TTDs) important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages. Here, we present a ‘sequential precipitation input tagging’ (SPIT) framework to tag all input precipitation events at regular intervals over an extended period (monthly tags over seven years). SPIT is applied at six National Ecological Observatory Network sites to calculate TTDs and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations (δQ-δ18O and δ2H) within a water-tagging enabled version of the Weather Research and Forecast hydrologic model. Throughout seven simulation years, the fraction of simulated discharge derived from tagged events increased each year, with the final year’s tagged stream water fraction (TSWF) ranging 21% to 100%. When the TSWF was ≥75%, simulated MTTs range 190 days to 850 days and Fyw 1% to 24%, with a root mean squared error (RMSE) of 456 days and 14.5%. The RMSE for δ18O is 1.08‰ and δ2H 6.58‰. Low TSWF values early in the simulation period highlights the need to apply SPIT over many years to fully understand the TTD. At daily timescales, model MTT and Fyw exhibit a power-law relationship with precipitation, discharge, and groundwater. The successful implementation of SPIT within a tracer-enabled version of an operational hydrologic model allows for a reproducible approach to calculate water transit times and hydrologic tracers.

The timescales associated with precipitation moving through watersheds reveal processes that are critical to understanding many hydrologic systems. Measurements of environmental stable water isotope ratios (δ 2H and δ 18O) have been used as tracers to study hydrologic timescales by examining how long it takes for incoming precipitation tracers become stream discharge, yet limited measurements both spatially and temporally have bounded macroscale evaluations so far. In this observation driven study across North American biomes within the National Ecological Observation Network (NEON), we examined δ 18O and δ 2H stable water isotope in precipitation (δP) and surface water (δQ) at 26 co-located sites. With an average 54 precipitation samples and 139 surface water samples per site, assessment of local meteoric water lines (LMWL) and local surface water line (LSWL) showed geographic variation across North America. Taking the ratio of estimated seasonal amplitudes of δP and δQ to calculate young water fractions ( Fyw), showed a Fyw range from 1% to 93% with most sites having Fyw below 20%. Calculated mean transit times (MTT) based on a gamma convolution model showed a range from 0.10 to 13.2 years, with half of the sites having MTT estimates lower than 2 years. Significant correlations (r) were found only between the Fyw and watershed area, longest flow length, and the longest flow length/slope, whereas the only significant correlation observed for MTT was with site latitude. The estimated Fyw and MTT provide information describing hydrologic processes at NEON sites, however limited correlations of Fyw and MTT with the environmental characteristics we analyzed demonstrate that these quantities are primarily driven by site or area specific factors. The analysis of isotope data presented here provides important constraints on isotope variation in North American biomes and the timescales of water movement through NEON study sites.

Water and carbon exchanges between the land and atmosphere reflect key ecohydrologic processes, from global climate change to local watershed dynamics. Environmental stable isotope ratios of H2O and CO2 fluxes have been used to study these processes, yet measurement constraints have limited macroscale surface-atmosphere isotope flux evaluations. Across North American biomes within the US National Ecological Observation Network (NEON), we have worked as a team to translate raw measurements of carbon and water stable isotopes into calibrated daily surface-atmosphere flux isotope ratios for precipitation, evapotranspiration, and net ecosystem carbon exchange. Using information theory metrics, we demonstrate that these isotope observations contain meaningful information about the bulk water and carbon fluxes, with isotope measurements carrying about the same amount of information as wind speed measurements. Decomposition of this multivariate mutual information further shows that: (1) this information is unique, i.e. not carried by other traditional ecosystem measurements; and (2) the information added by isotopes is larger in more arid and cool ecosystems. Combining these isotope fluxes with bulk hydrologic fluxes drawn from a suite of land surface models in a first-order mass balance framework also allows for evaluation of hydrologic model structure and estimated uncertainties in partitioning of fluxes into transpiration, evaporation, overland, and subsurface water fluxes. An inter-model comparison suggests distinct patterns in isotope flux composition associated with disparities in the relative contributions of partitioned fluxes. Our results show that conservative isotope tracers provide novel validation metrics for evaluation of land surface model performance across ecosystems at a continental scale. Broadly, this compilation of datasets - combined with both empirical and process-based isotope modeling - suggests NEON stable isotope observations can improve general understanding of land-surface processes influencing the water and carbon cycles from regional to global scales.

Sap flux probes have been used to study sap velocity since the early 20th century and have progressively improved in accuracy and usability. Advances are also being made in making these devices cheaper via open-sourced projects; however, these solutions require extensive time and skill to construct a reliable device. When our lab tried to replicate Miner’s results, only two of the first ten probes built passed rudimentary testing. We therefore redesigned the system in a PCB-based design that simplifies construction, and presents opportunity for automated mass manufacturability at a scale not possible with existing designs. New designs for both the Thermal Dissipation Method (TDM) and the Heat Ratio Method (HRM) techniques were tested. We present our open-source designs for wireless sap flux probes that communicate over 2km using the LoRa protocol through canopy to an internet hub, where data is logged in near-real-time and accessible online.

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature. Lastly, modeled stable carbon isotope fractionation differed under canopy water stress which illustrates the value of carbon isotopes in helping to characterize ecosystem function and elucidate differences attributable to model structure. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.