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Continental precipitation not routed to the oceans as runoff returns to the atmosphere as evapotranspiration. Partitioning this evapotranspiration flux into interception, transpiration, soil evaporation, and surface water evaporation is difficult using traditional hydrological methods, yet critical for understanding the water cycle and linked ecological processes. We combined two large-scale flux-partitioning approaches to quantify evapotranspiration subcomponents and the hydrologic connectivity of bound, plant-available soil waters with more mobile surface waters. Globally, transpiration is 64 ± 13% (mean ± 1 standard deviation) of evapotranspiration, and 65 ± 26% of evaporation originates from soils and not surface waters. We estimate that 38 ± 28% of surface water is derived from the plant-accessed soil water pool. This limited connectivity between soil and surface waters fundamentally structures the physical and biogeochemical interactions of water transiting through catchments.

Solar energy has the potential to offset a significant fraction of non-renewable electricity demands globally, yet it may occupy extensive areas when deployed at this level. There is growing concern that large renewable energy installations will displace other land uses. Where should future solar power installations be placed to achieve the highest energy production and best use the limited land resource? The premise of this work is that the solar panel efficiency is a function of the location’s microclimate within which it is immersed. Current studies largely ignore many of the environmental factors that influence Photovoltaic (PV) panel function. A model for solar panel efficiency that incorporates the influence of the panel’s microclimate was derived from first principles and validated with field observations. Results confirm that the PV panel efficiency is influenced by the insolation, air temperature, wind speed and relative humidity. The model was applied globally using bias-corrected reanalysis datasets to map solar panel efficiency and the potential for solar power production given local conditions. Solar power production potential was classified based on local land cover classification, with croplands having the greatest median solar potential of approximately 28 W/m 2 . The potential for dual-use, agrivoltaic systems may alleviate land competition or other spatial constraints for solar power development, creating a significant opportunity for future energy sustainability. Global energy demand would be offset by solar production if even less than 1% of cropland were converted to an agrivoltaic system.

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. Plain Language Summary Quantifying the capacity of floodplains to dissipate energy from flowing water is important in managing rivers, restoring habitats, and reducing flood risks. By integrating overbank flood characteristics measured at USGS gauging stations with vegetation properties of floodplains measured by NASA, this study analyzed how energy dissipation in the floodplain, via a hydraulic roughness coefficient, varies with vegetation biomass and flood depths. Results indicate that floodplain roughness increases with the density of vegetation and decreases with flow velocity. A new mathematical function is presented to estimate floodplain roughness based on remotely sensed vegetation properties for various velocities. Key Points 4,927 estimates of floodplain roughness were calculated using flow observations and compared to LiDAR vegetation data Floodplain roughness increases with increasing biomass and inundation depths and decreases with increasing flow velocity Our model's Manning's n estimates yield lower errors in reach‐scale floodplain flow predictions than n based solely on land cover

Extra-tropical cyclones, such as 2012 Superstorm Sandy, pose a significant climatic threat to the northeastern United Sates, yet prediction of hydrologic and thermodynamic processes within such systems is complicated by their interaction with mid-latitude water patterns as they move poleward. Fortunately, the evolution of these systems is also recorded in the stable isotope ratios of storm-associated precipitation and water vapor, and isotopic analysis provides constraints on difficult-to-observe cyclone dynamics. During Superstorm Sandy, a unique crowdsourced approach enabled 685 precipitation samples to be obtained for oxygen and hydrogen isotopic analysis, constituting the largest isotopic sampling of a synoptic-scale system to date. Isotopically, these waters span an enormous range of values (> 21‰ for δ(18)O, > 160‰ for δ(2)H) and exhibit strong spatiotemporal structure. Low isotope ratios occurred predominantly in the west and south quadrants of the storm, indicating robust isotopic distillation that tracked the intensity of the storm's warm core. Elevated values of deuterium-excess (> 25‰) were found primarily in the New England region after Sandy made landfall. Isotope mass balance calculations and Lagrangian back-trajectory analysis suggest that these samples reflect the moistening of dry continental air entrained from a mid-latitude trough. These results demonstrate the power of rapid-response isotope monitoring to elucidate the structure and dynamics of water cycling within synoptic-scale systems and improve our understanding of storm evolution, hydroclimatological impacts, and paleo-storm proxies.

Quantifying relative contributions of plant transpiration (T) and soil evaporation to evapotranspiration (ET) is crucial to better understand how vegetation influences and controls ET, the largest efflux of the terrestrial water balance. Here, we derive estimates of transpiration fraction (T/ET) using consistent isotope‐based ET partitioning methods for 13 sites spanning five ecosystem types of the continental US, capturing 56 snapshots of T/ET during the growing season. We found transpiration dominated the ET flux across all sites with a mean T/ET of 0.81 ± 0.08 (±standard error). Sites and dates with higher vegetation indices exhibited higher T/ET and transpiration rates, with the latter increasing 0.30 mm/day per unit Leaf Area Index and 2.9 mm/day per unit Normalized Difference Vegetation Index. Counter to expectations, antecedent precipitation had no effect on T/ET. Despite the breadth of ecosystems and conditions represented, evaporation exceeded transpiration only once, suggesting that evaporation rarely dominates ET in the growing season. Plain Language Summary In this study, we quantify how plant water use (transpiration) contributes to the transfer of water from land to the atmosphere (evapotranspiration) across diverse U.S. ecosystems. Using distinct chemical signatures of water vapor from soil evaporation and plant transpiration, we measured their relative contributions to the atmosphere. From a snapshot of 56 dates at 13 sites, we found that transpiration is the dominant contributor to evapotranspiration during the growing season, accounting for, on average 81%. We quantified this in different ecosystems, including forests, grasslands, and shrublands, and found the highest levels of transpiration contributions at the alpine site, and lowest at the shrubland site. Cross‐site analyses like this are typically pursued through simulation modeling rather than observation‐based field‐collected data. Observation‐based research remains crucial for understanding how environmental systems function. We found that rain occurrences before storms had no apparent effect on the fraction of transpiration versus evaporation, which conflicts with the common expectation that evaporation is high after storms. Our results showed that ecosystems with more plant cover, such as forests, tend to have higher levels of transpiration (relative to total water lost through evapotranspiration); this relationship was surprisingly strong given that it spanned many sites and conditions. Key Points Transpiration accounted for most of evapotranspiration during the growing season, averaging 81% across the sampled sites and dates Ratios of transpiration to evapotranspiration increased with vegetation indices and were independent of antecedent precipitation On average, transpiration increased by 2.9 mm per day per unit increase in Normalized Difference Vegetation Index

Determining the factors that influence the distribution of woody vegetation cover and resolving the sensitivity of woody vegetation cover to shifts in environmental forcing are critical steps necessary to predict continental-scale responses of dryland ecosystems to climate change. We use a 6-year satellite data record of fractional woody vegetation cover and an 11-year daily precipitation record to investigate the climatological controls on woody vegetation cover across the African continent. We find that--as opposed to a relationship with only mean annual rainfall--the upper limit of fractional woody vegetation cover is strongly influenced by both the quantity and intensity of rainfall events. Using a set of statistics derived from the seasonal distribution of rainfall, we show that areas with similar seasonal rainfall totals have higher fractional woody cover if the local rainfall climatology consists of frequent, less intense precipitation events. Based on these observations, we develop a generalized response surface between rainfall climatology and maximum woody vegetation cover across the African continent. The normalized local gradient of this response surface is used as an estimator of ecosystem vegetation sensitivity to climatological variation. A comparison between predicted climate sensitivity patterns and observed shifts in both rainfall and vegetation during 2009 reveals both the importance of rainfall climatology in governing how ecosystems respond to interannual fluctuations in climate and the utility of our framework as a means to forecast continental-scale patterns of vegetation shifts in response to future climate change.

Water transit times strongly influence water quality, temperature, and seasonal hydrologic response of river systems. How water transit times may shift under future climates remains unconstrained, especially in mountainous regions experiencing rapid snowpack declines. Here, we estimated historical (2006–2013) and future (2086–2093) water transit times in five headwater catchments within the U.S. Pacific Northwest using sequential precipitation input tagging within the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model. Our results indicate water transit times are 18% (35–64 days) faster on average under the Representative Carbon Pathways (RCP) 8.5 climate scenario due to shifts in rain-snow partitioning, with higher fractions of younger water in the wet season and older water in the dry season. These results suggest shifts in rain-snow partitioning in snowmelt dominated catchments of the Pacific Northwest will shorten water transit times leading to likely impacts on regional water quality, temperature, and hydrologic seasonality.

Field measurements of hydrologic tracers indicate varying magnitudes of geochemical separation between subsurface pore waters. The potential for conventional soil physics alone to explain isotopic differences between preferential flow and tightly-bound water remains unclear. Here, we explore physical drivers of isotopic separations using 650 different model configurations of soil, climate, and mobile/immobile soil-water domain characteristics, without confounding fractionation or plant uptake effects. We find simulations with coarser soils and less precipitation led to reduced separation between pore spaces and drainage. Amplified separations are found with larger immobile domains and, to a lesser extent, higher mobile-immobile transfer rates. Nonetheless, isotopic separations remained small (<4‰ for δ 2 H) across simulations, indicating that contrasting transport dynamics generate limited geochemical differences. Therefore, conventional soil physics alone are unlikely to explain large ecohydrological separations observed elsewhere, and further efforts aimed at reducing methodological artifacts, refining understanding of fractionation processes, and investigating new physiochemical mechanisms are needed. Soil physics simulations show water isotope ratios can differ among drainage, mobile and immobile storages due to transport processes alone, but effects were smaller than field data implying unrepresented processes underly ecohydrologic separation.

Land surface models (LSMs) play a crucial role in elucidating water and carbon cycles by simulating processes such as plant transpiration and evaporation from bare soil, yet calibration often relies on comparing LSM outputs of landscape total evapotranspiration (ET) and discharge with measured bulk fluxes. Discrepancies in partitioning into component fluxes predicted by various LSMs have been noted, prompting the need for improved evaluation methods. Stable water isotopes serve as effective tracers of component hydrologic fluxes, but data and model integration challenges have hindered their widespread application. Leveraging National Ecological Observation Network measurements of water isotope ratios at 16 US sites over 3 years combined with LSM‐modeled fluxes, we employed an isotope‐enabled mass balance framework to simulate ET isotope values (δET) within three operational LSMs (Mosaic, Noah, and VIC) to evaluate their partitioning. Models simulating δET values consistent with observations were deemed more reflective of water cycling in these ecosystems. Mosaic exhibited the best overall performance (Kling‐Gupta Efficiency of 0.28). For both Mosaic and Noah there were robust correlations between bare soil evaporation fraction and error (negative) as well as transpiration fraction and error (positive). We found the point at which errors are smallest (x‐intercept of the multi‐site regression) is at a higher transpiration fraction than is currently specified in the models. Which means that transpiration fraction is underestimated on average. Stable isotope tracers offer an additional tool for model evaluation and identifying areas for improvement, potentially enhancing LSM simulations and our understanding of land‐surface hydrologic processes. Plain Language Summary Models help us understand where and how much water moves in our environment. For example, how much water moves through plants (transpiration) and how much evaporates from the soil. We usually check how correct these models are by comparing the combined evaporation and transpiration (ET) and water discharge, with field measurements. This approach can lead to errors, as models often disagree on how to split ET into plant transpiration and soil evaporation. Water isotopes (water molecules with different atomic weights) can help identify the right split in ET, but the lack of data and the difficulty in using this data in models has hindered their implementation. We used newly available water isotope data from the National Ecological Observation Network from 16 sites across the U.S. We followed this water through the models and compared their predicted isotope values of ET with observations. Models with good predictions will most likely have a correct split of ET. Analysis showed that for Noah and Mosaic models, the split of transpiration is too small on average. By following stable isotopes as a new tool for model evaluation, researchers can better identify areas for improvement, leading to more accurate simulations of water movement. Key Points An isotope mass balance was applied to operational land surface models to evaluate their hydrologic partitioning of evapotranspiration Isotopic composition of water vapor in evapotranspiration from 16 National Ecological Observatory Network sites were compared to simulations Evaporation and transpiration fraction were strongly correlated with simulation error; elucidating their over‐ and underestimation

Terrestrial evapotranspiration is the second‐largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross‐disciplinary group of ET scientists to overcome the challenges identified in this paper and ultimately advance our integrated understanding of ET. Key Points The main challenge in ET science is reconciling spatial data with point data from various sources across heterogeneous areas Each of the three general approaches to ET science (in situ measurements, partitioning, remote sensing) has strengths and weaknesses Communication and translation across these disciplines are key to closing the gaps