Patterns of local and nonlocal water resource use across the western U.S. determined via stable isotope intercomparisons

pre-printIn the western U.S., the mismatch between public water demands and natural water availability necessitates large interbasin transfers of water as well as groundwater mining of fossil aquifers. Here we identify probable situations of nonlocal water use in both space and time based on isotopic comparisons between tap waters and potential water resources within hydrologic basins. Our approach, which considers evaporative enrichment of heavy isotopes during storage and distribution, is used to determine the likeli-hood of local origin for 612 tap water samples collected from across the western U.S. We find that 64% of samples are isotopically distinct from precipitation falling within the local hydrologic basin, a proxy for groundwater with modern recharge, and 31% of samples are isotopically distinct from estimated surface water found within the local basin. Those samples inconsistent with local water sources, which we suggest are likely derived from water imported from other basins or extracted from fossil aquifers, are primarily clus- tered in southern California, the San Francisco Bay area, and central Arizona. Our isotope-based estimates of nonlocal water use are correlated with both hydrogeomorphic and socioeconomic properties of basins, suggesting that these factors exert a predictable influence on the likelihood that nonlocal waters are used to supply tap water. We use these basin properties to develop a regional model of nonlocal water resource use that predicts (r2=0.64) isotopically inferred patterns and allows assessment of total interbasin transfer and/or fossil aquifer extraction volumes across the western U.S

Global synthesis of vegetation control on evapotranspiration partitioning

Author's manuscript made available in accordance with the publisher's policy.Evapotranspiration (ET) is an important component of the global hydrological cycle. However, to what extent transpiration ratios (T/ET) are controlled by vegetation and the mechanisms of global-scale T/ET variations are not clear. We synthesized all the published papers that measured at least two of the three components (E, T, and ET) and leaf area index (LAI) simultaneously. Nonlinear relationships between T/ET and LAI were identified for both the overall data set and agricultural or natural data subsets. Large variations in T/ET occurred across all LAI ranges with wider variability at lower LAI. For a given LAI, higher T/ET was observed during later vegetation growing stage within a season. We developed a function relating T/ET to the growing stage relative to the timing of peak LAI. LAI and growing stage collectively explained 43% of the variations in the global T/ET data set, providing a new way to interpret and model global T/ET variability

A mesic maximum in biological water use demarcates biome sensitivity to aridity shifts

Biome function is largely governed by how efficiently available resources can be used and yet for water, the ratio of direct biological resource use (transpiration, E_T) to total supply (annual precipitation, P) at ecosystem scales remains poorly characterized. Here, we synthesize field, remote sensing and ecohydrological modelling estimates to show that the biological water use fraction (E_T/P) reaches a maximum under mesic conditions; that is, when evaporative demand (potential evapotranspiration, E_P) slightly exceeds supplied precipitation. We estimate that this mesic maximum in E_T/P occurs at an aridity index (defined as E_P/P) between 1.3 and 1.9. The observed global average aridity of 1.8 falls within this range, suggesting that the biosphere is, on average, configured to transpire the largest possible fraction of global precipitation for the current climate. A unimodal E_T/P distribution indicates that both dry regions subjected to increasing aridity and humid regions subjected to decreasing aridity will suffer declines in the fraction of precipitation that plants transpire for growth and metabolism. Given the uncertainties in the prediction of future biogeography, this framework provides a clear and concise determination of ecosystems' sensitivity to climatic shifts, as well as expected patterns in the amount of precipitation that ecosystems can effectively use

Stable Isotopes of Water Vapor in the Vadose Zone: A Review of Measurement and Modeling Techniques

Author's manuscript made available in accordance with the publisher's policy.The stable isotopes of soil water vapor can be useful in the study of ecosystem processes. Modeling has historically dominated the measurement of these parameters due to sampling difficulties. We discuss new developments in modeling and measurement, including the implications of including soil water potential in the Craig–Gordon modeling framework. The stable isotopes of soil water vapor are useful tracers of hydrologic processes occurring in the vadose zone. The measurement of soil water vapor isotopic composition (δ18O, δ2H) is challenging due to difficulties inherent in sampling the vadose zone airspace in situ. Historically, these parameters have therefore been modeled, as opposed to directly measured, and typically soil water vapor is treated as being in isotopic equilibrium with liquid soil water. We reviewed the measurement and modeling of soil water vapor isotopes, with implications for studies of the soil–plant–atmosphere continuum. We also investigated a case study with in situ measurements from a soil profile in a semiarid African savanna, which supports the assumption of liquid–vapor isotopic equilibrium. A contribution of this work is to introduce the effect of soil water potential (Ѱ) on kinetic fractionation during soil evaporation within the Craig–Gordon modeling framework. Including Ѱ in these calculations becomes important for relatively dry soils (Ѱ < −10 MPa). Additionally, we assert that the recent development of laser-based isotope analytical systems may allow regular in situ measurement of the vadose zone isotopic composition of water in the vapor phase. Wet soils pose particular sampling difficulties, and novel techniques are being developed to address these issues

Uncertainties in the assessment of the isotopic composition of surface fluxes: A direct comparison of techniques using laser-based water vapor isotope analyzers

Author's manuscript made available in accordance with the publisher's policy.The isotopic composition of surface fluxes is a key environmental tracer currently estimated with a variety of methods, including: Keeling mixing models, the flux-gradient technique, and eddy covariance. We present a direct inter-comparison of these three methods used to estimate the isotopic ratio of water vapor in surface fluxes (δET) over half-hour periods, with a focus on the statistical uncertainty of each method image We develop expressions for image a function of instrument precision, sample size, and atmospheric conditions. Uncertainty estimators are validated with high frequency (1 Hz) data from multiple configurations of commercial off-axis integrated cavity output spectroscopy (ICOS) systems. We find measurement techniques utilizing the high frequency capabilities of ICOS system outperform those methods where a single average of the isotopic composition is obtained at each height, with improvements attributed to large sample counts and increased variation in observed concentrations. Analytically, and with supporting data, we show that over 30 minute periods the Keeling plot and flux-gradient techniques produce nearly identicalδET and image values, while eddy covariance calculations always introduce more uncertainty given the same high frequency data. This additional uncertainty is proportional to the reciprocal of the correlation coefficient between vertical wind speed and water vapor mixing ratio. Finally, given the inverse relationship between δET uncertainties and the range of water vapor observed, we propose that experimental designs should attempt to maximize both sample count and the coefficient of variation in atmospheric water vapor

The streamwater microbiome encodes hydrologic data across scales

Many fundamental questions in hydrology remain unanswered due to the limited information that can be extracted from existing data sources. Microbial communities constitute a novel type of environmental data, as they are comprised of many thousands of taxonomically and functionally diverse groups known to respond to both biotic and abiotic environmental factors. As such, these microscale communities reflect a range of macroscale conditions and characteristics, some of which also drive hydrologic regimes. Here, we assess the extent to which streamwater microbial communities (as characterized by 16S gene amplicon sequence abundance) encode information about catchment hydrology across scales. We analyzed 64 summer streamwater DNA samples collected from subcatchments within the Willamette, Deschutes, and John Day river basins in Oregon, USA, which range 0.03–29,000 km2 in area and 343–2334 mm/year of precipitation. We applied information theory to quantify the breadth and depth of information about common hydrologic metrics encoded within microbial taxa. Of the 256 microbial taxa that spanned all three watersheds, we found 9.6 % (24.5/256) of taxa, on average, shared information with a given hydrologic metric, with a median 15.6 % (range = 12.4–49.2 %) reduction in uncertainty of that metric based on knowledge of the microbial biogeography. All of the hydrologic metrics we assessed, including daily discharge at different time lags, mean monthly discharge, and seasonal high and low flow durations were encoded within the microbial community. Summer microbial taxa shared the most information with winter mean flows. Our study demonstrates quantifiable relationships between streamwater microbial taxa and hydrologic metrics at different scales, likely resulting from the integration of multiple overlapping drivers of each. Streamwater microbial communities are rich sources of information that may contribute fresh insight to unresolved hydrologic questions

Contribution of water-limited ecoregions to their own supply of rainfall

The occurrence of wet and dry growing seasons in water-limited regions remains poorly understood, partly due to the complex role that these regions play in the genesis of their own rainfall. This limits the predictability of global carbon and water budgets, and hinders the regional management of naturalresources. Using novel satellite observations and atmospheric trajectory modelling, we unravel the origin and immediate drivers of growing-season precipitation, and the extent to which ecoregions themselves contribute to their own supply of rainfall. Results show that persistent anomalies in growing-season precipitation—and subsequent biomass anomalies—are caused by a complex interplay of land and ocean evaporation, air circulation and local atmospheric stability changes. For regions such as the Kalahari and Australia, the volumes of moisture recycling decline in dry years, providing a positive feedback that intensifies dry conditions. However, recycling ratios increase up to40%, pointing to the crucial role of these regions in generating their own supply of rainfall; transpiration in periods of water stress allows vegetation to partly offset the decrease in regional precipitation. Findings highlight the need to adequately represent vegetation–atmosphere feedbacks in models to predict biomass changes and to simulate the fate of water-limited regions in our warming climate

Using atmospheric trajectories to model the isotopic composition of rainfall in central Kenya

Publisher’s version made available under a Creative Commons license.The isotopic composition of rainfall (δ2H and δ18O) is an important tracer in studies of the ecohydrology, plant physiology, climate and biogeochemistry of past and present ecosystems. The overall continental and global patterns in precipitation isotopic composition are fairly well described by condensation temperature and Rayleigh fractionation during rainout. However, these processes do not fully explain the isotopic variability in the tropics, where intra-storm and meso-scale dynamics may dominate. Here we explore the use of atmospheric back-trajectory modeling and associated meteorological variables to explain the large variability observed in the isotopic composition of individual rain events at the study site in central Kenya. Individual rain event samples collected at the study site (n = 41) range from −51‰ to 31‰ for δ2H and the corresponding monthly values (rain volume-weighted) range from −15‰ to 15‰. Using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, we map back-trajectories for all individual rain hours occurring at a research station in central Kenya from March 2010 through February 2012 (n = 544). A multiple linear regression analysis demonstrates that a large amount of variation in the isotopic composition of rainfall can be explained by two variables readily obtained from the HYSPLIT model: (1) solar radiation along the trajectory for 48 hours prior to the event, and (2) distance covered over land. We compare the measurements and regression model results to the isotopic composition expected from simple Rayleigh distillation along each trajectory. The empirical relationship described here has applications across temporal scales. For example, it could be used to help predict short-term changes in the isotopic composition of plant-available water in the absence of event-scale sampling. One can also reconstruct monthly, seasonal and annual weighted mean precipitation isotope signatures for a single location based only on hourly rainfall data and HYSPLIT model results. At the study site in East Africa, the annual weighted mean δ2H from measured and modeled values are −7.6‰ and −7.4‰, respectively, compared to −18‰ predicted for the study site by the Online Isotopes in Precipitation Calculator

Hydrologic connectivity constrains partitioning of global terrestrial water fluxes

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 s.d.) of evapotranspiration, and 65±26% of evaporation originates from soils and not surface waters. We estimate 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 though catchments.This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in the journal Science on 10 July 2015, Volume 349 number 6244, DOI:10.1126/science.aaa5931. The published article is copyrighted by the American Association for the Advancement of Science and can be found at: http://www.sciencemag.org/journals

Sensitivity of evapotranspiration components in remote sensing-based models

Accurately estimating evapotranspiration (ET) at large spatial scales is essential to our understanding of land-atmosphere coupling and the surface balance of water and energy. Comparisons between remote sensing-based ET models are difficult due to diversity in model formulation, parametrization and data requirements. The constituent components of ET have been shown to deviate substantially among models as well as between models and field estimates. This study analyses the sensitivity of three global ET remote sensing models in an attempt to isolate the error associated with forcing uncertainty and reveal the underlying variables driving the model components. We examine the transpiration, soil evaporation, interception and total ET estimates of the Penman-Monteith model from the Moderate Resolution Imaging Spectroradiometer (PM-MOD), the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL) and the Global Land Evaporation Amsterdam Model (GLEAM) at 42 sites where ET components have been measured using field techniques. We analyse the sensitivity of the models based on the uncertainty of the input variables and as a function of the raw value of the variables themselves. We find that, at 10% added uncertainty levels, the total ET estimates from PT-JPL, PM-MOD and GLEAM are most sensitive to Normalized Difference Vegetation Index (NDVI) (%RMSD = 100.0), relative humidity (%RMSD = 122.3) and net radiation (%RMSD = 7.49), respectively. Consistently, systemic bias introduced by forcing uncertainty in the component estimates is mitigated when components are aggregated to a total ET estimate. These results suggest that slight changes to forcing may result in outsized variation in ET partitioning and relatively smaller changes to the total ET estimates. Our results help to explain why model estimates of total ET perform relatively well despite large inter-model divergence in the individual ET component estimates