192 research outputs found

    Global synthesis of vegetation control on evapotranspiration partitioning

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    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

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

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    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 (ή18O, ή2H) 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

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

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    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

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    Publisher’s version made available under a Creative Commons license.The isotopic composition of rainfall (ή2H and ή18O) 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 ή2H 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 ή2H 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

    Sensitivity of evapotranspiration components in remote sensing-based models

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    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
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