Search

The maximum information entropy production model (MaxEnt), the relative humidity at equilibrium approach (ETRHEQ), and the Surface Flux Equilibrium model (SFE) are three recently developed models to estimate evapotranspiration. Although the connection between ETRHEQ and SFE is evident, no attempts have been made to investigate the congruence, distinctions, or potential complementarity between the two models and MaxEnt. Our mathematical analysis demonstrates that minimizing the vertical variance of RH in ETRHEQ is equivalent to minimizing the dissipation function of energy fluxes in MaxEnt, under the assumption of the same eddy diffusivity of heat and water vapor and with a specific expression for the ratio between the thermal inertia terms for H and LE. The connection between ETRHEQ, SFE, and MaxEnt is independent of Monin‐Obukhov similarity theory (MOST)'s extremum solution, and MOST's extreme solution can be viewed as equivalent to introducing a constant correction factor to account for atmospheric stability. While ETRHEQ and MaxEnt can be united within a single hydrometeorological framework, they diverge in their approaches to modeling evapotranspiration, particularly in how they address the roles of vegetation and land surface heterogeneity. More importantly, the unified framework suggests that turbulence fluxes within the atmospheric boundary layer adhere to the principles of maximum information entropy production. The way in which dissipation, along with its associated entropy production, is established using information entropy theory deviates from traditional thermodynamic entropy formulations. Exploring the connection between thermodynamic and information entropy and developing proper formulations of dissipation for energy fluxes presents an appealing avenue for prospective research. Plain Language Summary: This paper seeks to establish a common theory for explaining the effectiveness of the maximum information entropy production model (MaxEnt), the relative humidity at equilibrium approach (ETRHEQ), and the Surface Flux Equilibrium model (SFE) in estimating evapotranspiration over a wide range of conditions. It uncovers that under reasonable assumptions, ETRHEQ's method in terms of minimizing the vertical variance in relative humidity is equivalent to MaxEnt's approach to minimizing dissipation. The united theory suggests that the movement of air and energy in the lower atmosphere follows the principles of maximum information entropy production, a concept that is a bit different from traditional ideas of entropy in thermodynamics. Looking into how thermodynamic entropy and information entropy are connected and figuring out the right way to calculate dissipation and entropy production for energy flux could lead to new insights in atmospheric science and land‐atmosphere interactions. Key Points: The study presented a pure theorical analysis to unifying MaxEnt, ETRHEQ, and SFE within the same hydrometeorological frameworkMinimizing the vertical variance of RH in ETRHEQ is equivalent to minimizing the dissipation function of energy fluxes in MaxEntThe connection between MaxEnt, ETRHEQ, and SFE is independent of Monin‐Obukhov similarity theory (MOST)'s extremum solution [ABSTRACT FROM AUTHOR]

Scarce water resources across the globe have prompted the development of data‐driven water budgets to account for and distribute limited water more effectively across various land uses and purposes. Data‐driven approaches for estimating individual water budget components have been extensively developed and subsequently reviewed (e.g., evapotranspiration, precipitation, groundwater, surface water, runoff), but the state of the art of data‐driven approaches for estimating and integrating complete water budgets has not been the subject of a review paper to our knowledge. In this review, we fill this void by reviewing 81 systematically identified publications from the last decade (2012–2022) on data‐driven water budget approaches. We describe the current state of measurements and data products for data‐driven water budgets for various spatiotemporal scales. Our analysis suggests that spatiotemporal parameters drive the approach for data‐driven water budgets, with larger spatiotemporal scales relying more on satellite remote sensing data products and smaller spatiotemporal scales relying more on ground‐based monitoring. The incorporation of satellite remote sensing data products and ground‐based monitoring was common across various spatiotemporal scales and enabled the estimation of complete water budgets in areas of limited data availability. We conclude that improved reporting of simplifying assumptions, uncertainty analysis methods, and data sources are required for the alignment of water budget estimations between resource managers at varied spatiotemporal scales. Our review calls for the standardization of data‐driven water budget reporting protocols to improve the interpretability of data‐driven water budgets across decision‐makers working at various spatiotemporal scales. Plain Language Summary: Scarce water resources across the globe have prompted the monitoring of water budgets using data, which we refer to as a data‐driven water budget. We review the current state of measurements and data products for data‐driven water budgets of various scales—from field to region and over minutes to decades. We conclude that satellite remote sensing data products are suitable for data‐driven water budgets over large areas and long periods, but ground‐based data are more suitable over small areas and shorter periods. We identify challenges for data‐driven water budgets, which call for standardized reporting protocols for data‐driven water budgets. Key Points: The frequency and spatial scale of data‐driven water budgets differ in the integration of ground‐based and satellite remote sensing dataThe simplifying assumptions, uncertainty, and data sources should be reported in a data‐driven water budgetThe standardization of data‐driven water budget reporting protocols is needed for decision‐makers working at various spatiotemporal scales [ABSTRACT FROM AUTHOR]

This paper reconciles the state‐of‐the‐art observations and simulations of evapotranspiration (ET) temporal variability through a diagnostic framework composed of an observation‐model‐theory triplet. Specifically, a confirmed theoretical tool, Evapotranspiration Temporal VARiance Decomposition (EVARD), is used as a benchmark to estimate ET monthly variance (σET2) across the contiguous United States (CONUS) with inputs including hydroclimatic observations, Gravity Recovery and Climate Experiment‐based terrestrial water storage, four observation‐based products (ETRSUW by the University of Washington, ETRSMOD16 from MOD16 Global Terrestrial ET Data Set, ETFLUXNET upscaled from of fluxtower observations, and ETGLEAM from Global Land Evaporation Amsterdam Model), and four operational land surface models (LSMs: MOSAIC, NOAH, NOAH‐MP, and VIC). Five experiments are systematically designed to evaluate and diagnose possible errors and uncertainties in ET temporal variance estimated by the four observation‐based ET products and the four LSM simulations. Based on the results of these experiments, the following diagnostic hypotheses regarding the uncertainty of the observation‐based ET products are illustrated: ETRSUW captures the high σET2 signals in the Midwest with negligible bias and moderate uncertainty over the contiguous United States; ETFLUXNET systematically underestimates σET2 over CONUS but with the lowest level of uncertainty; ETRSMOD16 has medium bias with the highest level of uncertainty, and the spatial distribution of high σET2 signal from ETRSMOD16 is different from other estimates; ETGLEAM has slight negative bias and medium uncertainty, and σET2 in the West Coast is smaller than that from ETVARD. Regarding the LSMs, it is found that any of the four LSMs can be the best depending on a certain set of reference observations. The study reveals that LSMs have shown a reasonably worthy, though not perfect, capability in estimating ET and its variability in regions/aquifers with limited human interference. However, RS‐based observations and theoretical estimates suggest that all the four LSMs examined in this study are not able to accurately predict the ET variability in regions/aquifers heavily influenced by human activities like Central Valley and High Plains aquifers; they all underestimate ET variability along the West Coast due to seasonal vegetation responses to Mediterranean climate and human water use. In addition, LSMs underestimate intraannual ET variance in California and the High Plains with underestimated terrestrial storage change components in ET variance, due to the inappropriate representation of groundwater pumping and its impact on ET and other hydrologic processes. This paper urges advancing hydrologic knowledge by finding congruence among models, data, and theories. Key Points: A diagnostic framework based on an observation‐model‐theory triplet is provided for cross‐validating hydrologic theories, observations, and modelsThe spatial patterns of ET variance assessed from four observation‐based ET products are inconsistent; meanwhile, any of the four LSMs can be the best one for a certain set of reference observationsDue to limited representation of human dimensions on ET and other hydrologic processes, LSMs are not able to accurately predict the ET variability in regions/aquifers heavily influenced by human activities, like Central Valley and High Plains aquifers [ABSTRACT FROM AUTHOR]

Current literature provides large number of publications about ecohydrological processes and their effect on the biota in drylands. Given the limited laboratory and field experiments in such systems, many of these publications are based on mathematical models of varying complexity. The underlying implicit assumption is that the data set used to evaluate these models covers the parameter space of conditions that characterize drylands and that the models represent the actual processes with acceptable certainty. However, a question raised is to what extent these mathematical models are valid when confronted with observed ecosystem complexity? This Introduction reviews the 16 papers that comprise the Special Section on Eco-hydrology of Semiarid Environments: Confronting Mathematical Models with Ecosystem Complexity. The subjects studied in these papers include rainfall regime, infiltration and preferential flow, evaporation and evapotranspiration, annual net primary production, dispersal and invasion, and vegetation greening. The findings in the papers published in this Special Section show that innovative mathematical modeling approaches can represent actual field measurements. Hence, there are strong grounds for suggesting that mathematical models can contribute to greater understanding of ecosystem complexity through characterization of space-time dynamics of biomass and water storage as well as their multiscale interactions. However, the generality of the models and their low-dimensional representation of many processes may also be a ''curse'' that results in failures when particulars of an ecosystem are required. It is envisaged that the search for a unifying ''general'' model, while seductive, may remain elusive in the foreseeable future. It is for this reason that improving the merger between experiments and models of various degrees of complexity continues to shape the future research agenda. [ABSTRACT FROM AUTHOR]

The first issue of WRR appeared eight years after the launch of Sputnik, but by WRR's 25th anniversary, only seven papers that used remote sensing had appeared. Over the journal's second 25 years, that changed remarkably, and remote sensing is now widely used in hydrology and other geophysical sciences. We attribute this evolution to production of data sets that scientists not well versed in remote sensing can use, and to educational initiatives like NASA's Earth System Science Fellowship program that has supported over a thousand scientists, many in hydrology. We review progress in remote sensing in hydrology from a water balance perspective. We argue that progress is primarily attributable to a creative use of existing and past satellite sensors to estimate such variables as evapotranspiration rates or water storage in lakes and reservoirs and to new and planned missions. Recent transforming technologies include the Gravity Recovery and Climate Experiment (GRACE), the European Soil Moisture and Ocean Salinity (SMOS) and U.S. Soil Moisture Active Passive (SMAP) missions, and the Global Precipitation Measurement (GPM) mission. Future missions include Surface Water and Ocean Topography (SWOT) to measure river discharge and lake, reservoir, and wetland storage. Measurement of some important hydrologic variables remains problematic: retrieval of snow water equivalent (SWE) from space remains elusive especially in mountain areas, even though snow cover extent is well observed, and was the topic of 4 of the first 5 remote sensing papers published in WRR. We argue that this area deserves more strategic thinking from the hydrology community. [ABSTRACT FROM AUTHOR]

A theoretical analysis of transport in a controlled hydrologic volume, inclusive of two willow trees and forced by erratic water inputs, is carried out contrasting the experimental data described in a companion paper. The data refer to the hydrologic transport in a large lysimeter of different fluorobenzoic acids seen as tracers. Export of solute is modeled through a recently developed framework which accounts for nonstationary travel time distributions where we parameterize how output fluxes (namely, discharge and evapotranspiration) sample the available water ages in storage. The relevance of this work lies in the study of hydrologic drivers of the nonstationary character of residence and travel time distributions, whose definition and computation shape this theoretical transport study. Our results show that a large fraction of the different behaviors exhibited by the tracers may be charged to the variability of the hydrologic forcings experienced after the injection. Moreover, the results highlight the crucial, and often overlooked, role of evapotranspiration and plant uptake in determining the transport of water and solutes. This application also suggests that the ways evapotranspiration selects water with different ages in storage can be inferred through model calibration contrasting only tracer concentrations in the discharge. A view on upscaled transport volumes like hillslopes or catchments is maintained throughout the paper. [ABSTRACT FROM AUTHOR]

In this paper, we test the hypothesis that natural catchments utilize hedging strategy for evapotranspiration and water storage carryover with uncertain future precipitation. The hedging strategy for evapotranspiration in catchments under different levels of water availability is analytically derived with marginal utility principle. It is found that there exists hedging between evapotranspiration for present and future only with a portion of water availability. Observation data sets of 160 catchments in the United States covering the period from 1983 to 2003 demonstrate the existence of hedging in catchment hydrology and validate the proposed hedging strategy. We also find that more water is allocated to carryover storage for hedging against the future evapotranspiration deficit in the catchments with larger aridity indexes or with larger variability in future precipitation, i.e., long-term climate and precipitation variability control the degree of hedging. [ABSTRACT FROM AUTHOR]

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) was launched to the International Space Station on 29 June 2018 by the National Aeronautics and Space Administration (NASA). The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as Level‐3 (L3) latent heat flux (LE) data products. These data are generated from the Level‐2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear‐sky ET product (L3_ET_PT‐JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear‐sky instantaneous/time of overpass: r2 = 0.88; overall bias = 8%; normalized root‐mean‐square error, RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are overrepresented. The 70‐m‐high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1‐km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data. Key Points: ECOSTRESS is a state‐of‐the‐art combination of thermal bands, spatial and temporal resolutions, and measurement accuracy and precisionData from 82 eddy covariance sites were coalesced concurrently with the first year of ECOSTRESS for Stage 1 validationClear‐sky ET from ECOSTRESS compared well against a wide range of eddy covariance sites, vegetation classes, climate zones, and times of day [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is, after precipitation, the second largest flux at the land surface in the water cycle and occurs mainly during daytime. Less attention has been given to water fluxes from the land surface into the atmosphere during nighttime (i.e., between sunset and sunrise). The nighttime ET (ETN) may be estimated based on models that use meteorological data; however, due to missing experimental long‐term data, the verification of ETN estimates is limited. In this paper, the amount of ETN for two grassland ecosystems was determined from highly temporally resolved and precise weighing lysimeter data. We found that annual ETN ranged between 3.5% and 9.5% of daytime annual ET (ETD) and occurred mainly during wet soil and canopy surface conditions, which suggests that ETN is largely related to evaporation. ETN was positively correlated with wind speed. Dew formation, ranging from 4.8% to 6.4% of annual precipitation, was in absolute terms larger than ETN. The prediction of ETN with the Penman‐Monteith model improved if the aerodynamic and surface resistance parameters were based on vegetation height observations and the nighttime stomatal resistance parameter was assumed to be zero. The occurrence of hot days during the observation period showed to increase average ETN rates. Our results suggest that ETN can be observed with precision weighing lysimeters, was a not negligible component in the water balance of the grassland ecosystems, and thus needs more attention when simulating land surface hydrological processes. Key Points: Nighttime evapotranspiration as determined with precision weighing lysimeters contributes annually up to 10% of daytime evapotranspirationNighttime evapotranspiration can be predicted based on a modified parameterized Penman‐Monteith modelWind was the most significant environmental driver for nighttime evapotranspiration [ABSTRACT FROM AUTHOR]

This paper reports about the experimental evidence collected on the transport of five fluorobenzoate tracers injected under controlled conditions in a vegetated hydrologic volume, a large lysimeter (fitted with load cells, sampling ports, and an underground chamber) where two willows prompting large evapotranspiration fluxes had been grown. The relevance of the study lies in the direct and indirect measures of the ways in which hydrologic fluxes, in this case, evapotranspiration from the upper surface and discharge from the bottom drainage, sample water and solutes in storage at different times under variable hydrologic forcings. Methods involve the accurate control of hydrologic inputs and outputs and a large number of suitable chemical analyses of water samples in discharge waters. Mass extraction from biomass has also been performed ex post. The results of the 2 year long experiment established that our initial premises on the tracers' behavior, known to be sorption-free under saturated conditions which we verified in column leaching tests, were unsuitable as large differences in mass recovery appeared. Issues on reactivity thus arose and were addressed in the paper, in this case attributed to microbial degradation and solute plant uptake. Our results suggest previously unknown features of fluorobenzoate compounds as hydrologic tracers, potentially interesting for catchment studies owing to their suitability for distinguishable multiple injections, and an outlook on direct experimental closures of mass balance in hydrologic transport volumes involving fluxes that are likely to sample differently stored water and solutes. [ABSTRACT FROM AUTHOR]

Accurately estimating actual evapotranspiration (ET) across global land surface is one of the key challenges in terrestrial hydrological cycles and energy flux balance studies. Gridded ET products have the potential for application in ungauged basins, but their uncertainties are possibly large and it remains unclear which one is best for a given basin. The water balance (WB) method provides a direct estimate of basin scale ET, but it cannot be used in ungauged basins where streamflow data are unavailable. Here, we first assess the performance of ET from 10 global ET products against WB ET estimates in 43 large river basins. The paper then uses three indirect evaluation methods [Three Cornered Hat (TCH), Arithmetic Average (AA), and Bayesian Three Cornered Hat] to identify the optimal ET products without the need of prior information, and to generate fusion products combining the ET from multiple products. Using the evaluation results derived from the WB method as the reference, the results show that the three methods have great success in identifying poorer products, suggesting that they are useful in filtering poor ET products in applications. However, the ability of such methods in identifying better ET products degrades slightly. The AA fusion product, which combines ET outputs from multiple products, is marginally better than the best single ET product in many of the 43 basins. Because of its simplicity, it could be used to reduce the uncertainty in ET estimates from multiple products for ungauged basins and regions. Key Points: A comprehensive study on reducing the uncertainty in evapotranspiration (ET) estimates from 10 global ET products for application in ungauged river basinsThe indirect evaluation methods without using prior information, particularly Arithmetic Average (AA) and Bayesian Three Cornered Hat can successfully identify the poor ET productsThe AA fusion product, which combines ET outputs from multiple products, is generally marginally better than the best single ET product [ABSTRACT FROM AUTHOR]

At the catchment scale, soil moisture patterns have been observed to exhibit different types of dependence on topography. Some catchments have their wettest locations in the valley bottoms, while others have their wettest locations on hillslopes that are oriented away from the sun. Additionally, some catchments have soil moisture patterns that maintain a similar organization at all times (temporal stability), while other catchments have soil moisture patterns that change through time (temporal instability). Although these tendencies are well known, the reasons for their occurrence at a particular catchment are not well understood. In this paper, we investigate conditions under which different types of topographic dependence and different degrees of temporal instability can occur through the use of a new conceptual model. The type of topographic dependence and the degree of instability are quantified by two metrics that are also introduced in the paper, and the effects of soil, vegetation, and climatic parameters on these metrics are then evaluated. The evaluations indicate that saturated horizontal hydraulic conductivity, pore disconnectedness, and a vegetation evapotranspiration efficiency parameter have strong effects on the organization and instability of the soil moisture patterns. In contrast, annual potential evapotranspiration alone has less impact on the organization or its stability. [ABSTRACT FROM AUTHOR]

Research into the role of catchment vegetation within the hydrologic cycle has a long history in the hydrologic literature. Relationships between vegetation type and catchment evapotranspiration and runoff were primarily assessed through paired catchment studies during the 20th century. Results from over 200 paired catchment studies from around the world have been reported in the literature. Two constraints on utilizing the results from paired catchment studies in the wider domain have been that the catchment areas studied are generally (1) small (<10 km2) and (2) from a narrow range of climate types. The majority of reported paired catchment studies are located in the USA (∼47%) and Australia (∼27%) and experience mainly temperate (Köppen C) and cold (Köppen D) climate types. In this paper we assess the impact of vegetation type on mean annual evapotranspiration through a large, spatially, and climatically diverse data set of 699 catchments from around the world. These catchments are a subset of 861 unregulated catchments considered for the analysis. Spatially averaged precipitation and temperature data, in conjunction with runoff and land cover information, are analyzed to draw broad conclusions about the vegetation impact on mean annual evapotranspiration. In this analysis any vegetation impact signal is assessed through differences in long-term catchment average actual evapotranspiration, defined as precipitation minus runoff, between catchments grouped by vegetation type. This methodology differs from paired catchment studies where vegetation impact is assessed through streamflow responses to a controlled, within catchment, land cover change. The importance of taking the climate type experienced by the catchments into account when assessing the vegetation impact on evapotranspiration is demonstrated. Tropical and temperate forested catchments are found to have statistically significant higher median evapotranspiration, by about 170 mm and 130 mm, respectively, than non-forested catchments. Unexpectedly, cold forested catchments exhibit significantly lower median evapotranspiration, by about 90 mm, than non-forested catchments. No significant difference was found between median evapotranspiration of temperate evergreen and deciduous forested catchments though sample sizes were small. Temperate evergreen needleleaf forested catchments were found to have significantly higher median evapotranspiration than evergreen broadleaf forested catchments though sample sizes were small. The significant temperate forest versus non-forest difference in median evapotranspiration was found to persist for catchments with areas <1,000 km2, but not for catchments with areas ≥1,000 km2, which is consistent with the suggestion that the vegetation impact on evapotranspiration diminishes as catchment area increases. In summary, the results presented here are consistent with those drawn from reviews of paired catchment results. However, this paper demonstrates the value of a diverse hydroclimatic data set when assessing the vegetation impact on evapotranspiration as the magnitude of impact is observed to vary across climate types. [ABSTRACT FROM AUTHOR]

Lateral waterfluxes are not realistically taken into account in soil column models, although they influence the dynamic evolution of the vertical soil moisture profile. By neglecting these fluxes, the modeling of the soil-vegetation-atmosphere continuum is incomplete, and the feedbacks between these three compartments cannot be fully simulated. These fluxes have an importance in the different fields where soil column models are used: hydrology, hydrometeorology, biogeochemical cycles, ecology, and soil weathering. This paper introduces a novel Hydrological Hillslope-based Soil Column model (H2SC) that simulates the temporal evolution of the water table depth and evapotranspiration fluxes and their interaction. The interconnected processes are infiltration, evapotranspiration, vertical soil water movements, and the nonexplicitly modeled lateral fluxes flowing through the soil column. These lateral fluxes are modeled as a drainage function built from physically based equations that describe a simplified hillslope hydrology. This drainage function can be easily implemented in any soil column model without penalizing computational times. The H2SC model was validated on numerical experiments where a 2-D hillslope simulation performed with an integrated hydrologic model was compared with simulations using the H2SC 1-D model. Each of the H2SC simulations represents a specific location of a soil column along the hillslope. Different climate forcings, soil properties, and geometric shapes of the hillslope were tested. The model was then applied at the locations of two piezometers in the Strengbach catchment, France. The model reproduced the temporal evolution of the water table level fairly well for both the numerical experiments and for the real test case. [ABSTRACT FROM AUTHOR]

Reliable estimates of regional evapotranspiration are necessary to improve water resources management and planning. However, direct measurements of evaporation are expensive and difficult to obtain. Some of the difficulties are illustrated in a comparison of several satellite-based estimates of evapotranspiration for the Upper Blue Nile (UBN) basin in Ethiopia. These estimates disagree both temporally and spatially. All the available data products underestimate evapotranspiration leading to basin-scale mass balance errors on the order of 35 percent of the mean annual rainfall. This paper presents a methodology that combines satellite observations of rainfall, terrestrial water storage as well as river-flow gauge measurements to estimate actual evapotranspiration over the UBN basin. The estimates derived from these inputs are constrained using a one-layer soil water balance and routing model. Our results describe physically consistent long-term spatial and temporal distributions of key hydrologic variables, including rainfall, evapotranspiration, and river-flow. We estimate an annual evapotranspiration over the UBN basin of about 2.55 mm per day. Spatial and temporal evapotranspiration trends are revealed by dividing the basin into smaller subbasins. The methodology described here is applicable to other basins with limited observational coverage that are facing similar future challenges of water scarcity and climate change. [ABSTRACT FROM AUTHOR]

The memory timescale that characterizes root-zone soil moisture remains the dominant measure in seasonal forecasts of land-climate interactions. This memory is a quasi-deterministic timescale associated with the losses (e.g., evapotranspiration) from the soil column and is often interpreted as persistence in soil moisture states. Persistence, however, represents a distribution of time periods where soil moisture resides above or below some prescribed threshold and is therefore inherently probabilistic. Using multiple soil moisture data sets collected at high resolution (subhourly) across different biomes and climates, this paper explores the differences, underlying dynamics, and relative importance of memory and persistence timescales in root-zone soil moisture. A first-order Markov process, commonly used to interpret soil moisture fluctuations derived from climate simulations, is also used as a reference model. Persistence durations of soil moisture below the plant water-stress level (chosen as the threshold), and the temporal spectrum of upcrossings and downcrossings of this threshold, are compared to the memory timescale and spectrum of the full time series, respectively. The results indicate that despite the differences between meteorological drivers, the spectrum of threshold-crossings is similar across sites, and follows a unique relation with that of the full soil moisture series. The distribution of persistence times exhibits an approximate stretched exponential type and reflects a likelihood of exceeding the memory at all sites. However, the rainfall counterpart of these distributions shows that persistence of dry atmospheric periods is less likely at sites with long soil moisture memory. The cluster exponent, a measure of the density of threshold-crossings in a time frame, reveals that the clustering tendency in rainfall events (on-off switches) does not translate directly to clustering in soil moisture. This is particularly the case in climates where rainfall and evapotranspiration are out of phase, resulting in less ordered (more independent) persistence in soil moisture than in rainfall. [ABSTRACT FROM AUTHOR]

The Noah-MP land surface model adopts a multiparameterization framework to accommodate various alternative parameterizations for more than 10 physical processes. In this paper, the parameterizations implemented in Noah-MP associated with under-canopy turbulence and root water uptake are enhanced with: (i) an under-canopy turbulence scheme currently adopted by the Community Land Model (CLM), (ii) two vertical root distribution functions, i.e., an exponential and an asymptotic formulation, and (iii) three soil water stress functions ( βt) controlling root water uptake, e.g., a soil water potential ( ψ)-based function, a nonlinear soil moisture ( θ)-based power function and an empirical threshold approach considering preferential uptake from the moist part of the soil column. A comprehensive data set of in situ micrometeorological observations and profile soil moisture/temperature measurements collected from an alpine meadow site in the northeastern Tibetan Plateau is utilized to assess the impact of the augmentations on the Noah-MP performance. The results indicate that (i) implementation of the CLM under-canopy turbulence scheme greatly resolves the overestimation of sensible heat flux and underestimation of soil temperature across the profile, (ii) both exponential and asymptotic vertical root distribution functions better represent the Tibetan conditions enabling a better representation of the measured soil moisture dynamics, and (iii) the ψ-based βt functions overestimate surface soil moisture, the default linear θ-based βt function underestimates latent heat flux during the dry-down, while both the nonlinear power function and empirical threshold approach simultaneously simulate well soil moisture, and latent and sensible heat fluxes. Additionally, the parameter uncertainty associated with soil water stress function and hydraulic parameterization is addressed. [ABSTRACT FROM AUTHOR]

The impact of urban development on surface flow has been studied extensively over the last half century, but effects on groundwater systems are still poorly understood. Previous studies of the influence of urban development on subsurface storage have not revealed any consistent pattern, with results showing increases, decreases, and negligible change in groundwater levels. In this paper, we investigated the effects of four key features that impact subsurface storage in urban landscapes. These include reduced vegetative cover, impervious surface cover, infiltration and inflow (I&I) of groundwater and storm water into wastewater pipes, and other anthropogenic recharge and discharge fluxes including water supply pipe leakage and well and reservoir withdrawals. We applied the integrated groundwater-surface water-land surface model ParFlow.CLM to the Baltimore metropolitan area. We compared the base case (all four features) to simulations in which an individual urban feature was removed. For the Baltimore region, the effect of infiltration of groundwater into wastewater pipes had the greatest effect on subsurface storage (I&I decreased subsurface storage 11.1% relative to precipitation minus evapotranspiration after 1 year), followed by the impact of water supply pipe leakage and lawn irrigation (combined anthropogenic discharges and recharges led to a 7.4% decrease) and reduced vegetation (1.9% increase). Impervious surface cover led to a small increase in subsurface storage (0.56% increase) associated with decreased groundwater discharge as base flow. The change in subsurface storage due to infiltration of groundwater into wastewater pipes was largest despite the smaller spatial extent of surface flux modifications, compared to other features. [ABSTRACT FROM AUTHOR]

Water table dynamics are linked to the atmosphere through evapotranspiration and recharge. The assimilation of observed evapotranspiration values should thus improve groundwater model results. This paper presents a method for assimilating evapotranspiration data into a coupled unsaturated zone and groundwater model using the ensemble Kalman filter. The method is tested for a synthetically generated losing stream system in climatic conditions common in South Australia. The study focused on areas with a deep (recharge area) and a shallow (extraction area) water table and an intermediate area showing seasonal variations between these two (transition area). The data assimilation algorithm consistently improved the model states in the three areas when the ensemble spread was adequate. Improvements were also obtained in the calculation of net recharge and modeled actual evapotranspiration. The results indicate the potential to improve groundwater models using remote sensing observations of actual evapotranspiration values. [ABSTRACT FROM AUTHOR]

The pressure on water resources, deteriorating water quality, and uncertainties associated with the climate change create an environment of conflict in large and complex river system. The Black Sea Basin (BSB), in particular, suffers from ecological unsustainability and inadequate resource management leading to severe environmental, social, and economical problems. To better tackle the future challenges, we used the Soil and Water Assessment Tool (SWAT) to model the hydrology of the BSB coupling water quantity, water quality, and crop yield components. The hydrological model of the BSB was calibrated and validated considering sensitivity and uncertainty analysis. River discharges, nitrate loads, and crop yields were used to calibrate the model. Employing grid technology improved calibration computation time by more than an order of magnitude. We calculated components of water resources such as river discharge, infiltration, aquifer recharge, soil moisture, and actual and potential evapotranspiration. Furthermore, available water resources were calculated at subbasin spatial and monthly temporal levels. Within this framework, a comprehensive database of the BSB was created to fill the existing gaps in water resources data in the region. In this paper, we discuss the challenges of building a large-scale model in fine spatial and temporal detail. This study provides the basis for further research on the impacts of climate and land use change on water resources in the BSB. [ABSTRACT FROM AUTHOR]

The Community Land Model (CLM) includes a large variety of parameterizations, also for flow in the unsaturated zone and soil properties. Soil properties introduce uncertainties into land surface model predictions. In this paper, soil moisture and soil properties are updated for the coupled CLM and Community Microwave Emission Model (CMEM) by the Local Ensemble Transform Kalman Filter (LETKF) and the state augmentation method. Soil properties are estimated through the update of soil textural properties and soil organic matter density. These variables are used in CLM for predicting the soil moisture retention characteristic and the unsaturated hydraulic conductivity, and the soil texture is used in CMEM to calculate the soil dielectric constant. The following scenarios were evaluated for the joint state and parameter estimation with help of synthetic L-band brightness temperature data assimilation: (i) the impact of joint state and parameter estimation; (ii) updating of soil properties in CLM alone, CMEM alone or both CLM and CMEM; (iii) updating of soil properties without soil moisture update; (iv) the observation localization of LETKF. The results show that the characterization of soil properties through the update of textural properties and soil organic matter density can strongly improve with assimilation of brightness temperature data. The optimized soil properties also improve the characterization of soil moisture, soil temperature, actual evapotranspiration, sensible heat flux, and soil heat flux. The best results are obtained if the soil properties are updated only. The coupled CLM and CMEM model is helpful for the parameter estimation. If soil properties are biased, assimilation of soil moisture data with only state updates increases the root mean square error for evapotranspiration, sensible heat flux, and soil heat flux. [ABSTRACT FROM AUTHOR]

This paper presents a strategy for diagnosing and interpreting hydrological nonstationarity, aiming to improve hydrological models and their predictive ability under changing hydroclimatic conditions. The strategy consists of four elements: (i) detecting potential systematic errors in the calibration data; (ii) hypothesizing a set of 'nonstationary' parameterizations of existing hydrological model structures, where one or more parameters vary in time as functions of selected covariates; (iii) trialing alternative stationary model structures to assess whether parameter nonstationarity can be reduced by modifying the model structure; and (iv) selecting one or more models for prediction. The Scott Creek catchment in South Australia and the lumped hydrological model GR4J are used to illustrate the strategy. Streamflow predictions improve significantly when the GR4J parameter describing the maximum capacity of the production store is allowed to vary in time as a combined function of: (i) an annual sinusoid; (ii) the previous 365 day rainfall and potential evapotranspiration; and (iii) a linear trend. This improvement provides strong evidence of model nonstationarity. Based on a range of hydrologically oriented diagnostics such as flow-duration curves, the GR4J model structure was modified by introducing an additional calibration parameter that controls recession behavior and by making actual evapotranspiration dependent only on catchment storage. Model comparison using an information-theoretic measure (the Akaike Information Criterion) and several hydrologically oriented diagnostics shows that the GR4J modifications clearly improve predictive performance in Scott Creek catchment. Based on a comparison of 22 versions of GR4J with different representations of nonstationarity and other modifications, the model selection approach applied in the exploratory period (used for parameter estimation) correctly identifies models that perform well in a much drier independent confirmatory period. [ABSTRACT FROM AUTHOR]

After vegetation fires, discharge of streams and rivers is often higher than before. This is usually attributed to decreased canopy interception and evapotranspiration caused by vegetation removal, and to increased overland flow resulting from increased soil water repellency. In this paper we examine whether fire-induced changes in preferential flow can reinforce this postfire streamflow response. We studied five recently burned soils and adjacent unburned soils in Portugal and found that by reducing topsoil moisture and increasing soil moisture variability, fire increased the propensity for preferential flow. This was confirmed by 2-D soil moisture and repellency profiles that showed preferential paths in burned soil that were more distinct, wetter, and slightly narrower than in unburned soil. Since water infiltrating along preferential flow paths bypasses the dry soil matrix, we suggest that narrow flow paths promote deep infiltration- which effect size varies with soil depth, (effective) rainfall, and overland flow. We pose that the resulting increase in infiltration increases drainage and interflow because the excess water cannot stay in the soil, and incorporate fire-induced or -enhanced preferential flow into a conceptual model of flow routing that explains the commonly observed increase in stream flow postfire. [ABSTRACT FROM AUTHOR]

Numerical models of heat and moisture diffusion in the soil-vegetation-atmosphere continuum are linked through the moisture flux from the surface to the atmosphere. This mass flux represents a heat exchange as latent heat flux, coupling water, and energy balance equations. In this paper, a new approach for estimating key parameters governing moisture and heat diffusion equation and the closure function which links these equations, is introduced. Parameters of the system are estimated by developing objective functions that link atmospheric forcing, surface states, and unknown parameters. This approach is based on conditional averaging of heat and moisture diffusion equations on land surface temperature and moisture states, respectively. A single objective function is expressed that measures moisture and temperature-dependent errors solely in terms of observed forcings and surface states. This objective function is minimized with respect to the parameters to identify evaporation and drainage models and estimate water and energy balance flux components. The approach is calibration free (surface flux observations are not required), it is not hampered by missing data and does not require continuous records. Uncertainty of parameter estimates is obtained from the inverse of Hessian of the objective function, which is an approximation of the error covariance matrix. Uncertainty analysis and analysis of the covariance approximation, guides the formulation of a well-posed estimation problem. Accuracy of this method is examined through its application over three different field sites. This approach can be applied to diverse climates and land surface conditions with different spatial scales, using remotely sensed measurements. [ABSTRACT FROM AUTHOR]

In wetlands or riparian areas, water withdrawal by plants with access to groundwater or the capillary fringe often causes diurnal groundwater fluctuations. Various approaches use the characteristics of these fluctuations for estimation of daily groundwater evapotranspiration rates. The objective of this paper was to review the available methods, compare them with measured evapotranspiration and assess their recharge assumptions. For this purpose, we employed data of 85 rain-free days of a weighable groundwater lysimeter situated at a grassland site in the Spreewald wetland in north-east Germany. Measurements of hourly recharge and daily evapotranspiration rates were used to assess the different approaches. Our results showed that a maximum of 50% of the day to day variance of the daily evapotranspiration rates could be explained by the approaches based on groundwater fluctuations. Simple and more complex methods performed similarly. For some of the approaches, there were indications that erroneous assumptions compensated each other (e.g., when overestimated recharge counteracted underestimated storage change). We found that the usage of longer time spans resulted in improved estimates of the daily recharge rates and that the estimates were further enhanced by including two night averages. When derived from fitting estimates of recharge or evapotranspiration with according measurements the specific yield, needed to convert changes in water level to water volumes, differed considerably among the methods (from 0.022 to 0.064). Thus, the specific yield can be seen as 'correction factor' that compensates for inadequate process descriptions. [ABSTRACT FROM AUTHOR]

Reference crop evapotranspiration (ETo) estimation is of importance in irrigation water management for the calculation of crop water requirements and its scheduling, in rainfall-runoff modeling and in numerous other water resources studies. Due to its importance, several direct and indirect methods have been employed to determine the reference crop evapotranspiration but success has been limited because the direct measurement methods lack in precision and accuracy due to scale issues and other problems, while some of the more accurate indirect methods, e.g., the Penman-Monteith benchmark model, are time-consuming and require weather input data that are not routinely monitored. This paper has used the Kohonen self-organizing map (KSOM), unsupervised artificial neural networks, to predict the ETo. based on observed daily weather data at two climatically diverse basins: a small experimental catchment in temperate Edinburgh, UK and a semiarid lake basin in Udaipur, India. This was achieved by using the powerful clustering capability of the KSOM to analyze the multidimensional data array comprising the estimated ETo (based on the Food and Agricultural Organization (FAO) Penman-Monteith model) and different subsets of climatic variables known to affect it. The findings indicate that the KSOM-based ETo estimates even with fewer input variables were in good agreement with those obtained using the conventional FAO Penman-Monteith formulation employing the full complement of weather data at the two locations. More crucially, the KSOM-based estimates were also found to be significantly superior to those estimated using currently recommended empirical ETo methods for data scarce situations such as those in developing countries. [ABSTRACT FROM AUTHOR]

Surface fresh water (i.e., blue water) is a vital and indispensable resource for human water use in the agricultural, industrial, and domestic sectors. In this paper, global water availability is calculated by forcing the global hydrological model PCR-GLOBWB with daily global meteorological fields for the period 1958-2001. To represent blue water availability, a prognostic reservoir operation scheme was included in order to produce monthly time series of global river discharge modulated by reservoir operations. To specify green water availability for irrigated areas, actual transpiration from the model was used. Thus, the computed water availability reflects the climatic variability over 1958-2001 and is contrasted against the monthly water demand using the year 2000 as a benchmark in the companion paper. As the water that is withdrawn to meet demand directly interferes with blue water availability along the drainage network, this paper evaluates model performance for three regimes reflecting different degrees of human interference: natural discharge, discharge regulated by reservoirs, and modified discharge. In the case of modified discharge, the net blue water demand for the year 2000 is subtracted directly from the regulated discharge, taking water demand equal to consumptive water use. Results show that model simulations of monthly river discharge compare well with observations from most of the large rivers. Exceptions are basins subject to large extractions for irrigation purposes, where simulated discharge exceeds the observations even when water demand is taken into account. Including the prognostic reservoir operation scheme results in mixed performance, with a poorer approximation of peak flows but with a marginally better simulation of low flows and persistence. A comparison of simulated actual evapotranspiration with that from the ERA-40 reanalysis as a proxy for observed rates shows similar patterns over nonirrigated areas but substantial deviations over major irrigated areas. As expected, assimilated actual evapotranspiration over these areas includes water from alternative sources, whereas the simulations with PCR-GLOBWB are limited by soil moisture, i.e., green water availability. On the basis of this evidence we conclude that the simulation provides adequate fields of water availability to assess water stress at the monthly scale, for which a separate validation is provided in the companion paper. [ABSTRACT FROM AUTHOR]

The quantification of uncertainty in hydrologic modeling is a difficult task, as it arises from a combination of physical measurement errors, errors due to different temporal or spatial scales, and errors in the mathematical description of hydrologic processes. This paper presents an approach to infer during a calibration process the statistical properties of the principal error sources, namely, parameter, precipitation, potential evapotranspiration, and structural model uncertainty, by means of sequential data assimilation (SDA). We perform SDA using a particle filter that combines stochastic universal resampling and kernel smoothing with local shrinkage to improve its performance in comparison to traditional filters. Precipitation, potential evapotranspiration, and structural model uncertainty are incorporated into the calibration process using multiplicative error models. The particle filter is applied to a large-scale distributed model of the Rhine River to demonstrate its usefulness when characterizing error sources. Diagnostic checks and a synthetic case study show that the posterior distributions can be considered as reliable. The posterior multiplier distributions are used to identify whether a systematic bias exists and to illustrate that uncertainty from those sources can be reduced significantly in comparison to the prior assumptions adopted. Evaluating the predictive uncertainty shows that the overall error in hydrologic models is sufficiently characterized by the different error sources used here. Results indicate, however, that the assumptions taken in the output error model and the simplifications of the multiplicative models do not always hold in practice. Therefore, more sophisticated error models and a better quantification of the discharge measurement error are required to further improve characterization of error sources. [ABSTRACT FROM AUTHOR]

Water and energy fluxes control the development of northern peatlands and influence their carbon budget. Blanket bogs are peatlands that occur in temperate maritime regions where precipitation is much greater than evapotranspiration (ET). In this paper, five years (October 2002-September 2007) of ET and energy fluxes derived from eddy-covariance measurements were analyzed in the context of the predicted climate change for Ireland. Monthly ET at the Glencar Atlantic blanket bog varied little, ranging between a minimum of 12 mm month−1 and a maximum of 56 mm month−1 over the five years, resulting in an annual ET average of 394 mm, with typical highest daily values of 2.5-3.0 mm. Compared to other peatland types, Glencar had lower summer ET and a lower ET/potential ET ratio, despite having higher precipitation and water table. The ET was limited not only by the low vapor pressure deficit and cool summer temperatures but also by the low cover of vascular plants and mosses (essential for transpiration). The energy budget was similar to other peatland types in terms of net radiation and sensible heat fluxes, but had lower latent and higher ground heat fluxes. A comparison among the five years suggests that the predicted climate change (greater winter precipitation, lower summer precipitation, and higher all year round temperatures) will probably increase winter ET, while the summer energy flux patterns will not be profoundly affected. However, if the frequency of summer rain events should diminish, the moss component of these ecosystems may become water stressed, ultimately leading to lower evapotranspiration. [ABSTRACT FROM AUTHOR]

Nitrate pollution of surface waters is widespread in lowland catchments with intensive agriculture. For identification of effective nitrate concentration reducing measures the nitrate fluxes within catchments need to be quantified. In this paper we applied a mass transfer function approach to simulate catchment-scale nitrate transport. This approach was extended with time-varying travel time distributions and removal of nitrate along flow paths by denitrification to be applicable for lowland catchments. Numerical particle tracking simulations revealed that transient travel time distributions are highly irregular and rapidly changing, reflecting the dynamics of rainfall and evapotranspiration. The solute transport model was able to describe 26 years of frequently measured chloride and nitrate concentrations in the Hupsel Brook catchment (6.6 km2 lowland catchment in the Netherlands) with an R2 value of 0.86. Most of the seasonal and daily variations in concentrations could be attributed to temporal changes of the travel time distributions. A full sensitivity analysis revealed that measurements other than just surface water nitrate and chloride concentrations are needed to constrain the uncertainty in denitrification, plant uptake, and mineralization of organic matter. Despite this large uncertainty, our results revealed that denitrification removes more nitrate from the Hupsel Brook catchment than stream discharge. This study demonstrates that a catchment-scale lumped approach to model chloride and nitrate transport processes suffices to accurately capture the dynamics of catchment-scale surface water concentration as long as the model includes detailed transient travel time distributions. [ABSTRACT FROM AUTHOR]

Plants growing along hydrologic gradients adjust their biomass allocation and distribution in response to interspecific competition. Furthermore, susceptibility of a community to invasion is to some extent mediated by differences in growth habit, including root architecture and canopy hight. With reference to the study of a schematic wetland, the aim of this paper is (1) to test, via numerical modeling, the capacity of native plants to counteract an alien dominant species and cause eco-hydrological shifts of the ecosystem by changing their growth habit (e.g. allocating biomass below ground and by so doing changing the evapotranspiration locally) and (2) to test the impact on biodiversity of management practices that alter nutrient supply. The results demonstrated that unique combinations of vegetation types characterized by different growth habits may lead to different vegetation patterns under the same hydrologic forcing, and additionally, the vegetation patterns may change in response to major hydrological shifts, which could be related to diverse wetland management and restoration practices. [ABSTRACT FROM AUTHOR]

The Chaobai River basin in northern China consists of two major tributaries, the Chao River and Bai River. Monthly observations of precipitation, streamflow, and panevaporation data are available for 35 years (1961-1966 and 1973-2001). Using the annual time series of the observed streamflow, one break point at 1979 is detected and is adopted to divide the data set into two study periods, the 'before' and 'after' periods marking the onset of significant anthropogenic alteration of the flow (reservoirs and silt retention dams, five times increase in population) and significant changes in land use (conversion to terraced fields versus sloping fields). The distributed time-variant gain model (DTVGM) was used to evaluate the water resources of the area. Furthermore, the Bayesian method used by Engeland et al. (2005) was used in this paper to evaluate two uncertainty sources (i.e., the model parameter and model structure) and for assessing the DTVGM's performance over the Chaobai River basin. Comparing the annual precipitation means over 13 years (1961-1966 and 1973-1979), the means of the second period (1980-2001) decreased by 5.4% and 4.9% in the Chao River and Bai River basins, respectively. However, the related annual runoff decreased by 40.3% and 52.8%, respectively, a much greater decline than exhibited by precipitation. Through the monthly model simulation and the fixing-changing method, it is determined that decreases in runoff between the two periods can be attributed to 35% (31%) from climate variations and 68% (70%) from human activities in the Chao River (Bai River). Thus, human impact exerts a dominant influence upon runoff decline in the Chaobai River basin compared to climate. This study enhances our understanding of the relative roles of climate variations and human activities on runoff. [ABSTRACT FROM AUTHOR]

Uncertainty analysis is starting to be widely acknowledged as an integral part of hydrological modeling. The conventional treatment of uncertainty analysis in hydrologic modeling is to assume a deterministic model structure, and treat its associated parameters as imperfectly known, thereby neglecting the uncertainty associated with the model structure. In this paper, a modeling framework that can explicitly account for the effect of model structure uncertainty has been proposed. The modeling framework is based on initially generating different realizations of the original data set using a non-parametric bootstrap method, and then exploiting the ability of the self-organizing algorithms, namely genetic programming, to evolve their own model structure for each of the resampled data sets. The resulting ensemble of models is then used to quantify the uncertainty associated with the model structure. The performance of the proposed modeling framework is analyzed with regards to its ability in characterizing the evapotranspiration process at the Southwest Sand Storage facility, located near Ft. McMurray, Alberta. Eddy-covariance-measured actual evapotranspiration is modeled as a function of net radiation, air temperature, ground temperature, relative humidity, and wind speed. Investigating the relation between model complexity, prediction accuracy, and uncertainty, two sets of experiments were carried out by varying the level of mathematical operators that can be used to define the predictand-predictor relationship. While the first set uses just the additive operators, the second set uses both the additive and the multiplicative operators to define the predictand-predictor relationship. The results suggest that increasing the model complexity may lead to better prediction accuracy but at an expense of increasing uncertainty. Compared to the model parameter uncertainty, the relative contribution of model structure uncertainty to the predictive uncertainty of a model is shown to be more important. Furthermore, the study advocates that the search to find the optimal model could be replaced by the quest to unearth possible models for characterizing hydrological processes. [ABSTRACT FROM AUTHOR]

In semi-arid regions the evapotranspiration rates depend on both the spatial distribution of the vegetation and the soil moisture, for a given radiation regime. Remote sensing can provide high resolution spatially distributed estimation ( o ∼ 10-100 m) of land surface states. However, data on the near surface air properties are not readily available at the same resolution and are often taken as spatially uniform over a greater region. Concern for how this scale mismatch might lead to erroneous flux estimations motivates this effort. This paper examines the relative roles of variability in the two dominant atmospheric states, wind speed and air temperature, on the variability of the surface fluxes. The study is conducted with a Large Eddy Simulation (LES) model of the Atmospheric Boundary Layer (ABL), where the boundary conditions are given by a surface energy balance model based on remotely sensed land surface data. Simulations have been performed for the late morning hours of two clear-sky summer days during the SGP97 experiment with different wetness conditions over an area characterized by a high contrast in surface temperature, canopy cover, and roughness between vegetated and dry bare soil areas. Spatial variability in canopy density effects both the air temperature T a, through the energy partitioning, and the wind speed U, via the roughness, leading to local variations at 5 m above the ground of the order of 1 K and 1 m/s, respectively. Simulations show that the T a variability tends to decrease the sensible heat flux H (− 30 W/m2) over bare soil areas and to increase it (+30 W/m2) over dense vegetation, thus reducing the total variability of the surface fluxes relative to those that would be estimated for spatially constant T a, as observed in previous studies. The variability in U tends to increase H over bare soil (+50 W/m2), while having negligible effects over the vegetation, thus increasing the spatial variance of surface fluxes. However, when considered together, the combined effect is limited (< 10 W/m2), due to a partial canceling of effects. Consequently, for operational applications, such effects on regional flux estimation are typically minor. An interesting implication for ignoring atmospheric variability over the bare soil locations, with marked water limitation, is a significant local error (>50%) in the estimation of the evaporative fraction EF. [ABSTRACT FROM AUTHOR]

The translation of rainfall variability into variability in evapotranspiration, soil moisture, or runoff depends on many factors. Previously published results indicate that the sensitivity of evapotranspiration to rainfall at the interannual timescale generally increases as catchment aridity increases. This paper generalizes these results to the interstorm timescale by calculating the variance of interstorm evapotranspiration from a stochastic model of soil moisture balance. The derived analytical solution is compared to expressions for the variability of antecedent and poststorm soil moisture. This analysis shows that variability of interstorm evapotranspiration is low when average storm depth or average interstorm potential evapotranspiration is small relative to soil moisture capacity, as evapotranspiration is limited by the available water and energy. When water and energy inputs are larger, interstorm evapotranspiration variability is closely connected to variability in antecedent and poststorm soil moisture. The interstorm evapotranspiration deviation ratio is also calculated and compared to results from the interannual timescale. The effects of variable potential evapotranspiration and soil moisture controls on the rate of actual evapotranspiration are also considered. [ABSTRACT FROM AUTHOR]

The structure and function of vegetation regulate fluxes across the biosphere-atmosphere interface with large effects in water-limited ecosystems. Vegetation dynamics are often neglected in hydrological modeling except for simple prescriptions of seasonal phenology. However, changes in vegetation densities, influencing the partitioning of incoming solar energy into sensible and latent heat fluxes, can result in long-term changes in both local and global climates with resulting feedbacks on vegetation growth. This paper seeks a simple vegetation dynamics model (VDM) for simulation of the leaf area index (LAI) dynamics in hydrologic models. Five variants of a VDM are employed, with a range of model complexities. The VDMs are coupled to a land surface model (LSM), with the VDM providing the LAI evolution through time and the LSM using this to compute the land surface fluxes and update the soil water contents. We explore the models through case studies of water-limited grass fields in California (United States) and North Carolina (United States). Results show that a simple VDM, simulating only the living aboveground green biomass (i.e., with low parameterization), is able to accurately simulate the LAI. Results also highlight the importance of including the VDM in the LSM when studying the climate-soil-vegetation interactions over moderate to long timescales. The inclusion of the VDM in the LSM is demonstrated to be essential for assessing the impact of interannual rainfall variability on the water budget of a water limited region. [ABSTRACT FROM AUTHOR]

Non‐water‐limited canopy resistance (rcs, also known as the bulk stomatal resistance or surface resistance) is a critical variable in estimating potential evapotranspiration (PET), which is widely used in ecohydrology related fields. However, quantifying rcs is a challenging work. Here we develop an approach for estimating rcs over the globe. Comparing results over the globe and across 10 ET data sets (used as inputs), which are based on diverse mechanisms and algorithms, we find that the approach can capture canopy resistance well (mean correlation of 0.84 ± 0.04, mean relative Root Mean Squared Error of 4.4% ± 1.0%, and mean relative Mean Absolute Error of 5.8% ± 1.4%), and the estimated rcs are very close to those estimated using another method (R2 = 0.92), which is based on a quite different hypothesis that is only suitable for saturated regions. Based on these, we find that the rcs shows an overall increasing trend (0.43 ± 0.13 s m−1 year−1) over the globe (at 77.6% ± 3.9% of the land grid cells) during 1982–2014, and the air temperature dominates the variabilities of rcs in regions with decreasing rcs (mean relative contribution of 57.9% ± 11.4%), while air CO2 concentration controls the changes in rcs in regions with increasing rcs (mean relative contribution of 47.3% ± 8.0%). Moreover, we also find that the traditional PET estimator explicitly overestimates the increasing trends in PET, and tends to overestimate (underestimate) the increasing (decreasing) trends in regions with increasing (decreasing) PET. These findings can improve our knowledge on the complex water‐vegetation‐environment interactions and would be helpful for developing more accurate models for quantifying the impacts of global change on water resources. Key Points: An approach is developed to estimate the non‐water‐limited canopy resistance (rcs) over the globeChanges in Ta ([CO2]) dominate the variabilities of rcs in regions with decreasing (increasing) rcsTraditional potential evapotranspiration (PET) overestimates (underestimates) the increasing (decreasing) PET trends in regions with increasing (decreasing) PET [ABSTRACT FROM AUTHOR]

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a scientific mission that collects high spatio‐temporal resolution (∼70 m, 1–5 days average revisit time) thermal images since its launch on 29 June 2018. As a predecessor of future missions, one of the main objectives of ECOSTRESS is to retrieve and understand the spatio‐temporal variations in terrestrial evapotranspiration (ET) and its responses to soil water availability and atmospheric aridity. In the European ECOSTRESS Hub (EEH), by taking advantage of land surface temperature (LST) retrievals, we generated ECOSTRESS ET products over Europe and Africa using three models with different structures and parameterization schemes, namely Surface Energy Balance System (SEBS) and Two Source Energy Balance (TSEB) parametric models, as well as the non‐parametric Surface Temperature Initiated Closure (STIC) model. A comprehensive evaluation of the EEH ET products was conducted with respect to flux measurements from 19 eddy covariance sites in Europe over six different biomes with diverse aridity levels. Results revealed comparable performances of STIC and SEBS (RMSE of ∼70 W m−2). However, the relatively complex TSEB model produced a higher RMSE of ∼90 W m−2. Comparison between STIC ET estimates and the operational ECOSTRESS ET product from NASA PT‐JPL model showed a larger RMSE (around 50 W m−2 higher) for the PT‐JPL ET estimates. Substantial overestimation (>80 W m−2) in PT‐JPL ET estimates was evident over shrublands and savannas, presumably due to weak constraint of LST in the model. Overall, the EEH supports ET retrieval for the future high‐resolution thermal missions. Key Points: Evapotranspiration products over Europe and Africa were generated using three models (Surface Temperature Initiated Closure, Surface Energy Balance System, and Two Source Energy Balance) in the European ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) HubComparison at 19 eddy covariance sites revealed noteworthy model divergence with increasing aridity and vegetation sparsenessA substantial overestimation of the official NASA ECOSTRESS PT‐JPL evapotranspiration product was found under high water limitations [ABSTRACT FROM AUTHOR]

Agriculture is the world's largest consumer of water resources, and accurate measurement of crop water footprint (CWF) can provide a scientific basis for evaluating the water use characteristics of agricultural production and guiding water management. The measurement of regional CWF requires large amounts of ground data, and remote sensing provides an effective means to scientifically measure the CWF on a large scale. In this study, we developed an effective means to estimate regional maize CWF based on global evapotranspiration (MOD16 and Global Land Data Assimilation System (GLDAS)‐Noah) products in China. And we also calculated the CWF based on the FAO Penman‐Monteith equation (FAO‐PM) on the site scale in China. We assessed the accuracy of these methods by comparing them against eight eddy‐covariance based flux tower measurements. Links and differences behind the results of the three water footprint calculations were analyzed in terms of the basic principles and characteristics of the calculations. The results showed that the CWF had a similar distribution based on the MOD16 and GLDAS‐Noah, reflecting the influence of regional soil moisture on the CWF. Computational rationale analysis of the three quantitative methods showed that the ETc‐based method from the FAO‐PM model was similar to the MOD16‐ and GLDAS‐Noah‐based CWF in the wetter areas, two remote sensing‐based methods considered the water constraints during soil evaporation and water dissipation during dry and wet canopy conditions, and were closer to reality than the ETc‐based methods in measuring the CWF in arid and semi‐arid regions. Key Points: An effective means based on MOD16 and Global Land Data Assimilation System (GLDAS)‐Noah was developed for simulating regional maize crop water footprint (CWF)The accuracy of the estimated CWF based on FAO‐PM was influenced by the soil moistureThe CWF estimated by MOD16 or GLDAS‐Noah was closer to the reality than that estimated by FAO‐PM, especially in arid and semi‐arid region [ABSTRACT FROM AUTHOR]

For a shallow aquifer and a fully penetrating stream, the ideal baseflow curve does not plot as a straight line on semilog paper, and its recession rate continuously decreases with time. For a deep aquifer and a shallow-entrenched stream, the ideal baseflow generally decays exponentially, and its recession rate decreases with increasing stream entrenchment. In the case of loss from evapotranspiration, the baseflow curves steepen progressively with time, and the stream may become influent. In the case of gain from confined aquifers, the baseflow curves become flatter. The recharge results in shifting of the baseflow curves upward in magnitude or laterally in time. The baseflow peak occurs at about 0.75 T from the beginning of recharge to the aquifer, where T denotes the effective duration of recharge. The lag between the total flow peak and the baseflow peak depends on rainfall, soil, and basin factors. The variability of these factors precludes the notion of a constant lag. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall‐to‐wall explanatory variable maps to generate CONUS‐wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national‐scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time. Plain Language Summary: In the water cycle, most of the rain either evaporates or is converted to water vapor by plants. This combined amount of water is termed evapotranspiration (ET). Water resource managers need to be able to estimate ET to ensure that plants have adequate water supply, and to improve our understanding of the water remaining to replenish streams or groundwater. However, estimating ET over large areas and long time periods is a challenge. There are many simplified ET equations based on meteorological inputs that can be used, but each can give significantly different results. In this work, we use three national‐scale ET data sets to assess the performance of several equations and evaluate how performance depends on variables such as land cover type. We combine the strengths of different equations by producing an ensemble estimate where equations that perform better in a certain type of setting are weighted more heavily in those areas. We produce monthly ensemble ET maps for 1895–2018 at 800 m resolution, a finer spatial resolution and longer timespan than currently available. We find these maps provide an improvement in performance relative to six currently available products, and may be useful for water resource models and assessments. Key Points: Performance of several equations for actual evapotranspiration is evaluated against three national scale observational data setsRelative performance, Bayesian model averaging, and a random forest are used to produce monthly weighted ensemble evapotranspiration mapsThese evapotranspiration maps provide improved timespan, spatial resolution, and accuracy relative to several currently available products [ABSTRACT FROM AUTHOR]

A three‐stage precipitation partitioning framework is proposed to study the climate controls on mean annual groundwater evapotranspiration (GWET) for 33 gauged watersheds in west‐central Florida. Daily GWET, total evapotranspiration (ET), groundwater recharge, base flow, and total runoff are simulated by the Integrated Hydrologic Model, which dynamically couples a surface water model (HSPF) and a groundwater flow model (MODFLOW). The roles of GWET on long‐term water balance are quantified by four ratios. The ratios of GWET to total available water, watershed wetting, ET, and recharge decrease exponentially with watershed aridity index (WAI), which is defined as the ratio of potential evapotranspiration to total available water. In the one‐stage precipitation partitioning framework, the contribution of GWET to the ratio between total ET and available water for ET (i.e., the y‐axis of Budyko curve) decreases with WAI. In the two‐stage precipitation partitioning framework, the contribution of GWET to the ratio between total ET and watershed wetting (i.e., Horton index) decreases with WAI. The changes in GWET caused by intra‐monthly (IM) climate variability are the highest among the temporal scales of climate variability investigated to understand controls on GWET. The inter‐annual, intra‐annual, and IM climate variabilities lead to increase of GWET; but the sub‐daily climate variability results in decrease of GWET. For the third stage of partitioning, given the same ratio of potential GWET to available water for GWET, higher percentage of forest and wetland and lower percentage of impervious land contribute to higher ratio of GWET to available water for GWET. Key Points: A three‐stage precipitation partitioning framework is proposed to understand climate control on mean annual groundwater evapotranspiration (GWET)The contribution of GWET to Horton index and the y‐axis of Budyko curve declines with watershed aridity index in the study sitesThe roles of long‐term climate, climate variability and land cover on mean annual GWET are quantified [ABSTRACT FROM AUTHOR]

Despite interest in the contribution of evapotranspiration (ET) of residential turfgrass lawns to household and municipal water budgets across the United States, the spatial and temporal variability of residential lawn ET across large scales is highly uncertain. We measured instantaneous ET (ETinst) of lawns in 79 residential yards in six metropolitan areas: Baltimore, Boston, Miami, Minneapolis‐St. Paul (mesic climates), Los Angeles and Phoenix (arid climates). Each yard had one of four landscape types and management practices: traditional lawn‐dominated yards with high or low fertilizer input, yards with water‐conserving features, and yards with wildlife‐friendly features. We measured ETinst in situ during the growing season using portable chambers and identified environmental and anthropogenic factors controlling ET in residential lawns. For each household, we used ETinst to estimate daily ET of the lawn (ETdaily) and multiplied ETdaily by the lawn area to estimate the total volume of water lost through ET of the lawn (ETvol). ETdaily varied from 0.9 ± 0.4 mm d1 in mesic cities to 2.9 ± 0.7 mm d−1 in arid cities. Neither ETinst nor ETdaily was significantly influenced by yard landscape types and ETinst patterns indicated that lawns may be largely decoupled from regional rain‐driven climate patterns. ETvol ranged from ∼0 L d−1 to over 2,000 L d−1, proportionally increasing with lawn area. Current irrigation and lawn management practices did not necessarily result in different ETinst or ETdaily among traditional, water‐conserving, or wildlife‐friendly yards, but smaller lawn areas in water‐conserving and wildlife‐friendly yards resulted in lower ETvol. Plain Language Summary: Turfgrass lawns in residential yards can have significant water requirements. However, it is difficult to estimate how much water is consumed by lawns in households that vary in landscape type, management, and climate both within and across different cities. We visited 79 residential households in the United States and measured water use, or evapotranspiration (ET), of turfgrass lawns in six cities with different climates and yard management practices. Lawns used 0.6–1.3 mm of water per day in humid cities, and 2.2–3.6 mm per day in hot and dry cities. Lawn water use was more strongly influenced by climate, particularly solar radiation, than yard landscape type when comparing lawns of similar sizes. However, we found that most yards with conventional landscape types had much larger lawns than yards designed for water conservation or certified to be wildlife friendly. Therefore, the total estimated water use of lawns in each yard differed considerably among households. We conclude that widespread adoption of alternative yard landscape types such as xeriscaping, rain gardens, and wildlife‐certified may effectively reduce lawn water consumption in US cities. Key Points: Evapotranspiration (ET) per unit ground area of residential lawns in six US cities was largely driven by incoming solar radiation rather than yard landscape typeHowever, water‐conserving and wildlife‐friendly yard landscape types had smaller lawns, leading to lower volumetric ET losses per householdLawn ET per unit ground area was higher in arid cities, illustrating de‐coupling of lawn ET from regional climate patterns due to irrigation [ABSTRACT FROM AUTHOR]

Water residence time (WRT) is an important lake attribute that influences almost all in‐lake nutrient processes. However, information on WRT is often missing or outdated, especially in regions lacking lake inflow or outflow observations. Recent advances in global precipitation and evapotranspiration (ET) products and calibration‐free ET models provide the possibility of estimating lake WRT at large scales using estimated runoff from the water balance over the lake catchment. Here, we tested four global ET products and two calibration‐free ET models for estimating the mean annual lake outflow and WRT of 67 globally distributed lakes using precipitation inputs from four global precipitation products. The results show that the WRT estimated using the water balance method and global ET estimates generally correlates well with reference WRT (R = 0.90 ∼ 0.99) when using reliable precipitation inputs and is slightly more accurate than the estimates from the existing global WRT dataset and methods (R = 0.79 ∼ 0.94). Despite the large relative error (RE) in the estimates of the WRT, the RE of the phosphorus retention derived from the estimated WRT is acceptable (RE < ±30%). The simplicity and versatility of this approach underline its potential applications to large‐scale studies that require a fair estimation of WRT. Key Points: Lake residence time estimated by the water balance method using global evapotranspiration (ET) estimates is more accurate than existing methodsThe relative error (RE) of phosphorus retention derived from the estimated residence time is within an acceptable rangeUncertainties in precipitation input are more crucial to lake residence time estimation than uncertainties in ET estimates [ABSTRACT FROM AUTHOR]

Land surface models typically ignore plant hydraulic processes and use empirical soil moisture stress functions to limit transpiration and photosynthesis. How plant hydraulics impacts the predictions of carbon and water fluxes and their responses to drought remains unclear. Here, we developed an analytical plant hydraulic scheme wherein hydraulic capacitances at the leaf level and stem level were considered, and incorporated it into the vegetation interface processes model (hereafter, VIP‐PHS). Then, we calibrated the VIP‐PHS parameters using a Markov Chain Monte Carlo (MCMC) method and conducted an ecosystem‐scale evaluation of the VIP‐PHS at 30 FLUXNET sites. The results showed that VIP‐PHS improved evapotranspiration (ET) and gross primary production (GPP) simulations across the studied sites, reducing the root mean square error (RMSE) by 0.02–0.27 mm day−1 and 0.04–0.52 g C m−2 day−1 in relation to the empirical soil hydraulic scheme (hereafter, VIP‐SHS). VIP‐PHS decreased the RMSE in ET and GPP by up to 45% and 55% in evergreen needleleaf forests. Compared to VIP‐SHS, VIP‐PHS decreased the sensitivities of ET and GPP to soil moisture stress, and significantly improved ET and GPP predictions under low soil moisture conditions. The sensitivity analysis showed that larger stem hydraulic capacitance better relieved xylem water stress, resulting in greater transpiration and GPP and less‐negative daily minimum stem water potential. These findings highlight the need to incorporate plant hydraulics into the next generation of Earth system models under future drought conditions. Key Points: A plant hydraulic scheme that described water transport through the plant was proposedAn ecosystem‐scale evaluation at 30 FLUXNET sites showed plant hydraulic model (VIP‐PHS) improved evapotranspiration (ET) and gross primary production (GPP) simulations, especially under low soil moistureVIP‐PHS decreased the sensitivities of ET and GPP to soil moisture stress in relation to VIP‐SHS [ABSTRACT FROM AUTHOR]

To accurately project future water availability under a drying climate, it is important to understand how precipitation is partitioned into other terrestrial water balance components, such as fluxes (evaporation, transpiration, runoff) and changes in storage (soil moisture, groundwater). Many studies have reported unexpected large runoff reductions during drought, particularly for multi‐year events, and some studies report a persistent change in partitioning even after the meteorological drought has ended. This study focused on understanding how actual evapotranspiration (AET) and change in subsurface storage (ΔS) respond to climate variability and change, examining Australia's Millennium Drought (MD, 1997–2009). The study initially conducted a catchment‐scale water balance analysis to investigate interactions between ΔS and AET. Then the water balance analysis was extended to regional scale to investigate ΔS using interpolated rainfall and discharge with remotely sensed AET. Lastly, we evaluated conceptual rainfall‐runoff model performance of two commonly used models against these water balance estimates. The evaluation of water‐balance‐derived ΔS against Gravity Recovery and Climate Experiment (GRACE) estimates shows a significant multiyear storage decline; however, with different rates. In contrast, AET rates (annualized) remained approximately constant before and during the MD, contrasting with some reports of evapotranspiration enhancement elsewhere. Overall, given AET remained approximately constant, drought‐induced precipitation reductions were partitioned into ΔS and streamflow. The employed conceptual rainfall‐runoff models failed to realistically represent AET during the MD, suggesting the need for improved conceptualization of processes. This study provides useful implications for explaining future hydrological changes if similar AET behavior is observed under a drying climate. Key Points: For a multiyear drought, we investigated the impact of precipitation reductions on water balance fluxes and change in storageActual evapotranspiration was approximately unchanged even under prolonged droughts in a water‐limited regionBecause of this, precipitation reduction during the multiyear drought was partitioned into reductions in streamflow and subsurface storage [ABSTRACT FROM AUTHOR]

The effects of precipitation (Pr) and evapotranspiration (ET) on surface soil moisture (SSM) play an essential role in the land‐atmosphere system. Here we evaluate multimodel differences of these effects within the Coupled Model Intercomparison Project Phase 5 (CMIP5) compared to Soil Moisture Active Passive (SMAP) products and ECMWF Reanalysis v5 (ERA5) as references in a frequency domain. The variability of SSM, Pr, and ET within three frequency bands (1/7 ∼ 1/30 days−1, 1/30 ∼ 1/90 days−1, and 1/90 ∼ 1/365 days−1) after normalization is quantified using Fourier transform. We analyze the impact of ET and Pr on SSM variability based on a transfer function assuming that these variables form a linear time‐invariant (LTI) system. For the total effects of ET and Pr on SSM variability, the CMIP5 estimations are smaller than the reference data in the two higher frequency bands and are larger than the reference data in the lowest frequency band. Besides, the effects on SSM by Pr and ET are found to be different across the three frequency bands. In each frequency band, the variability of the factor that dominates SSM (i.e., Pr or ET) from CMIP5 is smaller than that from the references. This study identifies the spatiotemporal distribution of differences between CMIP5 models and references (SMAP and ERA5) in simulating ET and Pr effects on SSM within three frequency bands. This study provides insightful information on how soil moisture variability is affected by varying precipitation and evapotranspiration at different time scales within Earth System Models. Plain Language Summary: Climate is influenced by the interactions between the land surface and atmosphere boundary, and soil moisture is a key component of these physical processes. Precipitation and evapotranspiration, as two major variables involved in these interactions, have been largely regarded as essential processes affecting soil moisture dynamics. However, Earth System Models have large uncertainties in simulating these effects. This study compares the average performance of 14 Earth System Models in capturing the effects of precipitation and evapotranspiration on surface soil moisture variability. We find that (a) soil moisture is mainly affected by precipitation at weekly to seasonal time scales and by evapotranspiration at seasonal to annual time scales; (b) compared to two largely used reference data, the total effects of precipitation and evapotranspiration on soil moisture is smaller at weekly to seasonal time scales and are larger at seasonal to annual time scale; and (c) spatially, models tend to simulate less variability of precipitation or evapotranspiration as a major control on surface soil moisture. Key Points: The effects of precipitation and evapotranspiration on soil moisture variability can be analyzed in a frequency domainPrecipitation dominates weekly to seasonal variability and evapotranspiration dominates seasonal to annual variability of soil moistureEarth System Models shall be improved in simulating soil moisture temporal variabilities [ABSTRACT FROM AUTHOR]

The ability to quantify evapotranspiration (ET) is crucial for smart agriculture and sustainable groundwater management. Efficient ET estimation strategies often rely on the vertical‐flow assumption to assimilate data from soil‐moisture sensors. While adequate in some large‐scale applications, this assumption fails when the horizontal component of the local flow velocity is not negligible due to, for example, soil heterogeneity or drip irrigation. We present novel implementations of the ensemble Kalman filter (EnKF) and the maximum likelihood estimation (MLE), which enable us to infer spatially varying ET rates and root water uptake profiles from soil‐moisture measurements. While the standard versions of EnKF and MLE update the predicted soil moisture prior to computing ET, ours treat the ET sink term in Richards' equation as an updatable observable. We test the prediction accuracy and computational efficiency of our methods in a setting representative of drip irrigation. Our strategies accurately estimate the total ET rates and root‐uptake profiles and do so up to two‐orders of magnitude faster than the standard EnKF. Plain Language Summary: The ability to quantify evapotranspiration (ET) is crucial for smart agriculture and sustainable groundwater management. We present novel implementations of the ensemble Kalman filter and the maximum likelihood estimation, which enable us to infer spatially varying ET rates and root water uptake profiles from soil‐moisture measurements. We test the prediction accuracy and computational efficiency of our methods in a setting representative of drip irrigation. Our strategies accurately estimate the total ET rates and root‐uptake profiles and do so up to two‐orders of magnitude faster than the standard techniques. Key Points: Current strategies for evapotranspiration estimations from moisture sensors rely on the vertical‐flow assumption, which fails for drip irrigationOur implementations of ensemble Kalman filter (EnKF) and maximum likelihood estimation overcome this limitationBoth methods outperform the standard EnKF approach, which updates soil moisture, by up to two orders of magnitude [ABSTRACT FROM AUTHOR]

Estimation of actual evapotranspiration (ETa) is challenging due to its complex interactions with surrounding environments; thus, understanding the complexity and predictability of ETa along with its influencing factors is essential to improve ETa estimation. Based on the FLUXNET and ChinaFLUX datasets, we first examined whether daily ETa exhibited chaotic behaviors, and then investigated how daily ETa complexity and predictability varied across climate regimes and ecosystems using the chaos theory. The results of recurrence plot and correlation dimension (CD) analysis suggested the existence of chaotic behaviors in daily ETa, implying the system controlling ETa processes was deterministic with a limited number of controlling variables. The recurrence quantification analysis further revealed a varying degree of complexity for ETa processes (e.g., determinism‐DET with a range from 0.01% to 40.7%) across the sites. Specifically, daily ETa featured stronger deterministic properties (e.g., higher DET and lower CD values) and thus higher predictability in humid and arid regions; whereas, higher degrees of daily ETa complexity emerged in sub‐humid and semi‐arid regions due to more complex interactions with environmental factors. Moreover, primary environmental controls on daily ETa complexity varied with climatic and land surface conditions. Results showed that energy and water supplies along with average daily temperature and relative humidity were the primary controls on the ETa complexity across the sites, while leaf area index also played an important role at drier sites. As a first attempt, this study provides additional avenues to understand the complexity of ETa processes from a global perspective using the chaos theory. Key Points: Chaotic behaviors of daily actual evapotranspiration (ETa) across 81 sites were investigated using the chaos theoryHigher degrees of daily ETa complexity emerged at sub‐humid and semi‐arid sites than those at humid and arid sitesEnvironmental controls on daily ETa complexity varied with climatic and land surface conditions [ABSTRACT FROM AUTHOR]

The extent and mechanisms by which precipitation extremes affect hydrological processes in the critical zone (CZ) of loess possessing a thick unsaturated zone remains poorly understood. To this end, we here employed a coupled liquid‒vapor‒heat‒airflow STEMMUS (simultaneous transfer of energy, mass, and momentum in unsaturated soil) model to investigate the impact of extreme precipitation, at both event and annual scales, on CZ hydrological processes within a semiarid loess site vegetated by apple trees on China's Loess Plateau. At the event scale, the vapor flux was two orders of magnitude lower than the liquid water flux. However, the thermal vapor flux penetrated to depths of 200 cm, whereas the isothermal liquid water flux only infiltrated to 100 cm during the study period, implying that thermal‐gradient‐driven vapor transfer is an important mechanism for deep‐layer recharge (DLR). At the annual scale, the DLR below 200 cm during extremely wet years was 6.5 times larger than that during extremely dry years. In contrast, extreme changes in climate had only limited impacts on evapotranspiration; the difference between extremely wet and extremely dry years averaged only 35 mm, much less than the difference in precipitation, which averaged 310 mm. However, the extremely dry years showed a higher ratio (0.58) between transpiration and evapotranspiration than did the extremely wet years (0.51). The findings reported here improve our understanding of CZ hydrological processes related to precipitation extremes in semiarid loess regions. Key Points: Thermal‐gradient‐driven vapor transfer is an important mechanism for deep‐layer recharge (DLR) in loessThe DLR below 200 cm during extremely wet years was 6.5 times larger than that during extremely dry yearsExtreme changes in precipitation had only limited impacts on evapotranspiration [ABSTRACT FROM AUTHOR]