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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]

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]

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 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]

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]

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 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]

Evapotranspiration (ET) is a key component of water cycle and is strongly modulated by below‐ground (e.g., dynamic effective rooting depth, Zr) and above‐ground (e.g., LAI and canopy height, CH) vegetation dynamics. Existing studies mainly focus on the effect of above‐ground vegetation dynamics on ET, while it is still unclear how Zr affects ET. Moreover, it is challenging to parameterize Zr dynamically in large‐scale hydrological and biogeochemical models due to data scarcity. Here, we estimate Zr in China from 1982 to 2015 based on Guswa's carbon cost‐benefit model, and update ET partitioning algorithm by replacing CH with Zr in PT‐JPLsm model to form the PT‐JPLzr model. We find that root mean square error (RMSE) between modeled (based on PT‐JPLzr model) and observed ET is 8.25% lower than that of PT‐JPLsm model at 16 in‐situ ET observation sites. Comparing with T/ET from the satellite‐based products, our results highlight the improved performance of PT‐JPLzr (R2 = 0.66) due to incorporated Zr, which is superior to that of PT‐JPLsm model (R2 = 0.62). Transpiration (T) limited by changes in soil moisture (SM) is more sensitive to Zr than CH. Thus, Zr improves the PT‐JPL model performance by affecting the sensitivity of T to soil moisture deficit. Moreover, SM and LAI are main drivers of T/ET spatial variability in drier and wetter regions, respectively. These findings highlight the critical role of Zr in regulating the effects of soil moisture deficit on ET. Key Points: We extend the static plant rooting depth to estimate the dynamic effective rooting depth (Zr) across ChinaZr is incorporated into evapotranspiration (ET) model to simultaneously consider the joint effects of canopy structure and rooting depth on ETTranspiration limited by soil moisture deficit is more sensitive to changes in Zr than canopy height (CH) [ABSTRACT FROM AUTHOR]

[i] The surface energy fluxes and related évapotranspiration processes across the Indus Basin were estimated for the hydrological year 2007 using satellite measurements. The new ETLook remote sensing model (version 1) infers information on actual Evaporation (E) and actual Transpiration (T) from combined optical and passive microwave sensors, which can observe the land-surface even under persistent overcast conditions. A two-layer Penman-Monteith equation was applied for quantifying soil and canopy evaporation. The novelty of the paper is the computation of ? and ? across a vast area (116.2 million ha) by using public domain microwave data that can be applied under all weather conditions, and for which no advanced input data are required. The average net radiation for the basin was estimated as being 112 Wm~2. The basin average sensible, latent and soil heat fluxes were estimated to be 80, 32, and 0 Wm"2, respectively. The average évapotranspiration (ET) and evaporative fraction were 1.2 mm d~1 and 0.28, respectively. The basin wide ET was 496 ± 16.8 km3 yr-1. Monte Carlo analysis have indicated 3.4% error at 95% confidence interval for a dominant land use class. Results compared well with previously conducted soil moisture, lysimeter and Bowen ratio measurements at field scale (R2 = 0.70 ; RMSE = 0.45 mm d~1 ; RE = -11.5% for annual ET). ET results were also compared against earlier remote sensing and modeling studies for various regions and provinces in Pakistan (R2 = 0.76; RMSE = 0.29 mmd~1 ; RE = 6.5% for annual ET). The water balance for all irrigated areas together as one total system in Pakistan and India (26.02 million ha) show a total ET value that is congruent with the ET value from the ETLook surface energy balance computations. An unpublished validation of the same ETLook model for 23 jurisdictional areas covering the entire Australian continent showed satisfactory results given the quality of the watershed data and the diverging physiographic and climatic conditions (R2 = 0.70 ; RMSE = 0.31 mmd~1 ; RE = -2.8% for annual ET). Eight day values of latent heat fluxes in Heibei (China) showed a good resemblance (R2 = 0.92 ; RMSE = 0.04 mm d~1 ; RE = 9.5% for annual ET). It is concluded that ETLook is a novel model that can be operationalized further--especially after improving the preprocessing of spacebome soil moisture data. This preprocessing includes (1) downscaling of topsoil moisture from 25 to 1 km pixels, and (2) translation of topsoil moisture into subsoil moisture values. [ABSTRACT FROM AUTHOR]

This work focuses on the description and the use of the probability density functions (pdfs) of travel, residence and évapotranspiration times, which are comprehensive descriptors of the fate of rainfall water particles traveling through catchments, and provide key information on hydrologie flowpaths, partitioning of precipitation, circulation and turnover of pollutants. Exploiting some analytical solutions to the transport problem derived by Botter et al. (2011), this paper analyzes the features of travel, residence and évapotranspiration time pdfs resulting from different assumptions on the mixing processes occurring during streamflow formation and plant uptake (namely, complete mixing and translatory flow). The ensuing analytical solutions are analyzed through numerical Monte Carlo simulations of a stochastic model of soil moisture and streamflow dynamics. Travel and residence time pdfs are shown to be time-variant as they mirror the variability of the relevant hydrological fluxes. In particular, the temporal fluctuations of the mean residence time are shown to reflect rainfall dynamics, whereas the variability of the mean travel time is chiefly driven by streamflow dynamics, with lower frequency and higher amplitude fluctuations. Dry climates enhance the effect of the type of mixing on catchment transport features (e.g., mean travel times and seasonal dynamics of stream concentrations). The implications for the interpretation of tracer experiments are also discussed, showing through specific examples that models disregarding nonstationarity may significantly misestimate travel time pdfs. [ABSTRACT FROM AUTHOR]

Soil moisture and evapotranspiration (ET) are important components of boreal forest hydrology that affect ecological processes and land‐atmosphere feedbacks. Future trends in soil moisture in particular are uncertain. Therefore, accurate modeling of these dynamics and understanding of concomitant sources of uncertainty are critical. Here, we conduct a global sensitivity analysis, Monte Carlo parameterization, and analysis of parameter uncertainty and its contribution to future soil moisture and ET uncertainty using a physically based ecohydrologic model in multiple boreal forest types. Soil and plant hydraulic parameters and LAI have the largest effects on simulated summer soil moisture at two contrasting sites. In future scenario simulations, the selection of parameters and global climate model (GCM) choice between two GCMs influence projected changes in soil moisture and ET about as much as the projected effects of climate change in the less sensitive GCM with a late‐century, high‐emissions scenario, though the relative effects of parameters, GCM, and climate vary among hydrologic variables and study sites. Saturated volumetric water content and sensitivity of stomatal conductance to vapor pressure deficit have the most statistically significant effects on change in ET and soil moisture, though there is considerable variability between sites and GCMs. The results of this study provide estimates of: (a) parameter importance and statistical significance for soil moisture modeling, (b) parameter values for physically based soil‐vegetation‐atmosphere transfer models in multiple boreal forest types, and (c) the contributions of uncertainty in these parameters to soil moisture and ET uncertainty in future climates. Plain Language Summary: Future changes in soil water content and evapotranspiration (ET) in boreal regions will influence forest dynamics, permafrost thaw rates and have the potential to alter feedbacks between the land surface and the atmosphere, potentially influencing regional climate dynamics. These changes are uncertain and difficult to model because of the complexity of the boreal ecological and hydrological systems. In this study, we conduct experiments with a hydrological model to better understand which parameters most influence soil water content and ET, how much uncertainty these parameters contribute, and how specific parameter values affect whether soils become wetter or drier and by how much. We find that the parameters that control how tightly soils retain water and how much plants close their stomata and hence reduce transpiration in response to dry conditions, have the largest influences. Interactions between parameters are also important. Even when these parameter values are constrained by model performance in comparison with observations, parameter choice can determine whether soils become wetter or drier in future conditions. These findings suggest that modelers should carefully consider how parameter selection influences simulated future hydrologic conditions and highlight specific parameters that are worthy of further attention. Key Points: Modeled summer soil moisture at rooting depth is most sensitive to soil and plant hydraulic parameters and parameter interactions.Parameter uncertainty affects projected change in evapotranspiration and θVWC about as much as climate change or choice between two global climate models.We present parameter values useful for hydrologic modeling in multiple boreal forest types while quantifying the impacts of equifinality. [ABSTRACT FROM AUTHOR]

Understanding daytime (ETD) and nighttime (ETN) evapotranspiration is critical for accurately evaluating terrestrial water and carbon cycles. However, unlike ETD, the factors influencing ETN remain poorly understood. Here, long‐term ETD and ETN data from five FLUXNET sites along a climate gradient in Northern Australia were analyzed to compare their responses to environmental drivers at different temporal scales. We found that (a) across the sites, mean annual ETN/ETD (ETN¯/ETD¯) ranged between 5.1% and 11.7%, which was mainly determined by ETD¯ variations. Particularly, vegetation and meteorological variables mostly controlled ETD¯, while ETN¯ was largely related to air temperature and net radiation (Rn) due to lower nighttime atmospheric water demands; (b) At individual sites, ETD and ETN exhibited higher correlations with meteorological and vegetation variables at monthly timescales than at annual timescales. Monthly ETD and ETN were also strongly coupled, especially under drier climatic conditions. At daily timescales, leaf area index and soil water content (SWC) controlled ETD with SWC being more important at drier sites; whereas, SWC was the dominant factor controlling ETN. At half‐hourly timescales, the boosted regression tree method quantitively showed that ETD and ETN were controlled by Rn and SWC, respectively. Overall, the results showed that ETN was less responsive to environmental variables, illustrating that ETD and ETN responded differently to diverse climate regimes and ecosystems at varying temporal scales. These findings provide a critical evaluation for contrasting ETD and ETN interactions in constantly changing environments, which has important implications for ecosystem water balance and land surface processes modeling. Key Points: Variations in mean annual ETN/ETD ratio (5.1%–11.7%) across the sites were mostly determined by the spatial variability in ETDETD and ETN responded differently to climatic drivers from half‐hourly to annual scales, which also depended on ecosystems typesAt site levels, leading controls were Rn for half‐hourly ETD, leaf area index (LAI), and soil water content (SWC) for daily to annual ETD, and SWC for half‐hourly to annual ETN [ABSTRACT FROM AUTHOR]

Microwave brightness temperature observations from the NASA Soil Moisture Active Passive (SMAP) mission and gauge‐based precipitation data over the United States are used to reconstruct the soil water loss function and then historical (1979–2019) hydrological fluxes in the form of evapotranspiration (ET) and drainage (D) are quantified. Over the period of study, with the exception of snowy and hyper‐arid regions, we observe a correlation of R2 > 0.6 between SMAP‐precipitation derived drainage estimates and streamflow measurements from the U.S. Geological Survey (USGS). There is a bias between estimated drainage and USGS streamflow with an underestimation of about 1 mm day−1 in southwest United States to 3 mm day−1 in parts of the eastern United States. SMAP‐derived sensitivities of drainage and ET partitioning with respect to precipitation anomalies are also calculated. In parts of the Great Plains the drainage partitioning exhibits a near‐linear response, while in the southeast United States, the response is nonlinear. Partitioning also is examined for 6 four‐digit hydrologic unit basins wherein year‐to‐year variations in drainage partitioning are shown to be key mediators in translating precipitation anomalies into streamflow anomalies. Observation‐driven drainage and ET estimates are obtained without relying on full hydrologic and Land Surface Models (LSMs). This independence (isolation from model parameterization assumptions) provides a path toward using satellite‐derived landscape hydrological diagnostics to assess hydrologic models and LSMs as well as to guide their further development. Key Points: A large amount of hydrologic information is encoded within satellite remote sensing observations of soil moistureSMAP‐era soil moisture and precipitation information, without reliance on models, can characterize landscape hydrological partitioningHistorical remote sensing and precipitation‐based drainage estimates closely track streamflow measurements across the United States [ABSTRACT FROM AUTHOR]

Quantifying the transpiration fraction of evapotranspiration (T/ET) is crucial for understanding plant functionality in ecosystem water cycles, land‐atmosphere interactions, and the global water budget. However, the controls and mechanisms underlying the temporal change of T/ET remain poorly understood in arid and semiarid areas, especially for remote regions with sparse observations such as the Tibetan Plateau (TP). In this study, we used combined high‐frequency laser spectroscopy and chamber methods to constrain estimates of T/ET for an alpine meadow ecosystem in the central TP. The three isotopic end members in ET (δET), soil evaporation (δE), and plant transpiration (δT) were directly determined by three newly customized chambers. Results showed that the seasonal variations of δET, δE, and δT were strongly affected by the precipitation isotope (R2 = 0.53). The δ18O‐based T/ET agreed with that of δ2H. Isotope‐based T/ET ranged from 0.15 to 0.73 during the periods of observation, with an average of 0.43. This mean result was supported by T/ET derived from a two‐source model and eddy covariance observations. Our overarching finding is that at the seasonal timescale, surface soil water content (θ) dominated the change of T/ET, with leaf area index playing only a secondary role. Our study confirms the critical impact of soil water on the temporal change of T/ET in water‐limited regions such as the TP. This knowledge sheds light on diverse land‐surface processes, global hydrological cycles, and their modeling. Key Points: Laser spectroscopy and the chamber method were used to estimate T/ET in the central Tibetan PlateauNear‐surface soil water content dominated the temporal change of T/ET, with leaf area index playing a secondary roleOur study highlights the critical impact of environmental conditions on the temporal change of T/ET in water‐limited regions [ABSTRACT FROM AUTHOR]

Ecohydrological processes in semiarid shrublands and other dryland ecosystems are sensitive to discrete pulses of precipitation. Anticipated changes in the frequency and magnitude of precipitation events are expected to impact the spatial and temporal distribution of soil moisture in these drylands, thereby impacting their ecohydrological processes. Recent field studies have shown that in dryland ecosystems, transpiration dynamics and plant productivity are largely a function of deep soil moisture available after large precipitation events, regardless of where the majority of plant roots occur. However, the strength of this relationship and how and why it varies throughout the year remains unclear. We present eddy covariance, soil moisture, and sap flow measurements taken over an 18‐month period in conjunction with an analysis of biweekly precipitation, shallow soil, deep soil, and stem stable water isotope samples from a creosotebush‐dominated shrubland ecosystem at the Santa Rita Experimental Range in southern Arizona. Within the context of a hydrologically defined two‐layer conceptual framework, our results support that transpiration is associated with the availability of deep soil moisture and that the source of this moisture varies seasonally. Therefore, changes in precipitation pulses that alter the timing and magnitude of the availability of deep soil moisture are expected to have major consequences for dryland ecosystems. Our findings offer insights that can improve the representation of drylands within regional and global models of land surface atmosphere exchange and their linkages to the hydrologic cycle. Key Points: Shallow and deep soil moisture are isotopically distinct at this warm semiarid shrublandDeep moisture tends to be isotopically similar to precipitation from previous seasonShrubs use deep moisture all year round [ABSTRACT FROM AUTHOR]

The partitioning of incident precipitation into evapotranspiration, runoff, drainage, storage change, and hydrologic fluxes depends on the soil moisture state. With the availability of global remotely sensed soil moisture fields, the functional dependence of each flux on soil moisture may be identifiable. In this study we develop an observation‐driven approach to map key hydroclimatology fields using remotely sensed soil moisture and gauge‐based precipitation data only. National Aeronautics and Space Administration's Soil Moisture Active Passive (SMAP) low‐frequency microwave brightness temperature observations and precipitation fields, from the National Centers for Environmental Prediction, are the sole inputs into an adjoint‐state variational estimation framework. Furthermore, the proposed methodology does not rely on micrometeorological information, or land surface models. The approach is flexible by design so that almost any partitioning pattern can result from estimation and corresponding evapotranspiration and drainage fields can be quantified. Three‐year averaged summer season evapotranspiration estimates are compared with available vapor flux at in situ AmeriFlux eddy‐covariance sites. Basin‐averaged drainage over major U.S. hydrologic units is also compared with U.S. Geological Survey streamgages measurements. The remote sensing‐based estimated hydroclimate fields explain about 70% of the variance in the in situ measurements. This exploratory study adds to the body of evidence emerging in literature that a significant amount of hydrologic information is encoded in the dynamic fields of remotely sensed soil moisture. Observation‐driven hydroclimate data fields that are independent of land surface models can provide valuable insights into the state of the water cycle and guide future development of land surface models. Key Points: A significant amount of hydrologic information is encoded in the dynamic fields of surface soil moistureVariational estimation is used to partition precipitation into evapotranspiration and drainage fluxesObservation‐driven maps of evapotranspiration and drainage hydroclimates explain about 70% of their corresponding in situ variance [ABSTRACT FROM AUTHOR]

Evapotranspiration and photosynthetic carbon uptake are both constrained by water availability, with presumed water‐limited and water‐independent but energy‐limited regimes. We investigate water availability's relationships with evaporative fluxes and photosynthetic measures at continental scale using surface and satellite‐based observations. The observation‐driven approach is independent of prior model‐based estimates. We find water‐limited and water‐independent regimes for both energy and carbon cycle processes in spatial and temporal aggregate, differences in water‐limitation relationships across ecohydrological regions, and more consistent signs of water limitation in photosynthetic than evaporative processes. Ecosystem water use efficiency's response to water availability changes in sign with aridity state across time and space generally but shows negative correlations in temporal anomalies. Plain Language Summary: Evaporation and plant CO2 uptake both require water to be available at the land surface. From satellite and weather station data, we find simple relationships between these processes and the amount of available water. Even though evaporation and CO2 uptake are linked through water loss from plant leaves, we find that the relationships between each of these and the amount of available soil water are different; it seems that plant CO2 uptake is similarly sensitive to the amount of available water, in wet and dry environments, while evaporation is much more sensitive in dry environments. The amount of water used in the landscape for similar amounts of photosynthesis changes with soil wetness in the Western United States but remains relatively constant in the eastern United States. Key Points: Water‐limited and energy‐limited regimes are observed in the energy and carbon cycles at scale, which vary with regionGross primary productivity and solar‐induced fluorescence are similar in response to moisture limitation/abundanceEcosystem water use efficiency's response to water availability changes in sign with aridity state [ABSTRACT FROM AUTHOR]

The precipitation partitioning between evapotranspiration (ET) and runoff (R) at the land surface is controlled by atmospheric boundary layer and terrestrial hydrological processes. These processes in land surface models are manifested primarily as stomatal conductance, soil moisture limitation factor to transpiration (β‐factor), turbulence, and runoff generation. What are the sensitivities of precipitation partitioning to the parameterizations of these processes? To address this overarching question, the annual and seasonal means of ET and R over the conterminous United States were simulated using 48 configurations of the Noah land surface model with multiparameterization options (Noah‐MP). The Sobol' total sensitive index was used to quantify the sensitivity of ET and R to the parameterizations of the four processes mentioned above. Results show that the sensitivities of the annual means depend on climatic conditions and the interplay between ET and R plays an important role. In humid regions, precipitation is mostly partitioned into R, whereas the simulations can be more sensitive to ET's parameterizations. In arid regions, ET accounts for the major partition, whereas the simulations can be more sensitive to the runoff parameterization. Seasonal means exhibit different sensitivities from the annual means. The seasonal mean ET is more sensitive to ET's parameterizations, and R is more sensitive to the runoff parameterization. The β‐factor, which is neglectable for the annual means, is important for summer‐time ET. Mediated by the terrestrial water storage memories, ET interplays R across seasons. The winter‐time R is still sensitive to the stomatal conductance that only modulates growing‐season ET. Key Points: The sensitivity of precipitation partitioning to land surface parameterizations is quantified using the Sobol' sensitivity indexThe parameterization sensitivity depends on climatic conditions and seasons and varies with the time scaleThe influence of stomatal conductance can extend beyond growing seasons due to the terrestrial water storage memories [ABSTRACT FROM AUTHOR]

Abstract: Unsaturated flow modeling is widely used to estimate potential groundwater recharge. In semiarid regions, modeled recharge is usually highly uncertain due to the uncertainty in model parameters and also because recharge is often a small fraction of overall rainfall and actual evapotranspiration (AET). This study attempted to assess the usefulness of soil moisture and AET data on reducing the recharge uncertainty using an experimental site in semiarid southeastern Australia as an example. A biophysically based model capable of simulating unsaturated flow, energy balance, and plant growth was employed to conduct recharge modeling. Soil moisture measured at five different depths of the vadose zone and AET derived from an eddy covariance tower were used to constrain the recharge modeling. The best‐calibrated model shows reasonable agreement between modeled and simulated soil moisture and AET time series, with three‐year average recharge of 50.9 mm. The model uncertainty analysis using Monte Carlo simulations indicates that recharge estimated from the unsaturated flow modeling could be highly uncertain (0–213 mm/year). The uncertainty analysis shows that the soil moisture was more useful than AET in constraining groundwater recharge, particularly the measurements at the top of both soil horizons. The combined use of both the soil moisture and AET led to the most constrained recharge uncertainty (14.8–87.3 mm/year). This study suggests that for practical applications, soil moisture data from at least the top of each soil horizon and AET data (either remotely sensed or directly measured) should be used together to constrain recharge modeling. [ABSTRACT FROM AUTHOR]

The Southeastern United States experiences recurring hydrological droughts, which can reduce water availability and result in water deficits. Long-term monitoring data from Panola Mountain Research Watershed, a small, forested, seasonally water-limited watershed near Atlanta, GA, was used to quantify interactions of climatic variability with shallow and deep storage and evapotranspiration. Watershed storage (WS) and actual evapotranspiration (AET) were estimated monthly from 1985 through 2015 using a relationship with baseflow and a water-budget approach, respectively. A watershed shallow storage (SS) water budget, based on soil moisture profile data, indicated a transition from recharge to surplus as dormant season SS increased to field capacity, and a transition from utilization of stored water to water deficits as growing season SS declined toward its wilting point. Deeper storage appeared unavailable to AET during dry conditions. The majority of deeper storage recharge occurred during the dormant season and required SS to be near field capacity. WS was an effective drought indicator. Growing season droughts typically occurred when WS was below normal at the end of the dormant season and growing season precipitation (P) was below or near normal. A hydrologic persistence analysis showed that monthly month-standardized WS was significantly correlated (p-value<0.05) with past monthly month-standardized WS for the previous 19 months and with past monthly P for the previous 11 months, indicating the importance of past hydrologic conditions on WS. These findings allowed assessment of expected climatic changes on the water cycle, which included effects on future recharge, water deficits, and drought occurrence. [ABSTRACT FROM AUTHOR]

Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern. [ABSTRACT FROM AUTHOR]

In this study, we develop and apply a mapping estimation capability for key unknown parameters that link the surface water and energy balance equations. The method is applied to the Gourma region in West Africa. The accuracy of the estimation method at point scale was previously examined using flux tower data. In this study, the capability is scaled to be applicable with remotely sensed data products and hence allow mapping. Parameters of the system are estimated through a process that links atmospheric forcing (precipitation and incident radiation), surface states, and unknown parameters. Based on conditional averaging of land surface temperature and moisture states, respectively, a single objective function is posed that measures moisture and temperature-dependent errors solely in terms of observed forcings and surface states. This objective function is minimized with respect to parameters to identify evapotranspiration and drainage models and estimate water and energy balance flux components. The uncertainty of the estimated parameters (and associated statistical confidence limits) is obtained through the inverse of Hessian of the objective function, which is an approximation of the covariance matrix. This calibration-free method is applied to the mesoscale region of Gourma in West Africa using multiplatform remote sensing data. The retrievals are verified against tower-flux field site data and physiographic characteristics of the region. The focus is to find the functional form of the evaporative fraction dependence on soil moisture, a key closure function for surface and subsurface heat and moisture dynamics, using remote sensing data. [ABSTRACT FROM AUTHOR]

To investigate the effects of expanding rubber ( Hevea brasiliensis) cultivation on water cycling in Mainland Southeast Asia (MSEA), evapotranspiration ( ET) was measured within rubber plantations at Bueng Kan, Thailand, and Kampong Cham, Cambodia. After energy closure adjustment, mean annual rubber ET was 1211 and 1459 mm yr−1 at the Thailand and Cambodia sites, respectively, higher than that of other tree-dominated land covers in the region, including tropical seasonal forest (812-1140 mm yr−1), and savanna (538-1060 mm yr−1). The mean proportion of net radiation used for ET by rubber (0.725) is similar to that of tropical rainforest (0.729) and much higher than that of tropical seasonal forest (0.595) and savanna (0.548). Plant area index (varies with leaf area changes), explains 88.2% and 73.1% of the variance in the ratio of latent energy flux (energy equivalent of ET) to potential latent energy flux ( LE/ LEpot) for midday rain-free periods at the Thailand and Cambodia sites, respectively. High annual rubber ET results from high late dry season water use, associated with rapid refoliation by this brevideciduous species, facilitated by tapping of deep soil water, and by very high wet season ET, a characteristic of deciduous trees. Spatially, mean annual rubber ET increases strongly with increasing net radiation ( Rn) across the three available rubber plantation observation sites, unlike nonrubber tropical ecosystems, which reduce canopy conductance at high Rn sites. High water use by rubber raises concerns about potential effects of continued expansion of tree plantations on water and food security in MSEA. [ABSTRACT FROM AUTHOR]

Given a time series of potential evapotranspiration and rainfall data, there are at least two approaches for estimating vertical percolation rates. One approach involves solving Richards' equation (RE) with a plant uptake model. An alternative approach involves applying a simple soil moisture accounting procedure (SMAP) based on a set of conceptual stores and conditional statements. It is often desirable to parameterize distributed vertical percolation models using regional soil texture maps. This can be achieved using pedotransfer functions when applying RE. However, robust soil texture based parameterizations for more simple SMAPs have not previously been available. This article presents a new SMAP designed to emulate the response of a one-dimensional homogenous RE model. Model parameters for 231 different soil textures are obtained by calibrating the SMAP model to 20 year time series from equivalent RE model simulations. The results are then validated by comparing to an additional 13 years of simulated RE model data. The resulting work provides a new simple two parameter (% sand and % silt) SMAP, which provides consistent vertical percolation data as compared to RE based models. Results from the 231 numerical simulations are also found to be qualitatively consistent with intuitive ideas concerning soil texture and soil moisture dynamics. Vertical percolation rates are found to be highest in sandy soils. Sandy soils are found to provide less water for evapotranspiration. Surface runoff is found to be more important in soils with high clay content. [ABSTRACT FROM AUTHOR]

Soil moisture is a key water cycle parameter known to interact with atmospheric processes. Arguably, land surface models that simulate land surface processes and surface fluxes to the atmosphere do not capture adequately the spatial variability of soil moisture, particularly over areas with complex topography. In this study, version 3.5 of the Community Land Model (CLM3.5) is applied with a new parameterization in an effort to correct the spatial bias of soil moisture and understand the consequential effects on the simulated water cycle fluxes and states in the Blue Nile Basin. This parameterization accounts for a groundwater recharge term from surface water, a process that is not included in CLM, providing an effective two-way interaction scheme between rivers and groundwater. Using satellite soil moisture data, this parameterized term is shown to have a positive correlation to contributing area, defined at each model grid cell and representing the number of grid cells that drain to that local grid cell. With the new parameterization applied to CLM, soil moisture, soil temperature, evapotranspiration flux, water table depth, and vegetation water content all showed significant differences from the control CLM run (without the parameterization) at or above the 95% confidence level. The differences in the spatial distribution of these variables are expected to affect precipitation simulations from regional climate modeling. As the Blue Nile is a region that has one of the greatest interannual and seasonal precipitation variability globally, the ability to predict this variability is essential for optimal reservoir operations including buffering of water resources during times of drought. [ABSTRACT FROM AUTHOR]

Recent U.S. Supreme Court rulings have limited federal protections for geographically isolated wetlands (GIWs) except where a 'significant nexus' to a navigable water body is demonstrated. Geographic isolation does not imply GIWs are hydrologically disconnected; indeed, wetland-groundwater interactions may yield important controls on regional hydrology. Differences in specific yield (Sy) between uplands and inundated GIWs drive differences in water level responses to precipitation and evapotranspiration, leading to frequent reversals in hydraulic gradients that cause GIWs to act as both groundwater sinks and sources. These reversals are predicted to buffer surficial aquifer dynamics and thus base flow delivery, a process we refer to as landscape hydrologic capacitance. To test this hypothesis, we connected models of soil moisture, upland water table, and wetland stage to simulate hydrology of a low-relief landscape with GIWs, and explored the influences of total wetland area, individual wetland size, climate, and soil texture on water table and base flow variation. Increasing total wetland area and decreasing individual wetland size substantially decreased water table and base flow variation (e.g., reducing base flow standard deviation by as much as 50%). GIWs also decreased the frequency of extremely high and low water tables and base flow deliveries. For the same total wetland area, landscapes with fewer (i.e., larger) wetlands exhibited markedly lower hydrologic capacitance than those with more (i.e., smaller) wetlands, highlighting the importance of small GIWs to regional hydrology. Our results suggest that GIWs buffer dynamics of the surficial aquifer and stream base flow, providing an indirect but significant nexus to the regional hydrologic system. [ABSTRACT FROM AUTHOR]

We examined 3 years of measured daily values of all major water budget components (precipitation P, potential evapotranspiration PET, actual evapotranspiration ET, and runoff R) and volumetric soil water content θ of a small, forested catchment located in the west of Germany. The spatial distribution of θ was determined from a wireless sensor network of 109 points with 3 measurement depths each; ET was calculated from eddy-covariance tower measurements. The water budget was dominantly energy limited, with ET amounting to approximately 90% of PET, and a runoff ratio R/P of 56%. P, ET, and R closed the long-term water budget with a residual of 2% of precipitation. On the daily time scale, the residual of the water budget was larger than on the annual time scale, and explained to a moderate extent by θ ( R2 = 0.40). Wavelet analysis revealed subweekly time scales, presumably dominated by unaccounted fast-turnover storage terms such as interception, as a major source of uncertainty in water balance closure. At weekly resolution, soil water content explained more than half ( R2 = 0.62) of the residual. By means of combined empirical orthogonal function and cluster analysis, two slightly different spatial patterns of θ could be identified that were associated with mean θ values below and above 0.35 cm3/cm3, respectively. The timing of these patterns as well as the varying coherence between PET, ET, and soil water content responded to changes in water availability, including a moderate response to the European drought in spring 2011. [ABSTRACT FROM AUTHOR]

Six models with differing representation of the physical process in the coupled soil-plant system are tested to simultaneously reproduce the dynamics of soil water contents, evapotranspiration, and leaf area index during a growing season of winter wheat at two contrasting field plots in the Kraichgau and the Swabian Alb regions in South-West Germany. The main aim of the study is the assessment of the performance and the identification of structural deficits of the models LEACHN, SUCROS, CERES, GECROS, and SPASS as well as the land-surface model CLM3.5. The calibration of each model is posed in a multiobjective framework with three different objective functions that summarize the fit between model simulations and the three observation types. The AMALGAM evolutionary search algorithm is utilized to simultaneously estimate the most important soil hydraulic and plant parameters. The six models exhibit a wide variability in the trade-offs between the fitting to the data types. Mechanistic process description, particularly of the root system, reduces the trade-off considerably for the SPASS and GECROS models. These models adequately simulate the reduction of root water uptake and transpiration during senescence under nonlimited soil water supply. The SPASS model in particular shows an overall better performance as compared to the more simpler models which is related to an adequate level of structural complexity in the interplay of all model compartments combined with a relatively low parameter sensitivity to the weighting scheme in the multiobjective optimization. The dynamic consideration of the root system formation is particularly important, which is simulated quite detailed in the SPASS model as a function of nitrogen (N) and water availability in the different soil horizons. The proposed multiobjective calibration procedure proved to be very useful to identify processes that are important to adequately simulate the coupled soil-plant system. The consideration of these processes and our insights about the value of different data types for model calibration is expected to lead to more accurate, predictive land-surface models. [ABSTRACT FROM AUTHOR]

The objective function of the inverse problem in Soil-Vegetation-Atmosphere-Transfer (SVAT) models can be expressed as the aggregation of two criteria, accounting for the uncertainties of surface soil moisture ( θ) and evapotranspiration ( ET), retrieved from remote sensing (RS). In this context, we formulate a Weighted-Objective-Function (WOF) with respect to model effective soil hydraulic parameters, comprising of two components for θ and ET, respectively, and a dimensionless coefficient w. Given that the sensitivity of θ is increased by omitting the periods when soil moisture decoupling occurs, we also introduce within the WOF a threshold, θd, which outlines the decoupling of the surface and root-zone moisture. The optimal values of w and θd are determined by using a novel framework, weighted objective function selector algorithm (WOFSA). This performs numerical experiments, assuming known reference conditions. In particular, it solves the inverse problem for different sets of θ and ET, considering the uncertainties of retrieving them from RS, and then runs the hydrological model to obtain the simulated water fluxes and their residuals, ΔWF, against the reference responses. It estimates the two unknown variables, w and θd, by maximizing the linear correlation between the WOF and maximum ΔWF. The framework is tested using a modified Soil-Water-Atmosphere-Plant (SWAP) model, under 22 contrasting hydroclimatic scenarios. It is shown that for each texture class, w can be expressed as function of the average θ and ET-fraction, while that for all scenarios θd can be modeled as function of the average θ, average ET, and standard deviation of ET. Based on the outcomes of this study, we also provide recommendations on the most suitable time period for soil moisture measurements for capturing its dynamics and thresholds. Finally, we propose the implementation of WOFSA within multiobjective calibration, as a generalized tool for recognizing robust solutions from the Pareto front. [ABSTRACT FROM AUTHOR]

An adaptation of a simple model for evapotranspiration ( E) estimations in drylands based on remotely sensed leaf area index and the Penman-Monteith equation (PML model) (Leuning et al., 2008) is presented. Three methods for improving the consideration of soil evaporation influence in total evapotranspiration estimates for these ecosystems are proposed. The original PML model considered evaporation as a constant fraction ( f) of soil equilibrium evaporation. We propose an adaptation that considers f as a variable primarily related to soil water availability. In order to estimate daily f values, the first proposed method ( fSWC) uses rescaled soil water content measurements, the second ( fZhang) uses the ratio of 16 days antecedent precipitation and soil equilibrium evaporation, and the third ( fdrying), includes a soil drying simulation factor for periods after a rainfall event. E estimates were validated using E measurements from eddy covariance systems located in two functionally different sparsely vegetated drylands sites: a littoral Mediterranean semiarid steppe and a dry-subhumid Mediterranean montane site. The method providing the best results in both areas was fdrying (mean absolute error of 0.17 mm day−1) which was capable of reproducing the pulse-behavior characteristic of soil evaporation in drylands strongly linked to water availability. This proposed model adaptation, fdrying, improved the PML model performance in sparsely vegetated drylands where a more accurate consideration of soil evaporation is necessary. [ABSTRACT FROM AUTHOR]

The relation between storage and discharge is an essential characteristic of many rainfall-runoff models. The simple dynamical systems approach, in which a rainfall-runoff model is constructed from a single storage-discharge relation, has been successfully applied to humid catchments. Here we investigate (1) if and when the less humid lowland Hupsel Brook catchment also behaves like a simple dynamical system by hydrograph fitting, and (2) if system parameters can be inferred from streamflow recession rates or more directly from soil moisture storage observations. Only 39% of the fitted monthly hydrographs yielded Nash-Sutcliffe efficiencies above 0.5, from which we can conclude that the Hupsel Brook catchment does not always behave like a simple dynamical system. Model results were especially poor in summer, when evapotranspiration is high and the thick unsaturated zone attenuates the rainfall input. Using soil moisture data to obtain system parameters is not trivial, mainly because there is a discrepancy between local and catchment storage. Parameters obtained with direct storage-discharge fitting led to a strong underestimation of the response of runoff to rainfall, while recession analysis leads to an overestimation. [ABSTRACT FROM AUTHOR]

Groundwater can serve as an important resource for woody vegetation in semiarid landscapes, particularly when soil water is functionally depleted and unavailable to plants. This study examines the uptake of groundwater by deciduous blue oak trees ( Quercus douglasii) in a California oak savanna. Here we present a suite of direct and indirect methods that demonstrate its occurrence and quantify its rates. The study site is underlain by a thin soil layer and fractured metavolcanic bedrock. Typical depth to groundwater is approximately 8 m. A variety of water storage and flux measurements were collected from 2005 to 2008, including groundwater levels, soil moisture contents, sap flows, and latent heat fluxes. During the dry season, groundwater uptake rates ranged from 4 to 25 mm month−1 and approximately 80% of total ET during June, July, and August came from groundwater. Leaf and soil water potentials supported these results, indicating that groundwater uptake was thermodynamically favorable over soil water uptake for key portions of the growing season. These findings strongly suggest that blue oaks should be considered obligate phreatophytes and that groundwater reserves provide a buffer to rapid changes in their hydroclimate, if these assets are not otherwise depleted by prolonged drought or human consumption. While groundwater uptake may provide for short-term protection, it should be viewed not as a mechanism for continued plant growth. It allows the woody vegetation to subsist during the summer but not to flourish. [ABSTRACT FROM AUTHOR]

Advanced land surface models (LSMs) offer detailed estimates of distributed hydrological fluxes and storages. These estimates are extremely valuable for studies of climate and water resources, but they are difficult to verify as field measurements of soil moisture, evapotranspiration, and surface and subsurface runoff are sparse in most regions. In contrast, river discharge is a hydrologic flux that is recorded regularly and with good accuracy for many of the world's major rivers. These measurements of discharge spatially integrate all upstream hydrological processes. As such, they can be used to evaluate distributed LSMs, but only if the simulated runoff is properly routed through the river basins. In this study, a rapid, computationally efficient source-to-sink (STS) routing scheme is presented that generates estimates of river discharge at gauge locations based on gridded runoff output. We applied the scheme as a postprocessor to archived output of the Global Land Data Assimilation System (GLDAS). GLDAS integrates satellite and ground-based data within multiple offline LSMs to produce fields of land surface states and fluxes. The application of the STS routing scheme allows for evaluation of GLDAS products in regions that lack distributed in situ hydrological measurements. We found that the four LSMs included in GLDAS yield very different estimates of river discharge and that there are distinct geographic patterns in the accuracy of each model as evaluated against gauged discharge. The choice of atmospheric forcing data set also had a significant influence on the accuracy of simulated discharge. [ABSTRACT FROM AUTHOR]

The study of water exchange between soil, plants, and the atmosphere in response to seasonal or periodic droughts is critical to modeling the hydrologic cycle and biogeochemical processes in water-controlled ecosystems. An essential step in such studies is to characterize changes in evaporation and transpiration under water stress. The objectives of this study are to investigate how soil moisture controls the evapotranspiration in a Californian oak savanna that experiences seasonal droughts, using multiyear field observations at the daily and stand scale, and to model these controls stochastically. The influence of soil moisture on evapotranspiration at the stand scale is studied using correlations between tower-based evapotranspiration measurements and representative soil moisture obtained by aggregating point measurements. The observed pattern of this effect is found in agreement with an existing model that features a linear reduction of the evapotranspiration when soil moisture falls below a critical value. The model parameters are inferred using a Bayesian framework, and they are found to vary from year to year because of climate variability. The comparison between various aggregations of soil moisture at the stand scale from point measurements demonstrates that the spatial variability of the soil moisture and the water uptake capacity limited by the root biomass need be taken into account to produce a model that is most resistant to interannual variability. Finally, the parameterized model is used to predict the actual evapotranspiration with uncertainty estimates determined using the joint distribution of the parameters derived from the Bayesian framework. The satisfactory agreement between the predicted and measured evapotranspiration suggests that the calibrated model can be incorporated into water balance studies in the future. [ABSTRACT FROM AUTHOR]

Soil moisture distribution emerges as a key link between hydrologic and ecologic processes in semiarid grassland and shrubland, as it influences evapotranspiration, respiration, and assimilation. In support, we present three years of data (2002-2004) collected from a semiarid grassland and shrubland within the Sevilleta National Wildlife Refuge of central New Mexico; the two sites are separated by about 5 km. Instrumentation includes an eddy covariance tower and typical micrometeorological devices at both locations. Additionally, the grassland site features six soil moisture profiles and the shrubland site features four soil moisture profiles, with the maximum depth at 52.5 cm. At both sites, most rain falls during the warm season, but large storms do occur at other times of the year, e.g., spring of 2004. Soil moisture pulses at 2.5 cm follow almost all rain events, whereas only four pulses in the 3-year record are observed at 52.5 cm in the grassland and two in the shrubland; these deeper pulses follow large precipitation events or a series of smaller events. The daily times series of evapotranspiration ( ET) is similar between the grassland and shrubland, supporting the results of Kurc and Small (2004). ET variations largely reflect changes in the soil moisture at 2.5 cm. In contrast, though the daily time series of net ecosystem exchange ( NEE) at both sites covary, the magnitudes of peaks in net negative ecosystem exchange ( NEE−) and net positive ecosystem exchange ( NEE+) are over twice the magnitude at grassland than at the shrubland. Furthermore, pulses associated with NEE− peaks last much longer than ET pulses, of the order of 1-2 months, without any particular adherence to the climatologically defined rainy season. These NEE− pulses reflect changes in deeper soil moisture, i.e., 52.5 cm at the grassland and 37.5 cm at the shrubland. Finally, evidence of soil moisture driven respiration is found throughout the NEE time series, with spikes of NEE+ following most rain events; however, longer periods of NEE+ also occur during relatively dry periods. Modeled assimilation suggests that the relationship between assimilation and soil moisture is strongest at depths at least 30 cm below the surface. [ABSTRACT FROM AUTHOR]

While it is generally believed that the magnitude and composition of vegetation cover influence land-atmosphere water and carbon fluxes, observations indicate that in some cases, fluxes are insensitive to land cover contrasts. This seeming inconsistency may be resolved by contrasting fluxes over short and long timescales. To explore this potential contrast, we developed and tested a model designed to simulate daily to decadal land surface water and carbon fluxes and vegetation dynamics for water-limited ecosystems. The model reproduces (R2 > 0.76) observed daily fluxes under increasing water limitation and captures representative dynamics of leaf area and fractional cover of dominant grass and wood vegetation. We parameterized the model for southern African savannas and conducted two sets of numerical experiments with either having fixed (static) grass and wood covers or allowing them to adjust dynamically with production. Static simulations reveal that the direct effect of rainfall on soil moisture is more important than the prevailing grass and wood cover states in controlling annual transpiration and production. Dynamic simulations indicate sensitivity of daily fluxes to vegetation cover states during high soil water periods. However, depletion of finite soil water prevents an integrated effect from lasting over interstorm to annual timescales. Correspondingly, while seasonal vegetation dynamics enhance seasonality in fluxes, vegetation dynamics have only minor influence on annual transpiration and production. In fact, annual rainfall explains most (R > 0.85) of the temporal variation in annual water and carbon fluxes. Hence, despite alteration of daily and seasonal distributions of fluxes, for water-limited ecosystems, vegetation dynamics have little effect on annual transpiration and production. [ABSTRACT FROM AUTHOR]

Tower-based measurements of mass and energy exchanges at the end of the growing season in central Botswana were used to evaluate functional relationships commonly applied to predict water and carbon fluxes between savanna landscapes and the atmosphere. Following a large rainfall event, daily evapotranspiration ( ET daily) exhibited an exponential decay consistent with a derived analytical expression based on critical and wilting-point soil moisture limits for savanna vegetation native to the study region. A piecewise linear soil moisture limitation function provided good estimates of ET daily as a function of potential evapotranspiration and soil moisture ( R2 = 0.92). Comparison of a soil moisture mass balance with measured ET daily indicated deeper root water uptake at a site with more woody vegetation compared with a grass-dominated site. Linear correlation ( R2 = 0.90) of daytime CO2 flux and evapotranspiration supported a constant water use efficiency to estimate carbon fluxes from water fluxes. Daytime and nighttime CO2 fluxes responded similarly to soil drying, enabling estimation of total daily CO2 flux from ET daily. These experimental results support a simple model of savanna land-atmosphere exchange over interstorm periods. [ABSTRACT FROM AUTHOR]

Observations are used to examine how soil moisture influences the surface radiation budget, ground heat flux, and available energy in semiarid environments. Defining this relationship is critical to understand interactions between the land surface and the atmosphere, in particular assessing if a feedback exists between soil moisture and rainfall anomalies. We use two summers of data collected from semiarid grassland and shrubland ecosystems in central New Mexico. The response of surface radiation budget components and other variables to soil moisture variations are quantified via linear regression. Then, the variations are scaled over the observed range of soil moisture (15% volumetric water content). The soil temperature is lower by >10°C when the surface soil is wet, compared to when the soil is dry. This temperature decrease results in a measured decrease of 85-100 W m−2 in longwave radiation emitted at the surface. The increase in net longwave radiation is equal in magnitude because downward longwave radiation does not vary with soil moisture. The observed changes in net shortwave radiation are relatively minor (<10 W m−2), as the surface albedo decreases by only 1.5% when soil is wet. Net radiation increases by an amount roughly equal to the decrease in emitted longwave radiation (∼85-100 W m−2). Changes in ground heat flux are not detectable, given the noise in the data. Therefore the available energy, Q a, is higher by 80 W m−2 when the soil is wet. This change is 22% of average Q a at the shrubland site and 19% at the grassland site. The observed soil moisture-induced Q a variations are large compared to other sources of Q a variability, so they should influence boundary layer moist static energy. However, the intervals during which soil moisture is high and therefore Rn and Q a are enhanced are short, on the order of several days. Therefore feedbacks to rainfall may be limited. Compared to other environments, the influence of soil moisture on Rn and Q a is likely greater in semiarid environments because soil moisture-induced fluctuations in evaporative fraction and surface temperature are relatively large. [ABSTRACT FROM AUTHOR]

In connection with evapotranspiration studies Pontacyl Brilliant Pink, a fluorescent dye, was used to trace the movement of water in two species of woody phreatophytes, willow and wildrose. The dye was introduced into water surrounding the plant roots on August 4, 1964. Thereafter, leaf samples were collected periodically until the end of the growing season in October. Fluorometric measurements showed the presence of the dye in the leaves. Dye was also found in samples of roots and stems and in transpired water collected in plastic bags. Dye concentration was greatest in the upper part of the stems. As a tracer the dye offers a rapid method for studying the source, movement, and disposal of water used by phreatophytes. The method is rapid and inexpensive, and the laboratory determination is not difficult. The fluorometric determinations were made with a GK Turner Fluorometer Model 111, which has a sensitivity of 1 ppb. [ABSTRACT FROM AUTHOR]