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The impact of elevated air temperature and heat stress on human health is a global concern. It not only affects our well-being directly, but also reduces our physical work capacity, leading to negative effects on society and economic productivity. Climate change has already affected the climate in Luxembourg and, based on the results of regional climate models, extreme heat events will become more frequent and intense in the future. To assess historical conditions, the micro-scaleRayManPro 3.1 model was used to simulate the thermal stress levels for different genders and age classes based on hourly input data spanning the last two decades. For the assessment of future conditions, with a special emphasis on heat waves, a multi-model ensemble of regional climate models for different emission scenarios taken from the Coordinated Regional Climate Downscaling Experiment (CORDEX) was used. For both, the past and future conditions in Luxemburg, an increase in the heat stress levels was observed. Small differences for different age groups and genders became obvious. In addition to the increase in the absolute number of heat waves, an intensification of higher temperatures and longer durations were also detected. Although some indications of the adaptation to rising air temperatures can be observed for high-income countries, our results underscore the likelihood of escalating heat-related adverse effects on human health and economic productivity unless more investments are made in research and risk management strategies. [ABSTRACT FROM AUTHOR]

Highlights • A novel RWU scheme based on the root hydraulic architecture is integrated in a LSM. • Root hydraulic properties control transpiration during prolonged dry conditions. • Soil parameterization uncertainty influences transpiration and soil water content. • Roots distribution induce larger variability in the hydraulic model response. Abstract A detailed representation of plant hydraulic traits and stomatal closure in land surface models (LSMs) is a prerequisite for improved predictions of ecosystem drought response. This work presents the integration of a macroscopic root water uptake (RWU) model based on the hydraulic architecture approach in the LSM of the Terrestrial Systems Modeling Platform. The novel RWU approach is based on three parameters derived from first principles that describe the root system equivalent conductance, the compensatory RWU conductance, and the leaf water potential at stomatal closure, which defines the water stress condition for the plants. The developed RWU model intrinsically accounts for changes in the root density as well as for the simulation of the hydraulic lift process. The standard and the new RWU approach are compared by performing point-scale simulations for cropland over a sheltered minirhizotron facility in Selhausen, Germany, and validated against transpiration fluxes estimated from sap flow and soil water content measurements at different depths. Numerical sensitivity experiments are carried out using different soil textures and root distributions in order to evaluate the interplay between soil hydrodynamics and plant characteristics, and the impact of assuming time-constant plant physiological properties. Results show a good agreement between simulated and observed transpiration fluxes for both RWU models, with a more distinct response under water stress conditions and with uncertainty in the soil parameterization prevailing to the differences due to changes in the model formulation. The hydraulic RWU model exhibits also a lower sensitivity to the root distributions when simulating the onset of the water stress period. Finally, an analysis of variability across the soil and root scenarios indicates that differences in soil water content are mainly influenced by the root distribution, while the transpiration flux in both RWU models is additionally determined by the soil characteristics. [ABSTRACT FROM AUTHOR]

In the hydrologic cycle, continental landmasses constitute a sink for atmospheric moisture as annual terrestrial precipitation commonly exceeds evapotranspiration. Simultaneously, humans intervene in the hydrologic cycle and pump groundwater to sustain, for example, drinking water and food production. Here we use a coupled groundwater-to-atmosphere modeling platform, set up over the European continent, to study the influence of groundwater pumping and irrigation on the net atmospheric moisture import of the continental landmasses, which defines the strength of the continental sink. Water use scenarios are constructed to account for uncertainties of atmospheric feedback during the heatwave year 2003. We find that human water use induces groundwater-to-atmosphere feedback, which potentially weaken the continental sink over arid watersheds in southern Europe. This feedback is linked to groundwater storage, which suggests that atmospheric feedbacks to human water use may contribute to drying of watersheds, thereby raising water resources and socio-economic concerns beyond local sustainability considerations. [ABSTRACT FROM AUTHOR]

This study compares two modeling platforms, ParFlow.WRF (PF.WRF) and the Terrestrial Systems Modeling Platform (TerrSysMP), with a common 3D integrated surface-groundwater model to examine the variability in simulated soil-vegetation-atmosphere interactions. Idealized and hindcast simulations over the North Rhine-Westphalia region in western Germany for clear-sky conditions and strong convective precipitation using both modeling platforms are presented. Idealized simulations highlight the strong variability introduced by the difference in land surface parameterizations (e.g., ground evaporation and canopy transpiration) and atmospheric boundary layer (ABL) schemes on the simulated land-atmosphere interactions. Results of the idealized simulations also suggest a different range of sensitivity in the two models of land surface and atmospheric parameterizations to water-table depth fluctuations. For hindcast simulations, both modeling platforms simulate net radiation and cumulative precipitation close to observed station data, while larger differences emerge between spatial patterns of soil moisture and convective rainfall due to the difference in the physical parameterization of the land surface and atmospheric component. This produces a different feedback by the hydrological model in the two platforms in terms of discharge over different catchments in the study area. Finally, an analysis of land surface and ABL heat and moisture budgets using the mixing diagram approach reveals different sensitivities of diurnal atmospheric processes to the groundwater parameterizations in both modeling platforms. [ABSTRACT FROM AUTHOR]

Plant physiological properties have a significant influence on the partitioning of radiative forcing, the spatial and temporal variability of soil water and soil temperature dynamics, and the rate of carbon fixation. Because of the direct impact on latent heat fluxes, these properties may also influence weather-generating processes, such as the evolution of the atmospheric boundary layer (ABL). In this work, crop-specific physiological characteristics, retrieved from detailed field measurements, are included in the biophysical parameterization of the Terrestrial Systems Modeling Platform (TerrSysMP). The physiological parameters for two typical European midlatitudinal crops (sugar beet and winter wheat) are validated using eddy covariance fluxes over multiple years from three measurement sites located in the North Rhine-Westphalia region of Germany. Comparison with observations and a simulation utilizing the generic crop type shows clear improvements when using the crop-specific physiological characteristics of the plant. In particular, the increase of latent heat fluxes in conjunction with decreased sensible heat fluxes as simulated by the two crops leads to an improved quantification of the diurnal energy partitioning. An independent analysis carried out using estimates of gross primary production reveals that the better agreement between observed and simulated latent heat adopting the plant-specific physiological properties largely stems from an improved simulation of the photosynthesis process. Finally, to evaluate the effects of the crop-specific parameterizations on the ABL dynamics, a series of semi-idealized land-atmosphere coupled simulations is performed by hypothesizing three cropland configurations. These numerical experiments reveal different heat and moisture budgets of the ABL using the crop-specific physiological properties, which clearly impacts the evolution of the boundary layer. [ABSTRACT FROM AUTHOR]

Abstract: Problems in hydrology and water management that involve both surface water and groundwater are best addressed with simulation models that can represent the interactions between these two flow regimes. In the current generation of coupled models, a variety of approaches is used to resolve surface–subsurface interactions and other key processes such as surface flow propagation. In this study we compare two physics-based numerical models that use a 3D Richards equation representation of subsurface flow. In one model, surface flow is represented by a fully 2D kinematic approximation to the Saint–Venant equations with a sheet flow conceptualization. In the second model, surface routing is performed via a quasi-2D diffusive formulation and surface runoff follows a rill flow conceptualization. The coupling between the land surface and the subsurface is handled via an explicit exchange term resolved by continuity principles in the first model (a fully-coupled approach) and by special treatment of atmospheric boundary conditions in the second (a sequential approach). Despite the significant differences in formulation between the two models, we found them to be in good agreement for the simulation experiments conducted. In these numerical tests, on a sloping plane and a tilted V-catchment, we examined saturation excess and infiltration excess runoff production under homogeneous and heterogeneous conditions, the dynamics of the return flow process, the differences in hydrologic response under rill flow and sheet flow parameterizations, and the effects of factors such as grid discretization, time step size, and slope angle. Low sensitivity to vertical discretization and time step size was found for the two models under saturation excess and homogeneous conditions. Larger sensitivity and differences in response were observed under infiltration excess and heterogeneous conditions, due to the different coupling approaches and spatial discretization schemes used in the two models. For these cases, the sensitivity to vertical and temporal resolution was greatest for processes such as reinfiltration and ponding, although the differences between the hydrographs of the two models decreased as mesh and step size were progressively refined. In return flow behavior, the models are in general agreement, with the largest discrepancies, during the recession phase, attributable to the different parameterizations of diffusion in the surface water propagation schemes. Our results also show that under equivalent parameterizations, the rill and sheet flow conceptualizations used in the two models produce very similar responses in terms of hydrograph shape and flow depth distribution. [Copyright &y& Elsevier]

Land surface temperature (LST) is a preeminent state variable that controls the energy and water exchange between the Earth's surface and the atmosphere. At the landscape-scale, LST is derived from thermal infrared radiance measured using space-borne radiometers. In contrast, plot-scale LST estimation at flux tower sites is commonly based on the inversion of upwelling longwave radiation captured by tower-mounted radiometers, whereas the role of the downwelling longwave radiation component is often ignored. We found that neglecting the reflected downwelling longwave radiation leads not only to substantial bias in plot-scale LST estimation, but also have important implications for the estimation of surface emissivity on which LST is co-dependent. The present study proposes a novel method for simultaneous estimation of LST and emissivity at the plot-scale and addresses in detail the consequences of omitting down-welling longwave radiation as frequently done in the literature. Our analysis uses ten eddy covariance sites with different land cover types and found that the LST values obtained using both upwelling and downwelling longwave radiation components are 0.5–1.5 K lower than estimates using only upwelling longwave radiation. Furthermore, the proposed method helps identify inconsistencies between plot-scale radiometric and aerodynamic measurements, likely due to footprint mismatch between measurement approaches. We also found that such inconsistencies can be removed by slight corrections to the upwelling longwave component and subsequent energy balance closure, resulting in realistic estimates of surface emissivity and consistent relationships between energy fluxes and surface-air temperature differences. The correspondence between plot-scale LST and landscape-scale LST depends on site-specific characteristics, such as canopy density, sensor locations and viewing angles. Here we also quantify the uncertainty in plot-scale LST estimates due to uncertainty in tower-based measurements using the different methods. The results of this work have significant implications for the combined use of aerodynamic and radiometric measurements to understand the interactions and feedbacks between LST and surface-atmosphere exchange processes. [ABSTRACT FROM AUTHOR]

Global evaporation monitoring from Earth observation thermal infrared satellite missions is historically challenged due to the unavailability of any direct measurements of aerodynamic temperature. State‐of‐the‐art one‐source evaporation models use remotely sensed radiometric surface temperature as a substitute for the aerodynamic temperature and apply empirical corrections to accommodate for their inequality. This introduces substantial uncertainty in operational drought mapping over complex landscapes. By employing a non‐parametric model, we show that evaporation can be directly retrieved from thermal satellite data without the need of any empirical correction. Independent evaluation of evaporation in a broad spectrum of biome and aridity yielded statistically significant results when compared with eddy covariance observations. While our simplified model provides a new perspective to advance spatio‐temporal evaporation mapping from any thermal remote sensing mission, the direct retrieval of aerodynamic temperature also generates the highly required insight on the critical role of biophysical interactions in global evaporation research. Plain Language Summary: Water lost by plants through evaporation is strongly linked with the temperature at an unknown height within the canopy. Because this in‐canopy temperature cannot be typically measured by a satellite, the majority of the global evaporation models substitute this with skin temperature, or the near‐surface temperature observed by the satellite sensors. Such methods do not fully capture the physical and biological processes governing the magnitude and variability of plant water use under severe water stress, leading to substantial errors in water cycle monitoring in the dry regions. Here, we show how a simple model that requires no anticipated parameter, provides not only reasonable estimates of evaporation in a variety of dry and wet conditions, but also a better insight into the role of plant water stress and greenness in the difference between the in‐canopy temperature and skin temperature. This model offers an alternative and novel perspective that can be used in images from current and future thermal satellite missions to advance global plant water use mapping for several water management applications and to investigate the highly complex land‐atmosphere interactions and feedback mechanisms. Key Points: Aerodynamic temperature and evaporation well estimated from physical principles and available energy‐water limits in different ecosystemsWater stress and vegetation cover influences the difference between aerodynamic and radiometric temperatures through plant homeostasisNon‐parametric model offers a parameter‐sparse approach describing evaporation, canopy conductance and vapor pressure deficit relationship [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is a preeminent state variable that controls the energy and water exchange between the Earth's surface and the atmosphere. At the landscape-scale, LST is derived from thermal infrared radiance measured using space-borne radiometers. In contrast, plot-scale LST estimation at flux tower sites is commonly based on the inversion of upwelling longwave radiation captured by tower-mounted radiometers, whereas the role of the downwelling longwave radiation component is often ignored. We found that neglecting the reflected downwelling longwave radiation leads not only to substantial bias in plot-scale LST estimation, but also have important implications for the estimation of surface emissivity on which LST is co-dependent. The present study proposes a novel method for simultaneous estimation of LST and emissivity at the plot-scale and addresses in detail the consequences of omitting down-welling longwave radiation as frequently done in the literature. Our analysis uses ten eddy covariance sites with different land cover types and found that the LST values obtained using both upwelling and downwelling longwave radiation components are 0.5–1.5 K lower than estimates using only upwelling longwave radiation. Furthermore, the proposed method helps identify inconsistencies between plot-scale radiometric and aerodynamic measurements, likely due to footprint mismatch between measurement approaches. We also found that such inconsistencies can be removed by slight corrections to the upwelling longwave component and subsequent energy balance closure, resulting in realistic estimates of surface emissivity and consistent relationships between energy fluxes and surface-air temperature differences. The correspondence between plot-scale LST and landscape-scale LST depends on site-specific characteristics, such as canopy density, sensor locations and viewing angles. Here we also quantify the uncertainty in plot-scale LST estimates due to uncertainty in tower-based measurements using the different methods. The results of this work have significant implications for the combined use of aerodynamic and radiometric measurements to understand the interactions and feedbacks between LST and surface-atmosphere exchange processes. [ABSTRACT FROM AUTHOR]

Abstract: Several physically-based models that couple 1D or 2D surface and 3D subsurface flow have recently been developed, but few studies have evaluated the errors directly associated with the different coupling schemes. In this paper we analyze the causes of mass balance error for a conventional and a modified sequential coupling scheme in worst-case scenario simulations of Hortonian runoff generation on a sloping plane catchment. The conventional scheme is noniterative, whereas for the modified scheme the surface–subsurface exchange fluxes are determined via a boundary condition switching procedure that is performed iteratively during resolution of the nonlinear subsurface flow equation. It is shown that the modified scheme generates much lower coupling mass balance errors than the conventional sequential scheme. While both coupling schemes are sensitive to time discretization, the iterative control of infiltration in the modified scheme greatly limits its sensitivity to temporal resolution. Little sensitivity to spatial discretization is observed for both schemes. For the modified scheme the different factors contributing to coupling error are isolated, and the error is observed to be highly correlated to the flood recession duration. More testing, under broader hydrologic contexts and including other coupling schemes, is recommended so that the findings from this first analysis of coupling errors can be extended to other surface water–groundwater models. [Copyright &y& Elsevier]

A significant challenge in global change research is understanding how vegetation interacts with the environment to influence ecosystem gross primary productivity (GPP) through carbon assimilation. One emerging objective is to consistently predict GPP fluctuations worldwide by establishing a robust scaling relationship between GPP measured at flux towers and satellite spectral reflectance data. However, a major hurdle in achieving this goal is the discrepancy in spatial resolution between early satellite measurements and eddy flux measurements. By using a large set of growing season data covering 100 site-years in North and Central America, we explored the potential of transforming incident and reflected shortwave (R g) and photosynthetically active radiation (PAR) measurements into a broadband normalized difference vegetation index (NDVI) and near-infrared (NIR) reflectance of vegetation (NIRv) which simultaneously explains the GPP variability. We found that the broadband NDVI and NIRv derived from R g and PAR measurements at the daily time scale were highly correlated with Planet Fusion, Landsat-8/9, and Sentinel-2 narrowband NDVI and NIRv across a wide range of climate and ecological gradients. The differences between satellite and broadband NDVI and NIRv were found to be significantly associated with soil background variations, phenological stages, water stress and signal saturation of broadband NIR reflectance at high biomass. The seasonal variability of broadband NDVI and NIRv remarkably captured the seasonality of vegetation phenology, evaporative fraction, GPP and rainfall in different ecosystems. Although saturation of GPP at high NDVI was evident, a linear relationship between broadband NIRv times incident PAR versus GPP indicated the effectiveness of NIRv-based approach to capture the hidden light use efficiency impacts on GPP. Our study concludes that inexpensive measurement of R g and PAR components can provide reliable information on NDVI, NIRv, and GPP uninterruptedly. This enhances the sensing capability of flux tower sites without requiring additional spectrometer measurements. The proposed in-situ vegetation indices make a compelling case on using radiation signals for handshaking between ecosystem-scale measurements and remote sensing observables relevant to carbon uptake. • Shortwave radiation and PAR measurements transformed into a broadband NDVI and NIRv. • Broadband NDVI highly correlated with NDVI from Planet, Sentinel-2, Landsat8/9. • PAR*NIRv linearly explained GPP variability across ecosystems of varying water stress. • Broadband NDVI from proximal sensing is a proxy of satellite NDVI at flux tower sites. [ABSTRACT FROM AUTHOR]

Assessing the availability of freshwater resources under current and future climatic conditions requires an improved understanding of the terrestrial–atmospheric system and anthropogenic impacts. Especially during heatwaves and droughts, additional groundwater is abstracted to meet increased water demands for e.g. agriculture, thereby putting water resources under additional stress. While recent studies highlight the direct impacts of human water use on terrestrial water fluxes and states, the impact may be much larger, more far-reaching, and potentially exacerbated through atmospheric feedbacks induced by human water use. Moreover, these atmospheric feedbacks can exceed watershed boundaries and affect local to remote water use sustainability. In this study, we use the coupled groundwater-to-atmosphere modeling platform TerrSysMP to assess the impact of human water use on land and atmospheric processes, such as evaporation, water vapor transport and precipitation. Furthermore, we apply the Lagrangian particle dispersion model FLEXPART to the output from TerrSysMP, which allows us to trace atmospheric water vapor and identify feedback pathways. Simulations cover continental Europe and consist of a four-member human water use ensemble to account for uncertainties in water use estimates and the associated feedbacks during the heatwave year 2003. We determine atmospheric feedback pathways of human water use and evaluate their reach across watersheds, which enables us to disentangle contributions to water availability change. Our results indicate that human water use affects atmospheric processes beyond the watershed-scale, and that these atmospheric feedbacks crucially contribute to terrestrial water storage change. In particular, arid watersheds in Southern Europe suffer additional drying through atmospheric feedbacks induced by human water use. Moreover, we find that the incorporation of human water use in the modeling system improves the simulation of local evaporation and precipitation by 3 and 13% on average, respectively. Our findings constitute a novel process-based view of the anthropogenic impact on the full terrestrial hydrologic cycle across watersheds, and highlight concerns of sustainability. [ABSTRACT FROM AUTHOR]

Summary Process-based hydrological models have a long history dating back to the 1960s. Criticized by some as over-parameterized, overly complex, and difficult to use, a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrological model. This is especially the case in situations where knowledge of flow paths or distributed state variables and/or preservation of physical constraints is important. Examples of this include: spatiotemporal variability of soil moisture, groundwater flow and runoff generation, sediment and contaminant transport, or when feedbacks among various Earth’s system processes or understanding the impacts of climate non-stationarity are of primary concern. These are situations where process-based models excel and other models are unverifiable. This article presents this pragmatic view in the context of existing literature to justify the approach where applicable and necessary. We review how improvements in data availability, computational resources and algorithms have made detailed hydrological simulations a reality. Avenues for the future of process-based hydrological models are presented suggesting their use as virtual laboratories, for design purposes, and with a powerful treatment of uncertainty. [ABSTRACT FROM AUTHOR]

Aerodynamic resistance (hereafter r a) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of r a plays a pivotal role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links r a with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates. The present study investigates the influence of r a and its relation to LST uncertainties on the performance of three structurally different SEB models. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE , the energy equivalent of ET in W/m2) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST , LAI, and in-situ meteorological datasets were evaluated against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019. Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underestimation of H. Overestimation of LE was associated with discrepancies in r a retrievals under conditions of high atmospheric instability, during which uncertainties in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive difference in LST coincided with low r a (high wind speeds) and caused a slight underestimation of LE at the water-limited sites. The impact of r a on the LE residual error was found to be of the same magnitude as the influence of LST uncertainties in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for the mesic forest ecosystems indicated minor dependency on r a for modelling LE (VIP < 0.4), which was due to a higher roughness length and lower LST resulting in the dominance of mechanically generated turbulence, thereby diminishing the importance of buoyancy production for the determination of r a. • Modelled latent heat flux is uncertain under drought due to aerodynamic resistance. • Overestimation of aerodynamic resistance at water-limited sites for low wind speed. • Stability links aerodynamic resistance with surface temperature and sensible heat. • Novel formulations for aerodynamic resistance are needed to model latent heat flux. [ABSTRACT FROM AUTHOR]

Evaporative water losses from catchments are strongly determined by vegetation atdiurnal and seasonal time scales. The opening and closing of stomata controls surfaceconductance at the hourly scale, whereas seasonal variations in leaf area index have aneffect on maximum possible surface conductance as well as the surface albedo andaerodynamic conductance. This implies that vegetation impacts all components ofthe surface energy balance, i.e. absorbed shortwave radiation, longwave radiativeexchange, ground heat flux, sensible heat exchange and latent heat flux. At the sametime, all the surface energy balance components are linked through the surfacetemperature feedback in a non-linear way that precludes exact analytical solutions of theproblem. The Penman-Monteith (PM) equation is commonly considered the best physically-basedanalytical approximation for calculating evapotranspiration (ET) from a vegetated surface.However, common misconceptions about appropriate use of the equation as wellas the underlying assumptions can result in substantially skewed predictions ofET sensitivity to variability in climatic conditions. These misconceptions include: Disregard for the two-sided sensible heat exchange by plant leaves and associated omissions (Schymanski and Or, HESS 21(2), 2016) Representation of ET as a product of &#x0022;unstressed&#x0022; ET and a moisture stress factor Omission of interactions between surface temperature, buoyancy and the aerodynamic conductance Here we used eddy covariance observations and modelling results to illustrate the effectsof the above misconceptions on our understanding of ET sensitivity to climate. Our resultscast a serious shadow of doubt on the suitability of state-of-the-art ET models and call forin-depth research on the process of free (thermal) convection, surface-atmosphere coupling atthe plot scale and their interactions with the biological control of the canopy conductance. [ABSTRACT FROM AUTHOR]

Worldwide ecosystems primary production and survival are largely limited by soil water availability, and affected by plant traits that control water uptake, transport, and release in the atmosphere. In order to understand how these complex systems will react to future climates, and optimally adjust their management, the development of experimental and modelling approaches is crucial. In particular, integrating process-based representations plant hydraulics and stomatal closure in land surface models (LSMs) is a major challenge as the limited computational resources necessitate the use of simplified descriptions of these processes.We present methods used to identify scale consistent emergent principles governing water flow in plants. We show that simplistic mechanistic expressions arise from the cell to the root system scale, and along stems whose geometry, saturated conductivity, sensitivity to cavitation, and leaf area vary continuously with height.Our results support that cavitation is a whole‐stem emergent property; in which compounding effects of gravity and vertical traits variations reported experimentally all substantially contribute to the occurrence of hydraulic failure in tall trees, and need to be accounted for in LSMs. Furthermore, a macroscopic solution of water flow in plant hydraulic architectures was implemented in the Terrestrial Systems Modeling Platform. As compared to the standard approach, this new model of water capture characteristically exhibits a different sensitivity of the onset of water stress to root distribution and soil properties. [ABSTRACT FROM AUTHOR]