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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 (Rg) 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 Rg 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 Rg 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.

Groundwater is by far the largest unfrozen freshwater resource on the planet. It plays a critical role as the bottom of the hydrologic cycle, redistributing water in the subsurface and supporting plants and surface water bodies. However, groundwater has historically been excluded or greatly simplified in global models. In recent years, there has been an international push to develop global scale groundwater modeling and analysis. This progress has provided some critical first steps. Still, much additional work will be needed to achieve a consistent global groundwater framework that interacts seamlessly with observational datasets and other earth system and global circulation models. Here we outline a vision for a global groundwater platform for groundwater monitoring and prediction and identify the key technological and data challenges that are currently limiting progress. Any global platform of this type must be interdisciplinary and cannot be achieved by the groundwater modeling community in isolation. Therefore, we also provide a high-level overview of the groundwater system, approaches to groundwater modeling and the current state of global groundwater representations, such that readers of all backgrounds can engage in this challenge.

Diagnosing and predicting evaporation through satellite‐based surface energy balance (SEB) and land surface models (LSMs) faces challenges due to the non‐linear responses of aerodynamic (ga) and stomatal conductance (gcs) to concurrent soil and atmospheric drought. Despite a soaring popularity to refine gcs formulation in LSMs by integrating soil‐plant hydraulics, SEB models often overlook the utility of gcs. This oversight is attributed to the overriding emphasis on reducing ga uncertainties and the lack of coordination between these two modeling communities. This disengagement between modeling communities poses a persistent challenge in understanding divergent evaporation estimates during intense soil‐atmospheric drought. Here we conducted a theoretical experiment over two contrasting European forest sites to examine the sensitivity of conductances and evaporative fluxes to a water‐stress factor (β‐factor), coupled with land surface temperature (LST) and vapor pressure deficit (representing soil and atmospheric drought proxy). Utilizing a non‐parametric diagnostic model (Surface Temperature Initiated Closure, STIC) and a prognostic model (Community Land Model, CLM5.0), the analysis revealed that the β‐factor, alongside different functional forms of conductances and the loose coupling of CLM5.0 conductances to LST, significantly influenced the response of the two models to soil and atmospheric drought. These discrepancies propagated in the estimates of evaporative fluxes between STIC and CLM5.0. The analysis reaffirms the need for a consensus on theory and models capturing the sensitivity of biophysical conductances to soil‐atmospheric drought interplay. It emphasizes the need for fostering collaboration between modeling communities to enhance the prediction of evaporation in complex environmental conditions. Plain Language Summary: The regulation of plant water loss through evaporation is governed by two key physical and biological attributes: aerodynamic and stomatal conductance. The magnitude and variability of these conductances and their degree of regulation on evaporation is heavily dependent on how the conductances respond to the conjugate dryness from the soil and the atmosphere. Because these conductances cannot be typically measured at a large scale, the majority of the global evaporation models use different mechanistic functions to estimate them, which involves many empirical parameters. Such methods do not fully capture the evaporation variability of ecosystems during water stress, leading to large errors in water cycle monitoring. Our model‐based synthetic experiment shows how two structurally different models with different functional forms of the conductances respond very differently to emerging soil‐atmospheric water stress and produce divergent estimates of evaporation in a variety of dry and wet conditions. This study not only provides insights into the role of conjugate effects of soil and atmospheric drought in explaining the conductances and evaporation variability but also suggests a novel perspective for reconciling predictive and remote sensing evaporation models, benefiting water management, testing plant water use theories, and understanding land‐atmosphere interactions. Key Points: Diagnostic (STIC) and prognostic (CLM5.0) evaporation models show distinct levels of sensitivity to water stressSTIC and CLM5.0 evaporation models better agree in simulating the energy fluxes as compared to underlying biophysical conductanceMajor differences in the simulated stomatal conductance are due to divergences in the physiological assumptions of the two evaporation modeling approaches [ABSTRACT FROM AUTHOR]

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]

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]

Forest transpiration is controlled by the atmospheric water demand, potentially constrained by soil moisture availability, and regulated by plant physiological properties. During summer periods, soil moisture availability at sites with thin soils can be limited, forcing the plants to access moisture stored in the weathered bedrock. Land surface models (LSMs) have considerably evolved in the description of the physical processes related to vegetation water use, but the effects of bedrock position and water uptake from fractured bedrock have not received much attention. In this study, the Community Land Model version 5.0 (CLM 5) is implemented at four forested sites with relatively shallow bedrock and located across an environmental gradient in Europe. Three different bedrock configurations (i.e., default, deeper, and fractured) are applied to evaluate if the omission of water uptake from weathered bedrock could explain some model deficiencies with respect to the simulation of seasonal transpiration patterns. Sap flow measurements are used to benchmark the response of these three bedrock configurations. It was found that the simulated transpiration response of the default model configuration is strongly limited by soil moisture availability at sites with extended dry seasons. Under these climate conditions, the implementation of an alternative (i.e., deeper and fractured) bedrock configuration resulted in a better agreement between modeled and measured transpiration. At the site with a continental climate, the default model configuration accurately reproduced the magnitude and temporal patterns of the measured transpiration. The implementation of the alternative bedrock configurations at this site provided more realistic water potentials in plant tissues but negatively affected the modeled transpiration during the summer period. Finally, all three bedrock configurations did not show differences in terms of water potentials, fluxes, and performances on the more northern and colder site exhibiting a transition between oceanic and continental climate. Model performances at this site are low, with a clear overestimation of transpiration compared to sap flow data. The results of this study call for increased efforts into better representing lithological controls on plant water uptake in LSMs. [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]

Emphasizing the physical intricacies of integrated hydrology and feedbacks in simulating connected, variably saturated groundwater-surface water systems, the Integrated Hydrologic Model Intercomparison Project initiated a second phase (IH-MIP2), increasing the complexity of the benchmarks of the first phase. The models that took part in the intercomparison were ATS, Cast3M, CATHY, GEOtop, HydroGeoSphere, MIKE-SHE, and ParFlow. IH-MIP2 benchmarks included a tilted v-catchment with 3-D subsurface; a superslab case expanding the slab case of the first phase with an additional horizontal subsurface heterogeneity; and the Borden field rainfall-runoff experiment. The analyses encompassed time series of saturated, unsaturated, and ponded storages, as well as discharge. Vertical cross sections and profiles were also inspected in the superslab and Borden benchmarks. An analysis of agreement was performed including systematic and unsystematic deviations between the different models. Results show generally good agreement between the different models, which lends confidence in the fundamental physical and numerical implementation of the governing equations in the different models. Differences can be attributed to the varying level of detail in the mathematical and numerical representation or in the parameterization of physical processes, in particular with regard to ponded storage and friction slope in the calculation of overland flow. These differences may become important for specific applications such as detailed inundation modeling or when strong inhomogeneities are present in the simulation domain. [ABSTRACT FROM AUTHOR]

There are a growing number of large-scale, complex hydrologic models that are capable of simulating integrated surface and subsurface flow. Many are coupled to land-surface energy balance models, biogeochemical and ecological process models, and atmospheric models. Although they are being increasingly applied for hydrologic prediction and environmental understanding, very little formal verification and/or benchmarking of these models has been performed. Here we present the results of an intercomparison study of seven coupled surface-subsurface models based on a series of benchmark problems. All the models simultaneously solve adapted forms of the Richards and shallow water equations, based on fully 3-D or mixed (1-D vadose zone and 2-D groundwater) formulations for subsurface flow and 1-D (rill flow) or 2-D (sheet flow) conceptualizations for surface routing. A range of approaches is used for the solution of the coupled equations, including global implicit, sequential iterative, and asynchronous linking, and various strategies are used to enforce flux and pressure continuity at the surface-subsurface interface. The simulation results show good agreement for the simpler test cases, while the more complicated test cases bring out some of the differences in physical process representations and numerical solution approaches between the models. Benchmarks with more traditional runoff generating mechanisms, such as excess infiltration and saturation, demonstrate more agreement between models, while benchmarks with heterogeneity and complex water table dynamics highlight differences in model formulation. In general, all the models demonstrate the same qualitative behavior, thus building confidence in their use for hydrologic applications. [ABSTRACT FROM AUTHOR]

Digital elevation models (DEMs) at different resolutions (180, 360, and 720 m) are used to examine the impact of different levels of landscape representation on the hydrological response of a 690-km catchment in southern Quebec. Frequency distributions of local slope, plan curvature, and drainage area are calculated for each grid size resolution. This landscape analysis reveals that DEM grid size significantly affects computed topographic attributes, which in turn explains some of the differences in the hydrological simulations. The simulations that are then carried out, using a coupled, process-based model of surface and subsurface flow, examine the effects of grid size on both the integrated response of the catchment (discharge at the main outlet and at two internal points) and the distributed response (water table depth, surface saturation, and soil water storage). The results indicate that discharge volumes increase as the DEM is coarsened, and that coarser DEMs are also wetter overall in terms of water table depth and soil water storage. The reasons for these trends include an increase in the total drainage area of the catchment for larger DEM cell sizes, due to aggregation effects at the boundary cells of the catchment, and to a decrease in local slope and plan curvature variations, which in turn limits the capacity of the watershed to transmit water downslope and laterally. The results obtained also show that grid resolution effects are less pronounced during dry periods when soil moisture dynamics are mostly controlled by vertical fluxes of evaporation and percolation. Copyright © 2010 John Wiley & Sons, Ltd. [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]

A hydrological model (SWAT) is used to quantify some of the indicators that make up the analysis matrix of a multicriteria decision support system (DSS). The analysis concerns the possible construction of a second, new dam on the Caia catchment in southern Portugal, its connectivity to an existing dam, and the impact of a hypothesized climate change scenario. We describe the definition of the decision criteria for the Caia problem, the linking of a reservoir operation module to SWAT (needed to transform SWAT output into DSS indicator values), an improvement to SWAT’s weather generator for the future climate scenario, the data processing and model simulation effort, and the use of various DSS functionalities to analyze the three options (existing dam and reservoir, new dam with reservoir hydraulically connected to the existing one, two reservoirs not hydraulically connected) and the two scenarios (current and future climate). This example of the conjunctive use of a distributed simulation model and a multicriteria DSS illustrates how these tools can interact in providing decision support for a multifaceted water resources management problem. [ABSTRACT FROM AUTHOR]

10.3390/w12010121 13 Camporese M., Paniconi C., Putti M., Orlandini S. Surface-subsurface flow modeling with path-based runoff routing, boundary condition-based coupling, and assimilation of multisource observation data. Li et al. proposed an efficient integrated modelling approach, whereby the baseflow is treated as a black box and forecasted using a long-term memory method, while the surface flow is simulated using a spatio-temporal variable source mixed runoff generation module, based on hydrological response units constructed from eco-geomorphological units. Environmental research is rapidly evolving toward an integration of different disciplines, and this is also reflected in hydrology and the hydrological modelling community. In this modelling application, the authors explore the potential of integrated surface-subsurface models to simulate salt transport processes leading to soil salinisation, which is a major environmental issue in arid and semi-arid regions, including the possible impacts of land use and climate change. [Extracted from the article]

Operational weather and flood forecasting has been performed successfully for decades and is of great socioeconomic importance. Up to now, forecast products focus on atmospheric variables, such as precipitation, air temperature and, in hydrology, on river discharge. Considering the full terrestrial system from groundwater across the land surface into the atmosphere, a number of important hydrologic variables are missing especially with regard to the shallow and deeper subsurface (e.g., groundwater), which are gaining considerable attention in the context of global change. In this study, we propose a terrestrial monitoring/forecasting system using the Terrestrial Systems Modeling Platform (TSMP) that predicts all essential states and fluxes of the terrestrial hydrologic and energy cycles from groundwater into the atmosphere. Closure of the terrestrial cycles provides a physically consistent picture of the terrestrial system in TSMP. TSMP has been implemented over a regional domain over North Rhine-Westphalia and a continental domain over Europe in a real-time forecast/monitoring workflow. Applying a real-time forecasting/monitoring workflow over both domains, experimental forecasts are being produced with different lead times since the beginning of 2016. Real-time forecast/monitoring products encompass all compartments of the terrestrial system including additional hydrologic variables, such as plant available soil water, groundwater table depth, and groundwater recharge and storage. [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]