Assimilation of in situ and satellite data in mechanistic terrestrial ecosystem models helps to constrain critical model parameters and reduce uncertainties in the simulated energy, water and carbon fluxes. So far the assimilation of eddy covariance measurements from flux-tower sites has been conducted mostly for individual sites ("single-site" optimization). Here we develop a variational data assimilation system to optimize 21 parameters of the ORCHIDEE biogeochemical model, using net CO₂ flux (NEE) and latent heat flux (LE) measurements from 12 temperate deciduous broadleaf forest sites. We assess the potential of the model to simulate, with a single set of inverted parameters, the carbon and water fluxes at these 12 sites. We compare the fluxes obtained from this "multi-site" (MS) optimization to those of the prior model, and of the "single-site" (SS) optimizations. The model-data fit analysis shows that the MS approach decreases the daily root-mean-square difference (RMS) to observed data by 22%, which is close to the SS optimizations (25% on average). We also show that the MS approach distinctively improves the simulation of the ecosystem respiration (R_eco), and to a lesser extent the gross primary productivity (GPP), although we only assimilated net CO₂ flux. A process-oriented parameter analysis indicates that the MS inversion system finds a unique combination of parameters which is not the simple average of the different SS sets of parameters. Finally, in an attempt to validate the optimized model against independent data, we observe that global-scale simulations with MS optimized parameters show an enhanced phase agreement between modeled leaf area index (LAI) and satellite-based observations of normalized difference vegetation index (NDVI).

We introduce EcH₂O-iso, a new development of the physically based, fully distributed ecohydrological model EcH₂O where the tracking of water isotopic tracers (²H and ¹⁸O) and age has been incorporated. EcH₂O-iso is evaluated at a montane, low-energy experimental catchment in northern Scotland using 16 independent isotope time series from various landscape positions and compartments, encompassing soil water, groundwater, stream water, and plant xylem. The simulation results show consistent isotopic ranges and temporal variability (seasonal and higher frequency) across the soil profile at most sites (especially on hillslopes), broad model–data agreement in heather xylem, and consistent deuterium dynamics in stream water and in groundwater. Since EcH₂O-iso was calibrated only using hydrometric and energy flux datasets, tracking water composition provides a truly independent validation of the physical basis of the model for successfully capturing catchment hydrological functioning, both in terms of the celerity in energy propagation shaping the hydrological response (e.g. runoff generation under prevailing hydraulic gradients) and flow velocities of water molecules (e.g. in consistent tracer concentrations at given locations and times). Additionally, we show that the spatially distributed formulation of EcH₂O-iso has the potential to quantitatively link water stores and fluxes with spatiotemporal patterns of isotope ratios and water ages. However, our case study also highlights model–data discrepancies in some compartments, such as an over-dampened variability in groundwater and stream water lc-excess, and over-fractionated riparian topsoils. The adopted minimalistic framework, without site-specific parameterisation of isotopes and age tracking, allows us to learn from these mismatches in further model development and benchmarking needs, while taking into account the idiosyncracies of our study catchment. Notably, we suggest that more advanced conceptualisation of soil water mixing and of plant water use would be needed to reproduce some of the observed patterns. Balancing the need for basic hypothesis testing with that of improved simulations of catchment dynamics for a range of applications (e.g. plant water use under changing environmental conditions, water quality issues, and calibration-derived estimates of landscape characteristics), further work could also benefit from including isotope-based calibration.

Large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model–data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely the Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO₂ concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The assimilation of atmospheric CO₂, using the general circulation model (GCM) of the Laboratoire de Météorologie Dynamique (LMDz; step 3), provides an overall constraint (i.e., constraint on large-scale net CO₂ fluxes), resulting in an improvement of the fit to the observed atmospheric CO₂ growth rate. Thus, the optimized model predicts a land C (carbon) sink of around 2.2 PgC yr⁻¹ (for the 2000–2009 period), which is more compatible with current estimates from the Global Carbon Project (GCP) than the prior value. The consistency of the stepwise approach is evaluated with back-compatibility checks. The final optimized model (after step 3) does not significantly degrade the fit to MODIS-NDVI and FLUXNET data that were assimilated in the first two steps, suggesting that a stepwise approach can be used instead of the more “challenging” implementation of a simultaneous optimization in which all data streams are assimilated together. Most parameters, including the scalar of the initial soil carbon pool size, changed during the optimization with a large error reduction. This work opens new perspectives for better predictions of the land carbon budgets.

Intermittent rivers and ephemeral streams (IRES) are now recognized to support specific freshwater biodiversity and ecosystem services and represent approximately half of the global river network, a fraction that is likely to increase in the context of global changes. Despite large research efforts on IRES during the past few decades, there is a need for developing a systemic approach to IRES that considers their hydrological, hydrogeological, hydraulic, ecological, and biogeochemical properties and processes, as well as their interactions with human societies. Thus, we assert that the interdisciplinary approach to ecosystem research promoted by critical zone sciences and socio‐ecology is relevant. These approaches rely on infrastructure—Critical Zone Observatories (CZO) and Long‐Term Socio‐Ecological Research (LTSER) platforms—that are representative of the diversity of IRES (e.g., among climates or types of geology. We illustrate this within the French CZO and LTSER, including their diversity as socio‐ecosystems, and detail human interactions with IRES. These networks are also specialized in the long‐term observations required to detect and measure ecosystem responses of IRES to climate and human forcings despite the delay and buffering effects within ecosystems. The CZO and LTSER platforms also support development of innovative techniques and data analysis methods that can improve characterization of IRES, in particular for monitoring flow regimes, groundwater‐surface water flow, or water biogeochemistry during rewetting. We provide scientific and methodological perspectives for which this interdisciplinary approach and its associated infrastructure would provide relevant and original insights that would help fill knowledge gaps about IRES.This article is categorized under: Water and Life > Stresses and Pressures on Ecosystems Science of Water > Hydrological Processes Water and Life > Conservation, Management, and Awareness

While most landscapes respond to extreme rainfalls with increased surface water outflows, very flat and poorly drained ones have little capacity to do this and their most common responses include (i) increased water storage leading to rising water tables and floods, (ii) increased evaporative water losses, and, after reaching high levels of storage, (iii) increased liquid water outflows. The relative importance of these pathways was explored in the extensive plains of the Argentine Pampas, where two significant flood episodes (denoted FE1 and FE2) occurred in 2000–2003 and 2012–2013. In two of the most flood‐prone areas (Western and Lower Pampa, 60,000 km² each), surface water cover reached 31 and 19% during FE1 in each subregion, while FE2 covered up to 22 and 10%, respectively. From the spatiotemporal heterogeneity of the flood events, we distinguished slow floods lasting several years when the water table is brought to the surface following sustained precipitation excesses in groundwater‐connected systems (Western Pampa), and “fast” floods triggered by surface water accumulation over the course of weeks to months, typical of poor surface‐groundwater connectivity (Lower Pampa) or when exceptionally strong rainfalls overwhelm infiltration capacity. Because of these different hydrological responses, precipitation and evapotranspiration were strongly linked in the Lower Pampa only, while the connection between water fluxes and storage was limited to the Western Pampa. In both regions, evapotranspirative losses were strongly linked to flooded conditions as a regulatory feedback, while liquid water outflows remained negligible.